A novel class of Hsp90 inhibitors isolated by structure-based virtual screening

A novel class of 3-phenyl-2-styryl-3H-quinazolin-4-one Hsp90 inhibitors with in vitro anti-tumor activity are identified by structure-based virtual screening of a chemical database with docking simulations in the N-terminal ATP-binding site, in vitro ATPase assay using yeast Hsp90, and cell-based Her2 degradation assay in a consecutive fashion. These results exemplify the usefulness of the structure-based virtual screening with molecular docking in drug discovery. The structural features responsible for a tight binding of the inhibitors in the active site of Hsp90 are discussed in detail.     

Targeting drug-efflux pumps -- a pharmacoinformatic approach

In line with our studies on propafenone-type inhibitors of P-glycoprotein (P-gp), we applied several methods to approach virtual screening tools for identification of new P-gp inhibitors on one hand and the molecular basis of ligand-protein interaction on the other hand. For virtual screening, a combination of autocorrelation vectors and selforganising artificial neural networks proved extremely valuable in identifying P-gp inhibitors with structurally new scaffolds. For a closer view on the binding region for propafenone-type ligands we applied a combination of pharmacophore-driven photoaffinity labeling and protein homology modeling. On LmrA, a bacterial homologue of P-gp, we were able to identify distinct regions on transmembrane helices 3, 5 and 6 which show significant changes in the labeling pattern during different steps of the catalytic cycle.     

Identification of potential inhibitors for HCV NS3 genotype 4a by combining protein–ligand interaction fingerprint, 3D pharmacophore,docking, and dynamic simulation

HCV NS3 protease domain has been one of the most attractive targets for developing new drugs for HCV infection and many drugs were successfully developed, but all of them were designed for targeting HCV genotype 1 infection. HCV genotype 4a dominant in Egypt has paid less attention. Here, we describe our protocol of virtual screening in identification of novel potential potent inhibitors for HCV NS3 of genotype 4a using homology modeling, PLIF (protein–ligand interaction fingerprint), docking, pharmacophore, and dynamic simulation. A high-quality 3D model of HCV NS3 protease of genotype 4a was constructed using crystal structure of HCV NS3 protease of genotype 1b (PDB ID: 4u01) as a template. PLIF was generated using five crystal structures of HCV NS3 (PDB ID: 4u01, 3kee, 4ktc, 4i33, and 5epn) which revealed the most important residues and their interactions with the co-crystalized ligands. A 3D pharmacophore model consisting of six features was developed from the generated PLIF data and then used as a screening filter for 11,244 compounds. Only 423 compounds passed the pharmacophore filter and entered the docking-based virtual screening stage. The highest ranked five hits from docking result (compound (C1–C5)) were selected for further analysis. They exhibited stronger interaction and higher binding affinity than HCV NS3 protease ligands. Dynamic simulation of the protein–best lead complex was performed to validate and augment the virtual screening results and it showed that these compounds have a strong binding affinity and could be very effective in treating HCV genotype 4a infections.     

Identification of novel drug scaffolds for inhibition of SARS-CoV 3-Chymotrypsin-like protease using virtual and high-throughput screenings

We have used a combination of virtual screening (VS) and high-throughput screening (HTS) techniques to identify novel, non-peptidic small molecule inhibitors against human SARS-CoV 3CLpro. A structure-based VS approach integrating docking and pharmacophore based methods was employed to computationally screen 621,000 compounds from the ZINC library. The screening protocol was validated using known 3CLpro inhibitors and was optimized for speed, improved selectivity, and for accommodating receptor flexibility. Subsequently, a fluorescence-based enzymatic HTS assay was developed and optimized to experimentally screen approximately 41,000 compounds from four structurally diverse libraries chosen mainly based on the VS results. False positives from initial HTS hits were eliminated by a secondary orthogonal binding analysis using surface plasmon resonance (SPR). The campaign identified a reversible small molecule inhibitor exhibiting mixed-type inhibition with a K_i value of 11.1 μM. Together, these results validate our protocols as suitable approaches to screen virtual and chemical libraries, and the newly identified compound reported in our study represents a promising structural scaffold to pursue for further SARS-CoV 3CLpro inhibitor development.     

