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Enzyme reactions have numerous applications in diverse disciplines of science like chemistry, biology and biomechanics. In this study, we examine the role and act of enzymes in chemical reactions which is considered in the frame of fractional order model. The proposed model includes system of four equations which are studied via Caputo fractional operator. The systems of non-linear equations are evaluated by a semi-analytical approach called q -homotopy analysis transform method. The uniqueness and existence of the solutions has been investigated through fixed point theorem. The solutions of the proposed model are achieved through the considered method and the obtained outcomes are in the form of series which shows rapid convergence. The solutions are computed and graphs are plotted for the obtained results using mathematica software. The achieved results by the proposed method are unique and illustrate the significant dynamics of the considered model via 3D plots and graphs. The results of this study demonstrate the importance and effectiveness of projected derivative and technique in the analysis of time dependent fractional mathematical models. This study also gives an idea to extend the applications of enzymatic reactions in drug development, bio mechanics, and chemical reactions in various cellular metabolisms. Also, enzymatic reactions have a vital role in the fields of the food industry for processing food, in biotechnology for the manufacture of biofuels, and in metabolic engineering to design metabolic pathways. [ABSTRACT FROM AUTHOR]

Drug-induced gene expression profiles can identify potential mechanisms of toxicity. We focus on obtaining signatures for cardiotoxicity of FDA-approved tyrosine kinase inhibitors (TKIs) in human induced-pluripotent-stem-cell-derived cardiomyocytes, using bulk transcriptomic profiles. We use singular value decomposition to identify drug-selective patterns across cell lines obtained from multiple healthy human subjects. Cellular pathways affected by cardiotoxic TKIs include energy metabolism, contractile, and extracellular matrix dynamics. Projecting these pathways to published single cell expression profiles indicates that TKI responses can be evoked in both cardiomyocytes and fibroblasts. Integration of transcriptomic outlier analysis with whole genomic sequencing of our six cell lines enables us to correctly reidentify a genomic variant causally linked to anthracycline-induced cardiotoxicity and predict genomic variants potentially associated with TKI-induced cardiotoxicity. We conclude that mRNA expression profiles when integrated with publicly available genomic, pathway, and single cell transcriptomic datasets, provide multiscale signatures for cardiotoxicity that could be used for drug development and patient stratification. Using a new computational pipeline for identification of drug-selective transcriptomic responses and FAERS data, the authors identified potential pathways and genomic variants indicative of cancer drug cardiotoxicity in iPSC-derived cardiomyocytes. [ABSTRACT FROM AUTHOR]

Accurately predicting ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties early in drug development is essential for selecting compounds with optimal pharmacokinetics and minimal toxicity. Existing ADMET-related benchmark sets are limited in utility due to their small dataset sizes and the lack of representation of compounds used in drug discovery projects. These shortcomings hinder their application in model building for drug discovery. To address this issue, we propose a multi-agent data mining system based on Large Language Models that effectively identifies experimental conditions within 14,401 bioassays. This approach facilitates merging entries from different sources, culminating in the creation of PharmaBench. Additionally, we have developed a data processing workflow to integrate data from various sources, resulting in 156,618 raw entries. Through this workflow, we constructed PharmaBench, a comprehensive benchmark set for ADMET properties, which comprises eleven ADMET datasets and 52,482 entries. This benchmark set is designed to serve as an open-source dataset for the development of AI models relevant to drug discovery projects. [ABSTRACT FROM AUTHOR]

In the post-antibiotic era, antivirulence therapies are becoming refractory to the clinical application of existing antimicrobial regimens. Moreover, in an attempt to explore alternate intervention strategies, drug repurposing is gaining attention over development of novel drugs/antimicrobials. With the prevalence of multidrug resistance and high medical burden associated with Pseudomonas aeruginosa, there is an urgent need to devise novel therapeutics to combat this bacterial pathogen. In this context, the present study was undertaken to scrutinize the anti-quorum sensing (QS) and antivirulence potential of commonly consumed drugs such as fexofenadine (FeX), ivermectin (IvM), nitrofurantoin (NiT), levocetrizine (LvC), atorvastatin (AtS), and aceclofenac (AcF), against P. aeruginosa. The methodology involved assessment of antibacterial activity against P. aeruginosa PAO1 and quorum quenching (QQ) potential using Agrobacterium tumefaciens NTL4 biosensor strain. The antivirulence prospects were investigated by estimating the production of hallmark virulence factors in P. aeruginosa accompanied by molecular docking to predict drug associations with the QS receptors. Interestingly, all the drugs harbored antibacterial, anti-QS, and antivirulence potential in vitro, which consequently disrupted QS circuits and attenuated pseudomonal virulence phenotypically by significantly lowering the production of pyocyanin, hemolysin, pyochelin, and total bacterial protease in vitro. Moreover, the findings were validated by computational studies that predicted strong molecular interactions between the test drugs and QS receptors of P. aeruginosa. Hence, this study is the first to suggest the prospect of repurposing FeX, IvM, NiT, LvC, AtS, and AcF against P. aeruginosa. [ABSTRACT FROM AUTHOR]

The selection and combination of dose regimens for antimalarials involve complex considerations including pharmacokinetic and pharmacodynamic interactions. In this study, we use immediate ex vivo P. falciparum field isolates to evaluate the effect of cabamiquine and pyronaridine as standalone treatments and in combination therapy. We feed the data into a pharmacometrics model to generate an interaction map and simulate meaningful clinical dose ratios. We demonstrate that the pharmacometrics model of parasite growth and killing provides a detailed description of parasite kinetics against cabamiquine-susceptible and resistant parasites. Pyronaridine monotherapy provides suboptimal killing rates at doses as high as 720 mg. In contrast, the combination of a single dose of 330 mg cabamiquine and 360 mg pyronaridine provides over 90% parasite killing in most of the simulated patients. The described methodology that combines a rapid, 3R-compliant in vitro method and modelling to set meaningful doses for new antimalarials could contribute to clinical drug development. Here the authors use drug susceptibility data from Plasmodium falciparum field isolates in a pharmacometric model to evaluate cabamiquine and pyronaridine efficacy, both individually and in combination. The combined treatment shows over 90% parasite reduction in most simulated cases, providing valuable guidance for clinical dose selection in real-world settings. [ABSTRACT FROM AUTHOR]

The solid tumors provide a series of biological barriers in cellular microenvironment for designing drug delivery methods based on advanced stimuli-responsive materials. These intertumoral and intratumoral barriers consist of perforated endotheliums, tumor cell crowding, vascularity, lymphatic drainage blocking effect, extracellular matrix (ECM) proteins, hypoxia, and acidosis. Triggering opportunities have been drawn for solid tumor therapies based on single and dual stimuli-responsive drug delivery systems (DDSs) that not only improved drug targeting in deeper sites of the tumor microenvironments, but also facilitated the antitumor drug release efficiency. Single and dual stimuli-responsive materials which are known for their lowest side effects can be categorized in 17 main groups which involve to internal and external stimuli anticancer drug carriers in proportion to microenvironments of targeted solid tumors. Development of such drug carriers can circumvent barriers in clinical trial studies based on their superior capabilities in penetrating into more inaccessible sites of the tumor tissues. In recent designs, key characteristics of these DDSs such as fast response to intracellular and extracellular factors, effective cytotoxicity with minimum side effect, efficient permeability, and rate and location of drug release have been discussed as core concerns of designing paradigms of these materials. [ABSTRACT FROM AUTHOR]

