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The opportunistic bacterial pathogen Pseudomonas aeruginosa causes a wide range of infections that are difficult to treat, largely because of the spread of antibiotic-resistant isolates. Antivirulence therapy, í.e. the use of drugs that inhibit the expression or activity of virulence factors, is currently considered an attractive strategy to reduce P. aeruginosa pathogenicity and complement antibiotic treatments. Because of the multifactorial nature of P. aeruginosa virulence and the broad arsenal of virulence factors this bacterium can produce, the regulatory networks that control the expression of multiple virulence traits have been extensively explored as potential targets for antivirulence drug development. The intracellular signaling molecule diadenosine tetraphosphate (Ap4A) has been reported to control stress resistance and virulence-related traits in some bacteria, but its role has not been investigated in P. aeruginosa so far. To fill this gap, we generated a mutant of the reference strain P. aeruginosa PAO1 that lacks the Ap4A-hydrolysing enzyme ApaH and, consequently, accumulates high intracellular levels of Ap4A. Phenotypic and transcriptomic analyses revealed that the lack of ApaH causes a drastic reduction in the expression of several virulence factors, including extracellular proteases, elastases, siderophores, and quorum sensing signal molecules. Accordingly, infection assays in plant and animal models demonstrated that ApaH-deficient cells are significantly impaired in infectivity and persistence in different hosts, including mice. Finally, deletion of apaH in P. aeruginosa clinical isolates demonstrated that the positive effect of ApaH on the production of virulence-related traits and on infectivity is conserved in P. aeruginosa. This study provides the first evidence that the Ap4A-hydrolysing enzyme ApaH is important for P. aeruginosa virulence, highlighting this protein as a novel potential target for antivirulence therapies against P. aeruginosa. Author summary: Novel therapeutic interventions are urgently needed to address the threat of antimicrobial resistance. Inhibition of the virulence potential of bacterial pathogens, the so called antivirulence approach, is an alternative or complementary strategy to standard antibiotic-based therapies. The identification of suitable targets is essential to promote and advance antivirulence drug discovery programs. By combining in vitro analyses and in vivo infection assays, we demonstrated that the enzyme ApaH, which is responsible for the degradation of the intracellular signaling molecule diadenosine tetraphosphate, contributes to the virulence of the important human pathogen Pseudomonas aeruginosa. Indeed, loss of ApaH drastically reduces the production of several virulence factors in both laboratory and clinical isolates, and impairs P. aeruginosa ability to cause infection in plant, insect and rodent models. These results, together with the absence of ApaH homologues in mammals, make ApaH a promising target for the development of anti-P. aeruginosa antivirulence drugs. [ABSTRACT FROM AUTHOR]

Rare cancers are defined by low incidence rates, and may lack evidence that supports uniform standards of care and relevant clinical guidelines. Rare cancers may represent up to 24% of all cancers, yet remain understudied and underappreciated in terms of their clinical and ultimately societal impact. The PLOS Rare Cancer Collection brings together a broad range of research endeavors that are being undertaken in rare cancers research ranging from basic biological evaluations to therapeutic drug development. This Overview presents a brief background to the Collection and highlights the contributions of included articles. [ABSTRACT FROM AUTHOR]

Background: Surgical Patients and hospitals are now facing financial strain due to direct anesthetic demand as a result of the development of new anesthetic drugs, equipment, and techniques. Up to 15% of a hospital's pharmacy budget is currently allocated to anesthetic drug expenses. Drug wastage during anesthesia practice is a widespread hidden source of healthcare waste that leads to anesthetic drug shortages as well as poor operating room efficiency. On the other hand, despite the fact that it is preventable in the vast majority of cases, it is well described that drug wastage is routinely observed, including in developing countries where the consequences significantly affect both hospitals and patients. Methods: This review aims to review the prevalence of anesthetic drug waste across the world and systematically formulate and describe preventive strategies. Relevant publications were identified using systematic searches on databases including Google Scholar, Medline (PubMed), the Cochrane Library, and Embase. In addition, papers were detected and then selected through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria guidelines and the inclusion and exclusion criteria. Using the predetermined terms and dates from the searching databases, a total of 504 articles were identified. Based on the screening criteria, 16 papers were considered eligible and included in the final review. In addition, the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis was used for evaluating the quality of selected articles. This study is registered on PROSPERO, number CRD42024497044. Results: Of the sixteen publications from eleven different nations that were considered suitable for inclusion, only two of them addressed the waste of inhalational anesthetics. In more than half of eligible articles, propofol was the frequently wasted drug that contributed to increased financial loss through drug waste. The first most significant factor contributing to the waste of intravenous and inhalational anesthetics was the disposal of multidrug vials following their use for a single patient and high fresh gas flow, respectively. Conclusion: Anesthetic medication waste is a common occurrence worldwide, despite the fact that it is expensive and has a significant negative impact on operating room efficiency. Because the majority of drug waste is avoidable, preventive measures may lower drug waste and improve patient and hospital efficiency. [ABSTRACT FROM AUTHOR]

With the increasing problem of antimicrobial drug resistance, the search for new antimicrobial agents has become a crucial task in the field of medicine. Antimicrobial peptides, as a class of naturally occurring antimicrobial agents, possess broad-spectrum antimicrobial activity and lower risk of resistance development. However, traditional screening methods for antimicrobial peptides are inefficient, necessitating the development of an efficient screening model. In this study, we aimed to develop an ensemble learning model for the identification of antimicrobial peptides, named E-CLEAP, based on the Multilayer Perceptron Classifier (MLP Classifier). By considering multiple features, including amino acid composition (AAC) and pseudo amino acid composition (PseAAC) of antimicrobial peptides, we aimed to improve the accuracy and generalization ability of the identification process. To validate the superiority of our model, we employed five-fold cross-validation and compared it with other commonly used methods for antimicrobial peptide identification. In the experimental results on an independent test set, E-CLEAP achieved accuracies of 97.33% and 84% for the AAC and PseAAC features, respectively. The results demonstrated that our model outperformed other methods in all evaluation metrics. The findings of this study highlight the potential of the E-CLEAP model in enhancing the efficiency and accuracy of antimicrobial peptide screening, which holds significant implications for drug development, disease treatment, and biotechnology advancement. Future research can further optimize the model by incorporating additional features and information, as well as validating its reliability on larger datasets and in real-world environments. The source code and all datasets are publicly available at https://github.com/Wangsicheng52/E-CLEAP. [ABSTRACT FROM AUTHOR]

BAK and BAX execute intrinsic apoptosis by permeabilising the mitochondrial outer membrane. Their activity is regulated through interactions with pro-survival BCL-2 family proteins and with non-BCL-2 proteins including the mitochondrial porin VDAC2. VDAC2 is important for bringing both BAK and BAX to mitochondria where they execute their apoptotic function. Despite this important function in apoptosis, while interactions with pro-survival family members are well characterised and have culminated in the development of drugs that target these interfaces to induce cancer cell apoptosis, the interaction between BAK and VDAC2 remains largely undefined. Deep scanning mutagenesis coupled with cysteine linkage identified key residues in the interaction between BAK and VDAC2. Obstructive labelling of specific residues in the BH3 domain or hydrophobic groove of BAK disrupted this interaction. Conversely, mutating specific residues in a cytosol-exposed region of VDAC2 stabilised the interaction with BAK and inhibited BAK apoptotic activity. Thus, this VDAC2–BAK interaction site can potentially be targeted to either inhibit BAK-mediated apoptosis in scenarios where excessive apoptosis contributes to disease or to promote BAK-mediated apoptosis for cancer therapy. BAK and BAX execute apoptotic cell death by increasing the permeability of the mitochondria outer membrane, and this is regulated by interactions with the mitochondrial channel protein VDAC2. This study maps the key residues involved in the BAK:VDAC2 interaction and demonstrate that this interaction can be targeted to either promote or inhibit apoptosis. [ABSTRACT FROM AUTHOR]

Nearly 300 million individuals live with chronic hepatitis B virus (HBV) infection (CHB), for which no curative therapy is available. As viral diversity is associated with pathogenesis and immunological control of infection, improved methods to characterize this diversity could aid drug development efforts. Conventionally, viral sequencing data are mapped/aligned to a reference genome, and only the aligned sequences are retained for analysis. Thus, reference selection is critical, yet selecting the most representative reference a priori remains difficult. We investigate an alternative pangenome approach which can combine multiple reference sequences into a graph which can be used during alignment. Using simulated short-read sequencing data generated from publicly available HBV genomes and real sequencing data from an individual living with CHB, we demonstrate alignment to a phylogenetically representative 'genome graph' can improve alignment, avoid issues of reference ambiguity, and facilitate the construction of sample-specific consensus sequences more genetically similar to the individual's infection. Graph-based methods can, therefore, improve efforts to characterize the genetics of viral pathogens, including HBV, and have broader implications in host-pathogen research. [ABSTRACT FROM AUTHOR]

Despite their widespread use as therapeutics, clinical development of small molecule drugs remains challenging. Among the many parameters that undergo optimization during the drug development process, increasing passive cell permeability (i.e., log(P)) can have some of the largest impact on potency. Cyclic peptides (CPs) have emerged as a viable alternative to small molecules, as they retain many of the advantages of small molecules (oral availability, target specificity) while being highly effective at traversing the plasma membrane. However, the relationship between the dominant conformations that typify CPs in an aqueous versus a membrane environment and cell permeability remain poorly characterized. In this study, we have used Gaussian accelerated molecular dynamics (GaMD) simulations to characterize the effect of solvent on the free energy landscape of lariat peptides, a subset of CPs that have recently shown potential for drug development (Kelly et al., JACS 2021). Differences in the free energy of lariat peptides as a function of solvent can be used to predict permeability of these molecules, and our results show that permeability is most greatly influenced by N-methylation and exposure to solvent. Our approach lays the groundwork for using GaMD as a way to virtually screen large libraries of CPs and drive forward development of CP-based therapeutics. [ABSTRACT FROM AUTHOR]