Identification of novel CYP2A6 inhibitors by virtual screening

The human CYP2A6 enzyme metabolises several xenobiotics including nicotine, the addictive component in tobacco. Reduced activity of CYP2A6, either for genetic reasons or by administering inhibitors of CYP2A6, reduces tobacco smoking. The aim was to design novel inhibitors of CYP2A6 using 3D-QSAR analysis combined with virtual screening. A 3D-QSAR model was utilised to identify the most important features of the inhibitors, and this knowledge was used to design inhibitors for CYP2A6. Chemical database screening yielded several potent inhibitor candidates such as alkylamine derivatives (compound no. 5, IC(50)=0.1 μM) and 1-benzothiophene-3-carbaldehyde that can be used as lead compounds in the development of drugs for smoking reduction therapy.     

Identification of novel chemical inhibitors for ubiquitin C-terminal hydrolase-L3 by virtual screening

UCH-L3 (ubiquitin C-terminal hydrolase-L3) is a de-ubiquitinating enzyme that is a component of the ubiquitin-proteasome system and known to be involved in programmed cell death. A previous study of high-throughput drug screening identified an isatin derivative as a UCH-L3 inhibitor. In this study, we attempted to identify a novel inhibitor with a different structural basis. We performed in silico structure-based drug design (SBDD) using human UCH-L3 crystal structure data (PDB code; 1XD3) and the virtual compound library (ChemBridge CNS-Set), which includes 32,799 chemicals. By a two-step virtual screening method using DOCK software (first screening) and GOLD software (second screening), we identified 10 compounds with GOLD scores of over 60. To address whether these compounds exhibit an inhibitory effect on the de-ubiquitinating activity of UCH-L3, we performed an enzymatic assay using ubiquitin-7-amido-4-methylcoumarin (Ub-AMC) as the substrate. As a result, we identified three compounds with similar basic dihydro-pyrrole skeletons as UCH-L3 inhibitors. These novel compounds may be useful for the research of UCH-L3 function, and in drug development for UCH-L3-associated diseases.     

A discovery of novel Mycobacterium tuberculosis pantothenate synthetase inhibitors based on the molecular mechanism of actinomycin D inhibition

Mycobacterium tuberculosis pantothenate synthetase is a potential anti-tuberculosis target, and a high-throughput screening system was previously developed to identify its inhibitors. Using a similar system, we screened a small library of compounds and identified actinomycin D (ActD) as a weak inhibitor of pantothenate synthetase. A new method was established to discover more effective inhibitors by determining the molecular mechanism of ActD inhibition followed by structure-based virtual screening. The molecular interaction of inhibition was determined by circular dichroism and tryptophan fluorescence quenching. The structure-based search and virtual screening were performed using the Molecular Operating Environment (MOE) program and SYBYL 7.5, respectively. Two inhibitors were identified with an IC₅₀ for pantothenate synthetase that was at least ten times better than that of ActD.     

A novel and efficient ligand-based virtual screening approach using the HWZ scoring function and an enhanced shape-density model

In this work, we extend our previous ligand shape-based virtual screening approach by using the scoring function Hamza–Wei–Zhan (HWZ) score and an enhanced molecular shape-density model for the ligands. The performance of the method has been tested against the 40 targets in the Database of Useful Decoys and compared with the performance of our previous HWZ score method. The virtual screening results using the novel ligand shape-based approach demonstrated a favorable improvement (area under the receiver operator characteristics curve AUC?=?.89?±?.02) and effectiveness (hit rate HR^1%?=?53.0%?±?6.3 and HR^10%?=?71.1%?±?4.9). The comparison of the overall performance of our ligand shape-based method with the highest ligand shape-based virtual screening approach using the data fusion of multi queries showed that our strategy takes into account deeper the chemical information of the set of active ligands. Furthermore, the results indicated that our method are suitable for virtual screening and yields superior prediction accuracy than the other study derived from the data fusion using five queries. Therefore, our novel ligand shape-based screening method constitutes a robust and efficient approach to the 3D similarity screening of small compounds and open the door to a whole new approach to drug design by implementing the method in the structure-based virtual screening.     

