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Sodium-glucose co-transporter 1 (SGLT1) is primarily expressed on the membrane of enterocytes, a type of epithelial cell found in the intestines, where it mediates the unidirectional absorption of glucose and galactose. Beyond its well-established role in nutrient absorption, SGLT1 also plays a protective role in maintaining the integrity of the intestinal barrier. Specifically, the natural ligand of SGLT1 (d-glucose) and a synthetic C -glucoside developed by our group can induce a protective anti-inflammatory effect on the intestinal epithelium. In this paper, we report the creation of a small library of C -glycoside, putative ligands for SGLT1, to gain further insights into its unclear mechanism of action. Preliminary biological experiments performed on an in vitro model of doxorubicin-induced mucositis, a severe intestinal inflammatory condition, indicate that the aromatic moiety present in all the compounds of the library is crucial for biological activity, while the sugar component appears to have less influence. These findings will be exploited to develop new, more potent anti-inflammatory compounds and to better understand and rationalize the protective mechanism of action.

MDA-9/Syntenin, a key scaffolding protein and a molecular hub involved in a diverse range of cell signaling responses, has proved to be a challenging target for the design and discovery of small molecule probes. In this paper, we report on the design and synthesis of small molecule ligands of this key protein. Genetic algorithm-based computational design and the five-eight step synthesis of three molecules led to ligands with affinities in the range of 1-3 µM, a 20-60-fold improvement over literature reports. The design and synthesis strategies, coupled with the structure-dependent gain or loss in affinity, afford the deduction of principles that should guide the design of advanced probes of MDA-9/Syntenin.

To accurately study human organ function and disease 'in the dish', it is necessary to develop reliable cell-based models that closely track human physiology. Our interest lay with the liver, which is the largest solid organ in the body. The liver is a multifunctional and highly regenerative organ; however, severe liver damage can have dire consequences for human health. A common cause of liver damage is adverse reactions to prescription drugs. Therefore, the development of predictive liver models that capture human drug metabolism patterns is required to optimise the drug development process. In our study, we aimed to identify compounds that could improve the metabolic function of stem cell-derived liver tissue. Therefore, we screened a compound library to identify additives that improved the maturity of in vitro -engineered human tissue, with the rationale that by taking such an approach, we would be able to fine-tune neonatal and adult cytochrome P450 metabolic function in stem cell-derived liver tissue.

Glucagon receptor (GCGR) is a class B1 G-protein-coupled receptor that plays a crucial role in maintaining human blood glucose homeostasis and is a significant target for the treatment of type 2 diabetes mellitus (T2DM). Currently, six small molecules (Bay 27-9955, MK-0893, MK-3577, LY2409021, PF-06291874, and LGD-6972) have been tested or are undergoing clinical trials, but only the binding site of MK-0893 has been resolved. To predict binding sites for other small molecules, we utilized both the crystal structure of the GCGR and MK-0893 complex and dynamic conformations. We docked five small molecules and selected the best conformation based on binding mode, docking score, and binding free energy. We performed MD simulations to verify the binding mode of the selected small molecules. Moreover, when selecting conformations, results of competitive binding were referred to. MD simulation indicated that Bay 27-9955 exhibits moderate binding stability in Pocket 3. MK-3577, LY2409021, and PF-06291874 exhibited highly stable binding to Pocket 2, consistent with experimental results. However, LY2409021 may also bind to Pocket 5. Additionally, LGD-6972 exhibited relatively stable binding in Pocket 5. We also conducted structural modifications of LGD-6972 based on the results of MD simulations and predicted its analogues' bioavailability, providing a reference for the study of GCGR small molecules.

G-quadruplexes (G4s) are non-canonical nucleic acid secondary structures that have gathered significant interest in medicinal chemistry over the past two decades due to their unique structural features and potential roles in a variety of biological processes and disorders. Traditionally, research efforts have focused on stabilizing G4s, while in recent years, the attention has progressively shifted to G4 destabilization, unveiling new therapeutic perspectives. This review provides an in-depth overview of recent advances in the development of small molecules, starting with the controversial role of TMPyP4. Moreover, we described effective metal complexes in addition to G4-disrupting small molecules as well as good G4 stabilizing ligands that can destabilize G4s in response to external stimuli. Finally, we presented antisense strategies as a promising approach for destabilizing G4s, with a particular focus on 2'-OMe antisense oligonucleotide, peptide nucleic acid, and locked nucleic acid. Overall, this review emphasizes the importance of understanding G4 dynamics as well as ongoing efforts to develop selective G4-unfolding strategies that can modulate their biological function and therapeutic potential.

Designing and developing inhibitors against the epigenetic target DNA methyltransferase (DNMT) is an attractive strategy in epigenetic drug discovery. DNMT1 is one of the epigenetic enzymes with significant clinical relevance. Structure-based de novo design is a drug discovery strategy that was used in combination with similarity searching to identify a novel DNMT inhibitor with a novel chemical scaffold and warrants further exploration. This study aimed to continue exploring the potential of de novo design to build epigenetic-focused libraries targeted toward DNMT1. Herein, we report the results of an in-depth and critical comparison of ligand- and structure-based de novo design of screening libraries focused on DNMT1. The newly designed chemical libraries focused on DNMT1 are freely available on GitHub.

The regulation of the cancer cell cycle heavily relies on cyclin-dependent kinases (CDKs). Targeting CDKs has been identified as a promising approach for effective cancer therapy. In recent years, there has been significant attention paid towards developing small-molecule CDK inhibitors in the field of drug discovery. Notably, five such inhibitors have already received regulatory approval for the treatment of different cancers, including breast tumors, lung malignancies, and hematological malignancies. This review provides an overview of the synthetic routes used to produce 17 representative small-molecule CDK inhibitors that have obtained regulatory approval or are currently being evaluated through clinical trials. It also discusses their clinical applications for treating CDK-related diseases and explores the challenges and limitations associated with their use in a clinical setting, which will stimulate the further development of novel CDK inhibitors. By integrating therapeutic applications, synthetic methodologies, and mechanisms of action observed in various clinical trials involving these CDK inhibitors, this review facilitates a comprehensive understanding of the versatile roles and therapeutic potential offered by interventions targeting CDKs.

A small library of 79 substituted phenylsulfonamidoalkyl sulfamates, 1b - 79b , was synthesized starting from arylsulfonyl chlorides and amino alcohols with different numbers of methylene groups between the hydroxyl and amino moieties yielding intermediates 1a - 79a , followed by the reaction of the latter with sulfamoyl chloride. All compounds were screened for their inhibitory activity on bovine carbonic anhydrase II. Compounds 1a - 79a showed no inhibition of the enzyme, in contrast to sulfamates 1b - 79b . Thus, the inhibitory potential of compounds 1b - 79b towards this enzyme depends on the substituent and the substitution pattern of the phenyl group as well as the length of the spacer. Bulkier substituents in the para position proved to be better for inhibiting CAII than compounds with the same substituent in the meta or ortho position. For many substitution patterns, compounds with shorter spacer lengths were superior to those with long chain spacers. Compounds with shorter spacer lengths performed better than those with longer chain spacers for a variety of substitution patterns. The most active compound held inhibition constant as low as K i = 0.67 μM (for 49b ) and a tert -butyl substituent in para position and acted as a competitive inhibitor of the enzyme.

