Identification of novel inhibitors of dipeptidylcarboxypeptidase of Leishmania donovani via ligand-based virtual screening and biological evaluation

Current treatment of leishmaniasis is based on chemotherapy, which relies on a handful of drugs with serious limitations, such as high cost, toxicity, and lack of efficacy in endemic regions. Therefore, development of new, effective, and affordable anti-leishmanial drugs is a global health priority. Dipeptidylcarboxypeptidase has been characterized and established as a drug target for antileishmanial drug discovery. We virtually screened a large chemical library of 15 452 compounds against a 3D model of dipeptidylcarboxypeptidase to identify novel inhibitors. The initial virtual screening using a ligand-based pharmacophore model identified 103 compounds. Forty-six compounds were shortlisted based on the docking scores and other scoring functions. Further, these compounds were subjected to biological assay, and four of them belonging to two chemical classes were identified as the lead compounds. Identification of these novel and chemically diverse inhibitors should provide leads to be optimized into candidates to treat these protozoan infections.     

应用虚拟筛选方法寻找链阳霉素A乙酰转移酶抑制剂

维吉尼亚霉素乙酰转移酶D(VatD)通过灭活链阳霉素A而在链阳霉素耐药性的产生中起重要作用。本研究采用虚拟筛选技术寻找VatD的抑制剂,此VatD抑制剂可以和链阳霉素联合使用,从而提供新的治疗耐药菌感染的方法。作者首次应用基于结构的虚拟筛选方法(分子对接)从含300 000化合物的商业化数据库中筛选对抗VatD底物结合位点的化合物,从200个评分最高的化合物中选取26个测定对VatD酶活性的抑制作用。将构建的质粒pRSET B/vatD转染宿主细胞E.coli(TrxB)用于过表达,纯化的VatD对维吉尼亚霉素M1表现乙酰转移酶活性。26个化合物中有3个对VatD表现抑制作用,IC₅₀分别为168.6,91.0和55.2 μmol·L^-1。其他化合物在反应体系中不溶解和/或对酶活性的抑制作用很小(IC₅₀>200 μmol·L^-1)。本文首次设计VatD的小分子化合物抑制剂,发现了3个有活性的化合物,希望其可作为先导化合物进一步发展为新的对抗链阳霉素耐药性的药物。     

Discovery of a novel and potent class of F. tularensis enoyl-reductase (FabI) inhibitors by molecular shape and electrostatic matching

Enoyl-acyl carrier protein (ACP) reductase, FabI, is a key enzyme in the bacterial fatty acid biosynthesis pathway (FAS II). FabI is an NADH-dependent oxidoreductase that acts to reduce enoyl-ACP substrates in a final step of the pathway. The absence of this enzyme in humans makes it an attractive target for the development of new antibacterial agents. FabI is known to be unresponsive to structure-based design efforts due to a high degree of induced fit and a mobile flexible loop encompassing the active site. Here we discuss the development, validation, and careful application of a ligand-based virtual screen used for the identification of novel inhibitors of the Francisella tularensis FabI target. In this study, four known classes of FabI inhibitors were used as templates for virtual screens that involved molecular shape and electrostatic matching. The program ROCS was used to search a high-throughput screening library for compounds that matched any of the four molecular shape queries. Matching compounds were further refined using the program EON, which compares and scores compounds by matching electrostatic properties. Using these techniques, 50 compounds were selected, ordered, and tested. The tested compounds possessed novel chemical scaffolds when compared to the input query compounds. Several hits with low micromolar activity were identified and follow-up scaffold-based searches resulted in the identification of a lead series with submicromolar enzyme inhibition, high ligand efficiency, and a novel scaffold. Additionally, one of the most active compounds showed promising whole-cell antibacterial activity against several Gram-positive and Gram-negative species, including the target pathogen. The results of a preliminary structure-activity relationship analysis are presented.     

Discovery of non-glycoside sodium-dependent glucose co-transporter 2 (SGLT2) inhibitors by ligand-based virtual screening

A ligand-based virtual screening strategy (a combination of pharmacophore model generation, shape-based scoring, and structure clustering analysis) was developed to discover novel SGLT2 inhibitors. The best pharmacophore model, generated from eight glycoside inhibitors, was utilized to virtually screen three chemical databases that led to the identification of three non-glycoside SGLT2 inhibitors. This is the first report of the generation of a pharmacophore model from glycosides that has then been used to discover novel non-glycosides hits.     