Target-mediated drug disposition (TMDD) is a phenomenon characterized by a drug's high-affinity binding to a target molecule, which significantly influences its pharmacokinetic profile within an organism. The comprehensive TMDD model delineates this interaction, yet it may become overly complex and computationally demanding in the absence of specific concentration data for the target or its complexes. Consequently, simplified TMDD models employing quasi-steady state approximations (QSSAs) have been introduced; however, the precise conditions under which these models yield accurate results require further elucidation. Here, we establish the validity of three simplified TMDD models: the Michaelis-Menten model reduced with the standard QSSA (mTMDD), the QSS model reduced with the total QSSA (qTMDD), and a first-order approximation of the total QSSA (pTMDD). Specifically, we find that mTMDD is applicable only when initial drug concentrations substantially exceed total target concentrations, while qTMDD can be used for all drug concentrations. Notably, pTMDD offers a simpler and faster alternative to qTMDD, with broader applicability than mTMDD. These findings are confirmed with antibody-drug conjugate real-world data. Our findings provide a framework for selecting appropriate simplified TMDD models while ensuring accuracy, potentially enhancing drug development and facilitating safer, more personalized treatments. Author summary: Target-mediated drug disposition (TMDD) is a phenomenon characterized by the high-affinity binding of a drug to its target molecule. The TMDD model can describe the process to elucidate the binding of the drug to its target and its elimination from the body. However, when target or complex concentrations are not available, simpler models of the TMDD model need to be used to avoid over-parameterization and to improve computational efficiency and analysis. Several simplified TMDD models based on quasi-equilibrium, Michaelis-Menten (MM), or quasi-steady-state (QSS) approximation have been proposed. However, their validity conditions have not been fully investigated. In this study, we derive the validity conditions for the approximations of the TMDD model, providing insights into the appropriate use of simplified models. We also propose a first-order approximation of the QSS model, which is faster than the QSS model and more accurate than the MM model. We also applied the simplified models to antibody-drug conjugate real-world data and obtained the same results. Our work provides clear guidance on the use of the simplified TMDD models, potentially leading to improved drug development and safer, more tailored treatments for patients. [ABSTRACT FROM AUTHOR]

We present here the solution structures of the protein thioredoxin-1 from Plasmodium falciparum (PfTrx-1), in its reduced and oxidized forms. They were determined by high-resolution NMR spectroscopy at 293 K on uniformly 13C-, 15N-enriched, matched samples allowing to identification of even small structural differences. PfTrx-1 shows an α/β-fold with a mixed five-stranded β-sheet that is sandwiched between 4 helices in a β1 α1 β2 α2 β3 α3 β4 β5 α4 topology. The redox process of the CGPC motif leads to significant structural changes accompanied by larger chemical shift changes from residue Phe25 to Ile36, Thr70 to Thr74, and Leu88 to Asn91. By high-field high-pressure NMR spectroscopy, rare conformational states can be identified that potentially are functionally important and can be used for targeted drug development. We performed these experiments in the pressure range from 0.1 MPa to 200 MPa. The mean combined, random-coil corrected B1* values of reduced and oxidized thioredoxin are quite similar with -0.145 and -0.114 ppm GPa-1, respectively. The mean combined, random-coil corrected B2* values in the reduced and oxidized form are 0.179 and 0.119 ppm GPa-2, respectively. The mean ratios of the pressure coefficients B2/B1 are -0.484 and -0.831 GPa-1 in the reduced and oxidized form respectively. They differ at some points in the structure after the formation of the disulfide bond between C30 and C33. The thermodynamical description of the pressure dependence of chemical shifts requires the assumption of at least three coexisting conformational states of PfTrx-1. These three conformational states were identified in the reduced as well as in the oxidized form of the protein, therefore, they represent sub-states of the two main oxidation states of PfTrx-1. [ABSTRACT FROM AUTHOR]

Background: Target Product Profiles (TPPs) are instrumental to help optimise the design and development of therapeutics, vaccines, and diagnostics–these products, in order to achieve the intended impact, should be aligned with users' preferences and needs. However, patients are rarely involved as key stakeholders in building a TPP. Methodology: Thirty-three cutaneous leishmaniasis (CL) patients from Brazil, Colombia, and Austria, infected with New-World Leishmania species, were recruited using a maximum variation approach along geographic, sociodemographic and clinical criteria. Semi-structured interviews were conducted in the respective patient's mother tongue. Transcripts, translated into English, were analysed using a framework approach. We matched disease experiences, preferences, and expectations of CL patients to a TPP developed by DNDi (Drug for Neglected Diseases initiative) for CL treatment. Principal findings: Patients' preferences regarding treatments ranged from specific efficacy and safety endpoints to direct and significant indirect costs. Respondents expressed views about trade-offs between efficacy and experienced discomfort/adverse events caused by treatment. Reasons for non-compliance, such as adverse events or geographical and availability barriers, were discussed. Considerations related to accessibility and affordability were relevant from the patients' perspective. Conclusions/Significance: NTDs affect disadvantaged populations, often with little access to health systems. Engaging patients in designing adapted therapies could significantly contribute to the suitability of an intervention to a specific context and to compliance, by tailoring the product to the end-users' needs. This exploratory study identified preferences in a broad international patient spectrum. It provides methodological guidance on how patients can be meaningfully involved as stakeholders in the construction of a TPP of therapeutics for NTDs. CL is used as an exemplar, but the approach can be adapted for other NTDs. Author summary: Our study addresses the challenge of involving patients in defining which medical product would work for their condition. When designing a new medical product, it is customary to identify a "target product profile" (TPP), which identifies the characteristics the product should have to meet in order to address the medical need it is intended for. For the product to be used as intended and achieve the desired effects, it should be adapted to the conditions and the people who will use it, so, patients' views are important, but rarely heard. Here, we use as an example cutaneous leishmaniasis, a skin and mucosal disease caused by a protozoan parasite, which disproportionally affects poor people across tropical and subtropical areas of the world. We collected patients' views about product safety, efficacy, costs, treatment administration, and perceived barriers, that contribute to specifying product characteristics in the TPP. Overall, our study contributes to the limited body of knowledge with an example and an adaptable methodology to give patients a voice in designing adapted medical products. Patients input may also contribute to redefining aspects of a TPP, such as affordability, instead of just the cost per unit. The methodology used here can be adapted and used for other neglected diseases to give patients a voice in designing medical products. [ABSTRACT FROM AUTHOR]

Identifying novel therapeutic agents is a fundamental challenge in contemporary drug development, especially in the context of complex diseases like cancer, neurodegenerative disorders, and metabolic syndromes. Here, we present a comprehensive computational study to identify potential inhibitors of SIRT1 (Sirtuin 1), a critical protein involved in various cellular processes and disease pathways. Leveraging the concept of drug repurposing, we employed a multifaceted approach that integrates molecular docking and molecular dynamics (MD) simulations to predict the binding affinities and dynamic behavior of a diverse set of FDA-approved drugs from DrugBank against the SIRT1. Initially, compounds were shortlisted based on their binding affinities and interaction analyses to identify safe and promising binding partners for SIRT1. Among these candidates, Doxercalciferol and Timiperone emerged as potential candidates, displaying notable affinity, efficiency, and specificity towards the binding pocket of SIRT1. Extensive evaluation revealed that these identified compounds boast a range of favorable biological properties and prefer binding to the active site of SIRT1. To delve deeper into the interactions, all-atom MD simulations were conducted for 500 nanoseconds (ns). These simulations assessed the conformational dynamics, stability, and interaction mechanism of the SIRT1-Doxercalciferol and SIRT1-Timiperone complexes. The MD simulations illustrated that the SIRT1-Doxercalciferol and SIRT1-Timiperone complexes maintain stability over a 500 ns trajectory. These insightful outcomes propose that Doxercalciferol and Timiperone hold promise as viable scaffolds for developing potential SIRT1 inhibitors, with implications for tackling complex diseases such as cancer, neurodegenerative disorders, and metabolic syndromes. [ABSTRACT FROM AUTHOR]

In the European Union, the Committee for Medicinal Products for Human Use of the European Medicines Agency (EMA) develop guidelines to guide drug development, supporting development of efficacious and safe medicines. A European Public Assessment Report (EPAR) is published for every medicine application that has been granted or refused marketing authorisation within the EU. In this work, we study the use of text embeddings and similarity metrics to investigate the semantic similarity between EPARs and EMA guidelines. All 1024 EPARs for initial marketing authorisations from 2008 to 2022 was compared to the 669 current EMA scientific guidelines. Documents were converted to plain text and split into overlapping chunks, generating 265,757 EPAR and 27,649 guideline text chunks. Using a Sentence BERT language model, the chunks were transformed into embeddings and fed into an in-house piecewise matching algorithm to estimate the full-document semantic distance. In an analysis of the document distance scores and product characteristics using a linear regression model, EPARs of anti-virals for systemic use (ATC code J05) and antihemorrhagic medicines (B02) present with statistically significant lower overall semantic distance to guidelines compared to other therapeutic areas, also when adjusting for product age and EPAR length. In conclusion, we believe our approach provides meaningful insight into the interplay between EMA scientific guidelines and the assessment made during regulatory review, and could potentially be used to answer more specific questions such as which therapeutic areas could benefit from additional regulatory guidance. [ABSTRACT FROM AUTHOR]