The beta-galactoside-binding mammalian lectin galectin-1 can bind, via its carbohydrate recognition domain (CRD), to various cell surface glycoproteins and has been implicated in a range of cancers. As a consequence of binding to sugar residues on cell surface receptors, it has been shown to have a pleiotropic effect across many cell types and mechanisms, resulting in immune system modulation and cancer progression. As a result, it has started to become a therapeutic target for both small and large molecules. In previous studies, we used fluorescence polarization (FP) assays to determine K D values to screen and triage small molecule glycomimetics that bind to the galectin-1 CRD. In this study, surface plasmon resonance (SPR) was used to compare human and mouse galectin-1 affinity measures with FP, as SPR has not been applied for compound screening against this galectin. Binding affinities for a selection of mono- and di-saccharides covering a 1000-fold range correlated well between FP and SPR assay formats for both human and mouse galectin-1. It was shown that slower dissociation drove the increased affinity at human galectin-1, whilst faster association was responsible for the effects in mouse galectin-1. This study demonstrates that SPR is a sound alternative to FP for early drug discovery screening and determining affinity estimates. Consequently, it also allows association and dissociation constants to be measured in a high-throughput manner for small molecule galectin-1 inhibitors.

Small-molecule drug design aims to generate compounds that target specific proteins, playing a crucial role in the early stages of drug discovery. Recently, research has emerged that utilizes the GPT model, which has achieved significant success in various fields to generate molecular compounds. However, due to the persistent challenge of small datasets in the pharmaceutical field, there has been some degradation in the performance of generating target-specific compounds. To address this issue, we propose an enhanced target-specific drug generation model, Adapt-cMolGPT, which modifies molecular representation and optimizes the fine-tuning process. In particular, we introduce a new fine-tuning method that incorporates an adapter module into a pre-trained base model and alternates weight updates by sections. We evaluated the proposed model through multiple experiments and demonstrated performance improvements compared to previous models. In the experimental results, Adapt-cMolGPT generated a greater number of novel and valid compounds compared to other models, with these generated compounds exhibiting properties similar to those of real molecular data. These results indicate that our proposed method is highly effective in designing drugs targeting specific proteins.

In the field of human health research, the homeostasis of copper (Cu) is receiving increased attention due to its connection to pathological conditions, including diabetes mellitus (DM). Recent studies have demonstrated that proteins associated with Cu homeostasis, such as ATOX1, FDX1, ATP7A, ATPB, SLC31A1, p53, and UPS, also contribute to DM. Cuproptosis, characterized by Cu homeostasis dysregulation and Cu overload, has been found to cause the oligomerization of lipoylated proteins in mitochondria, loss of iron-sulfur protein, depletion of glutathione, production of reactive oxygen species, and cell death. Further research into how cuproptosis affects DM is essential to uncover its mechanism of action and identify effective interventions. In this article, we review the molecular mechanism of Cu homeostasis and the role of cuproptosis in the pathogenesis of DM. The study of small-molecule drugs that affect these proteins offers the possibility of moving from symptomatic treatment to treating the underlying causes of DM.

The PD-1/PD-L1 complex is an immune checkpoint responsible for regulating the natural immune response, but also allows tumors to escape immune surveillance. Inhibition of the PD-1/PD-L1 axis positively contributes to the efficacy of cancer treatment. The only available therapeutics targeting PD-1/PD-L1 are monoclonal antibody-based drugs, which have several limitations. Therefore, small molecule compounds are emerging as an attractive alternative that can potentially overcome the drawbacks of mAb-based therapy. In this article, we present a novel class of small molecule compounds based on the terphenyl scaffold that bind to PD-L1. The general architecture of the presented structures is characterized by axial symmetry and consists of three elements: an m-terphenyl core, an additional aromatic ring, and a solubilizing agent. Using molecular docking, we designed a series of final compounds, which were subsequently synthesized and tested in HTRF assay and NMR binding assay to evaluate their activity. In addition, we performed an in-depth analysis of the mutual arrangement of the phenyl rings of the terphenyl core within the binding pocket of PD-L1 and found several correlations between the plane angle values and the affinity of the compounds towards the protein.

SARS-CoV-2 is the pathogen responsible for the most recent global pandemic, which has claimed hundreds of thousands of victims worldwide. Despite remarkable efforts to develop an effective vaccine, concerns have been raised about the actual protection against novel variants. Thus, researchers are eager to identify alternative strategies to fight against this pathogen. Like other opportunistic entities, a key step in the SARS-CoV-2 lifecycle is the maturation of the envelope glycoprotein at the RARR685↓ motif by the cellular enzyme Furin. Inhibition of this cleavage greatly affects viral propagation, thus representing an ideal drug target to contain infection. Importantly, no Furin-escape variants have ever been detected, suggesting that the pathogen cannot replace this protease by any means. Here, we designed a novel fluorogenic SARS-CoV-2-derived substrate to screen commercially available and custom-made libraries of small molecules for the identification of new Furin inhibitors. We found that a peptide substrate mimicking the cleavage site of the envelope glycoprotein of the Omicron variant (QTQTKSHRRAR-AMC) is a superior tool for screening Furin activity when compared to the commercially available Pyr-RTKR-AMC substrate. Using this setting, we identified promising novel compounds able to modulate Furin activity in vitro and suitable for interfering with SARS-CoV-2 maturation. In particular, we showed that 3-((5-((5-bromothiophen-2-yl)methylene)-4-oxo-4,5 dihydrothiazol-2-yl)(3-chloro-4-methylphenyl)amino)propanoic acid ( P3 , IC 50 = 35 μM) may represent an attractive chemical scaffold for the development of more effective antiviral drugs via a mechanism of action that possibly implies the targeting of Furin secondary sites (exosites) rather than its canonical catalytic pocket. Overall, a SARS-CoV-2-derived peptide was investigated as a new substrate for in vitro high-throughput screening (HTS) of Furin inhibitors and allowed the identification of compound P3 as a promising hit with an innovative chemical scaffold. Given the key role of Furin in infection and the lack of any Food and Drug Administration (FDA)-approved Furin inhibitor, P3 represents an interesting antiviral candidate.

This study aimed to identify potential BCL-2 small molecule inhibitors using deep neural networks (DNN) and random forest (RF), algorithms as well as molecular docking and molecular dynamics (MD) simulations to screen a library of small molecules. The RF model classified 61% (2355/3867) of molecules as 'Active'. Further analysis through molecular docking with Vina identified CHEMBL3940231, CHEMBL3938023, and CHEMBL3947358 as top-scored small molecules with docking scores of -11, -10.9, and 10.8 kcal/mol, respectively. MD simulations validated these compounds' stability and binding affinity to the BCL2 protein.