With the discovery of the antidepressive effects of ketamine and the increasing withdrawal of the pharmaceutical industry from the development of new psychotropic drugs, the psychiatric research into the clinical application of hallucinogens in psychiatry has literally blossomed in the last two decades. Promising results for various treatment approaches with psychedelic agents, such lysergic acid diethylamide (LSD) and psilocybin, and dissociative agents, such as ketamine and esketamine, have raised great hopes among researchers, clinicians and patients in recent years, so that there was already talk of a new era in psychiatry. As one of the first of these substances, in December 2019 intranasal esketamine was approved in the USA and the EU for the treatment of treatment-resistant depression and Switzerland followed in 2020. Recently, psilocybin was approved in Australia, Canada and Switzerland for compassionate use in exceptional cases for the treatment of depression, while large approval studies with various psychedelic agents are currently ongoing worldwide. The medical application of psychedelic agents and ketamine/esketamine is considered to be safe; however, as with all new forms of treatment it is of crucial importance that, in addition to the hopes, the specific challenges of these new treatment approaches must also be carefully considered and assessed. Excessive expectations and an insufficient risk-benefit estimation are detrimental to the patients and the reputation of the treating physician. Although a possible paradigm shift in the care of mental health is already being discussed, this review article consciously concentrates on the possible risks of treatment and the methodological weaknesses of the studies carried out so far. [ABSTRACT FROM AUTHOR]

Objectives: Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease with an unsatisfactory state of treatment. We aim to explore novel targets for SLE from a genetic standpoint. Methods: Cis-expression quantitative trait loci (eQTLs) for whole blood from 31,684 samples provided by the eQTLGen Consortium as well as two large SLE cohorts were utilized for screening and validating genes causally associated with SLE. Colocalization analysis was employed to further investigate whether changes in the expression of risk genes, as indicated by GWAS signals, influence the occurrence and development of SLE. Targets identified for drug development were evaluated for potential side effects using a phenome-wide association study (PheWAS). Based on the multiple databases, we explored the interactions between drugs and genes for drug prediction and the assessment of current medications. Results: The analysis comprised 5427 druggable genes in total. The two-sample Mendelian randomization (MR) in the discovery phase identified 20 genes causally associated with SLE and validated 8 genes in the replication phase. Colocalization analysis ultimately identified five genes (BLK, HIST1H3H, HSPA1A, IL12A, NEU1) with PPH4 > 0.8. PheWAS further indicated that drugs acting on BLK and IL12A are less likely to have potential side effects, while HSPA1A and NEU1 were associated with other traits. Four genes (BLK, HSPA1A, IL12A, NEU1) have been targeted for drug development in autoimmune diseases and other conditions. Conclusions:.This study identified five genes as therapeutic targets for SLE. Repurposing and developing drugs targeting these genes is anticipated to improve the existing treatment state for SLE. Key Points • We identified five gene targets of priority for the treatment of SLE, with BLK and IL12A indicating fewer side effects. • Among the existing drugs that target these candidate genes, Ustekinumab, Ebdarokimab, and Briakinumab (targeting the IL12 gene) and CD24FC (targeting HSPA1A) may potentially be repurposed for the treatment of SLE. [ABSTRACT FROM AUTHOR]

Antibody–drug conjugates (ADCs) represent a crucial component of targeted therapies in gastric cancer, potentially altering traditional treatment paradigms. Many ADCs have entered rigorous clinical trials based on biological theories and preclinical experiments. Modality trials have also been conducted in combination with monoclonal antibody therapies, chemotherapies, immunotherapies, and other treatments to enhance the efficacy of drug coordination effects. However, ADCs exhibit limitations in treating gastric cancer, including resistance triggered by their structure or other factors. Ongoing intensive researches and preclinical experiments are yielding improvements, while enhancements in drug development processes and concomitant diagnostics during the therapeutic period actively boost ADC efficacy. The optimal treatment strategy for gastric cancer patients is continually evolving. This review summarizes the clinical progress of ADCs in treating gastric cancer, analyzes the mechanisms of ADC combination therapies, discusses resistance patterns, and offers a promising outlook for future applications in ADC drug development and companion diagnostics. [ABSTRACT FROM AUTHOR]

With the continued development of biologics for the treatment of psoriasis, some patients have achieved optimal control, but a recommended biologic sequence if a biologic fails to initially improve the skin, termed primary nonresponse, or loses efficacy after initial improvement, termed secondary nonresponse, is still lacking. Primary and secondary nonresponse can occur with any class of biologics, and the type of nonresponse can drive the choice of whether to switch within a biologic class or to a different biologic class. The choice of biologic can also be challenging when managing psoriasis and concomitant psoriatic arthritis, as treatment differs on the basis of the severity of both diseases and further classification of axial and peripheral joint involvement. When choosing a biologic, each patient's comorbidities and preferences are also taken into account to provide the optimal therapy. With this lack of an established biologic sequence after biologic failure, the objective of our review is to define a therapy sequence for the tumor necrosis factor (TNF), interleukin-17 (IL-17), and interleukin-23 (IL-23) inhibitor classes in the treatment of psoriasis and psoriatic arthritis. Our proposed biologic sequence was derived through an analysis of the efficacy of each biologic class, primary and secondary nonresponse rates from clinical trials, and clinical experience with expert opinion. [ABSTRACT FROM AUTHOR]

The development of inhaled drugs for respiratory diseases is frequently impacted by lung pathology in non-clinical safety studies. To enable design of novel candidate drugs with the right safety profile, predictive in vitro lung toxicity assays are required that can be applied during drug discovery for early hazard identification and mitigation. Here, we describe a novel high-content imaging-based screening assay that allows for quantification of the tight junction protein occludin in A549 cells, as a model for lung epithelial barrier integrity. We assessed a set of compounds with a known lung safety profile, defined by clinical safety or non-clinical in vivo toxicology data, and were able to correctly identify 9 of 10 compounds with a respiratory safety risk and 9 of 9 compounds without a respiratory safety risk (90% sensitivity, 100% specificity). The assay was sensitive at relevant compound concentrations to influence medicinal chemistry optimization programs and, with an accessible cell model in a 96-well plate format, short protocol and application of automated imaging analysis algorithms, this assay can be readily integrated in routine discovery safety screening to identify and mitigate respiratory toxicity early during drug discovery. Interestingly, when we applied physiologically-based pharmacokinetic (PBPK) modelling to predict epithelial lining fluid exposures of the respiratory tract after inhalation, we found a robust correlation between in vitro occludin assay data and lung pathology in vivo, suggesting the assay can inform translational risk assessment for inhaled small molecules. [ABSTRACT FROM AUTHOR]

For more than two decades, regulatory agencies throughout the world released guidelines, rules and laws to stimulate and assist in paediatric drug development. In 2014, the National Health and Family Planning Commission (now known as the National Health Commission, NHC) and five other departments in China jointly issued 'Several Opinions on Safeguarding Medication for Children', after which several policies and regulations were issued to implement the priority review and approval of paediatric medicinal products and support the development of new drugs, including new dosage forms and strengths, for children. A total of 172 special medicinal products for children were approved from 2018 to 2022. Since 2016, the NHC, together with relevant administrative departments, has formulated and issued four paediatric drug lists containing 129 medicinal products to encourage research and development. At present, approximately 25 of these drugs (at exactly the same dosage forms and strengths as on the lists) have been approved for marketing, including antitumour drugs and immunomodulators, nervous system drugs, drugs for mental disorders and drugs for rare diseases. In this review, we analysed the regulations issued for promoting paediatric drug development in China, including the priority review and approval system, technical guidelines, data protection and financial support policies and general profiles of paediatric drug approval, clinical trials and the addition of information for children in the labels of marketed medicinal products. Finally, we discussed the challenges and possible strategies in the research and development of paediatric drugs in China. [ABSTRACT FROM AUTHOR]