采用药效团模型和分子对接方法筛选新型的组蛋白甲基转移酶G9a抑制剂

目的利用药效团模型和分子对接方法对商业化合物库ChemDiv中的G9afocused-libraries进行筛选,希望发现新骨架结构的G9a抑制剂。方法首先,使用Discovery studio 3.1软件分别构建基于配体的药效团模型和基于配体-受体复合物的药效团模型,并根据构建的2个模型再重新定义2个新的药效团模型。然后,构建测试集并测试药效团模型的预测能力。最后,选取最优药效团模型对G9afocused-libraries进行筛选,对筛选出的化合物使用CDOCKER分子对接进行分析与评价。结果测试结果显示,所构建的药效团模型具有一定的预测能力,通过该药效团筛选得到了2个结构新颖的潜在的G9a抑制剂。结论所构建的药效团模型具有一定的可靠性,虚拟筛选发现的G9a抑制剂还需进一步的实验证明。     

Molecular docking and high-throughput screening for novel inhibitors of protein tyrosine phosphatase-1B

High-throughput screening (HTS) of compound libraries is used to discover novel leads for drug development. When a structure is available for the target, computer-based screening using molecular docking may also be considered. The two techniques have rarely been used together on the same target. The opportunity to do so presented itself in a project to discover novel inhibitors for the enzyme protein tyrosine phosphatase-1B (PTP1B), a tyrosine phosphatase that has been implicated as a key target for type II diabetes. A corporate library of approximately 400 000 compounds was screened using high-throughput experimental techniques for compounds that inhibited PTP1B. Concurrently, molecular docking was used to screen approximately 235 000 commercially available compounds against the X-ray crystallographic structure of PTP1B, and 365 high-scoring molecules were tested as inhibitors of the enzyme. Of approximately 400 000 molecules tested in the high-throughput experimental assay, 85 (0.021%) inhibited the enzyme with IC50 values less than 100 microM; the most active had an IC50 value of 4.2 microM. Of the 365 molecules suggested by molecular docking, 127 (34.8%) inhibited PTP1B with IC50 values less than 100 microM; the most active of these had an IC50 of 1.7 microM. Structure-based docking therefore enriched the hit rate by 1700-fold over random screening. The hits from both the high-throughput and docking screens were dissimilar from phosphotyrosine, the canonical substrate group for PTP1B; the two hit lists were also very different from each other. Surprisingly, the docking hits were judged to be more druglike than the HTS hits. The diversity of both hit lists and their dissimilarity from each other suggest that docking and HTS may be complementary techniques for lead discovery.     

Discovery of a novel class of reversible non-peptide caspase inhibitors via a structure-based approach

In this paper, we report a simple structure-based iterative optimizations (SUBITO) strategy to identify and optimize new protein ligands and inhibitors. The approach is based on a combination of NMR-based screening and computational docking methods and enabled the identification of novel chemical leads among hundreds of thousands of commercially available compounds by screening only a few hundred compounds from a scaffold library followed by iterative screening steps where only few dozen compounds are tested. As an application, we report on the discovery of a novel class of non-peptide reversible caspase inhibitors, with IC(50) values in the low micromolar range.     

Discovery of novel DPP IV inhibitors: application of pharmacophore-based virtual screening

Dipeptidyl peptidase IV (DPP-IV) is a potential drug target for type-2 diabetes and DPP-IV inhibitors are known to efficiently improve glucose tolerance. In the present study, pharmacophore model for a set of 29 DPP-IV inhibitors was generated by ligand-based pharmacophore generation process. The best hypothesis, hypo 1, consisting of four chemical features, namely, one hydrogen bond donor, one hydrogen bond acceptor, one hydrophobe and one ring aromatic was validated by cost function analysis, test set prediction and Fischer test. The validated pharmacophore model was then used for searching new lead compounds from Maybridge and NCI database. Four compounds (CD01797, CD06202, CD02493, and AW01077) from Maybridge database and three compounds (NSC997, NSC2450, and NSC5815) from NCI database were identified as structurally diverse druggable novel leads with nM activity against DPP-IV.     