Tumor necrosis factor-α-induced protein 8-like 3 (TNFAIP8L3 or TIPE3) functions as a transfer protein for lipid second messengers. TIPE3 is highly upregulated in several human cancers and has been established to significantly promote tumor cell proliferation, migration, and invasion and inhibit the apoptosis of cancer cells. Thus, inhibiting the function of TIPE3 is expected to be an effective strategy against cancer. The advancement of artificial intelligence (AI)-driven drug development has recently invigorated research in anti-cancer drug development. In this work, we incorporated DFCNN, Autodock Vina docking, DeepBindBC, MD, and metadynamics to efficiently identify inhibitors of TIPE3 from a ZINC compound dataset. Six potential candidates were selected for further experimental study to validate their anti-tumor activity. Among these, three small-molecule compounds (K784-8160, E745-0011, and 7238-1516) showed significant anti-tumor activity in vitro, leading to reduced tumor cell viability, proliferation, and migration and enhanced apoptotic tumor cell death. Notably, E745-0011 and 7238-1516 exhibited selective cytotoxicity toward tumor cells with high TIPE3 expression while having little or no effect on normal human cells or tumor cells with low TIPE3 expression. A molecular docking analysis further supported their interactions with TIPE3, highlighting hydrophobic interactions and their shared interaction residues and offering insights for designing more effective inhibitors. Taken together, this work demonstrates the feasibility of incorporating deep learning and MD simulations in virtual drug screening and provides inhibitors with significant potential for anti-cancer drug development against TIPE3-.

Leishmaniasis, an infectious disease caused by pathogenic Leishmania parasites, affects millions of people in developing countries, and its re-emergence in developed countries, particularly in Europe, poses a growing public health concern. The limitations of current treatments and the absence of effective vaccines necessitate the development of novel therapeutics. In this study, we focused on identifying small molecule inhibitors which prevents the interaction between peroxin 5 (PEX5) and peroxisomal targeting signal 1 (PTS1), pivotal for kinetoplastid parasite survival. The Leishmania donovani PEX5, containing a C-terminal tetratricopeptide repeat (TPR) domain, was expressed and purified, followed by the quantification of kinetic parameters of PEX5-PTS1 interactions. A fluorescence polarization-based high-throughput screening assay was developed and small molecules inhibiting the Ld PEX5-PTS1 interaction were discovered through the screening of a library of 51,406 compounds. Based on the confirmatory assay, nine compounds showed half maximal inhibitory concentration (IC 50 ) values ranging from 3.89 to 24.50 µM. In silico docking using a homology model of Ld PEX5 elucidated that the molecular interactions between Ld PEX5 and the inhibitors share amino acids critical for PTS1 binding. Notably, compound P20 showed potent activity against the growth of L. donovani promastigotes, L. major promastigotes, and Trypanosoma brucei blood stream form, with IC 50 values of 12.16, 19.21, and 3.06 μM, respectively. The findings underscore the potential of targeting Ld PEX5-PTS1 interactions with small molecule inhibitors as a promising strategy for the discovery of new anti-parasitic compounds.

Mitochondrial RNA editing in trypanosomes represents an attractive target for developing safer and more efficient drugs for treating infections with trypanosomes because this RNA editing pathway is not found in humans. Other workers have targeted several enzymes in this editing system, but not the RNA. Here, we target a universal domain of the RNA editing substrate, which is the U-helix formed between the oligo-U tail of the guide RNA and the target mRNA. We selected a part of the U-helix that is rich in G-U wobble base pairs as the target site for the virtual screening of 262,000 compounds. After chemoinformatic filtering of the top 5000 leads, we subjected 50 representative complexes to 50 nanoseconds of molecular dynamics simulations. We identified 15 compounds that retained stable interactions in the deep groove of the U-helix. The microscale thermophoresis binding experiments on these five compounds show low-micromolar to nanomolar binding affinities. The UV melting studies show an increase in the melting temperatures of the U-helix upon binding by each compound. These five compounds can serve as leads for drug development and as research tools to probe the role of the RNA structure in trypanosomal RNA editing.

Pyruvate dehydrogenase kinases (PDKs) are serine/threonine kinases, that are directly involved in altered cancer cell metabolism, resulting in cancer aggressiveness and resistance. Dichloroacetic acid (DCA) is the first PDK inhibitor that has entered phase II clinical; however, several side effects associated with weak anticancer activity and excessive drug dose (100 mg/kg) have led to its limitation in clinical application. Building upon a molecular hybridization approach, a small library of 3-amino-1,2,4-triazine derivatives has been designed, synthesized, and characterized for their PDK inhibitory activity using in silico, in vitro, and in vivo assays. Biochemical screenings showed that all synthesized compounds are potent and subtype-selective inhibitors of PDK. Accordingly, molecular modeling studies revealed that a lot of ligands can be properly placed inside the ATP-binding site of PDK1. Interestingly, 2D and 3D cell studies revealed their ability to induce cancer cell death at low micromolar doses, being extremely effective against human pancreatic KRAS mutated cancer cells. Cellular mechanistic studies confirm their ability to hamper the PDK/PDH axis, thus leading to metabolic/redox cellular impairment, and to ultimately trigger apoptotic cancer cell death. Remarkably, preliminary in vivo studies performed on a highly aggressive and metastatic Kras-mutant solid tumor model confirm the ability of the most representative compound 5i to target the PDH/PDK axis in vivo and highlighted its equal efficacy and better tolerability profile with respect to those elicited by the reference FDA approved drugs, cisplatin and gemcitabine. Collectively, the data highlights the promising anticancer potential of these novel PDK-targeting derivatives toward obtaining clinical candidates for combatting highly aggressive KRAS-mutant pancreatic ductal adenocarcinomas.

High-resolution mass spectrometry is a promising technique in non-target screening (NTS) to monitor contaminants of emerging concern in complex samples. Current chemical identification strategies in NTS experiments typically depend on spectral libraries, chemical databases, and in silico fragmentation tools. However, small molecule identification remains challenging due to the lack of orthogonal sources of information (e.g., unique fragments). Collision cross section (CCS) values measured by ion mobility spectrometry (IMS) offer an additional identification dimension to increase the confidence level. Thanks to the advances in analytical instrumentation, an increasing application of IMS hybrid with high-resolution mass spectrometry (HRMS) in NTS has been reported in the recent decades. Several CCS prediction tools have been developed. However, limited CCS prediction methods were based on a large scale of chemical classes and cross-platform CCS measurements. We successfully developed two prediction models using a random forest machine learning algorithm. One of the approaches was based on chemicals' super classes; the other model was direct CCS prediction using molecular fingerprint. Over 13,324 CCS values from six different laboratories and PubChem using a variety of ion-mobility separation techniques were used for training and testing the models. The test accuracy for all the prediction models was over 0.85, and the median of relative residual was around 2.2%. The models can be applied to different IMS platforms to eliminate false positives in small molecule identification.