Seamless study designs have the potential to accelerate clinical development. The use of innovative seamless designs has been increasing in the oncology area; however, while the concept of seamless designs becomes more popular and accepted, many challenges remain in both the design and conduct of these trials. This may be especially true when seamless designs are used in late phase development supporting regulatory decision-making. The Innovative Design Scientific Working Group (IDSWG) Oncology team conducted a survey to understand the current use of seamless study designs for registration purposes in oncology clinical development. The survey was designed to provide insights into the benefits and to identify the roadblocks. A total of 16 questions were included in the survey that was distributed using the ASA Biopharmaceutical Section and IDSWG email listings from August to September 2022. A total of 51 responses were received, with 39 (76%) respondents indicating that their organizations had seamless oncology studies in planning or implementation for registration purposes. Detailed survey results are presented in the manuscript. Overall, while seamless designs offer advantages in terms of timeline reduction and cost saving, they also present challenges related to additional complexity and the need for efficient surrogate clinical endpoints in oncology drug development. [ABSTRACT FROM AUTHOR]

Background: This report describes the U.S. Food and Drug Administration (FDA) experience in establishing a dedicated mailbox, and in publishing related guidance, to address concerns among interested parties regarding the conduct of clinical trials during the COVID-19 public health emergency (PHE). Methods: Six hundred and thirty-four mailbox inquiries were received from March 2020 through February 2022. Qualitative methods were used to provide a structured description of, and identify common themes among, these inquiries. Results: Most inquiries came from U.S.-based interested parties, including sponsors, industry trade associations, academic institutions, hospitals, clinics, research sites, trial participants, and individual persons. Approximately one-fifth of questions were related directly to COVID-19 (e.g., proposals for treatment); other inquiries were related to conduct of routine trial-related activities, and concerns were often focused on maintaining compliance with good clinical practice. In March 2020, FDA published a guidance titled Conduct of Clinical Trials of Medical Products During the COVID-19 Public Health Emergency; the document was subsequently revised eight times based in part on issues raised in mailbox inquiries. Conclusions: The dedicated mailbox enabled expedited communication among invested parties during the COVID-19 PHE; FDA also provided updates of the aforementioned guidance. These efforts supported the continuance of ongoing trials and the initiation of new trials during the PHE in accordance with good clinical practice guidelines, thereby helping to ensure the safety of trial participants while maintaining the quality of trial data. By soliciting and responding to trial-related inquiries and addressing corresponding needs and concerns, FDA improved transparency and communication. [ABSTRACT FROM AUTHOR]

Two frequently cited figures by clinical research insiders and observers – the cost of missing a day to generate prescription drug sales and the cost of a day to conduct a clinical trial – are outdated and based on anecdotal evidence. In late 2023, the Tufts Center for the Study of Drug Development conducted empirical research to gather more accurate and granular estimates and to test whether average sales per day have changed over time. 645 drugs launched since 2000, and 409 clinical trial budgets were drawn from commercially available and proprietary data sets and analyzed. The results indicate that a single day equals approximately $500,000 in lost prescription drug or biologic sales, with daily prescription sales for infectious, hematologic, cardiovascular, and gastrointestinal diseases among the highest. The results also show that each year, the average sales per day of prescription drugs and biologics has decreased by approximately $80,000—$100,000. The estimated direct daily cost to conduct a clinical trial is approximately $40,000 per day for phase II and III clinical trials, with those in respiratory, rheumatology, and dermatology having the highest relative daily direct costs. [ABSTRACT FROM AUTHOR]

Background: Medical-product companies often outsource research and manufacturing needs to contracting or partnering organizations but then must manage a challenging patchwork of regulatory activities. A standalone regulatory agreement could clarify the relationships and responsibilities between companies working jointly on a single regulated product. This study explored the need for and current use of standalone regulatory agreements. Methods: A survey instrument was developed using an implementation framework and disseminated to mid- to senior-level employees and consultants for sponsor and vendor companies in the medical products sector. Results: Of 294 respondents, about half, primarily from companies with more than 200 employees, were familiar with standalone regulatory agreements, and half of this subgroup had moved forward to implement them. Such agreements were considered beneficial to clarify regulatory roles and responsibilities, standardize regulatory expectations between the companies, and stimulate earlier discussion about joint regulatory strategies. However, the development of regulatory agreements appears challenged by the fact that such agreements are not required by regulatory agencies overseeing medical products and have no standardized templates, agency or industry guidance. Respondents whose organizations do not now use regulatory agreements either had not considered or did not see a need for a standalone agreement. Conclusions: Standalone regulatory agreements are becoming more common but are not yet implemented fully by most companies. Their usefulness and content appeared to depend upon the type of partner, the complexity of the relationship and the availability of internal expertise and support. [ABSTRACT FROM AUTHOR]

The ICH E17 guidelines (2014–2017) on Multiregional Clinical Trials (MRCT) was a joint effort by the regulators and industry to facilitate simultaneous global drug development and registration through taking a strategic approach for clinical trials. In other words, the objective was to reduce the time it takes to bringing medications to patients around the world through minimizing unnecessary duplication of local or regional studies, which may add the regulatory burden to cost and time of bringing new therapies to patients. Under the auspices of ICH, training materials were created and provided to various stakeholders. Despite the successful promotion of the benefits of ICH E17 MRCT guidelines across the different regions, the uptake of some concepts (e.g., pooling strategy) in the ICH E17 guidelines has been slow. This paper describes various factors which could affect the conduct of MRCT at a global level, including ambiguity in definition of "region" (in MRCT), new regulatory requirements to enroll a diverse patient population, the use of decentralized clinical trials, use of data sources other than randomized clinical trials (e.g., use of Real Word Data), and the impact of the COVID-19 pandemic on the conduct of MRCT. [ABSTRACT FROM AUTHOR]

Introduction: ECLIM-SEHOP platform was created in 2017. Its main objective is to establish the infrastructure to allow Spanish participation into international academic collaborative clinical trials, observational studies, and registries in pediatric oncology. The aim of this manuscript is to describe the activity conducted by ECLIM-SEHOP since its creation. Methods: The platform's database was queried to provide an overview of the studies integrally and partially supported by the organization. Data on trial recruitment and set-up/conduct metrics since its creation until November 2023 were extracted. Results: ECLIM-SEHOP has supported 47 studies: 29 clinical trials and 18 observational studies/registries that have recruited a total of 5250 patients. Integral support has been given to 25 studies: 16 trials recruiting 584 patients and nine observational studies/registries recruiting 278 patients. The trials include front-line studies for leukemia, lymphoma, brain and solid extracranial tumors, and other key transversal topics such as off-label use of targeted therapies and survivorship. The mean time from regulatory authority submission to first patient recruited was 12.2 months and from first international site open to first Spanish site open was 31.3 months. Discussion: ECLIM-SEHOP platform has remarkably improved the availability and accessibility of international academic clinical trials and has facilitated the centralization of resources in childhood cancer treatment. Despite the progressive improvement on clinical trial set-up metrics, timings should still be improved. The program has contributed to leveling survival rates in Spain with those of other European countries that presented major differences in the past. [ABSTRACT FROM AUTHOR]

Over the last decade, automatic chemical design frameworks for discovering molecules with drug-like properties have significantly progressed. Among them, the variational autoencoder (VAE) is a cutting-edge approach that models the tractable latent space of the molecular space. In particular, the usage of a VAE along with a property estimator has attracted considerable interest because it enables gradient-based optimization of a given molecule. However, although successful results have been achieved experimentally, the theoretical background and prerequisites for the correct operation of this method have not yet been clarified. In view of the above, we theoretically analyze and rigorously reconstruct the entire framework. From the perspective of parameterized distribution and the information theory, we first describe how the previous model overcomes the limitations of the beta VAE in discovering molecules with the desired properties. Furthermore, we describe the prerequisites for training the above model. Next, from the log-likelihood perspective of each term, we reformulate the objectives for exploring latent space to generate drug-like molecules. The distributional constraints are defined in this study, which will break away from the invalid molecular search. We demonstrated that our model could discover a novel chemical compound for targeting BCL-2 family proteins in de novo approach. Through the theoretical analysis and practical implementation, the importance of the aforementioned prerequisites and constraints to operate the model was verified. [ABSTRACT FROM AUTHOR]