Dengue virus (DENV) is a public health challenge across the tropics and subtropics. Currently, there is no licensed prophylactic or antiviral treatment for dengue. The novel DENV inhibitor JNJ-1802 can significantly reduce viral load in mice and non-human primates. Here, using a mechanistic viral kinetic model calibrated against viral RNA data from experimental in-vitro infection studies, we assess the in-vitro inhibitory effect of JNJ-1802 by characterising infection dynamics of two DENV-2 strains in the absence and presence of different JNJ-1802 concentrations. Viral RNA suppression to below the limit of detection was achieved at concentrations of >1.6 nM, with a median concentration exhibiting 50% of maximal inhibitory effect (IC50) of 1.23x10-02 nM and 1.28x10-02 nM for the DENV-2/RL and DENV-2/16681 strains, respectively. This work provides important insight into the in-vitro inhibitory effect of JNJ-1802 and presents a first step towards a modelling framework to support characterization of viral kinetics and drug effect across different host systems. Author summary: Dengue poses a major challenge to global public health, with almost half of the world's population at risk of infection each year. However, currently, no licensed specific prophylactic or antiviral treatment for dengue exists. JNJ-1802, a novel dengue inhibitor under development by Janssen Pharmaceutica, is one of the most advanced candidate dengue antivirals and has recently been shown to significantly reduce viral load in pre-clinical animal studies. Here we use mathematical models, fitted to viral RNA data obtained from experimental infection studies in Vero cells, to quantify the in-vitro inhibitory effect of JNJ-1802 on the viral kinetics of two strains of dengue serotype 2. For both strains, we find the effect of JNJ-1802 on viral replication is strongly concentration-dependent, with viral suppression to below the limit of detection achieved at concentrations of 1.6 nM and above. This work is an important first step in quantifying the potential of JNJ-1802 as a dengue antiviral, and demonstrates how interdisciplinary research can help inform drug development and help inform dosing regimens. [ABSTRACT FROM AUTHOR]

Lysophosphatidylserine (LysoPS) is a naturally occurring lipid mediator involved in various physiological and pathological processes especially those related to the immune system. GPR34, GPR174, and P2Y10 have been identified as the receptors for LysoPS, and its analogues have been developed as agonists or antagonists for these receptors. However, the lack of structural information hinders the drug development with novel characteristics, such as nonlipid ligands and allosteric modulators. Here, we determined the structures of human GPR34 and GPR174 in complex with LysoPS and G protein by cryo-EM. Combined with structural analysis and functional studies, we elucidated the lipid-binding modes of these receptors. By structural comparison, we identified the structural features of GPR34 and GPR174 in active state. Taken together, our findings provide insights into ligand recognition and signaling of LysoPS receptors and will facilitate the development of novel therapeutics for related inflammatory diseases and autoimmune diseases. Lysophosphatidylserine (LysoPS) is a lipid signalling molecule implicated in a range of processes related to the immune system. This structural study reveals the mechanism of LysoPS recognition by two G protein-coupled receptors, GPR34 and GPR174, offering insights into lysophospholipid signaling and presenting opportunities for drug discovery. [ABSTRACT FROM AUTHOR]

Human cytomegalovirus (HCMV) is an important pathogen for which new antiviral drugs are needed. HCMV, like other herpesviruses, encodes a nuclear egress complex (NEC) composed of two subunits, UL50 and UL53, whose interaction is crucial for viral replication. To explore whether small molecules can exert selective antiviral activity by inhibiting NEC subunit interactions, we established a homogeneous time-resolved fluorescence (HTRF) assay of these interactions and used it to screen >200,000 compound-containing wells. Two compounds, designated GK1 and GK2, which selectively inhibited this interaction in the HTRF assay with GK1 also active in a co-immunoprecipitation assay, exhibited more potent anti-HCMV activity than cytotoxicity or activity against another herpesvirus. At doses that substantially reduced HCMV plaque formation, GK1 and GK2 had little or no effect on the expression of viral proteins and reduced the co-localization of UL53 with UL50 at the nuclear rim in a subset of cells. GK1 and GK2 contain an acrylamide moiety predicted to covalently interact with cysteines, and an analog without this potential lacked activity. Mass spectrometric analysis showed binding of GK2 to multiple cysteines on UL50 and UL53. Nevertheless, substitution of cysteine 214 of UL53 with serine (C214S) ablated detectable inhibitory activity of GK1 and GK2 in vitro, and the C214S substitution engineered into HCMV conferred resistance to GK1, the more potent of the two inhibitors. Thus, GK1 exerts selective antiviral activity by targeting the NEC. Docking studies suggest that the acrylamide tethers one end of GK1 or GK2 to C214 within a pocket of UL53, permitting the other end of the molecule to sterically hinder UL50 to prevent NEC formation. Our results prove the concept that targeting the NEC with small molecules can selectively block HCMV replication. Such compounds could serve as a foundation for development of anti-HCMV drugs and as chemical tools for studying HCMV. Author summary: Human cytomegalovirus (HCMV) causes severe diseases in newborns and in adults with compromised immunity. With no available vaccine for this virus, and with the drawbacks of existing anti-HCMV drugs, there is a pressing need for new effective treatments. HCMV, like other herpesviruses, uses an unusual process called nuclear egress by which viral capsids exit the nucleus. The interaction of two HCMV proteins plays a crucial role in nuclear egress. To investigate the possibility that a small compound can inhibit production of infectious HCMV by specifically targeting this interaction, we screened ~200,000 chemicals and found two related compounds that specifically inhibit the interaction of the two proteins in biochemical assays and exert anti-HCMV activity in cells. Both the inhibition of the interaction and the antiviral activity of at least one of the compounds depend upon the compounds binding to a specific location on one of the viral proteins. Our results provide compelling evidence that targeting these proteins is a valid strategy for developing new anti-HCMV drugs. The compounds that we identified might serve as a starting point for development of such drugs and as tools for studying the virus. [ABSTRACT FROM AUTHOR]

Public-private partnerships (PPPs) for neglected tropical diseases (NTDs) are often studied as an organizational form that facilitates the management and control of the huge costs of drug research and development. Especially the later stages of drug development, including clinical trials, become very expensive. This present study investigates whether and how the type of PPPs influences the initiation and duration of NTD clinical trials. Using the ClinicalTrials.gov database, a dataset of 1175 NTD clinical studies that started between 2000 and 2021 is analyzed based on affiliation information and project duration. For the NTD clinical trials that resulted from PPPs, the collaborating types were determined and analyzed, including the public sector-, private sector-, governmental sector-, and nongovernmental organization-led collaborations. The determinants for the discontinuation of all stopped clinical trials were categorized into scientific-, funding-, political-, and logistic dimensions. The results reveal that public sector-led PPPs were the most common collaborative types, and logistic and scientific issues were the most frequent determinants of stopped clinical trials. Trial registration: ClinicalTrials.gov. Author summary: In the present study, we focused on understanding the development of collaborative clinical trials for neglected tropical diseases that affect hundreds of millions of people each year. These diseases, largely prevalent in tropical regions, lead to huge economic and societal burdens. The current status of drug development in this field is caused and exacerbated by a combination of diverse political, market, and scientific factors. Our goal was to highlight the crucial role of collaborations between public entities and private organizations in initiating and promoting clinical trials for these neglected diseases. Our results show that public sector and nongovernmental organization-led collaborations were the most prevalent between 2000 and 2021. Logistic and scientific issues are the most frequent reasons for failures in this clinical trial dataset. In conclusion, our study paints an overview picture of the collaborative clinical trials against neglected tropical diseases. The results highlight the power of collaboration and innovation in addressing this kind of health need. We aspire that our insights will spark more conversations and initiatives aimed at providing equal healthcare opportunities for everyone. [ABSTRACT FROM AUTHOR]

Administering drug at a dose lower than that used in pivotal clinical trials, known as fractional dosing, can stretch scarce resources. Implementing fractional dosing with confidence requires understanding a drug's dose-response relationship. Clinical trials aimed at describing dose-response in scarce, efficacious drugs risk underdosing, leading dose-finding trials to not be pursued despite their obvious potential benefit. We developed a new set of response-adaptive randomized dose-finding trials and demonstrate, in a series of simulated trials across diverse dose-response curves, these designs' efficiency in identifying the minimum dose that achieves satisfactory efficacy. Compared to conventional designs, these trials have higher probabilities of identifying lower doses while reducing the risks of both population- and subject-level underdosing. We strongly recommend that, upon demonstration of a drug's efficacy, pandemic drug development swiftly proceeds with response-adaptive dose-finding trials. This unified strategy ensures that scarce effective drugs produce maximum social benefits. [ABSTRACT FROM AUTHOR]

Cellular senescence is a cell fate caused by multiple stresses. A 2008 article in PLOS Biology reported a senescence-associated secretory phenotype that can promote inflammation and cancer, eventually enabling the development of senolytic drugs. In this Perspective, the authors look back at a 2008 PLOS Biology article that reported a senescence-associated secretory phenotype that could promote inflammation and cancer, and discuss how that discovery eventually enabled the development of senolytic drugs. [ABSTRACT FROM AUTHOR]