Molecular glue (MG) compounds are a type of unique small molecule that can change the protein-protein interactions (PPIs) and interactomes by degrading, stabilizing, or activating the target protein after their binging. These small-molecule MGs are gradually being recognized for their potential application in treating human diseases, including cancer. Evidence suggests that small-molecule MG compounds could essentially target any proteins, which play critical roles in human disease etiology, where many of these protein targets were previously considered undruggable. Intriguingly, most MG compounds with high efficacy for cancer treatment can glue on and control multiple key protein targets. On the other hand, a single key protein target can also be glued by multiple MG compounds with distinct chemical structures. The high flexibility of MG-protein interaction profiles provides rich soil for the growth and development of small-molecule MG compounds that can be used as molecular tools to assist in unraveling disease mechanisms, and they can also facilitate drug development for the treatment of human disease, especially human cancer. In this review, we elucidate this concept by using various types of small-molecule MG compounds and their corresponding protein targets that have been documented in the literature.

Considering the potential bioactivities of natural product and natural product-like compounds with highly complex and diverse structures, the screening of collections and small-molecule libraries for high-throughput screening (HTS) and high-content screening (HCS) has emerged as a powerful tool in the development of novel therapeutic agents. Herein, we review the recent advances in divergent synthetic approaches such as complexity-to-diversity (Ctd) and biomimetic strategies for the generation of structurally complex and diverse indole-based natural product and natural product-like small-molecule libraries.

The use of in silico toxicity prediction methods plays an important role in the selection of lead compounds and in ADMET studies since in vitro and in vivo methods are often limited by ethics, time, budget and other resources. In this context, we present our new web tool VenomPred, a user-friendly platform for evaluating the potential mutagenic, hepatotoxic, carcinogenic and estrogenic effects of small molecules. VenomPred platform employs several in-house Machine Learning (ML) models developed with datasets derived from VEGA QSAR, a software that includes a comprehensive collection of different toxicity models and has been used as a reference for building and evaluating our ML models. The results showed that our models achieved equal or better performance than those obtained with the reference models included in VEGA QSAR. In order to improve the predictive performance of our platform, we adopted a consensus approach combining the results of different ML models, which was able to predict chemical toxicity better than the single models. This improved method was thus implemented in the VenomPred platform, a freely accessible webserver that takes the SMILES (Simplified Molecular-Input Line-Entry System) strings of the compounds as input and sends the prediction results providing a probability score about their potential toxicity.

Enterovirus genus has over one hundred genotypes and could cause several kinds of severe animal and human diseases. Understanding the role of conserved residues in the VP1 capsid protein among the enterovirus genus may lead to anti-enteroviral drug development. The highly conserved residues were found to be located at the loop and ß-barrel intersections. To elucidate the role of these VP1 residues among the enterovirus genus, alanine substitution reverse genetics (rg) variants were generated, and virus properties were investigated for their impact. Six highly conserved residues were identified as located near the inside of the canyon, and four of them were close to the ß-barrel and loop intersection. The variants rgVP1-R86A, rgVP1-P193A, rgVP1-G231A, and rgVP1-K256A were unable to be obtained, which may be due to disruption in the virus replication process. In contrast, rgVP1-E134A and rgVP1-P157A replicated well and rgVP1-P157A showed smaller plaque size, lower viral growth kinetics, and thermal instability at 39.5°C when compared to the rg wild type virus. These findings showed that the conserved residues located at the ß-barrel and loop junction play roles in modulating viral replication, which may provide a pivotal role for pan-enteroviral inhibitor candidate.

RORγT is a protein product of the RORC gene belonging to the nuclear receptor subfamily of retinoic-acid-receptor-related orphan receptors (RORs). RORγT is preferentially expressed in Th17 lymphocytes and drives their differentiation from naive CD4+ cells and is involved in the regulation of the expression of numerous Th17-specific cytokines, such as IL-17. Because Th17 cells are implicated in the pathology of autoimmune diseases (e.g., psoriasis, inflammatory bowel disease, multiple sclerosis), RORγT, whose activity is regulated by ligands, has been recognized as a drug target in potential therapies against these diseases. The identification of such ligands is time-consuming and usually requires the screening of chemical libraries. Herein, using a Tanimoto similarity search, we found corosolic acid and other pentacyclic tritepenes in the library we previously screened as compounds highly similar to the RORγT inverse agonist ursolic acid. Furthermore, using gene reporter assays and Th17 lymphocytes, we distinguished compounds that exert stronger biological effects (ursolic, corosolic, and oleanolic acid) from those that are ineffective (asiatic and maslinic acids), providing evidence that such combinatorial methodology (in silico and experimental) might help wet screenings to achieve more accurate results, eliminating false negatives.

Heat Shock Protein 70s (HSP70s) are key molecular chaperones that are overexpressed in many cancers and often associated with metastasis and poor prognosis. It has proven difficult to develop ATP-competitive, drug-like small molecule inhibitors of HSP70s due to the flexible and hydrophilic nature of the HSP70 ATP-binding site and its high affinity for endogenous nucleotides. The aim of this study was to explore the potential for the inhibition of HSP70 through alternative binding sites using fragment-based approaches. A surface plasmon resonance (SPR) fragment screen designed to detect secondary binding sites in HSP70 led to the identification by X-ray crystallography of a cryptic binding site in the nucleotide-binding domain (NBD) of HSP70 adjacent to the ATP-binding site. Fragment binding was confirmed and characterized as ATP-competitive using SPR and ligand-observed NMR methods. Molecular dynamics simulations were applied to understand the interactions with the protein upon ligand binding, and local secondary structure changes consistent with interconversion between the observed crystal structures with and without the cryptic pocket were detected. A virtual high-throughput screen (vHTS) against the cryptic pocket was conducted, and five compounds with diverse chemical scaffolds were confirmed to bind to HSP70 with micromolar affinity by SPR. These results identified and characterized a new targetable site on HSP70. While targeting HSP70 remains challenging, the new site may provide opportunities to develop allosteric ATP-competitive inhibitors with differentiated physicochemical properties from current series.