TASK-5 (KCNK15) belongs to the acid-sensitive subfamily of two-pore domain potassium (K2P) channels, which includes TASK-1 and TASK-3. TASK-5 stands out as K2P channel for which there is no functional data available, since it was reported in 2001 as non-functional and thus "silent". Here we show that TASK-5 channels are indeed non-functional as homodimers, but are involved in the formation of functional channel complexes with TASK-1 and TASK-3. TASK-5 negatively modulates the surface expression of TASK channels, while the heteromeric TASK-5-containing channel complexes located at the plasma membrane are characterized by changes in single-channel conductance, Gq-coupled receptor-mediated channel inhibition, and sensitivity to TASK modulators. The unique pharmacology of TASK-1/TASK-5 heterodimers, affected by a common polymorphism in KCNK15, needs to be carefully considered in the future development of drugs targeting TASK channels. Our observations provide an access to study TASK-5 at the functional level, particularly in malignant cancers associated with KCNK15. The TASK-5 potassium channel is thought to be non-functional. Here, the authors show that it forms complexes with TASK family members, resulting in heteromeric channels with unique pharmacology and potential as therapeutic targets. [ABSTRACT FROM AUTHOR]

Complex signaling pathways are believed to be responsible for drug resistance. Drug combinations perturbing multiple signaling targets have the potential to reduce drug resistance. The large-scale multi-omic datasets and experimental drug combination synergistic score data are valuable resources to study mechanisms of synergy (MoS) to guide the development of precision drug combinations. However, signaling patterns of MoS are complex and remain unclear, and thus it is challenging to identify synergistic drug combinations in clinical. Herein, we proposed a novel integrative and interpretable graph AI model, DeepSignalingFlow, to uncover the MoS by integrating and mining multi-omic data. The major innovation is that we uncover MoS by modeling the signaling flow from multi-omic features of essential disease proteins to the drug targets, which has not been introduced by the existing models. The model performance was assessed utilizing four distinct drug combination synergy evaluation datasets, i.e., NCI ALMANAC, O'Neil, DrugComb, and DrugCombDB. The comparison results showed that the proposed model outperformed existing graph AI models in terms of synergy score prediction, and can interpret MoS using the core signaling flows. The code is publicly accessible via Github: https://github.com/FuhaiLiAiLab/DeepSignalingFlow [ABSTRACT FROM AUTHOR]

Background: For centuries, plants have been used in the folk medicine of various cultures for their healing properties. It is amazing how nature has provided us with such powerful remedies. Oxalis corniculata (O. corniculata) has always been used traditionally for its medicinal attributes. In Asia, this herbaceous plant is used for treating many gastrointestinal disorders, such as diarrhea and dysentery. In African folk medicine, on the other hand, this herb is used for respiratory diseases, skin diseases, and fever. Main body: Scientific research has revealed numerous pharmacological potentials of this plant, including antitumor, antimicrobial, antioxidant, anti-inflammatory, and hepatoprotective properties. In addition, studies have indicated that the extract of this plant protects against oxidative stress, inflammation, and various diseases, including cancer and diabetes. Phytochemical analysis of O. corniculata revealed various relevant compounds, including phenolic acids, flavonoids, and alkaloids, which are responsible for its therapeutic properties. Conclusion: The various constituents of this plant have significant ethnomedicinal potential. The plant is a possible source of extracts and chemical compounds with pharmacological activity. In the future, O. corniculata could have an effective role in the development of modern drugs. The objective of this review is to summarize the current knowledge on the medicinal potential of O. corniculata, including its bioactive compounds, mechanisms of action, and therapeutic applications. [ABSTRACT FROM AUTHOR]

C4ʹ-modified nucleoside analogues continue to attract global attention for their use in antiviral drug development and oligonucleotide-based therapeutics. However, current approaches to C4ʹ-modified nucleoside analogues still involve lengthy (9–16 steps), non-modular routes that are unamenable to library synthesis. Towards addressing the challenges associated with their syntheses, we report a modular 5-step process to a diverse collection of C4ʹ-modified nucleoside analogues through a sequence of intramolecular trans-acetalizations of readily assembled polyhydroxylated frameworks. Overall, the 2–3 fold reduction in step-count compares favorably to even recently reported biocatalytic approaches and should ultimately enable new opportunities in drug design around this popular chemotype. C4ʹ-modified nucleoside analogues attract global attention, but current approaches for the synthesis involve lengthy, nonmodular routes. Herein, the authors report a modular 5-step process to a diverse collection of C4ʹ-modified nucleoside analogues through a sequence of intramolecular trans-acetalizations of polyhydroxylated frameworks. [ABSTRACT FROM AUTHOR]

Tunlametinib (科露平®) is an oral, selective, mitogen-activated protein kinase kinase 1 and 2 (MEK 1/2) inhibitor being developed by Shanghai KeChow Pharma, Inc. for the treatment of solid tumours with RAS and RAF mutations, including melanoma, non-small cell cancer (NSCLC), colorectal cancer (CRC) and neurofibromatosis type 1 (NF1) plexiform neurofibromas. In March 2024, tunlametinib was granted conditional approval in China (based on surrogate endpoints) for use in patients with NRAS-mutated advanced melanoma who have failed anti-PD-1/PD-L1 treatment. This article summarizes the milestones in the development of tunlametinib leading to this first approval for the treatment of solid tumours with RAS and RAF mutations. [ABSTRACT FROM AUTHOR]

Mavorixafor (XOLREMDI™) is an oral, selective C-X-C chemokine receptor 4 (CXCR4) antagonist developed by X4 Pharmaceuticals that blocks the binding of C-X-C chemokine ligand 12 (also known as stromal derived factor-1) to CXCR4. In April 2024, it became the first therapy to be approved for WHIM syndrome (named by an acronym for its observed characteristics of Warts, Hypogammaglobulinaemia, Infections and Myelokathexis) in the USA, where it is indicated for use in patients aged ≥ 12 years with WHIM syndrome to increase the number of circulating mature neutrophils and lymphocytes. Clinical development of mavorixafor is ongoing for chronic neutropenic disorders. This article summarizes the milestones in the development of mavorixafor leading to this first approval for use in patients aged ≥ 12 years with WHIM syndrome to increase the number of circulating mature neutrophils and lymphocytes. [ABSTRACT FROM AUTHOR]

Zolbetuximab (VYLOY™), a recombinant, chimeric, anti-claudin 18.2 (CLDN18.2) monoclonal antibody (mAb), is being developed by Astellas Pharma Inc. for the treatment of patients with HER2-negative (HER2-), CLDN18.2-positive (CLDN18.2+) advanced gastric or gastroesophageal junction (GEJ) adenocarcinoma and CLDN18.2+ advanced pancreatic adenocarcinoma. In March 2024, zolbetuximab was approved in Japan for the treatment of patients with HER2-, CLDN18.2+ unresectable, advanced/recurrent gastric cancer (the gastric cancer indication includes GEJ cancer). Zolbetuximab is also undergoing regulatory review for HER2-, CLDN18.2+ advanced gastric or GEJ adenocarcinoma in the USA, the EU, China, Australia and several other countries. This article summarizes the milestones in the development of zolbetuximab leading to this first approval for the treatment of patients with CLDN18.2+ gastrointestinal malignancies. [ABSTRACT FROM AUTHOR]