The proton–activated chloride (PAC) channel plays critical roles in ischemic neuron death, but its activation mechanisms remain elusive. Here, we investigated the gating of PAC channels using its novel bifunctional modulator C77304. C77304 acted as a weak activator of the PAC channel, causing moderate activation by acting on its proton gating. However, at higher concentrations, C77304 acted as a weak inhibitor, suppressing channel activity. This dual function was achieved by interacting with 2 modulatory sites of the channel, each with different affinities and dependencies on the channel's state. Moreover, we discovered a protonation–independent voltage activation of the PAC channel that appears to operate through an ion–flux gating mechanism. Through scanning–mutagenesis and molecular dynamics simulation, we confirmed that E181, E257, and E261 in the human PAC channel serve as primary proton sensors, as their alanine mutations eliminated the channel's proton gating while sparing the voltage–dependent gating. This proton–sensing mechanism was conserved among orthologous PAC channels from different species. Collectively, our data unveils the polymodal gating and proton–sensing mechanisms in the PAC channel that may inspire potential drug development. The proton-activated chloride (PAC) channel plays a critical role in ischemic neuron death, but its activation mechanisms remain elusive. This study reveals the proton gating and protonation-independent voltage gating mechanisms of the PAC channel, using its unique bifunctional modulator C77304, with implications for drug development. [ABSTRACT FROM AUTHOR]

Background: Discrepancies have been reported between what is being researched, and what patients/families deem important to be investigated. Our aim was to understand research priorities for those who live with cancer in Aotearoa/New Zealand, with emphasis on Māori. Methods: Adult outpatients with cancer and their whānau/family completed a survey (demographics, selecting keywords, free-text comments) at Christchurch hospital. Quantitative and qualitative data were evaluated using standard statistical and thematic analyses, respectively. Results: We recruited 205 participants, including both tūroro/patients (n = 129) and their whānau/family/carer (n = 76). Partnership with Māori health workers enabled greater recruitment of Māori participants (19%), compared to the proportion of Māori in Canterbury (9%). Cancer research was seen as a priority by 96% of participants. Priorities were similar between Māori and non-Māori participants, with the keywords 'Cancer screening', 'Quality of Life' and 'Development of new drugs' chosen most often. Free-text analysis identified three themes; 'Genetics and Prevention', 'Early Detection and Treatment', and 'Service Delivery', with some differences by ethnicity. Conclusions: Cancer research is a high priority for those living with cancer. In addition, participants want researchers to listen to their immediate and practical needs. These findings may inform future cancer research in Aotearoa. Māori terms and translation: Aotearoa (New Zealand) he aha ō whakaaro (what are your thoughts) hui (gathering) mate pukupuku (cancer) mokopuna (descendent) Ōtautahi (Christchurch) rongoā (traditional healing) tāne (male) te reo (Māori language) Te Whatu Ora (weaving of wellness, Health New Zealand) tikanga (methods, customary practices) tūroro (patients) (alternative terms used: whānau affected by cancer or tangata whaiora (person seeking health)) wahine (female) Waitaha (Canterbury) whakapapa (genealogy) whānau ((extended) family, based on whakapapa, here also carer) [ABSTRACT FROM AUTHOR]

The RNA N7-methyltransferase (MTase) activity of SARS-CoV-2's nsp14 protein is essential for viral replication and is a target for the development of new antivirals. Nsp14 uses S-adenosyl methionine (SAM) as the methyl donor to cap the 5' end of the SARS-CoV-2 mRNA and generates S-adenosyl homocysteine (SAH) as the reaction byproduct. Due to the central role of histone MTases in cancer, many SAM/SAH analogs with properties of cell permeability have recently been developed for the inhibition of these MTases. We have succeeded in identifying two such compounds (SGC0946 and SGC8158) that display significant antiviral activity and bind to the SARS-CoV-2 nsp14 N7-MTase core. Unexpectedly, crystal structures of SGC0946 and SGC8158 with the SARS-CoV-2 nsp14 N7-MTase core identify them as bi-substrate inhibitors of the viral MTase, co-occupying both the SAM and RNA binding sites; positing novel features that can be derivatized for increased potency and selectivity for SARS-CoV-2 nsp14. Taken together, the high-resolution structures and the accompanying biophysical and viral replication data provide a new avenue for developing analogs of SGC0946 and SGC8158 as antivirals. Author summary: SARS-CoV-2 and its variants have led to millions of deaths globally. The RNA N7-methyltransferase activity of SARS-CoV-2's nsp14 protein is essential for viral replication and represents a promising target for antiviral drug development. In this study, we identified two compounds (SGC0946 and SGC8158) with significant antiviral activity that bind to the SARS-CoV-2 nsp14 N7-MTase core. Co-crystal structures of these compounds with the N7-MTase core were determined, revealing features that can be modified for increased potency and selectivity. These findings provide an avenue for developing SGC0946/SGC8158 analogs as antivirals. [ABSTRACT FROM AUTHOR]

Background and objective: Cerebral ischemia-reperfusion injury (CIRI) is a major injury that seriously endangers human health and is characterized by high mortality and high disability. The total flavonoid extract of Dracocephalum moldavica L.(TFDM) in the treatment of CIRI has been proved by clinical practice. But the mechanism for the treatment of CIRI by TFDM has not been systematically revealed. Study design and methods: The active compounds contained in TFDM were screened by literature mining and pharmacokinetic parameters, and the targets related to CIRI were collected by searching Drugbank, Genecards and OMIM databases. Cytoscape software was used to construct the protein interaction network of TFDM for the prevention and treatment of CIRI. Geneontology and signal pathway enrichment were analyzed. The key target pathway network of TFDM compounds was constructed and verified by pharmacological experiment in vitro. Results: 21 active components were screened, 158 potential drug targets for the prevention and treatment of CIRI were obtained, 53 main targets were further screened in the protein-protein interaction network, and 106 signal pathways, 76 biological processes, 26 cell components and 50 molecular functions were enriched (P<0.05). Through the compound-target-pathway network, the key compounds that play a role in the prevention and treatment of CIRI, such as acacetin, apigenin and other flavonoids, as well as the corresponding key targets and key signal pathways, such as AKT1, SRC and EGFR were obtained. TFDM significantly decreased LDH, MDA levels and increased the NO activity levels in CIRI. Further studies have shown that TFDM increases the number of SRC proteins, and TFDM also increases p-AKT/ AKT. Molecular docking results showed that acacetin-7-O (- 6"-acetyl) -glucopyranoside, acacetin7-O-β-D-glucopyranoside, apigenin-7-O-β-D-galactoside respectively had good affinity for SRC protein. Acacetin-7-O (- 6"-acetyl) -glucopyranoside,acacetin-7-O-β-D-glucuronide, acacetin7-O-β-D-glucopyranoside had good affinity for AKT1 protein, respectively. Conclusion: Our research showed that TFDM had the characteristics of multi-component, multi-target and multi-channel in the treatment of CIRI. The potential mechanism may be associated with the following signaling pathways:1) the signaling pathways of VEGF/SRC, which promote angiogenesis, 2) the signaling pathways of PI3K/AKT, which inhibit apoptosis, and 3) acacetin-7-O (- 6"-acetyl) -glucopyranoside is expected to be used as a candidate monomer component for natural drugs for further development. [ABSTRACT FROM AUTHOR]

The druggability of small-molecule binding sites can be significantly affected by protein motions and conformational changes. Ligand binding, protein dynamics and protein function have been shown to be closely interconnected in myosins. The breakthrough discovery of omecamtiv mecarbil (OM) has led to an increased interest in small molecules that can target myosin and modulate its function for therapeutic purposes (myosin modulators). In this work, we use a combination of computational methods, including steered molecular dynamics, umbrella sampling and binding pocket tracking tools, to follow the evolution of the OM binding site during the recovery stroke transition of human β-cardiac myosin. We found that steering two internal coordinates of the motor domain can recapture the main features of the transition and in particular the rearrangements of the binding site, which shows significant changes in size, shape and composition. Possible intermediate conformations were also identified, in remarkable agreement with experimental findings. The differences in the binding site properties observed along the transition can be exploited for the future development of conformation-selective myosin modulators. Author summary: Small molecules, including drugs, tend to bind to crevices or pockets on the surface of proteins. The shape, size and composition of these binding sites can change as a result of the protein dynamics. This is particularly important if the motions that modulate the binding site are linked to the function of the protein, since molecules that can selectively target different binding site states will likely have different effects on the protein function. In this work we focus on β-cardiac myosin, a key protein for heart contraction that has become the subject of intensive research in recent years because of the therapeutic potential of its small-molecule modulators. Using computational techniques, we show how the binding site of the first-in-class cardiac myosin activator omecamtiv mecarbil changes during the recovery stroke, one of the main functional motions of the protein. Importantly, we identify features in the shape, size and composition of the site that can be exploited for the development of drugs that can target different stages of the recovery stroke and thus have different types of biological effects. [ABSTRACT FROM AUTHOR]

The active global SARS-CoV-2 pandemic caused more than 426 million cases and 5.8 million deaths worldwide. The development of completely new drugs for such a novel disease is a challenging, time intensive process. Despite researchers around the world working on this task, no effective treatments have been developed yet. This emphasizes the importance of drug repurposing, where treatments are found among existing drugs that are meant for different diseases. A common approach to this is based on knowledge graphs, that condense relationships between entities like drugs, diseases and genes. Graph neural networks (GNNs) can then be used for the task at hand by predicting links in such knowledge graphs. Expanding on state-of-the-art GNN research, Doshi et al. recently developed the Dr-COVID model. We further extend their work using additional output interpretation strategies. The best aggregation strategy derives a top-100 ranking of 8,070 candidate drugs, 32 of which are currently being tested in COVID-19-related clinical trials. Moreover, we present an alternative application for the model, the generation of additional candidates based on a given pre-selection of drug candidates using collaborative filtering. In addition, we improved the implementation of the Dr-COVID model by significantly shortening the inference and pre-processing time by exploiting data-parallelism. As drug repurposing is a task that requires high computation and memory resources, we further accelerate the post-processing phase using a new emerging hardware—we propose a new approach to leverage the use of high-capacity Non-Volatile Memory for aggregate drug ranking. [ABSTRACT FROM AUTHOR]