A rational therapeutic strategy is urgently needed for combating SARS-CoV-2 infection. Viral infection initiates when the SARS-CoV-2 receptor-binding domain (RBD) binds to the ACE2 receptor, and thus, inhibiting RBD is a promising therapeutic for blocking viral entry. In this study, the structure of lead antiviral candidate binder (LCB1), which has three alpha-helices (H1, H2, and H3), is used as a template to design and simulate several miniprotein RBD inhibitors. LCB1 undergoes two modifications: structural modification by truncation of the H3 to reduce its size, followed by single and double amino acid substitutions to enhance its binding with RBD. We use molecular dynamics (MD) simulations supported by ab initio density functional theory (DFT) calculations. Complete binding profiles of all miniproteins with RBD have been determined. The MD investigations reveal that the H3 truncation results in a small inhibitor with a -1.5 kcal/mol tighter binding to RBD than original LCB1, while the best miniprotein with higher binding affinity involves D17R or E11V + D17R mutation. DFT calculations provide atomic-scale details on the role of hydrogen bonding and partial charge distribution in stabilizing the minibinder:RBD complex. This study provides insights into general principles for designing potential therapeutics for SARS-CoV-2.

We report the discovery of several highly potent small molecules with low-nM potency against severe acute respiratory syndrome coronavirus (SARS-CoV; lowest half-maximal inhibitory concentration (IC 50 : 13 nM), SARS-CoV-2 (IC 50 : 23 nM), and Middle East respiratory syndrome coronavirus (MERS-CoV; IC 50 : 76 nM) in pseudovirus-based assays with excellent selectivity index (SI) values (>5000), demonstrating potential pan-coronavirus inhibitory activities. Some compounds showed 100% inhibition against the cytopathic effects (CPE; IC 100 ) of an authentic SARS-CoV-2 (US_WA-1/2020) variant at 1.25 µM. The most active inhibitors also potently inhibited variants of concern (VOCs), including the UK (B.1.1.7) and South African (B.1.351) variants and the Delta variant (B.1.617.2) originally identified in India in pseudovirus-based assay. Surface plasmon resonance (SPR) analysis with one potent inhibitor confirmed that it binds to the prefusion SARS-CoV-2 spike protein trimer. These small-molecule inhibitors prevented virus-mediated cell-cell fusion. The absorption, distribution, metabolism, and excretion (ADME) data for one of the most active inhibitors, NBCoV1, demonstrated drug-like properties. An in vivo pharmacokinetics (PK) study of NBCoV1 in rats demonstrated an excellent half-life (t 1/2 ) of 11.3 h, a mean resident time (MRT) of 14.2 h, and oral bioavailability. We expect these lead inhibitors to facilitate the further development of preclinical and clinical candidates.

Since December 2019, the new SARS-CoV-2-related COVID-19 disease has caused a global pandemic and shut down the public life worldwide. Several proteins have emerged as potential therapeutic targets for drug development, and we sought out to review the commercially available and marketed SARS-CoV-2-targeted libraries ready for high-throughput virtual screening (HTVS). We evaluated the SARS-CoV-2-targeted, protease-inhibitor-focused and protein-protein-interaction-inhibitor-focused libraries to gain a better understanding of how these libraries were designed. The most common were ligand- and structure-based approaches, along with various filtering steps, using molecular descriptors. Often, these methods were combined to obtain the final library. We recognized the abundance of targeted libraries offered and complimented by the inclusion of analytical data; however, serious concerns had to be raised. Namely, vendors lack the information on the library design and the references to the primary literature. Few references to active compounds were also provided when using the ligand-based design and usually only protein classes or a general panel of targets were listed, along with a general reference to the methods, such as molecular docking for the structure-based design. No receptor data, docking protocols or even references to the applied molecular docking software (or other HTVS software), and no pharmacophore or filter design details were given. No detailed functional group or chemical space analyses were reported, and no specific orientation of the libraries toward the design of covalent or noncovalent inhibitors could be observed. All libraries contained pan-assay interference compounds (PAINS), rapid elimination of swill compounds (REOS) and aggregators, as well as focused on the drug-like model, with the majority of compounds possessing their molecular mass around 500 g/mol. These facts do not bode well for the use of the reviewed libraries in drug design and lend themselves to commercial drug companies to focus on and improve.

Coppers play crucial roles in the maintenance homeostasis in living species. Approximately 20 enzyme families of eukaryotes and prokaryotes are known to utilize copper atoms for catalytic activities. However, small-molecule inhibitors directly targeting catalytic centers are rare, except for those that act against tyrosinase and dopamine-β-hydroxylase (DBH). This study tested whether known tyrosinase inhibitors can inhibit the copper-containing enzymes, ceruloplasmin, DBH, and laccase. While most small molecules minimally reduced the activities of ceruloplasmin and DBH, aside from known inhibitors, 5 of 28 tested molecules significantly inhibited the function of laccase, with the K i values in the range of 15 to 48 µM. Enzyme inhibitory kinetics classified the molecules as competitive inhibitors, whereas differential scanning fluorimetry and fluorescence quenching supported direct bindings. To the best of our knowledge, this is the first report on organic small-molecule inhibitors for laccase. Comparison of tyrosinase and DBH inhibitors using cheminformatics predicted that the presence of thione moiety would suffice to inhibit tyrosinase. Enzyme assays confirmed this prediction, leading to the discovery of two new dual tyrosinase and DBH inhibitors.

Store-operated calcium entry (SOCE) constitutes a fine-tuning mechanism responsible for the replenishment of intracellular stores. Hippocampal SOCE is regulated by store-operated channels (SOC) organized in tripartite complex TRPC6/ORAI2/STIM2. It is suggested that in neurons, SOCE maintains intracellular homeostatic Ca2+ concentration at resting conditions and is needed to support the structure of dendritic spines. Recent evidence suggests that positive modulators of SOC are prospective drug candidates to treat Alzheimer's disease (AD) at early stages. Although STIM2 and ORAI2 are definitely involved in the regulation of nSOC amplitude and a play major role in AD pathogenesis, growing evidence suggest that it is not easy to target these proteins pharmacologically. Existing positive modulators of TRPC6 are unsuitable for drug development due to either bad pharmacokinetics or side effects. Thus, we concentrate the review on perspectives to develop specific nSOC modulators based on available 3D structures of TRPC6, ORAI2, and STIM2. We shortly describe the structural features of existing models and the methods used to prepare them. We provide commonly used steps applied for drug design based on 3D structures of target proteins that might be used to develop novel AD preventing therapy.

Relaxin/insulin-like family peptide receptor 3 (RXFP3) belongs to class A G protein-coupled receptor family. RXFP3 and its endogenous ligand relaxin-3 are mainly expressed in the brain with important roles in the regulation of appetite, energy metabolism, endocrine homeostasis and emotional processing. It is therefore implicated as a potential target for treatment of various central nervous system diseases. Since selective agonists of RXFP3 are restricted to relaxin-3 and its analogs, we conducted a high-throughput screening campaign against 32,021 synthetic and natural product-derived compounds using a cyclic adenosine monophosphate (cAMP) measurement-based method. Only one compound, WNN0109-C011, was identified following primary screening, secondary screening and dose-response studies. Although displayed agonistic effect in cells overexpressing the human RXFP3, it also showed cross-reactivity with the human RXFP4. This hit compound may provide not only a chemical probe to investigate the function of RXFP3/4, but also a novel scaffold for the development of RXFP3/4 agonists.