As a class of biologically active molecules with significant immunomodulatory and anti-inflammatory effects, anti-inflammatory peptides have important application value in the medical and biotechnology fields due to their unique biological functions. Research on the identification of anti-inflammatory peptides provides important theoretical foundations and practical value for a deeper understanding of the biological mechanisms of inflammation and immune regulation, as well as for the development of new drugs and biotechnological applications. Therefore, it is necessary to develop more advanced computational models for identifying anti-inflammatory peptides. In this study, we propose a deep learning model named DAC-AIPs based on variational autoencoder and contrastive learning for accurate identification of anti-inflammatory peptides. In the sequence encoding part, the incorporation of multi-hot encoding helps capture richer sequence information. The autoencoder, composed of convolutional layers and linear layers, can learn latent features and reconstruct features, with variational inference enhancing the representation capability of latent features. Additionally, the introduction of contrastive learning aims to improve the model's classification ability. Through cross-validation and independent dataset testing experiments, DAC-AIPs achieves superior performance compared to existing state-of-the-art models. In cross-validation, the classification accuracy of DAC-AIPs reached around 88%, which is 7% higher than previous models. Furthermore, various ablation experiments and interpretability experiments validate the effectiveness of DAC-AIPs. Finally, a user-friendly online predictor is designed to enhance the practicality of the model, and the server is freely accessible at http://dac-aips.online. [ABSTRACT FROM AUTHOR]

In recent years, significant advancements have been made in molecular generation algorithms aimed at facilitating drug development, and molecular diversity holds paramount importance within the realm of molecular generation. Nonetheless, the effective quantification of molecular diversity remains an elusive challenge, as extant metrics exemplified by Richness and Internal Diversity fall short in concurrently encapsulating the two main aspects of such diversity: quantity and dissimilarity. To address this quandary, we propose Hamiltonian diversity, a novel molecular diversity metric predicated upon the shortest Hamiltonian circuit. This metric embodies both aspects of molecular diversity in principle, and we implement its calculation with high efficiency and accuracy. Furthermore, through empirical experiments we demonstrate the high consistency of Hamiltonian diversity with real-world chemical diversity, and substantiate its effects in promoting diversity of molecular generation algorithms. Our implementation of Hamiltonian diversity in Python is available at: https://github.com/HXYfighter/HamDiv. Scientific contribution We propose a more rational molecular diversity metric for the community of cheminformatics and drug development. This metric can be applied to evaluation of existing molecular generation methods and enhancing drug design algorithms. [ABSTRACT FROM AUTHOR]

The study of drug–target interaction plays an important role in the process of drug development. The subject of DTI forecasting has advanced significantly in the last several years, yielding numerous significant research findings and methodologies. Heterogeneous data sources provide richer information and comprehensive perspectives for drug–target interaction prediction, so many existing methods rely on heterogeneous networks, and graph embedding technology becomes an important technology to extract information from heterogeneous networks. These approaches, however, are less concerned with potential noisy information in heterogeneous networks and more focused on the extent of information extraction in those networks. Based on this, a potential DTI predictive network model called FBRWPC is proposed in this paper. It uses a fine-grained similarity selection program to first integrate similarity on similar networks and then a bidirectional random walk graph embedding learning method with restart to obtain an updated drug target interaction matrix. Through the use of similarity selection and fine-grained selection similarity integration, the framework can effectively filter out the noise present in heterogeneous networks and enhance the model's prediction performance. The experimental findings demonstrate that, even after being split up into four distinct types of data sets, FBRWPC can still retain great prediction performance, a sign of the model's resilience and good generalization. [ABSTRACT FROM AUTHOR]

Understanding protein function is pivotal in comprehending the intricate mechanisms that underlie many crucial biological activities, with far-reaching implications in the fields of medicine, biotechnology, and drug development. However, more than 200 million proteins remain uncharacterized, and computational efforts heavily rely on protein structural information to predict annotations of varying quality. Here, we present a method that utilizes statistics-informed graph networks to predict protein functions solely from its sequence. Our method inherently characterizes evolutionary signatures, allowing for a quantitative assessment of the significance of residues that carry out specific functions. PhiGnet not only demonstrates superior performance compared to alternative approaches but also narrows the sequence-function gap, even in the absence of structural information. Our findings indicate that applying deep learning to evolutionary data can highlight functional sites at the residue level, providing valuable support for interpreting both existing properties and new functionalities of proteins in research and biomedicine. Understanding protein function is vital for biomedicine. Here, authors develop a method using statistics-informed graph networks to predict functions from sequences. The method integrates evolutionary couplings and residue communities to improve the accuracy of function annotations for proteins. [ABSTRACT FROM AUTHOR]

Current antidiabetic medications have a plethora of harmful side effects, and most of the drugs do not contain 1,3,4-oxadiazole moiety. Therefore, research into the development of novel drugs which contain 1,3,4-oxadiazole moiety with fewer side effects is necessary. Novel fluorine-incorporated 1,3,4-oxadiazole derivatives (1c–1n) were synthesized, characterized, and evaluated for α-amylase and α-glucosidase enzyme inhibitor activity. An in vivo Drosophila melanogaster model and an in vitro system were used to investigate its antidiabetic properties, further, which were characterized by 1HNMR, MASS, and FT-IR. Spectroscopic techniques and DFT are used to calculate more geometrically optimized molecule structures using the B3LYP technique. The compounds were tested against the α-glucosidase and α-amylase enzymes. Among different compounds tested, compounds 1i (IC50 = 54.83 µg/ml), 1k (IC50 = 64.95 µg/ml), 1m (IC50 = 64.78 µg/ml), and 1n (IC50 = 66.30 µg/ml) showed significant α-amylase inhibitor efficacy compared to the acarbose (IC50 = 35.17 µg/ml); compounds 1m (IC50 = 74.64 µg/ml) and 1i (IC50 = 60.35 µg/ml) exhibited significant α-glucosidase inhibitory action compared to acarbose (IC50 = 46.06 µg/ml). The docking study exhibited that compound 1i creates six hydrogen bonds and compound 1m forms three hydrogen bonding contacts at the active site of the enzyme (PDBID:4w93). The obtained results are demonstrated that compounds 1i, 1m, 1n, and 1k had greater antidiabetic activities and can be further taken into consideration for antidiabetic therapeutic interventions. [ABSTRACT FROM AUTHOR]

Drug-induced cholestasis results in drug discontinuation and market withdrawal, and the prediction of cholestasis risk is critical in the early stages of drug development. Animal tests and membrane vesicle assay are currently being conducted to assess the risk of cholestasis in the preclinical stage. However, these methods have drawbacks, such as species differences with humans and difficulties in evaluating the effects of drug metabolism and other transporters, implying the need for a cholestasis risk assessment system using human hepatocytes. However, human hepatocytes hardly form functional, extended bile canaliculi, a requirement for cholestasis risk assessment. We previously established a culture protocol for functional, extended bile canaliculi formation in human iPSC-derived hepatocytes. In this study, we modified this culture protocol to support the formation of functional, extended bile canaliculi in human cryopreserved hepatocytes (cryoheps). The production of bile acids, which induces bile canaliculi extension, increased time-dependently during bile canaliculi formation using this protocol, suggesting that increased bile acid production may be involved in the extended bile canaliculi formation. We have also shown that our culture protocol can be applied to cryoheps from multiple donors and that bile canaliculi can be formed stably among different culture batches. Furthermore, this protocol enables long-term maintenance of bile canaliculi and scaling down to culture in 96-well plates. We expect our culture protocol to be a breakthrough for in vitro cholestasis risk assessment. [ABSTRACT FROM AUTHOR]