Non-alcoholic steatohepatitis (NASH) is the progressive form of nonalcoholic fatty liver disease (NAFLD) and a disease with high unmet medical need. Platform trials provide great benefits for sponsors and trial participants in terms of accelerating drug development programs. In this article, we describe some of the activities of the EU-PEARL consortium (EU Patient-cEntric clinicAl tRial pLatforms) regarding the use of platform trials in NASH, in particular the proposed trial design, decision rules and simulation results. For a set of assumptions, we present the results of a simulation study recently discussed with two health authorities and the learnings from these meetings from a trial design perspective. Since the proposed design uses co-primary binary endpoints, we furthermore discuss the different options and practical considerations for simulating correlated binary endpoints. [ABSTRACT FROM AUTHOR]

Accurate prediction of synergistic effects of drug combinations can reduce the experimental costs for drug development and facilitate the discovery of novel efficacious combination therapies for clinical studies. The drug combinations with high synergy scores are regarded as synergistic ones, while those with moderate or low synergy scores are additive or antagonistic ones. The existing methods usually exploit the synergy data from the aspect of synergistic drug combinations, paying little attention to the additive or antagonistic ones. Also, they usually do not leverage the common patterns of drug combinations across different cell lines. In this paper, we propose a multi-channel graph autoencoder (MGAE)-based method for predicting the synergistic effects of drug combinations (DC), and shortly denote it as MGAE-DC. A MGAE model is built to learn the drug embeddings by considering not only synergistic combinations but also additive and antagonistic ones as three input channels. The later two channels guide the model to explicitly characterize the features of non-synergistic combinations through an encoder-decoder learning process, and thus the drug embeddings become more discriminative between synergistic and non-synergistic combinations. In addition, an attention mechanism is incorporated to fuse each cell-line's drug embeddings across various cell lines, and a common drug embedding is extracted to capture the invariant patterns by developing a set of cell-line shared decoders. The generalization performance of our model is further improved with the invariant patterns. With the cell-line specific and common drug embeddings, our method is extended to predict the synergy scores of drug combinations by a neural network module. Experiments on four benchmark datasets demonstrate that MGAE-DC consistently outperforms the state-of-the-art methods. In-depth literature survey is conducted to find that many drug combinations predicted by MGAE-DC are supported by previous experimental studies. The source code and data are available at https://github.com/yushenshashen/MGAE-DC. Author summary: Drug combination therapy is widely employed for various complex diseases because of its advantages of enhancing the efficiency, overcoming the drug resistance and reducing dose-dependent toxicity relative to monotherapy. To identify novel reliable and efficacious drug combinations for the patients, various methods have been proposed in the past decades. The trial-based methods are based on the clinical trials directly, but may cause patients to receive unnecessary or even harmful treatments. The experimental methods are labour and cost intensive, it is infeasible to test the complete drug combination space due to the combinatorial explosion. Computational methods provide attractive solutions to make the prediction based on the known data in silico, and thus narrow down the searching range of potential combinations. We have developed a novel deep learning method, named MGAE-DC, for predicting the synergistic effects of drug combinations. Our method explicitly characterizes not only synergistic combinations but also non-synergistic ones to obtain discriminative drug embeddings. Our method also learns common features of drug combinations across the cell lines for improved generalization performance. Computational experiments have verified the effectiveness of MGAE-DC. [ABSTRACT FROM AUTHOR]

The importance of human cell-based in vitro tools to drug development that are robust, accurate, and predictive cannot be understated. There has been significant effort in recent years to develop such platforms, with increased interest in 3D models that can recapitulate key aspects of biology that 2D models might not be able to deliver. We describe the development of a 3D human cell-based in vitro assay for the investigation of nephrotoxicity, using RPTEC-TERT1 cells. These RPTEC-TERT1 proximal tubule organoids 'tubuloids' demonstrate marked differences in physiologically relevant morphology compared to 2D monolayer cells, increased sensitivity to nephrotoxins observable via secreted protein, and with a higher degree of similarity to native human kidney tissue. Finally, tubuloids incubated with nephrotoxins demonstrate altered Na+/K+-ATPase signal intensity, a potential avenue for a high-throughput, translatable nephrotoxicity assay. [ABSTRACT FROM AUTHOR]

To achieve homeostasis, the human biological system relies on the interaction between organs through the binding of ligands secreted from source organs to receptors located on destination organs. Currently, the changing roles that receptors perform in tissues are only partially understood. Recently, a methodology based on receptor co-expression patterns to classify their tissue-specific metabolic functions was suggested. Here we present an advanced framework to predict an additional class of inflammatory receptors that use a feature space of biological pathway enrichment analysis scores of co-expression networks and their eigengene correlations. These are fed into three machine learning classifiers–eXtreme Gradient Boosting (XGBoost), Support Vector Machines (SVM), and K-Nearest Neighbors (k-NN). We applied our methodology to subcutaneous and visceral adipose gene expression datasets derived from the GTEx (Genotype-Tissue Expression) project and compared the predictions. The XGBoost model demonstrated the best performance in predicting the pre-labeled receptors, with an accuracy of 0.89/0.8 in subcutaneous/visceral adipose. We analyzed ~700 receptors to predict eight new metabolic and 15 new inflammatory functions of receptors and four new metabolic functions for known inflammatory receptors in both adipose tissues. We cross-referenced multiple predictions using the published literature. Our results establish a picture of the changing functions of receptors for two adipose tissues that can be beneficial for drug development. [ABSTRACT FROM AUTHOR]

Drug-induced toxicity damages the health and is one of the key factors causing drug withdrawal from the market. It is of great significance to identify drug-induced target-organ toxicity, especially the detailed pathological findings, which are crucial for toxicity assessment, in the early stage of drug development process. A large variety of studies have devoted to identify drug toxicity. However, most of them are limited to single organ or only binary toxicity. Here we proposed a novel multi-label learning model named Att-RethinkNet, for predicting drug-induced pathological findings targeted on liver and kidney based on toxicogenomics data. The Att-RethinkNet is equipped with a memory structure and can effectively use the label association information. Besides, attention mechanism is embedded to focus on the important features and obtain better feature presentation. Our Att-RethinkNet is applicable in multiple organs and takes account the compound type, dose, and administration time, so it is more comprehensive and generalized. And more importantly, it predicts multiple pathological findings at the same time, instead of predicting each pathology separately as the previous model did. To demonstrate the effectiveness of the proposed model, we compared the proposed method with a series of state-of-the-arts methods. Our model shows competitive performance and can predict potential hepatotoxicity and nephrotoxicity in a more accurate and reliable way. The implementation of the proposed method is available at https://github.com/RanSuLab/Drug-Toxicity-Prediction-MultiLabel. Author summary: Drug-induced toxicity damages the health and is one of the key factors causing drug withdrawal from the market. Hence, to fully assess drug-induced toxicity, it is important to predict the detailed pathological findings, which are also crucial for toxicity mechanism understanding. However, most of the existing toxicity studies only predict binary toxicity (the toxicity or non-toxicity) or only predict the toxicity targeting single organ. The pathological findings of multiple organs are not well explored. Here we show, through the proposed Att-RethinkNet, it is possible to predict drug-induced pathological findings on both liver and kidney. Our results suggest that the Att-RethinkNet predicts potential hepatotoxicity and nephrotoxicity in a more accurate and reliable way, and it is applicable in multiple organs and takes account the compound type, dose, and administration time, so it is more comprehensive and generalized than the existing methods. The accurate prediction of pathological findings on multiple organs may benefit drug development. [ABSTRACT FROM AUTHOR]

Moraxella catarrhalis (M. catarrhalis) is a gram-negative bacterium, responsible for major respiratory tract and middle ear infection in infants and adults. The recent emergence of the antibiotic resistance M. catarrhalis demands the prioritization of an effective drug target as a top priority. Fortunately, the failure of new drugs and host toxicity associated with traditional drug development approaches can be avoided by using an in silico subtractive genomics approach. In the current study, the advanced in silico genome subtraction approach was applied to identify potential and pathogen-specific drug targets against M. catarrhalis. We applied a series of subtraction methods from the whole genome of pathogen based on certain steps i.e. paralogous protein that have extensive homology with humans, essential, drug like, non-virulent, and resistant proteins. Only 38 potent drug targets were identified in this study. Eventually, one protein was identified as a potential new drug target and forwarded to the structure-based studies i.e. histidine kinase (UniProt ID: D5VAF6). Furthermore, virtual screening of 2000 compounds from the ZINC database was performed against the histidine kinase that resulted in the shortlisting of three compounds as the potential therapeutic candidates based on their binding energies and the properties exhibited using ADMET analysis. The identified protein gives a platform for the discovery of a lead drug candidate that may inhibit it and may help to eradicate the otitis media caused by drug-resistant M. catarrhalis. Nevertheless, the current study helped in creating a pipeline for drug target identification that may assist wet-lab research in the future. [ABSTRACT FROM AUTHOR]