Molecule interacting with CasL 2 (MICAL2), a cytoskeleton dynamics regulator, are strongly expressed in several human cancer types, especially at the invasive front, in metastasizing cancer cells and in the neo-angiogenic vasculature. Although a plethora of data exist and stress a growing relevance of MICAL2 to human cancer, it is worth noting that only one small-molecule inhibitor, named CCG-1423 (1), is known to date. Herein, with the aim to develop novel MICAL2 inhibitors, starting from CCG-1423 (1), a small library of new compounds was synthetized and biologically evaluated on human dermal microvascular endothelial cells (HMEC-1) and on renal cell adenocarcinoma (786-O) cells. Among the novel compounds, 10 and 7 gave interesting results in terms of reduction in cell proliferation and/or motility, whereas no effects were observed in MICAL2-knocked down cells. Aside from the interesting biological activities, this work provides the first structure-activity relationships (SARs) of CCG-1423 (1), thus providing precious information for the discovery of new MICAL2 inhibitors.

Cytochrome P450 enzymes (CYPs) are the largest group of enzymes involved in human drug metabolism. Ligand tunnels connect their active site buried at the core of the membrane-anchored protein to the surrounding solvent environment. Recently, evidence of a superficial allosteric site, here denoted as hotspot 1 (H1), involved in the regulation of ligand access in a soluble prokaryotic CYP emerged. Here, we applied multi-scale computational modeling techniques to study the conservation and functionality of this allosteric site in the nine most relevant mammalian CYPs responsible for approximately 70% of drug metabolism. In total, we systematically analyzed over 44 μs of trajectories from conventional MD, cosolvent MD, and metadynamics simulations. Our bioinformatic analysis and simulations with organic probe molecules revealed the site to be well conserved in the CYP2 family with the exception of CYP2E1. In the presence of a ligand bound to the H1 site, we could observe an enlargement of a ligand tunnel in several members of the CYP2 family. Further, we could detect the facilitation of ligand translocation by H1 interactions with statistical significance in CYP2C8 and CYP2D6, even though all other enzymes except for CYP2C19, CYP2E1, and CYP3A4 presented a similar trend. As the detailed comprehension of ligand access and egress phenomena remains one of the most relevant challenges in the field, this work contributes to its elucidation and ultimately helps in estimating the selectivity of metabolic transformations using computational techniques.

Although a monoclonal antibody targeting the multifunctional ectoenzyme CD38 is an FDA-approved drug, few small molecule inhibitors exist for this enzyme that catalyzes inter alia the formation and metabolism of the N 1-ribosylated, Ca 2+ -mobilizing, second messenger cyclic adenosine 5'-diphosphoribose (cADPR). N 1-Inosine 5'-monophosphate ( N 1-IMP) is a fragment directly related to cADPR. 8-Substituted- N 1-IMP derivatives, prepared by degradation of cyclic parent compounds, inhibit CD38-mediated cADPR hydrolysis more efficiently than related cyclic analogues, making them attractive for inhibitor development. We report a total synthesis of the N 1-IMP scaffold from adenine and a small initial compound series that facilitated early delineation of structure-activity parameters, with analogues evaluated for inhibition of CD38-mediated hydrolysis of cADPR. The 5'-phosphate group proved essential for useful activity, but substitution of this group by a sulfonamide bioisostere was not fruitful. 8-NH 2 - N 1-IMP is the most potent inhibitor (IC 50 = 7.6 μM) and importantly HPLC studies showed this ligand to be cleaved at high CD38 concentrations, confirming its access to the CD38 catalytic machinery and demonstrating the potential of our fragment approach.

The pyrazolyl-urea Gege3 molecule has shown interesting antiangiogenic effects in the tumor contest. Here, we have studied the role of this compound as interfering with endothelial cells activation in response to the paracrine effects of annexin A1 (ANXA1), known to be involved in promoting tumor progression. ANXA1 has been analyzed in the extracellular environment once secreted through microvesicles (EVs) by pancreatic cancer (PC) cells. Particularly, Gege3 has been able to notably prevent the effects of Ac2-26, the ANXA1 mimetic peptide, and of PC-derived EVs on endothelial cells motility, angiogenesis, and calcium release. Furthermore, this compound also inhibited the translocation of ANXA1 to the plasma membrane, otherwise induced by the same ANXA1-dependent extracellular stimuli. Moreover, these effects have been mediated by the indirect inhibition of protein kinase Cα (PKCα), which generally promotes the phosphorylation of ANXA1 on serine 27. Indeed, by the subtraction of intracellular calcium levels, the pathway triggered by PKCα underwent a strong inhibition leading to the following impediment to the ANXA1 localization at the plasma membrane, as revealed by confocal and cytofluorimetry analysis. Thus, Gege3 appeared an attractive molecule able to prevent the paracrine effects of PC cells deriving ANXA1 in the tumor microenvironment.

Machine learning models predicting the bioactivity of chemical compounds belong nowadays to the standard tools of cheminformaticians and computational medicinal chemists. Multi-task and federated learning are promising machine learning approaches that allow privacy-preserving usage of large amounts of data from diverse sources, which is crucial for achieving good generalization and high-performance results. Using large, real world data sets from six pharmaceutical companies, here we investigate different strategies for averaging weighted task loss functions to train multi-task bioactivity classification models. The weighting strategies shall be suitable for federated learning and ensure that learning efforts are well distributed even if data are diverse. Comparing several approaches using weights that depend on the number of sub-tasks per assay, task size, and class balance, respectively, we find that a simple sub-task weighting approach leads to robust model performance for all investigated data sets and is especially suited for federated learning.

Methicillin-resistant Staphylococcus aureus (MRSA) is an important threat as it causes serious hospital and community acquired infections with deathly outcomes oftentimes, therefore, development of new treatments against this bacterium is a priority. Shikimate kinase, an enzyme in the shikimate pathway, is considered a good target for developing antimicrobial drugs; this is given because of its pathway, which is essential in bacteria whereas it is absent in mammals. In this work, a computer-assisted drug design strategy was used to report the first potentials inhibitors for Shikimate kinase from methicillin-resistant Staphylococcus aureus (SaSK), employing approximately 5 million compounds from ZINC15 database. Diverse filtering criteria, related to druglike characteristics and virtual docking screening in the shikimate binding site, were performed to select structurally diverse potential inhibitors from SaSK. Molecular dynamics simulations were performed to elucidate the dynamic behavior of each SaSK-ligand complex. The potential inhibitors formed important interactions with residues that are crucial for enzyme catalysis, such as Asp37, Arg61, Gly82, and Arg138. Therefore, the compounds reported provide valuable information and can be seen as the first step toward developing SaSK inhibitors in the search of new drugs against MRSA.