The tumour suppressor p16/CDKN2A and the metabolic gene, methyl-thio-adenosine phosphorylase (MTAP), are frequently co-deleted in some of the most aggressive and currently untreatable cancers. Cells with MTAP deletion are vulnerable to inhibition of the metabolic enzyme, methionine-adenosyl transferase 2A (MAT2A), and the protein arginine methyl transferase (PRMT5). This synthetic lethality has paved the way for the rapid development of drugs targeting the MAT2A/PRMT5 axis. MAT2A and its liver- and pancreas-specific isoform, MAT1A, generate the universal methyl donor S-adenosylmethionine (SAM) from ATP and methionine. Given the pleiotropic role SAM plays in methylation of diverse substrates, characterising the extent of SAM depletion and downstream perturbations following MAT2A/MAT1A inhibition (MATi) is critical for safety assessment. We have assessed in vivo target engagement and the resultant systemic phenotype using multi-omic tools to characterise response to a MAT2A inhibitor (AZ'9567). We observed significant SAM depletion and extensive methionine accumulation in the plasma, liver, brain and heart of treated rats, providing the first assessment of both global SAM depletion and evidence of hepatic MAT1A target engagement. An integrative analysis of multi-omic data from liver tissue identified broad perturbations in pathways covering one-carbon metabolism, trans-sulfuration and lipid metabolism. We infer that these pathway-wide perturbations represent adaptive responses to SAM depletion and confer a risk of oxidative stress, hepatic steatosis and an associated disturbance in plasma and cellular lipid homeostasis. The alterations also explain the dramatic increase in plasma and tissue methionine, which could be used as a safety and PD biomarker going forward to the clinic. [ABSTRACT FROM AUTHOR]

This article is an autobiographical account of a research career in inflammatory diseases, mechanisms and pharmacotherapy, drug research and development, in academia and industry in various European countries spanning the last 55 years. The author describes how tenacity and independent thought, learned in formative years, and tempered later by the development of good relationships with colleagues have guided his career. This has spanned research, among other fields, on prostaglandins as pro-and anti-inflammatory mediators, oxidative stress and antioxidants, phospholipid mediators, cytokines, innate and adaptive immune responses and the establishment of various inflammatory and immunological models. The author has helped discover and develop novel therapeutic approaches to pain, arthritic, dermatological, respiratory, and autoimmune disorders and contributed to bringing eight drug candidates to clinical trials. He has helped establish new research labs in four different centres and been involved in teaching undergraduate and mature students in three different universities. With extensive experience in scientific publishing and several international awards, he emphasises that without good teamwork, little can be achieved in scientific research. [ABSTRACT FROM AUTHOR]

Due to inadequate drug tissue penetration and low blood supply to the bone, the systemic delivery of medications during infection and inflammation of bone tissues frequently fails to heal abnormalities or lesions in bone tissues. In the quest for local delivery of antibiotics to treat the infection and bone-grafting particles to stimulate bone growth and regeneration, a series of composite films containing gelatin (G), chitosan (CH), carbonated hydroxyapatite (CHA), and various amounts of tetraethyl orthosilicate (TEOS) crosslinker were synthesized. The synthesis resulted in 4 (four) different composite films having a mass ratio of 0.3/0.3/0.5/x, where x = 0, 1.87, 3.73, and 5.60 for G/CH/CHA, G/CH/CHA/TEOS(2), G/CH/CHA/TEOS(4), and G/CH/CHA/TEOS(6), respectively. The composite films were characterized using SEM for morphology, SAA for specific surface area and pore volume, and FTIR and XRD for functional groups and crystal phase, respectively. Furthermore, tensile strength, water absorption capacity, polymer matrix degradation, Ca2+ release profile, drug loading capacity, drug unloading (release) profile, and drug release kinetics were determined to gain insights into the critical design parameters for preparing this drug carrier. A commercial film, Dentium™ (collagen-based), was included in the water absorption, drug loading capacity, drug release profile, and degradation tests. The biological performance of the film was evaluated from protein absorption and MC3T3I1 cell cytotoxicity. It was found that G/CH/CHA/TEOS(2) exhibited the lowest total pore volume, the highest tensile strength and protein absorption, similar water absorption and drug loading capacity, the lowest drug release rate, the lowest Ca2+ release rate, the lowest degradation rate, and cytocompatibility when compared to the other synthesized composite films. According to empirical mathematical modeling, the Higuchi and Korsmeyer-Peppas models best described the drug unloading (release) process for G/CH/CHA and G/CH/CHA/TEOS films through a diffusion process. When Dentium™ was included in the tests, Dentium™ exhibited the lowest water absorption, the lowest drug loading capacity, the highest drug release rate, and the lowest film degradation rate compared to all studied films. [ABSTRACT FROM AUTHOR]

Context: Computational drug repurposing methods have been continuously developed in recent years to alleviate the high costs associated with drug development. As drug targets or the products of disease-related genes, proteins play an important role in drug repurposing. Although the potential has been demonstrated, heterogeneous graphs with proteins as independent nodes have yet to be studied, where extracting high-quality protein features from heterogeneous graphs poses a significant challenge. A novel drug repurposing model based on the feature construction of multi-layer ensemble (DRML-Ensemble) is proposed in this study. The performance of DRML-Ensemble, as evaluated on publicly available datasets, achieves an AUPR value of 0.93 and an AUROC value of 0.92, surpassing those of existing state-of-the-art methods. Additionally, DRML-Ensemble demonstrates its notable ability for drug repurposing in Alzheimer's disease. Methods: DRML-Ensemble is primarily composed of multiple layers of heterogeneous graph feature construction (HGFC). Each HGFC can extract protein features by leveraging the relationships between drugs, diseases, and proteins. These protein features are then utilized in subsequent layers to build drug and disease features, facilitating drug repurposing. By stacking multiple layers, optimal protein features can be obtained from the heterogeneous graph, consequently improving the accuracy of drug repurposing. However, an excessive· stacking of layers usually affect the model's training process, for example, causing problems such as overfitting; a multi-layer ensemble prediction module is designed to further improve the model's performance. [ABSTRACT FROM AUTHOR]

In the 1980s, Orion Pharma, then a mid-ranking Nordic area pharmaceutical company, established a drug development programme on the inhibition of catechol O-methyltransferase (COMT). This enzyme, which plays an important role in the inactivation of catecholamine neurotransmitters and drugs with a catechol structure, thus came under consideration as a target in the innovative translational and clinical programme we describe in this historical review. The starting point was the conjecture that a peripherally acting COMT inhibitor might improve entry of levodopa into the brain. This had potentially significant implications for the medical treatment of Parkinson's disease (PD). The rationale was that more efficient delivery of levodopa to the brain might allow the high therapeutic doses of levodopa to be reduced and the dose interval to be extended. Elucidation of structure–activity relations paved the way for the discovery and development of entacapone, a 5-nitrocatechol that was a potent and highly specific inhibitor of COMT. Experience in phase III clinical trials established that entacapone, used as an adjunct to regular or controlled-release levodopa preparations (also including a peripherally acting dopa-decarboxylase inhibitor), increased ON-time and reduced OFF-time and improved clinical condition in patients with PD experiencing wearing-off, often with a reduced daily levodopa dose. Several of these studies also identified that entacapone improved patients' quality of life and was cost-effective. Subsequently, entacapone has been amalgamated into a triple-combination preparation (Stalevo®) with levodopa and carbidopa to create a flexible and convenient drug therapy for patients with PD who have end-of-dose motor fluctuations not stabilised on levodopa/dopa-decarboxylase inhibitor treatment. This review offers a historical perspective on a successful programme of drug development by researchers who played central roles in the progress from exploratory hypothesis to registered pharmaceutical product. [ABSTRACT FROM AUTHOR]