Copper is an essential micronutrient for most organisms that is required as a cofactor for crucial copper-dependent enzymes encoded by both prokaryotes and eukaryotes. Evidence accumulated over several decades has shown that copper plays important roles in the function of the mammalian immune system. Copper accumulates at sites of infection, including the gastrointestinal and respiratory tracts and in blood and urine, and its antibacterial toxicity is directly leveraged by phagocytic cells to kill pathogens. Copper-deficient animals are more susceptible to infection, whereas those fed copper-rich diets are more resistant. As a result, copper resistance genes are important virulence factors for bacterial pathogens, enabling them to detoxify the copper insult while maintaining copper supply to their essential cuproenzymes. Here, we describe the accumulated evidence for the varied roles of copper in the mammalian response to infections, demonstrating that this metal has numerous direct and indirect effects on immune function. We further illustrate the multifaceted response of pathogenic bacteria to the elevated copper concentrations that they experience when invading the host, describing both conserved and species-specific adaptations to copper toxicity. Together, these observations demonstrate the roles of copper at the host–pathogen interface and illustrate why bacterial copper detoxification systems can be viable targets for the future development of novel antibiotic drug development programs. Author summary: Copper is required by both animals and bacteria in small quantities as a micronutrient. During infection, the mammalian immune system increases the local concentration of copper, which gives rise to copper toxicity in the pathogen. In turn, bacterial pathogens possess specialized systems to resist this copper toxicity. Copper also plays important, indirect roles in the function of the immune system. In this review, we explain the diverse roles of copper in the human body with a focus on its functions within the immune system. We also describe how bacterial pathogens respond to the copper toxicity that they experience within the host during infection, illustrating both conserved copper homeostasis and detoxification systems in bacteria and species-specific adaptations that have been shown to be important to pathogenicity. The key role of copper at the host–pathogen interface and the essential requirement for pathogenic bacteria to resist copper toxicity makes the protein components that confer resistance on pathogens potential targets for future development of novel antibiotic drugs. [ABSTRACT FROM AUTHOR]

Computational drug repositioning aims to identify potential applications of existing drugs for the treatment of diseases for which they were not designed. This approach can considerably accelerate the traditional drug discovery process by decreasing the required time and costs of drug development. Tensor decomposition enables us to integrate multiple drug- and disease-related data to boost the performance of prediction. In this study, a nonnegative tensor decomposition for drug repositioning, NTD-DR, is proposed. In order to capture the hidden information in drug-target, drug-disease, and target-disease networks, NTD-DR uses these pairwise associations to construct a three-dimensional tensor representing drug-target-disease triplet associations and integrates them with similarity information of drugs, targets, and disease to make a prediction. We compare NTD-DR with recent state-of-the-art methods in terms of the area under the receiver operating characteristic (ROC) curve (AUC) and the area under the precision and recall curve (AUPR) and find that our method outperforms competing methods. Moreover, case studies with five diseases also confirm the reliability of predictions made by NTD-DR. Our proposed method identifies more known associations among the top 50 predictions than other methods. In addition, novel associations identified by NTD-DR are validated by literature analyses. [ABSTRACT FROM AUTHOR]

Tau protein is a key target of interest in developing therapeutics for neurodegenerative diseases. Here, we sought to develop a method that quantifies extracellular tau protein concentrations in human cerebrospinal fluid (CSF) without antibody-based enrichment strategies. We demonstrate that the fit-for-purpose validated method in Alzheimer's Disease CSF is limited to quasi quantitative measures of tau surrogate peptides. We also provide evidence that CSF total Tau measures by LC-MS are feasible in the presence of monoclonal therapeutic antibodies in human CSF. Our Tau LC-MS/MS method is a translational bioanalytical tool for assaying target engagement and pharmacodynamics for anti-tau antibody drug development campaigns. [ABSTRACT FROM AUTHOR]

Rare disease clinical trials are constrained to small sample sizes and may lack placebo-control, leading to challenges in drug development. This paper proposes a Bayesian model-based framework for early go/no-go decision making in rare disease drug development, using Duchenne muscular dystrophy (DMD) as an example. Early go/no-go decisions were based on projections of long-term functional outcomes from a Bayesian model-based analysis of short-term trial data informed by prior knowledge based on 6MWT natural history literature data in DMD patients. Frequentist hypothesis tests were also applied as a reference analysis method. A number of combinations of hypothetical trial designs, drug effects and cohort comparison methods were assessed. The proposed Bayesian model-based framework was superior to the frequentist method for making go/no-go decisions across all trial designs and cohort comparison methods in DMD. The average decision accuracy rates across all trial designs for the Bayesian and frequentist analysis methods were 45.8 and 8.98%, respectively. A decision accuracy rate of at least 50% was achieved for 42 and 7% of the trial designs under the Bayesian and frequentist analysis methods, respectively. The frequentist method was limited to the short-term trial data only, while the Bayesian methods were informed with both the short-term data and prior information. The specific results of the DMD case study were limited due to incomplete specification of individual-specific covariates in the natural history literature data and should be reevaluated using a full natural history dataset. These limitations aside, the framework presented provides a proof of concept for the utility of Bayesian model-based methods for decision making in rare disease trials. [ABSTRACT FROM AUTHOR]

Gallbladder cancer (GBC) is the most common biliary tract malignancy with a dismal prognosis. The development of new drugs may help to improve prognosis. This study found that fangchinoline, a bisbenzylisoquinoline alkaloids, inhibited the proliferation and clone formation of GBC cells in a dose-dependent manner. Moreover, Hoechst staining, TUNEL assays, and flow cytometry demonstrated that fangchinoline effectively induced apoptosis in GBC cells. Further studies found that an anti-apoptotic pathway, the PI3K/Akt/XIAP axis, was significantly inhibited in GBC cells after treating with fangchinoline. Finally, we confirmed that fangchinoline restrained xenograft tumor growth in vivo. Our findings indicate that fangchinoline can be considered a potential drug for GBC treatment. [ABSTRACT FROM AUTHOR]

Pediatric legislations in the European Union (EU) and the United States (US) have increased medicines approved for use in the pediatric population. Despite many similarities between these frameworks, the EU Paediatric Regulation more often provides regulators with a mandate to require pediatric drug development for novel medicinal products compared to US regulators. If used, this could give rise to differences in the guidance for pediatric use provided for clinicians in the two regions. However, the level of discordance in the guidance for pediatric use between the two regions is unknown. This cross-sectional study compares guidance for pediatric use in the EU Summary of Product Characteristics (SmPC) and the US Prescription Information (USPI) on the level of indications granted for novel medicinal products approved after the pediatric legislations came in to force in both regions. For all indications granted as of March 2020 for novel medicinal products approved in both regions between 2010 and 2018, we compared the guidance for pediatric use in the EU SmPC and the USPI. The guidance for pediatric use differed for 18% (61/348) of the listed indications covering 21% (45/217) of the products, but without the guidance being contradictory. Where guidance differed, an equal share was observed for indications with a higher level of information for pediatric use in one region over the other (49% (30/61) in the US; 51% (31/61) in the EU). The discrepancies in pediatric information could be explained by differences in regulations for 21% (13/61) of the indications. Only a few conditions and diseases (EU n = 4; US n = 1) were observed to cover potential pediatric use outside the approved adult indication. Although the EU Paediatric Regulation more often provides regulators a mandate for requiring pediatric drug development as compared to the US PREA, this was not reflected in the prescription information approved by the two regulatory authorities. [ABSTRACT FROM AUTHOR]

Toxoplasmosis is caused by Toxoplasma gondii and in immunocompromised patients, it may lead to seizures, encephalitis or death. The conserved enzyme prolyl-tRNA synthetase (PRS) is a validated druggable target in Toxoplasma gondii but the traditional 'single target–single drug' approach has its caveats. Here we describe two potent inhibitors namely halofuginone (HFG) and a novel ATP mimetic (L95) that bind to Toxoplasma gondii PRS simultaneously at different neighbouring sites to cover all three of the enzyme substrate subsites. HFG and L95 act as one triple-site inhibitor in tandem and form an unusual ternary complex wherein HFG occupies the 3'-end of tRNA and the L-proline (L-pro) binding sites while L95 occupies the ATP pocket. These inhibitors exhibit nanomolar IC50 and EC50 values independently, and when given together reveal an additive mode of action in parasite inhibition assays. This work validates a novel approach and lays a structural framework for further drug development based on simultaneous targeting of multiple pockets to inhibit druggable proteins. Author summary: Among infectious diseases, parasitic diseases are a major cause of death and morbidity. Toxoplasmosis is caused by an infection of the apicomplexan parasite Toxoplasma gondii. In immunocompromised patients Toxoplasmosis may lead to seizures, encephalitis or death. Novel therapeutics for human parasites are constantly needed. In recent years, the aminoacyl-tRNA synthetase (aaRS) enzyme family has been validated as a drug target for several parasitic infections. The Toxoplasma gondii prolyl-tRNA synthetase inhibitor halofuginone (HFG) has been validated earlier but here we show that an ATP-mimic called L95 is a potent inhibitor and can bind to the target enzyme in the presence of HFG. Thus the two inhibitors described in this study simultaneously occupy all three natural substrate (ATP, L-amino acid and 3'end of tRNA) binding pockets and thereby inhibit the enzyme leading to parasite death. This unprecedented double drugging of a pathogen enzyme may delay resistance mutation generation and this approach opens the path to multi-drugging of validated parasite proteins. [ABSTRACT FROM AUTHOR]