In silico approaches to identify novel myeloid cell leukemia-1 (Mcl-1) inhibitors for treatment of cancer

Myeloid cell leukemia-1 (Mcl-1) has been a validated and attractive target for cancer therapy. Over-expression of Mcl-1 in many cancers allows cancer cells to evade apoptosis and contributes to the resistance to current chemotherapeutics. Here, we identified new Mcl-1 inhibitors using a multi-step virtual screening approach. First, based on two different ligand-receptor complexes, 20 pharmacophore models were established by simultaneously using ‘Receptor-Ligand Pharmacophore Generation’ method and manual build feature method, and then carefully validated by a test database. Then, pharmacophore-based virtual screening (PB-VS) could be performed by using the 20 pharmacophore models. In addition, docking study was used to predict the possible binding poses of compounds, and the docking parameters were optimized before performing docking-based virtual screening (DB-VS). Moreover, a 3D QSAR model was established by applying the 55 aligned Mcl-1 inhibitors. The 55 inhibitors sharing the same scaffold were docked into the Mcl-1 active site before alignment, then the inhibitors with possible binding conformations were aligned. For the training set, the 3D QSAR model gave a correlation coefficient r² of 0.996; for the test set, the correlation coefficient r² was 0.812. Therefore, the developed 3D QSAR model was a good model, which could be applied for carrying out 3D QSAR-based virtual screening (QSARD-VS). After the above three virtual screening methods orderly filtering, 23 potential inhibitors with novel scaffolds were identified. Furthermore, we have discussed in detail the mapping results of two potent compounds onto pharmacophore models, 3D QSAR model, and the interactions between the compounds and active site residues.     

A minimalist approach to fragment-based ligand design using common rings and linkers: application to kinase inhibitors

We present a novel method for stepwise scaffold assembly that integrates fragment-by-fragment ligand design approaches with high-throughput virtual library screening (COREGEN). As an extension of our earlier studies of common features present in drug molecules, we investigate the hypothesis that most pharmaceutically interesting ligands can be expressed in terms of the ring-linker frameworks that comprise them. Analysis of 119 published kinase inhibitors from at least 18 different targets illustrates that a basis set of 4 rings and 8 linkers is sufficient to describe approximately 90% of ring and linker occurrences, respectively. A similar result was derived from a larger set of approximately 40,000 kinase inhibitors from curated patents. A method for ring-linker-based assembly of scaffold libraries that uses experimental information to guide the placement of anchor fragments is validated using a set of reported kinase inhibitors of Bcr-Abl, Cdk2, and Src. In every case, the predominant structural motif of reported ligand cores is reproduced and variations are suggested. To underscore generality of this approach, a novel scaffold for a cyclooxygenase-2 (COX-2) selective ligand is proposed.     

Identification of potential inhibitors for HCV NS5b of genotype 4a by combining dynamic simulation,protein–ligand interaction fingerprint, 3D pharmacophore,docking and 3D QSAR

Abstract

HCV NS5B polymerase has been one of the most attractive targets for developing new drugs for HCV infection and many drugs were successfully developed, but all of them were designed for targeting Hepatitis C Virus genotype 1 (HCV GT1). Hepatitis C virus genotype 4a (HCV GT4a) dominant in Egypt has paid less attention. Here, we describe our protocol of virtual screening in identification of novel potential potent inhibitors for HCV NS5B polymerase of GT4a using homology modeling, protein–ligand interaction fingerprint (PLIF), docking, pharmacophore, and 3D CoMFA quantitative structure activity relationship (QSAR). Firstly, a high-quality 3D model of HCV NS5B polymerase of GT4a was constructed using crystal structure of HCV NS5B polymerase of GT1 (PDB ID: 3hkw) as a template. Then, both the model and the template were simulated to compare conformational stability. PLIF was generated using five crystal structures of HCV NS5B (PDB ID: 4mia, 4mib, 4mk9, 4mka, and 4mkb), which revealed the most important residues and their interactions with the co-crystalized ligands. After that, a 3D pharmacophore model was developed from the generated PLIF data and then used as a screening filter for 17000328 drug-like zinc database compounds. 900 compounds passed the pharmacophore filter and entered the docking-based virtual screening stage. Finally, a 3D CoMFA QSAR was developed using 42 compounds as a training and 19 compounds as a test set. The 3D CoMFA QSAR was used to design and screen some potential inhibitors, these compounds were further evaluated by the docking stage. The highest ranked five hits from docking result (compounds (p1–p4) and compound q1) were selected for further analysis.