Background: Over the past decades, US Congress enabled the US Food and Drug Administration (FDA) to facilitate and expedite drug development for serious conditions filling unmet medical needs with five special designations and review pathways: orphan, fast track, accelerated approval, priority review, and breakthrough therapy. Objectives: This study reviews the FDA's five special designations for drug development regarding their safety, efficacy/clinical benefit, clinical trials, innovation, economic incentives, development timelines, and price. Methods: We conducted a keyword search to identify studies analyzing the impact of the FDA's special designations (orphan, fast track, accelerated approval, priority review, and breakthrough therapy) on the safety, efficacy/clinical benefit, trials, innovativeness, economic incentives, development times, and pricing of new drugs. Results were summarized in a narrative overview. Results: Expedited approval reduces new drugs' time to market. However, faster drug development and regulatory review are associated with more unrecognized adverse events and post-marketing safety revisions. Clinical trials supporting special FDA approvals frequently use small, non-randomized, open-label designs. Required post-approval trials to monitor unknown adverse events are often delayed or not even initiated. Evidence suggests that drugs approved under special review pathways, marketed as "breakthroughs", are more innovative and deliver a higher clinical benefit than those receiving standard FDA approval. Special designations are an economically viable strategy for investors and pharmaceutical companies to develop drugs for rare diseases with unmet medical needs, due to financial incentives, expedited development timelines, higher clinical trial success rates, alongside greater prices. Nonetheless, patients, physicians, and insurers are concerned about spending money on drugs without a proven benefit or even on drugs that turn out to be ineffective. While European countries established performance- and financial-based managed entry agreements to account for this uncertainty in clinical trial evidence and cost-effectiveness, the pricing and reimbursement of these drugs remain largely unregulated in the US. Conclusion: Special FDA designations shorten clinical development and FDA approval times for new drugs treating rare and severe diseases with unmet medical needs. Special-designated drugs offer a greater clinical benefit to patients. However, physicians, patients, and insurers must be aware that special-designated drugs are often approved based on non-robust trials, associated with more unrecognized side effects, and sold for higher prices. [ABSTRACT FROM AUTHOR]

Polygonum ciliinerve (Nakai) Ohwi is a perennial twining vine plant from the Polygonaceae family, which is a Chinese herbal medicine with great value for development and utilization. The purpose of this paper is to provide a systematic review of the botany, traditional uses, phytochemistry, pharmacology, pharmacokinetics, and toxicology of Polygonum ciliinerve (Nakai) Ohwi, as well as an outlook on the future research directions and development prospects of the plant. Data on Polygonum ciliinerve (Nakai) Ohwi were obtained from different databases, including China National Knowledge Infrastructure, Baidu Academic, Wanfang Database, Google Academic, PubMed, Web of Science, SpringerLink, Wiley; books; standards; and Ph.D. and MSc theses. So far, 86 compounds have been identified from Polygonum ciliinerve (Nakai) Ohwi, including anthraquinones, stilbenes, flavonoids, tannins, chromogenic ketones, organic acids and esters, lignans, isobenzofurans, alkaloids, naphthols, and others. Studies have found that Polygonum ciliinerve (Nakai) Ohwi has a wide range of pharmacological effects, including antiviral, antibacterial, anti-inflammatory and analgesic, antitumor, immunomodulatory, hypoglycemic, and antioxidant effects. Clinically, Polygonum ciliinerve (Nakai) Ohwi is very effective in the treatment of gastritis and chronic gastritis. Based on its traditional use, chemical composition, and pharmacological activity, Polygonum ciliinerve (Nakai) Ohwi is a promising source of natural medicine in drug development. [ABSTRACT FROM AUTHOR]

A complex interplay between various processes underlies the neuropathology of Alzheimer's disease (AD) and its progressive course. Several lines of evidence point to the coupling between Aβ aggregation and neuroinflammation and its role in maintaining brain homeostasis during the long prodromal phase of AD. Little is however known about how this protective mechanism fails and as a result, an irreversible and progressive transition to clinical AD occurs. Here, we introduce a minimal model of a coupled system of Aβ aggregation and inflammation, numerically simulate its dynamical behavior, and analyze its bifurcation properties. The introduced model represents the following events: generation of Aβ monomers, aggregation of Aβ monomers into oligomers and fibrils, induction of inflammation by Aβ aggregates, and clearance of various Aβ species. Crucially, the rates of Aβ generation and clearance are modulated by inflammation level following a Hill-type response function. Despite its relative simplicity, the model exhibits enormously rich dynamics ranging from overdamped kinetics to sustained oscillations. We then specify the region of inflammation- and coupling-related parameters space where a transition to oscillatory dynamics occurs and demonstrate how changes in Aβ aggregation parameters could shift this oscillatory region in parameter space. Our results reveal the propensity of coupled Aβ aggregation-inflammation systems to oscillatory dynamics and propose prolonged sustained oscillations and their consequent immune system exhaustion as a potential mechanism underlying the transition to a more progressive phase of amyloid pathology in AD. The implications of our results in regard to early diagnosis of AD and anti-AD drug development are discussed. [ABSTRACT FROM AUTHOR]

Rhinoviruses (RVs) cause upper respiratory tract infections and pneumonia in children and adults. These non-enveloped viruses contain viral coats of four capsid proteins: VP1, VP2, VP3, and VP4. The canyon on VP1 used cell surface receptor ICAM-1 as the site of attachment and for the internalization of viruses. To date, there has been no drug or vaccine available against RVs. In this study, bioactive natural compounds of rosemary (Salvia rosmarinus L.), which are known for their pharmacological potential, were considered to target the VP1 protein. A total of 30 bioactive natural compounds of rosemary were taken as ligands to target viral proteins. The PkCSM tool was used to detect their adherence to Lipinski's rule of five and the ADMET properties of the selected ligands. Further, the CB-Dock tool was used for molecular docking studies between the VP1 protein and ligands. Based on the molecular docking and ADMET profiling results, phenethyl amine (4 methoxy benzyl) was selected as the lead compound. A comparative study was performed between the lead compound and two antiviral drugs, Placonaril and Nitazoxanide, to investigate the higher potential of natural compounds over synthetic drugs. Placonaril also targets VP1 but failed in clinical trials while Nitazoxanide was examined in clinical trials against rhinoviruses. It was discovered from this study that the (4 methoxy benzyl) phenethyl amine exhibited less toxicity in comparison to other tested drugs against RVs. More research is needed to determine its potential and make it a good medication against RVs. [ABSTRACT FROM AUTHOR]

Secondary structure prediction is a key step in understanding protein function and biological properties and is highly important in the fields of new drug development, disease treatment, bioengineering, etc. Accurately predicting the secondary structure of proteins helps to reveal how proteins are folded and how they function in cells. The application of deep learning models in protein structure prediction is particularly important because of their ability to process complex sequence information and extract meaningful patterns and features, thus significantly improving the accuracy and efficiency of prediction. In this study, a combined model integrating an improved temporal convolutional network (TCN), bidirectional long short-term memory (BiLSTM), and a multi-head attention (MHA) mechanism is proposed to enhance the accuracy of protein prediction in both eight-state and three-state structures. One-hot encoding features and word vector representations of physicochemical properties are incorporated. A significant emphasis is placed on knowledge distillation techniques utilizing the ProtT5 pretrained model, leading to performance improvements. The improved TCN, achieved through multiscale fusion and bidirectional operations, allows for better extraction of amino acid sequence features than traditional TCN models. The model demonstrated excellent prediction performance on multiple datasets. For the TS115, CB513 and PDB (2018–2020) datasets, the prediction accuracy of the eight-state structure of the six datasets in this paper reached 88.2%, 84.9%, and 95.3%, respectively, and the prediction accuracy of the three-state structure reached 91.3%, 90.3%, and 96.8%, respectively. This study not only improves the accuracy of protein secondary structure prediction but also provides an important tool for understanding protein structure and function, which is particularly applicable to resource-constrained contexts and provides a valuable tool for understanding protein structure and function. [ABSTRACT FROM AUTHOR]