Background: To accelerate the progress towards onchocerciasis elimination, a macrofilaricidal drug that kills the adult parasite is urgently needed. Emodepside has shown macrofilaricidal activity against a variety of nematodes and is currently under clinical development for the treatment of onchocerciasis. The aims of this study were i) to characterize the population pharmacokinetic properties of emodepside, ii) to link its exposure to adverse events in healthy volunteers, and iii) to propose an optimized dosing regimen for a planned phase II study in onchocerciasis patients. Methodology / Principal findings: Plasma concentration-time profiles and adverse event data were obtained from 142 subjects enrolled in three phase I studies, including a single-dose, and a multiple-dose, dose-escalation study as well as a relative bioavailability study. Nonlinear mixed-effects modeling was used to evaluate the population pharmacokinetic properties of emodepside. Logistic regression modeling was used to link exposure to drug-related treatment-emergent adverse events (TEAEs). Emodepside pharmacokinetics were well described by a transit-absorption model, followed by a 3-compartment disposition model. Body weight was included as an allometric function and both food and formulation had a significant impact on absorption rate and relative bioavailability. All drug-related TEAEs were transient, and mild or moderate in severity. An increase in peak plasma concentration was associated with an increase in the odds of experiencing a drug-related TEAE of interest. Conclusions/Significance: Pharmacokinetic modeling and simulation was used to derive an optimized, body weight-based dosing regimen, which allows for achievement of extended emodepside exposures above target concentrations while maintaining acceptable tolerability margins. Author summary: Onchocerciasis ('River Blindness'), is a worm infection common in sub-Saharan Africa. More than 20 million people are suffering from the disease which can lead to disfiguring skin disease, visual impairment and permanent blindness. The currently recommended treatment is ivermectin, which kills the juvenile worms and reduces the severity of the symptoms, but fails to kill the adult worm. As a consequence, the treatment needs to be repeated for 10–15 years (life span of the adult worm), imposing a large burden on patients and communities. Hence, there is an urgent need for a new, safe and short-course drug that kills the adult worm and offers a rapid cure. Emodepside is a promising drug candidate which has recently been administered to healthy volunteers for the first time. In this study, we characterized the relationship between dose, systemic exposure in human and the probability of experiencing an adverse event. Modeling and simulation were used to propose a short-course dosing regimen which balances risks and benefits in order to achieve efficacy while maintaining safety. Our results support the further clinical development of emodepside thus contributing to onchocerciasis elimination efforts. [ABSTRACT FROM AUTHOR]

This paper studies the pharmaceutical production supply chain system composed of upstream and downstream pharmaceutical enterprises, and explores the impact of government subsidy strategies on the new drug research and development (R&D) decision variables and profits of pharmaceutical enterprises as well as social welfare, when considering both the horizontal spillover effects within the industry and the vertical spillover effects between industries. Comparing and analyzing the impact of these strategies including non-government subsidy strategy, pharmaceutical enterprise innovation input subsidy strategy, pharmaceutical enterprise innovative product subsidy strategy, patient price subsidy strategy, and patient medical insurance subsidy strategy. By establishing a four-stage Cournot duopoly model incorporating spillover effects, the equilibrium solutions are obtained by backward induction, and the impact of spillover effects on decision variables is investigated accordingly. Studies have shown that: (a) Government subsidy strategies can promote pharmaceutical enterprises' R&D investment and have a positive incentive effect on the pharmaceutical enterprises' profits and social welfare. (b) The patient medical insurance subsidy strategy is the optimal subsidy strategy, which can generate higher profits for pharmaceutical enterprises and higher social welfare. (c) The horizontal and vertical spillover effects have different effect on decision variables, enterprises' profits and social welfare under various subsidy strategies. [ABSTRACT FROM AUTHOR]

The increasing incidence of prostate cancer (PCa) indicates an urgent need for the development of new effective drug therapy. There are limited options to treat the PCa, this study tried to determine a new therapy option for this acute cancer. Androgen-independent PCa cell lines PC3 and DU145 were treated with different melatonin concentrations (0.1~3.5 mM) for 1~3 days and assessed cell migration, cell invasion, cycle arrest in G0/G1 phase as well as apoptosis. We utilized RNA-seq technology to analyze the transcriptional misregulation pathways in DU145 prostate cancer cell line with melatonin (0.5 mM) treatment. Data revealed 20031 genes were up and down-regulated, there were 271 genes that differentially expressed: 97 up-regulated (P<0.05) and 174 down-regulated (P<0.05) genes. Furthermore, RNA-seq results manifested that the melatonin treatment led to a significant increase in the expression levels of HPGD, IL2Rβ, NGFR, however, IGFBP3 and IL6 (P <0.05) had decreased expression levels. The immunoblot assay revealed the expression of IL2Rβ and NGFR genes was up-regulated, qPCR confirmed the gene expression of HPGD and IL2RB were also up-regulated in Du145 cells. Consequently, we probed mechanisms that generate kinetic patterns of NF-κB-dependent gene expression in PCa cells responding to a NF-κB-activation, the significant results were indicated by the inhibition of the NF-kB pathway via IL2Rβ actions. Based on our investigation, it could be concluded that melatonin is a chemotherapeutic molecule against PCa and provides a new idea for clinical therapy of PCa. [ABSTRACT FROM AUTHOR]

HIV pre-exposure prophylaxis (PrEP) is dominated by clinical therapeutic antiretroviral (ARV) drugs. Griffithsin (GRFT) is a non-ARV lectin with potent anti-HIV activity. GRFT's preclinical safety, lack of systemic absorption after vaginal administration in animal studies, and lack of cross-resistance with existing ARV drugs prompted its development for topical HIV PrEP. We investigated safety, pharmacokinetics (PK), pharmacodynamics (PD), and immunogenicity of PC-6500 (0.1% GRFT in a carrageenan (CG) gel) in healthy women after vaginal administration. This randomized, placebo-controlled, parallel group, double-blind first-in-human phase 1 study enrolled healthy, HIV-negative, non-pregnant women aged 24–45 years. In the open label period, all participants (n = 7) received single dose of PC-6500. In the randomized period, participants (n = 13) were instructed to self-administer 14 doses of PC-6500 or its matching CG placebo (PC-535) once daily for 14 days. The primary outcomes were safety and PK after single dose, and then after 14 days of dosing. Exploratory outcomes were GRFT concentrations in cervicovaginal fluids, PD, inflammatory mediators and gene expression in ectocervical biopsies. This trial is registered with ClinicalTrials.gov, number NCT02875119. No significant adverse events were recorded in clinical or laboratory results or histopathological evaluations in cervicovaginal mucosa, and no anti-drug (GRFT) antibodies were detected in serum. No cervicovaginal proinflammatory responses and no changes in the ectocervical transcriptome were evident. Decreased levels of proinflammatory chemokines (CXCL8, CCL5 and CCL20) were observed. GRFT was not detected in plasma. GRFT and GRFT/CG in cervicovaginal lavage samples inhibited HIV and HPV, respectively, in vitro in a dose-dependent fashion. These data suggest GRFT formulated in a CG gel is a safe and promising on-demand multipurpose prevention technology product that warrants further investigation. [ABSTRACT FROM AUTHOR]

A continuing challenge in modern medicine is the identification of safer and more efficacious drugs. Precision therapeutics, which have one molecular target, have been long promised to be safer and more effective than traditional therapies. This approach has proven to be challenging for multiple reasons including lack of efficacy, rapidly acquired drug resistance, and narrow patient eligibility criteria. An alternative approach is the development of drugs that address the overall disease network by targeting multiple biological targets ('polypharmacology'). Rational development of these molecules will require improved methods for predicting single chemical structures that target multiple drug targets. To address this need, we developed the Multi-Targeting Drug DREAM Challenge, in which we challenged participants to predict single chemical entities that target pro-targets but avoid anti-targets for two unrelated diseases: RET-based tumors and a common form of inherited Tauopathy. Here, we report the results of this DREAM Challenge and the development of two neural network-based machine learning approaches that were applied to the challenge of rational polypharmacology. Together, these platforms provide a potentially useful first step towards developing lead therapeutic compounds that address disease complexity through rational polypharmacology. Author summary: Many modern drugs are developed with the goal of modulating a single cellular pathway or target. However, many drugs are, in fact, 'dirty;' they target multiple cellular pathways or targets. This phenomenon is known as multi-targeting or polypharmacology. While some strive to develop 'cleaner' therapeutics that eliminate secondary targets, recent work has shown that multi-targeting therapeutics have key advantages for a variety of diseases. However, while multi-targeting drugs that affect a precisely-defined profile of targets may be more effective, it is difficult to computationally predict which molecules have desirable target profiles. Here, we report the results of a competitive crowdsourcing project (the Multi-Targeting Drug DREAM Challenge), where we challenged participants to predict chemicals that have desired target profiles for cancer and neurodegenerative disease. [ABSTRACT FROM AUTHOR]

Labelling of therapeutic antibodies with radionuclides or fluorophores is routinely used to study their pharmacokinetic properties. A critical assumption in utilizing labelled therapeutic antibodies is that the label has no unfavourable effects on antibody charge, hydrophobicity, or receptor affinity. Ideally, the labelled protein should not have any significant deviations from the physiological properties of the original molecule. This article describes an established quality in vitro assessment workflow for labelled antibodies that ensures better prediction of changes in antibody pharmacokinetic (PK) properties after modifications. This analysis package considers degradation and aggregation analysis by size-exclusion chromatography, changes in neonatal-Fc-receptor (FcRn) affinity, and heparin interaction. FcRn binding is important for antibody recycling and half-life extension, whereas heparin affinity provides estimates on the rate of endocytosis through unspecific cell surface binding. Additionally, mass spectrometric analysis to determine the degree of labelling (DoL) completes the package and the combined analysis data allow to predict the label contribution to the PK properties of the modified antibody. This analytical strategy for labelling 11 IgGs has been investigated using 2 different IgG1 constructs and applying 7 different types of labels. Each labelling resulted in a change in the physicochemical properties of the protein. Not only can the DoL of modified IgGs lead to a change in protein properties, but the type of label also can. Furthermore, it was demonstrated that the labelling process can also influence the behaviour of labelled mAbs. An identical label on different constructs of IgG1 can cause different affinities for FcRn and heparin. Considering the assessment data, only 6 of the 11 modified antibodies from this study can be recommended for subsequent experiments. In conclusion, a suitability assessment of labelled antibodies prior to any pharmacokinetic studies is essential to reduce cost, allocate resources and reduce the number of animal experiments during pre-clinical drug development. [ABSTRACT FROM AUTHOR]