Fragment-based discovery of novel thymidylate synthase leads by NMR screening and group epitope mapping

Solution-state nuclear magnetic resonance (NMR) is a versatile tool for the study of binding interactions between small molecules and macromolecular targets. We applied ligand-based NMR techniques to the study of human thymidylate synthase (hTS) using known nanomolar inhibitors and a library of small molecule fragments. Screening by NMR led to the rapid identification of ligand pairs that bind in proximal sites within the cofactor-binding pocket of hTS. Screening hits were used as search criteria within commercially available sources, and a subset of catalog analogs were tested for potency by in vitro assay and binding affinity by quantitative saturation transfer difference (STD)-NMR titration. Two compounds identified by this approach possess low micromolar affinity and potency, as well as excellent binding efficiency against hTS. Relative binding orientations for both leads were modeled using AutoDock, and the most likely bound conformations were validated using experimentally derived STD-NMR binding epitope data. These ligands represent novel starting points for fragment-based drug design of non-canonical TS inhibitors, and their binding epitopes highlight important and previously unexploited interactions with conserved residues in the cofactor-binding site.     

Discovery of novel and cardioselective diltiazem-like calcium channel blockers via virtual screening

With the effort to discover new chemotypes blocking L-type calcium channels (LTCCs), ligand-based virtual screening was applied with a specific interest toward the diltiazem binding site. Roughly 50000 commercially available compounds served as a database for screening. The filtering through predicted pharmacokinetic properties and structural requirements reduced the initial database to a few compounds for which the similarity was calculated toward two template molecules, diltiazem and 4-chloro-Ncyclopropyl- N-(4-piperidinyl)benzene-sulfonamide, the most interesting hit of a previous screening experiment. For 18 compounds, inotropic and chronotropic activity as well as the vasorelaxant effect on guinea pig were studied "in vitro", and for the most promising, binding studies to the diltiazem site were carried out. The procedure yielded several hits, confirming in silico techniques to be useful for finding new chemotypes. In particular, N-[2-(dimethylamino)ethyl]-3-hydroxy-2-naphthamide, N,Ndimethyl- N'-(2-pyridin-3-ylquinolin-4-yl)ethane-1,2-diamine, 2-[(4-chlorophenyl)(pyridin-2-yl)methoxy]- N,N-dimethylethanamine (carbinoxamine), and 7-[2-(diethylamino)ethoxy]-2H-chromen-2-one revealed interesting activity and binding to the benzothiazepine site.     

Combined pharmacophore models as virtual screening protocol against BRD4(1) inhibitor

Bromodomain-containing protein is involved in many essential cellular processes, such as chromosomes for cell cycle progression, cellular viability and embryonic stem cell regulation, which plays a significant role in cancers and lysine acetylation. However, there is no information available regarding the discovery for structurally novel existing BRD4(1) inhibitors up to date. Therefore, we collected reported compounds from GSK library to generate ligand-based pharmacophore and used 11 BRD4(1)-inhibitor co-crystal structures to establish our structure-based pharmacophore for multiple virtual screening of potent BRD4(1) inhibitors. These results may provide important information for further design and optimization of novel BRD4(1) inhibitors in cancer treatment. The results of this study will not only provide a better understanding of BRD4(1) inhibitors interaction, but will also assist the development of new potent hits for BRD4(1).     

Natural product-based phenols as novel probes for mycobacterial and fungal carbonic anhydrases

In order to discover novel probes that may help in the investigation and control of infectious diseases through a new mechanism of action, we have evaluated a library of phenol-based natural products (NPs) for enzyme inhibition against four recently characterized pathogen β-family carbonic anhydrases (CAs). These include CAs from Mycobacterium tuberculosis, Candida albicans, and Cryptococcus neoformans as well as α-family human CA I and CA II for comparison. Many of the NPs selectively inhibited the mycobacterial and fungal β-CAs, with the two best performing compounds displaying submicromolar inhibition with a preference for fungal over human CA inhibition of more than 2 orders of magnitude. These compounds provide the first example of non-sulfonamide inhibitors that display β over α CA enzyme selectivity. Structural characterization of the library compounds in complex with human CA II revealed a novel binding mode whereby a methyl ester interacts via a water molecule with the active site zinc.     