Cholangiocarcinomas (CHOLs), hepatobiliary malignancies, are characterized by high genetic heterogeneity, a rich tumor microenvironment, therapeutic resistance, difficulty diagnosing, and poor prognoses. Current knowledge of genetic alterations and known molecular markers for CHOL is insufficient, necessitating the need for further evaluation of the genome and RNA expression data in order to identify potential therapeutic targets, clarify the roles of these targets in the tumor microenvironment, and explore novel therapeutic drugs against the identified targets. Consequently, in our attempt to explore novel genetic markers associated with the carcinogenesis of CHOL, five genes ( SNX15 , ATP2A1 , PDCD10 , BET1 , and HMGA2 ), collectively termed CHOL-hub genes, were identified via integration of differentially expressed genes (DEGs) from relatively large numbers of samples from CHOL GEO datasets. We further explored the biological functions of the CHOL-hub genes and found significant enrichment in several biological process and pathways associated with stem cell angiogenesis, cell proliferation, and cancer development, while the interaction network revealed high genetic interactions with a number of onco-functional genes. In addition, we established associations between the CHOL-hub genes and tumor progression, metastasis, tumor immune and immunosuppressive cell infiltration, dysfunctional T-cell phenotypes, poor prognoses, and therapeutic resistance in CHOL. Thus, we proposed that targeting CHOL-hub genes could be an ideal therapeutic approach for treating CHOLs, and we explored the potential of HLC-018, a novel benzamide-linked small molecule, using molecular docking of ligand-receptor interactions. To our delight, HLC-018 was well accommodated with high binding affinities to binding pockets of CHOL-hub genes; more importantly, we found specific interactions of HLC-018 with the conserved sequence of the AT-hook DNA-binding motif of HMGA2 . Altogether, our study provides insights into the immune-oncogenic phenotypes of CHOL and provides valuable information for our ongoing experimental validation.

In continuation of our previous effort, different in silico selection methods were applied to 310 naturally isolated metabolites that exhibited antiviral potentialities before. The applied selection methods aimed to pick the most relevant inhibitor of SARS-CoV-2 nsp10. At first, a structural similarity study against the co-crystallized ligand, S-Adenosyl Methionine ( SAM ), of SARS-CoV-2 nonstructural protein (nsp10) (PDB ID: 6W4H) was carried out. The similarity analysis culled 30 candidates. Secondly, a fingerprint study against SAM preferred compounds 44 , 48 , 85 , 102 , 105 , 182 , 220 , 221 , 282 , 284 , 285 , 301 , and 302 . The docking studies picked 48 , 182 , 220 , 221 , and 284 . While the ADMET analysis expected the likeness of the five candidates to be drugs, the toxicity study preferred compounds 48 and 182 . Finally, a density-functional theory (DFT) study suggested vidarabine ( 182 ) to be the most relevant SARS-Cov-2 nsp10 inhibitor.

Chemical biology and drug discovery are two scientific activities that pursue different goals but complement each other. The former is an interventional science that aims at understanding living systems through the modulation of its molecular components with compounds designed for this purpose. The latter is the art of designing drug candidates, i.e., molecules that act on selected molecular components of human beings and display, as a candidate treatment, the best reachable risk benefit ratio. In chemical biology, the compound is the means to understand biology, whereas in drug discovery, the compound is the goal. The toolbox they share includes biological and chemical analytic technologies, cell and whole-body imaging, and exploring the chemical space through state-of-the-art design and synthesis tools. In this article, we examine several tools shared by drug discovery and chemical biology through selected examples taken from research projects conducted in our institute in the last decade. These examples illustrate the design of chemical probes and tools to identify and validate new targets, to quantify target engagement in vitro and in vivo, to discover hits and to optimize pharmacokinetic properties with the control of compound concentration both spatially and temporally in the various biophases of a biological system.

(1) Background: different previously synthesized pyrazoles and imidazo-pyrazoles showed interesting anti-angiogenic action, being able to interfere with ERK1/2, AKT and p38MAPK phosphorylation in different manners and with different potency; (2) Methods: here, a new small compound library, endowed with the same differently decorated chemical scaffolds, has been synthetized to obtain new agents able to inhibit different pathways involved in inflammation, cancer and human platelet aggregation. (3) Results: most of the new synthesized derivatives resulted able to block ROS production, platelet aggregation and p38MAPK phosphorylation both in platelets and Human Umbilical Vein Endothelial cells (HUVEC). This paves the way for the development of new agents with anti-angiogenic activity.

Drug-resistant Staphylococcus aureus is an imminent threat to public health, increasing the importance of drug discovery utilizing unexplored bacterial pathways and enzyme targets. De novo pyrimidine biosynthesis is a specialized, highly conserved pathway implicated in both the survival and virulence of several clinically relevant pathogens. Class I dihydroorotase (DHOase) is a separate and distinct enzyme present in gram positive bacteria (i.e., S. aureus , B. anthracis ) that converts carbamoyl-aspartate (Ca-asp) to dihydroorotate (DHO)-an integral step in the de novo pyrimidine biosynthesis pathway. This study sets forth a high-throughput screening (HTS) of 3000 fragment compounds by a colorimetry-based enzymatic assay as a primary screen, identifying small molecule inhibitors of S. aureus DHOase ( Sa DHOase), followed by hit validation with a direct binding analysis using surface plasmon resonance (SPR). Competition SPR studies of six hit compounds and eight additional analogs with the substrate Ca-asp determined the best compound to be a competitive inhibitor with a K D value of 11 µM, which is 10-fold tighter than Ca-asp. Preliminary structure-activity relationship (SAR) provides the foundation for further structure-based antimicrobial inhibitor design against S. aureus .

Rapid in silico selection of target focused libraries from commercial repositories is an attractive and cost-effective approach in early drug discovery. If structures of active compounds are available, rapid 2D similarity search can be performed on multimillion compounds' databases. This approach can be combined with physico-chemical parameter and diversity filtering, bioisosteric replacements, and fragment-based approaches for performing a first round biological screening. Our objectives were to investigate the combination of 2D similarity search with various 3D ligand and structure-based methods for hit expansion and validation, in order to increase the hit rate and novelty. In the present account, six case studies are described and the efficiency of mixing is evaluated. While sequentially combined 2D/3D similarity approach increases the hit rate significantly, sequential combination of 2D similarity with pharmacophore model or 3D docking enriched the resulting focused library with novel chemotypes. Parallel integrated approaches allowed the comparison of the various 2D and 3D methods and revealed that 2D similarity-based and 3D ligand and structure-based techniques are often complementary, and their combinations represent a powerful synergy. Finally, the lessons we learnt including the advantages and pitfalls of the described approaches are discussed.