The high prevalence of morbidity and mortality from bacterial infections, together with the growing threat of antibacterial resistance, necessitated the development of alternative new drugs from traditional medicine. In Ethiopia, Impatiens tinctoria A. Rich has been traditionally used for the treatment of fungal infections such as ringworms that cause tinea pedis and it have also different medical values. Scientific information on its biological activity against a broad range of bacteria and safety data is scant, compared to its folklore data. In this study, we evaluated antibacterial activities and acute oral toxicity of aqueous, ethanol and ethyl acetate root extracts of Impatiens tinctoria A. Rich. Aqueous, ethanol and ethyl acetate extracts of the plant were evaluated using agar hole diffusion and agar dilution methods. Biological activities of the plant extracts were expressed as a zone of inhibition diameter, minimum inhibitory concentration (mg/ml), and minimum bactericidal concentration (mg/ml). The safety studies were performed by oral acute toxicity study according to the organization of economic cooperation and development test Guidelines 420.Gram-positive bacteria were more susceptible to the extracts compared to gram-negative bacteria, especially against S. aureus and S. epidermidis, which are commonly found in the skin. Ethyl acetate extract was more potent than ethanol and aqueous extracts. The 50% lethal dose (LD50) of tested mice was above 9600 mg/kg. This study provides a scientific basis for the antibacterial activity of the root extracts of I. tinctoria A. Rich, where, the ethyl acetate extract showed the most promising activity. Therefore, the antibacterial potential and practical non-toxicity of the study plant extracts suggested the possibility of using it for the development of antimicrobial drugs by further studying the plant in different directions. [ABSTRACT FROM AUTHOR]

Nontuberculosis mycobacterial (NTM) infections are increasing in prevalence across the world. In many cases, treatment options for these infections are limited. However, there has been progress in recent years in the development of new antimycobacterial drugs. Here, we investigate the in vitro activity of SPR719, a novel aminobenzimidazole antibiotic and the active form of the clinical-stage compound, SPR720, against several isolates of Mycobacterium ulcerans, Mycobacterium marinum and Mycobacterium chimaera. We show that SPR719 is active against these NTM species with a MIC range of 0.125–4 μg/ml and that this compares favorably with the commonly utilized antimycobacterial antibiotics, rifampicin and clarithromycin. Our findings suggest that SPR720 should be further evaluated for the treatment of NTM infections. Author summary: Nontuberculosis mycobacteria represent a large group of diverse bacteria that live across a range of environments. Human contact with the habitats in which these organisms live can result in opportunistic infections. Among the NTM, Mycobacterium ulcerans causes necrotic skin ulcers that can lead to significant long term physical impairment; Mycobacterium marinum causes granulomatous skin lesions; and Mycobacterium chimaera has been linked to contaminated heater-cooler units used during cardiac surgery, resulting in prosthetic heart valve infections that are particularly difficult to treat. We performed laboratory experiments to test the susceptibility of these NTM species (M. ulcerans, M. marinum and M. chimaera) to a recently developed antibiotic, SPR719. We found that SPR719 inhibits the growth of these mycobacteria at concentration ranges similar to or better than commonly used anti-mycobacterial antibiotics. As SPR720, the oral prodrug of SPR719, has recently completed a Phase I safety, tolerability and PK study in healthy human volunteers, the potential exists for this product to be explored for the treatment of NTM infections, where new treatment options are urgently needed. [ABSTRACT FROM AUTHOR]

Background: The identification of a target-indication pair is regarded as the first step in a traditional drug discovery and development process. Significant investment and attrition occur during discovery and development before a molecule is shown to be safe and efficacious for the selected indication and becomes an approved drug. Many drug targets are functionally pleiotropic and might be good targets for multiple indications. Methodologies that leverage years of scientific contributions on drug targets to allow systematic evaluation of other indication opportunities are critical for both patients and drug discovery and development scientists. Methods: We introduced a network-based approach to systematically screen and prioritize disease indications for drug targets. The approach fundamentally integrates disease genomics data and protein interaction network. Further, the methodology allows for indication identification by leveraging state-of-art network algorithms to generate and compare the target and disease subnetworks. Results: We first evaluated the performance of our method on recovering FDA approved indications for 15 randomly selected drug targets. The results showed superior performance when compared with other state-of-art approaches. Using this approach, we predicted novel indications supported by literature evidence for several highly pursued drug targets such as IL12/IL23 combination. Conclusions: Our results demonstrated a potential global approach for indication expansion strategies. The proposed methodology enables rapid and systematic evaluation of both individual and combined drug targets for novel indications. Additionally, this approach provides novel insights on expanding the role of genes and pathways for developing therapeutic intervention strategies. [ABSTRACT FROM AUTHOR]

Background: Glioblastoma (GBM) is the most common malignant brain tumour among adult patients and represents an almost universally fatal disease. Novel therapies for GBM are being developed under the orphan drug legislation and the knowledge on the molecular makeup of this disease has been increasing rapidly. However, the clinical outcomes in GBM patients with currently available therapies are still dismal. An insight into the current drug development pipeline for GBM is therefore of particular interest. Objectives: To provide a quantitative clinical-regulatory insight into the status of FDA orphan drug designations for compounds intended to treat GBM. Methods: Quantitative cross-sectional analysis of the U.S. Food and Drug Administration Orphan Drug Product database between 1983 and 2020. STROBE criteria were respected. Results: Four orphan drugs out of 161 (2,4%) orphan drug designations were approved for the treatment for GBM by the FDA between 1983 and 2020. Fourteen orphan drug designations were subsequently withdrawn for unknown reasons. The number of orphan drug designations per year shows a growing trend. In the last decade, the therapeutic mechanism of action of designated compounds intended to treat glioblastoma shifted from cytotoxic drugs (median year of designation 2008) to immunotherapeutic approaches and small molecules (median year of designation 2014 and 2015 respectively) suggesting an increased focus on precision in the therapeutic mechanism of action for compounds the development pipeline. Conclusion: Despite the fact that current pharmacological treatment options in GBM are sparse, the drug development pipeline is steadily growing. In particular, the surge of designated immunotherapies detected in the last years raises the hope that elaborate combination possibilities between classical therapeutic backbones (radiotherapy and chemotherapy) and novel, currently experimental therapeutics may help to provide better therapies for this deadly disease in the future. [ABSTRACT FROM AUTHOR]

Drug-induced liver injury (DILI) is one of major causes of discontinuing drug development and withdrawing drugs from the market. In this study, we investigated chemical properties associated with DILI using in silico methods, to identify a physicochemical property useful for DILI screening at the early stages of drug development. Total of 652 drugs, including 432 DILI-positive drugs (DILI drugs) and 220 DILI-negative drugs (no-DILI drugs) were selected from Liver Toxicity Knowledge Base of US Food and Drug Administration. Decision tree models were constructed using 2,473 descriptors as explanatory variables. In the final model, the descriptor AMW, representing average molecular weight, was found to be at the first node and showed the highest importance value. With AMW alone, 276 DILI drugs (64%) and 156 no-DILI drugs (71%) were correctly classified. Discrimination with AMW was then performed using therapeutic category information. The performance of discrimination depended on the category and significantly high performance (>0.8 balanced accuracy) was obtained in some categories. Taken together, the present results suggest AMW as a novel descriptor useful for detecting drugs with DILI risk. The information presented may be valuable for the safety assessment of drug candidates at the early stage of drug development. [ABSTRACT FROM AUTHOR]

Cell death experiments are routinely done in many labs around the world, these experiments are the backbone of many assays for drug development. Cell death detection is usually performed in many ways, and requires time and reagents. However, cell death is preceded by slight morphological changes in cell shape and texture. In this paper, we trained a neural network to classify cells undergoing cell death. We found that the network was able to highly predict cell death after one hour of exposure to camptothecin. Moreover, this prediction largely outperforms human ability. Finally, we provide a simple python tool that can broadly be used to detect cell death. [ABSTRACT FROM AUTHOR]

Malaria, caused by infection with Plasmodium parasites, remains a significant global health concern. For decades, genetic intractability and limited tools hindered our ability to study essential proteins and pathways in Plasmodium falciparum, the parasite associated with the most severe malaria cases. However, recent years have seen major leaps forward in the ability to genetically manipulate P. falciparum parasites and conditionally control protein expression/function. The conditional knockdown systems used in P. falciparum target all 3 components of the central dogma, allowing researchers to conditionally control gene expression, translation, and protein function. Here, we review some of the common knockdown systems that have been adapted or developed for use in P. falciparum. Much of the work done using conditional knockdown approaches has been performed in asexual, blood-stage parasites, but we also highlight their uses in other parts of the life cycle and discuss new ways of applying these systems outside of the intraerythrocytic stages. With the use of these tools, the field's understanding of parasite biology is ever increasing, and promising new pathways for antimalarial drug development are being discovered. [ABSTRACT FROM AUTHOR]