Virtual screening identifies novel sulfonamide inhibitors of ecto-5'-nucleotidase

We aimed to identify inhibitors of ecto-5'-nucleotidase (ecto-5'-NT, CD73), a membrane-bound metallophosphoesterase that is implicated in the control of purinergic receptor signaling and a number of associated therapeutically relevant effects. Currently, only very few compounds, including ADP, its more stable analogue α,β-methylene-ADP, ATP, and anthraquinone derivatives are known to inhibit this enzyme. In the search for inhibitors with more drug-like properties, we applied a model structure-based virtual screening approach augmented by chemical similarity searching. On the basis of this analysis, 51 candidate compounds were finally selected for experimental evaluation. A total of 13 of these molecules were confirmed to have competitive inhibitory activity. The most potent inhibitor, 6-chloro-2-oxo-N-(4-sulfamoylphenyl)-2H-chromene-3-carboxylic acid amide (17), showed an IC(50) value of 1.90 μM. In contrast to the nucleotide- and anthraquinone-derived antagonists, the newly identified competitive inhibitors are uncharged at physiological pH values, possess a drug-like structure, and are structurally distinct from known active compounds.     

High throughput screening via mass spectrometry: a case study using acetylcholinesterase

Mass spectrometry-based screening can be applied to a wide range of targets, including those intractable targets that use substrates such as lipids, fatty acids, phospholipids, steroids, prostaglandins, and other compounds not generally amenable to conventional screening techniques. The major limitation to this approach is throughput, making HTS via mass spectrometry impractical. We present a mass spectrometry-based technique and hardware for lead discovery applications. Mass spectrometry enables the design of label-free assays using biologically native substrates for a wide range of enzymatic targets. This system can be used for the direct quantification of analytes in complex reaction mixtures with typical throughputs of 4-5 s per sample. A mass spectrometry-based assay was developed to identify inhibitors of acetylcholinesterase, an enzyme with clinical importance in Alzheimer's disease. The system was used to screen a small chemical library. Several potent inhibitors were identified, and the IC(50) values of the inhibitors were determined.     

3D-pharmacophore model based virtual screening to identify dual-binding site and selective acetylcholinesterase inhibitors

The formation of β-amyloid plaques in the brain is a key neurodegenerative event in Alzheimer’s disease (AD). Interestingly, research on acetylcholinesterase (AChE) enzyme has increased due to findings supporting this enzyme involvement in the β-amyloid peptide fibril formation during AD pathogenesis. In this investigation, chemical features based 3D pharmacophore models were developed from structurally diverse xanthostigmine derivatives, known inhibitors of AChE enzyme, using 3D-QSAR pharmacophore generation module in Discovery Studio2.5 (DS2.5). The constructed pharmacophore models for AChE inhibitors was further cross-validated using test set and Cat-Scramble methodology. The best quantitative pharmacophore model Hypo1, was used for screening the chemical databases of small compounds including Specs, NCI, and IBScreen, to identify the new compounds that are presumably able to act as dual-binding site AChE inhibitors. The screened virtual hits were then subjected to the Lipinski’s rule of five, blood–brain barrier (BBB), PSA, LogS, percent human oral absorption, and toxicity analysis. Finally, 32 compounds were identified as potential leads against AChE enzyme, showing good estimated activities and promising ADMET properties. Molecular docking of these compounds using FlexX software showed catalytic and peripheral anionic binding site interactions, so called dual binding of the AChE enzyme. Docking study was also performed on butyrylcholinesterase in order to understand the compound selectivity. This study may assist in the discovery and design of novel dual binding site and selective AChE inhibitors with potent inhibitory activity.     

Identification of novel nematode succinate dehydrogenase inhibitors: Virtual screening based on ligand-pocket interactions

To discover new nematicidal succinate dehydrogenase (SDH) inhibitors with novel structures, we conducted a virtual screening of the ChemBridge library with 1.7 million compounds based on ligand-pocket interactions. The homology model of Caenorhabditis elegans SDH was established, along with a pharmacophore model based on ligand-pocket interactions. After the pharmacophore-based and docking-based screening, 19 compounds were selected for the subsequent enzymatic assays. The results showed that compound 1 (ID: 7607321) exhibited inhibitory activity against SDH with a determined IC₅₀ value of 19.6 μM. Structural modifications and nematicidal activity studies were then carried out, which provided further evidence that compound 1 exhibited excellent nematicidal activity. Molecular dynamics simulations were then conducted to investigate the underlying molecular basis for the potency of these inhibitors against SDH. This work provides a reliable strategy and useful information for the future design of nematode SDH inhibitors.