Multiple viral targets are now available in the clinic to fight HIV infection. Even if this targeted therapy is highly effective at suppressing viral replication, caregivers are facing growing therapeutic failures in patients due to resistance, with or without treatment-adherence glitches. Accordingly, it is important to better understand how HIV and other retroviruses replicate in order to propose alternative antiviral strategies. Recent studies have shown that multiple cellular factors are implicated during the integration step and, more specifically, that integrase can be regulated through post-translational modifications. We have shown that integrase is phosphorylated by GCN2, a cellular protein kinase of the integrated stress response, leading to a restriction of HIV replication. In addition, we found that this mechanism is conserved among other retroviruses. Accordingly, we developed an in vitro interaction assay, based on the AlphaLISA technology, to monitor the integrase-GCN2 interaction. From an initial library of 133 FDA-approved molecules, we identified nine compounds that either inhibited or stimulated the interaction between GCN2 and HIV integrase. In vitro characterization of these nine hits validated this pilot screen and demonstrated that the GCN2-integrase interaction could be a viable solution for targeting integrase out of its active site.

Recently, multitargeted drugs are considered a potential approach in treating cancer. In this study, twelve in-house indole-based derivatives were preliminary evaluated for their inhibitory activities over VEGFR-2, CDK-1/cyclin B and HER-2. Compound 15l showed the most inhibitory activities among the tested derivatives over CDK-1/cyclin B and HER-2. Compound 15l was tested for its selectivity in a small kinase panel. It showed dual selectivity for CDK-1/cyclin B and HER-2. Moreover, in vitro cytotoxicity assay was assessed for the selected series against nine NCI cell lines. Compound 15l showed the most potent inhibitory activities among the tested compounds. A deep in silico molecular docking study was conducted for compound 15l to identify the possible binding modes into CDK-1/cyclin B and HER-2. The docking results revealed that compound 15l displayed interesting binding modes with the key amino acids in the binding sites of both kinases. In vitro and in silico studies demonstrate the indole-based derivative 15l as a selective dual CDK-1 and HER-2 inhibitor. This emphasizes a new challenge in drug development strategies and signals a significant milestone for further structural and molecular optimization of these indole-based derivatives in order to achieve a drug-like property.

The activation of signal transducer and activator of transcription 3 (STAT3), as well as up-regulation of cytokines and growth factors to promote STAT3 activation, have been found in the epidermis of psoriatic lesions. Recently, a series of synthetic compounds possessing the Michael acceptor have been reported as STAT3 inhibitors by covalently binding to cysteine of STAT3. We synthesized a Michael acceptor analog, SKSI-0412, and confirmed the binding affinity between STAT3 and SKSI-0412. We hypothesized that the SKSI-0412 can inhibit interleukin (IL)-17A-induced inflammation in keratinocytes. The introduction of IL-17A increased the phosphorylation of STAT3 in keratinocytes, whereas the inactivation of STAT3 by SKSI-0412 reduced IL-17A-induced STAT3 phosphorylation and IκBζ expression. In addition, human β defensin-2 and S100A7, which are regulated by IκBζ, were significantly decreased with SKSI-0412 administration. We also confirmed that SKSI-0412 regulates cell proliferation, which is the major phenotype of psoriasis. Based on these results, we suggest targeting STAT3 with SKSI-0412 as a novel therapeutic strategy to regulate IL-17A-induced psoriatic inflammation in keratinocytes.

Protein-ligand interaction analysis is important for drug discovery and rational protein design. The existing online tools adopt only a single conformation of the complex structure for calculating and displaying the interactions, whereas both protein residues and ligand molecules are flexible to some extent. The interactions evolved with time in the trajectories are of greater interest. MolADI is a user-friendly online tool which analyzes the protein-ligand interactions in detail for either a single structure or a trajectory. Interactions can be viewed easily with both 2D graphs and 3D representations. MolADI is available as a web application.

As a key enzyme regulating postprandial blood glucose, α-Glucosidase is considered to be an effective target for the treatment of diabetes mellitus. In this study, a simple, rapid, and effective method for enzyme inhibitors screening assay was established based on α-glucosidase catalyzes reactions in a personal glucose meter (PGM). α-glucosidase catalyzes the hydrolysis of maltose to produce glucose, which triggers the reduction of ferricyanide (K 3 [Fe(CN) 6 ]) to ferrocyanide (K 4 [Fe(CN) 6 ]) and generates the PGM detectable signals. When the α-glucosidase inhibitor (such as acarbose) is added, the yield of glucose and the readout of PGM decreased accordingly. This method can achieve the direct determination of α-glucosidase activity by the PGM as simple as the blood glucose tests. Under the optimal experimental conditions, the developed method was applied to evaluate the inhibitory activity of thirty-four small-molecule compounds and eighteen medicinal plants extracts on α-glucosidase. The results exhibit that lithospermic acid (52.5 ± 3.0%) and protocatechualdehyde (36.8 ± 2.8%) have higher inhibitory activity than that of positive control acarbose (31.5 ± 2.5%) at the same final concentration of 5.0 mM. Besides, the lemon extract has a good inhibitory effect on α-glucosidase with a percentage of inhibition of 43.3 ± 3.5%. Finally, the binding sites and modes of four active small-molecule compounds to α-glucosidase were investigated by molecular docking analysis. These results indicate that the PGM method is feasible to screening inhibitors from natural products with simple and rapid operations.

Biofilms, the predominant growth mode of microorganisms, pose a significant risk to human health. The protective biofilm matrix, typically composed of exopolysaccharides, proteins, nucleic acids, and lipids, combined with biofilm-grown bacteria's heterogenous physiology, leads to enhanced fitness and tolerance to traditional methods for treatment. There is a need to identify biofilm inhibitors using diverse approaches and targeting different stages of biofilm formation. This review discusses discovery strategies that successfully identified a wide range of inhibitors and the processes used to characterize their inhibition mechanism and further improvement. Additionally, we examine the structure-activity relationship (SAR) for some of these inhibitors to optimize inhibitor activity.

Matrix metalloproteinases (MMPs) are the family of proteases that are mainly responsible for degrading extracellular matrix (ECM) components. In the skin, the overexpression of MMPs as a result of ultraviolet radiation triggers an imbalance in the ECM turnover in a process called photoaging, which ultimately results in skin wrinkling and premature skin ageing. Therefore, the inhibition of different enzymes of the MMP family at a topical level could have positive implications for photoaging. Considering that the MMP catalytic region is mostly conserved across different enzymes of the MMP family, in this study we aimed to design a virtual screening (VS) workflow to identify broad-spectrum MMP inhibitors that can be used to delay the development of photoaging. Our in silico approach was validated in vitro with 20 VS hits from the Specs library that were not only structurally different from one another but also from known MMP inhibitors. In this bioactivity assay, 18 of the 20 compounds inhibit at least one of the assayed MMPs at 100 μM (with 5 of them showing around 50% inhibition in all the tested MMPs at this concentration). Finally, this VS was used to identify natural products that have the potential to act as broad-spectrum MMP inhibitors and be used as a treatment for photoaging.