Communicated by Ramaswamy H. Sarma     

Discovery of new Gram-negative antivirulence drugs: structure and properties of novel E. coli WaaC inhibitors

Heptosyltransferases such as WaaC represent promising and attractive targets for the discovery of new Gram-negative antibacterial drugs based on antivirulence mechanisms. We report herein our approach to the identification of the first micromolar inhibitors of WaaC and the preliminary SAR generated from this family of 2-aryl-5-methyl-4-(5-aryl-furan-2-yl-methylene)-2,4-dihydro-pyrazol-3-ones identified by virtual screening.     

Novel human mPGES-1 inhibitors identified through structure-based virtual screening

Microsomal prostaglandin E synthase-1 (mPGES-1) is an inducible prostaglandin E synthase after exposure to pro-inflammatory stimuli and, therefore, represents a novel target for therapeutic treatment of acute and chronic inflammatory disorders. It is essential to identify mPGES-1 inhibitors with novel scaffolds as new leads or hits for the purpose of drug design and discovery that aim to develop the next-generation anti-inflammatory drugs. Herein we report novel mPGES-1 inhibitors identified through a combination of large-scale structure-based virtual screening, flexible docking, molecular dynamics simulations, binding free energy calculations, and in vitro assays on the actual inhibitory activity of the computationally selected compounds. The computational studies are based on our recently developed three-dimensional (3D) structural model of mPGES-1 in its open state. The combined computational and experimental studies have led to identification of new mPGES-1 inhibitors with new scaffolds. In particular, (Z)-5-benzylidene-2-iminothiazolidin-4-one is a promising novel scaffold for the further rational design and discovery of new mPGES-1 inhibitors. To our best knowledge, this is the first time a 3D structural model of the open state mPGES-1 is used in structure-based virtual screening of a large library of available compounds for the mPGES-1 inhibitor identification. The positive experimental results suggest that our recently modeled trimeric structure of mPGES-1 in its open state is ready for the structure-based drug design and discovery.     

Discovery of novel inhibitors for DHODH via virtual screening and X-ray crystallographic structures

Amino-benzoic acid derivatives 1–4 were found to be inhibitors for DHODH by virtual screening, biochemical, and X-ray crystallographic studies. X-ray structures showed that 1 and 2 bind to DHODH as predicted by virtual screening, but 3 and 4 were found to be structurally different from the corresponding compounds initially identified by virtual screening.     

Identification of new Hsp90 inhibitors by structure-based virtual screening

Structure-based virtual screening identified pyrimidine-2,4,6-trione and 4H-1,2,4-triazole-3-thiol as novel scaffolds of Hsp90 ATPase inhibitors. Their binding modes in the ATP-binding pocket of Hsp90 were analyzed using AutoDoc program combined with molecular dynamics (MD) simulations.     

Discover natural compounds as potential phosphodiesterase-4B inhibitors via computational approaches

cAMP, intracellular cyclic adenosine monophosphate, is a ubiquitous second messenger that plays a key role in many physiological processes. PDE4B which can reduce the cAMP level by hydrolyzing cAMP to 5′-AMP has become a therapeutic target for the treatment of human diseases such as respiratory disorders, inflammation diseases, neurological and psychiatric disorders. However, the use of currently available PDE4B inhibitors is restricted due to serious side effects caused by targeting PDE4D. Hence, we are attempting to find out subfamily-selective PDE4B inhibitors from natural products, using computer-aided approaches such as virtual screening, docking, and molecular dynamics simulation. Finally, four potential PDE4B-selective inhibitors (ZINC67912770, ZINC67912780, ZINC72320169, and ZINC28882432) were found. Compared to the reference drug (roflumilast), they scored better during the virtual screening process. Binding free energy for them was ?317.51, ?239.44, ?215.52, and ?165.77 kJ/mol, better than ?129.05 kJ/mol of roflumilast. The pharmacophore model of the four candidate inhibitors comprised six features, including one hydrogen bond donor, four hydrogen bond acceptors, and one aromatic ring feature. It is expected that our study will pave the way for the design of potent PDE4B-selective inhibitors of new drugs to treat a wide variety of diseases such as asthma, COPD, psoriasis, depression, etc.     