Isotopic labeling is at the core of health and life science applications such as nuclear imaging, metabolomics and plays a central role in drug development. The rapid access to isotopically labeled organic molecules is a sine qua non condition to support these societally vital areas of research. Based on a rationally driven approach, this study presents an innovative solution to access labeled pyridines by a nitrogen isotope exchange reaction based on a Zincke activation strategy. The technology conceptualizes an opportunity in the field of isotope labeling. 15N-labeling of pyridines and other relevant heterocycles such as pyrimidines and isoquinolines showcases on a large set of derivatives, including pharmaceuticals. Finally, we explore a nitrogen-to-carbon exchange strategy in order to access 13C-labeled phenyl derivatives and deuterium labeling of mono-substituted benzene from pyridine-2H5. These results open alternative avenues for multiple isotope labeling on aromatic cores. The rapid access to isotopically labeled organic molecules is a sine qua non condition to support these societally vital areas of research. Here the authors present a solution to access labeled pyridines by a nitrogen isotope exchange reaction based on a Zincke activation strategy. [ABSTRACT FROM AUTHOR]

Virtual patients and digital patients/twins are two similar concepts gaining increasing attention in health care with goals to accelerate drug development and improve patients' survival, but with their own limitations. Although methods have been proposed to generate virtual patient populations using mechanistic models, there are limited number of applications in immuno-oncology research. Furthermore, due to the stricter requirements of digital twins, they are often generated in a study-specific manner with models customized to particular clinical settings (e.g., treatment, cancer, and data types). Here, we discuss the challenges for virtual patient generation in immuno-oncology with our most recent experiences, initiatives to develop digital twins, and how research on these two concepts can inform each other. [ABSTRACT FROM AUTHOR]

Heart-on-a-chip (HoC) has emerged as a highly efficient, cost-effective device for the development of engineered cardiac tissue, facilitating high-throughput testing in drug development and clinical treatment. HoC is primarily used to create a biomimetic microphysiological environment conducive to fostering the maturation of cardiac tissue and to gather information regarding the real-time condition of cardiac tissue. The development of architectural design and advanced manufacturing for these "3S" components, scaffolds, stimulation, and sensors is essential for improving the maturity of cardiac tissue cultivated on-chip, as well as the precision and accuracy of tissue states. In this review, the typical structures and manufacturing technologies of the "3S" components are summarized. The design and manufacturing suggestions for each component are proposed. Furthermore, key challenges and future perspectives of HoC platforms with integrated "3S" components are discussed. [ABSTRACT FROM AUTHOR]

Mycobacterium tuberculosis, a lethal pathogen in human history, causes millions of deaths annually, which demands the development of new concepts of drugs. Considering this fact, earlier research has explored the anti-tuberculosis potential of a probiotic strain, Lactocaseibacillus rhamnosus PMC203, leading to a subsequent focus on the molecular mechanism involved in its effect, particularly on autophagy. In this current study, immunoblotting-based assay exhibited a remarkable expression of autophagy marker LC3-II in the PMC203 treated group compared to an untreated group. A remarkable degradation of p62 was also noticed within treated cells compared to control. Furthermore, the immunofluorescence-based assay showed significant fold change in fluorescence intensity for alexa-647-LC3 and alexa-488-LC3, whereas p62 was degraded noticeably. Moreover, lysosomal biogenesis generation was elevated significantly in terms of LAMP1 and acidic vesicular organelles. As a result, PMC203-induced autophagy played a vital role in reducing M. tuberculosis burden within the macrophages in treated groups compared to untreated group. A colony -forming unit assay also revealed a significant reduction in M. tuberculosis in the treated cells over time. Additionally, the candidate strain significantly upregulated the expression of autophagy induction and lysosomal biogenesis genes. Together, these results could enrich our current knowledge of probiotics-mediated autophagy in tuberculosis and suggest its implications for innovatively managing tuberculosis. [ABSTRACT FROM AUTHOR]

Tuberculosis, caused by Mycobacterium tuberculosis, remains a major public health concern, demanding new antibiotics with innovative therapeutic principles due to the emergence of resistant strains. Benzothiazinones (BTZs) have been developed to address this problem. However, an unprecedented in vivo biotransformation of BTZs to hydride-Meisenheimer complexes has recently been discovered. Herein, we present a study of the influence of electron-withdrawing groups on the propensity of HMC formation in whole cells for a series of C-6-substituted BTZs obtained through reductive fluorocarbonylation as a late-stage functionalization key step. Gibbs free energy of reaction and Mulliken charges and Fukui indices on C-5 at quantum mechanics level were found as good indicators of in vitro HMC formation propensity. These results provide a first blueprint for the evaluation of HMC formation in drug development and set the stage for rational pharmacokinetic optimization of BTZs and similar drug candidates. Benzothiazinones (BTZs) are being developed as new antibiotics against the infection caused by Mycobacterium tuberculosis, however, BTZs can undergo an in vivo biotransformation to hydride-Meisenheimer complexes (HMC). Here, the authors show that HMC formation can be modulated by C-6 substitution of BTZ. [ABSTRACT FROM AUTHOR]

Sotatercept (sotatercept-csrk; WINREVAIRTM) is an activin signalling inhibitor that is being developed by Merck and Co., Inc. (Rahway, NJ, USA) for the treatment of pulmonary arterial hypertension. Sotatercept recently received approval in the USA for the treatment of adults with pulmonary arterial hypertension [World Health Organisation (WHO) Group 1] to increase exercise capacity, improve WHO functional class and reduce the risk of clinical worsening events. This article summarizes the milestones in the development of sotatercept leading to this first approval for pulmonary arterial hypertension. [ABSTRACT FROM AUTHOR]

Givinostat (DUVYZAT™), an orally available histone deacetylase inhibitor, is being developed by Italfarmaco for the treatment of muscular dystrophy and polycythemia vera. Givinostat received its first approval on 21 March 2024, in the USA, for the treatment of Duchenne muscular dystrophy (DMD) in patients 6 years of age and older. Approval was based on the results of the multinational phase III EPIDYS trial, in which givinostat recipients showed less decline than placebo recipients in the time taken to perform a functional task. Givinostat represents the first nonsteroidal treatment for DMD to be approved for use in patients irrespective of the specific genetic variant underlying their disease. Givinostat is available as an oral suspension to be administered twice daily with food. The recommended dosage is based on the body weight of the patient. In the EU, regulatory review of givinostat in DMD is currently underway. This article summarizes the milestones in the development of givinostat leading to this first approval for DMD. [ABSTRACT FROM AUTHOR]

Refractory chronic cough is a disabling disease with very limited therapeutic options. A better understanding of cough pathophysiology has led to the development of emerging drugs targeting cough receptors. Recent strides have illuminated novel therapeutic avenues, notably centred on modulating transient receptor potential (TRP) channels, purinergic receptors, and neurokinin receptors. By modulating these receptors, the goal is to intervene in the sensory pathways that trigger cough reflexes, thereby providing relief without compromising vital protective mechanisms. These innovative pharmacotherapies hold promise for improvement of refractory chronic cough by offering improved efficacy and potentially mitigating adverse effects associated with current recommended treatments. A deeper comprehension of their precise mechanisms of action and clinical viability is imperative for optimising therapeutic interventions and elevating patient care standards in respiratory health. This review delineates the evolving landscape of drug development in this domain, emphasising the significance of these advancements in reshaping the paradigm of cough management. [ABSTRACT FROM AUTHOR]