Crystal structure of avian aminoimidazole-4-carboxamide ribonucleotide transformylase in complex with a novel non-folate inhibitor identified by virtual ligand screening

Aminoimidazole-4-carboxamide ribonucleotide transformylase (AICAR Tfase), one of the two folate-dependent enzymes in the de novo purine biosynthesis pathway, is a promising target for anti-neoplastic chemotherapy. Although classic antifolates, such as methotrexate, have been developed as anticancer agents, their general toxicity and drug resistance are major issues associated with their clinical use and future development. Identification of inhibitors with novel scaffolds could be an attractive alternative. We present here the crystal structure of avian AICAR Tfase complexed with the first non-folate based inhibitor identified through virtual ligand screening of the National Cancer Institute Diversity Set. The inhibitor 326203-A (2-[5-hydroxy-3-methyl-1-(2-methyl-4-sulfophenyl)-1H-pyrazol-4-ylazo]-4-sulfo-benzoic acid) displayed competitive inhibition against the natural cofactor, 10-formyl-tetrahydrofolate, with a K(i) of 7.1 mum. The crystal structure of AICAR Tfase with 326203-A at 1.8 A resolution revealed a unique binding mode compared with antifolate inhibitors. The inhibitor also accessed an additional binding pocket that is not occupied by antifolates. The sulfonate group of 326203-A appears to form the dominant interaction of the inhibitor with the proposed oxyanion hole through interaction with a helix dipole and Lys(267). An aromatic interaction with Phe(316) also likely contributes to favorable binding. Based on these structural insights, several inhibitors with improved potency were subsequently identified in the National Cancer Institute Compound Library and the Available Chemical Directory by similarity search and molecular modeling methods. These results provide further support for our combined virtual ligand screening rational design approach for the discovery of novel, non-folate-based inhibitors of AICAR Tfase.     

Autodock Vina与Discovery Studio在虚拟筛选耐药蛋白抑制剂中的比较

随着大量与细菌耐药相关的基因的发现和其表达蛋白结构的成功测定,从已有的化合物中通过计算机模拟方法筛选对耐药蛋白靶点有作用的候选化合物,成为了药物发现的一个标准途径。虚拟筛选在耐药基因抑制剂的发现中可以提高效率、降低实验成本。本文介绍了Autodock Vina和Discovery Studio在基于分子对接法的虚拟筛选中的使用,并对比分析其对β-内酰胺酶活性位点的筛选结果。希望通过这种比较促进虚拟筛选在药物设计领域中的应用,提高耐药基因抑制剂的发现速度。     

Searching for anthranilic acid-based thumb pocket 2 HCV NS5B polymerase inhibitors through a combination of molecular docking, 3D-QSAR and virtual screening

A combination of the following computational methods: (i) molecular docking, (ii) 3-D Quantitative Structure Activity Relationship Comparative Molecular Field Analysis (3D-QSAR CoMFA), (iii) similarity search and (iv) virtual screening using PubChem database was applied to identify new anthranilic acid-based inhibitors of hepatitis C virus (HCV) replication. A number of known inhibitors were initially docked into the “Thumb Pocket 2” allosteric site of the crystal structure of the enzyme HCV RNA-dependent RNA polymerase (NS5B GT1b). Then, the CoMFA fields were generated through a receptor-based alignment of docking poses to build a validated and stable 3D-QSAR CoMFA model. The proposed model can be first utilized to get insight into the molecular features that promote bioactivity, and then within a virtual screening procedure, it can be used to estimate the activity of novel potential bioactive compounds prior to their synthesis and biological tests.     

Human sialidase inhibitors: Design,synthesis, and biological evaluation of 4-acetamido-5-acylamido-2-fluoro benzoic acids

Recent advances in the sialidase biology have clarified the role of human sialidases (NEU 1 to NEU4) in the development of various disease states such as cancer, diabetes and arteriosclerosis. Isoform selective human sialidase inhibitors could be a therapeutic tool or molecular probes for the exploration of the specific functions of human sialidases. In the present study, de novo design based virtual screening was performed to find a new class of human sialidase inhibitors using the experimental crystal structure of NEU2 isoform. A few of nitro benzene and fluoro benzoic acid were identified and a series of 4-acetamido-5-acylamido-2-fluoro benzoic acids were synthesized and, the inhibitory activity of all these compounds against all human sialidase enzymes was evaluated. All these compounds were found to have a poor inhibitory activity and only NEU2 showed more sensitivity to this series of compounds as compared to other isoforms. Molecular docking was performed to gain insight regarding the binding mode of these inhibitors and thereby provided valuable information for our study on the design of selective human sialidase inhibitors further.