Structure-based pharmacophore design and virtual screening for novel angiotensin converting enzyme 2 inhibitors

The metallopeptidase Angiotensin Converting Enzyme (ACE) is an important drug target for the treatment of hypertension, heart, kidney, and lung disease. Recently, a close and unique human ACE homologue termed ACE2 has been identified and found to be an interesting new cardiorenal disease target. With the recently resolved inhibitor-bound ACE2 crystal structure available, we have attempted a structure-based approach to identify novel potent and selective inhibitors. Computational approaches focus on pharmacophore-based virtual screening of large compound databases. Selectivity was ensured by initial screening for ACE inhibitors within an internal database and the Derwent World Drug Index, which could be reduced to zero false positives and 0.1% hit rate, respectively. An average hit reduction of 0.44% was achieved with a five feature hypothesis, searching approximately 3.8 million compounds from various commercial databases. Seventeen compounds were selected based on high fit values as well as diverse structure and subjected to experimental validation in a bioassay. We show that all compounds displayed an inhibitory effect on ACE2 activity, the six most promising candidates exhibiting IC50 values in the range of 62-179 microM.     

Discovery of potential Zika virus RNA polymerase inhibitors by docking-based virtual screening

Zika virus (ZIKV) infection has been associated with Guillain-Barre syndrome in adults and microcephaly in infants. The existence of insufficient structural data in most of the protein databases hinders the synthesis of anti-ZIKV pharmaceutics. In this work, we attempted to model the catalytic domain of the ZIKV RNA polymerase (RdRpC) along with a detailed assessment of conserved aspartates in ZIKV RdRpC palm domain as potential drug targets. The conserved and catalytically active aspartate residues present in the predicted RdRpC protein were virtually screened against a ZINC database for inhibitors, and the selected potential drug candidates were further filtered based on their ADMET profiles. One of the pharmacokinetically active compounds (Ligand 6) showed a remarkable docking profile against the strictly conserved aspartate residues of the RdRpC active site. We hypothesize that the Ligand 6 may form a potential drug candidate for RdRpC inhibition in the clinical treatment of ZIKV infection.     

Discovery of novel wee1 inhibitors via structure-based virtual screening and biological evaluation

Wee1 plays a critical role in the arrest of G2/M cell cycle for DNA repair before entering mitosis. Many cancer cells have been identified as overexpression of Wee1. In this research, pharmacophore modeling, molecular docking and molecular dynamics simulation approaches were constructed to identify novel potential Wee1 inhibitors. A compound 8 was found to have a novel skeleton against Wee1 with an IC₅₀ value of 22.32 µM and a K_i value of 13.11 µM. Kinetic assays were employed to evaluate the compound 8 as a competitive inhibitor. Compound 8 was tested against A-549 tumor cell lines with IC₅₀ value of 17.8 µM. To investigate the intermolecular interaction of Wee1 and compound 8, further molecular dynamics simulations were performed. It indicates that the binding mode of compound 8 and reference ligand is similar. The active core scaffold of compound 8 could represent a promising lead compound for studying Wee1 and be used for further structural optimization to design more potent Wee1 inhibitors.     

Discovery of novel IDO1 inhibitors via structure-based virtual screening and biological assays

Indoleamine 2,3-dioxygenase 1 (IDO1) is a heme-containing enzyme that catalyzes the first and rate-limiting step in catabolism of tryptophan via the kynurenine pathway, which plays a pivotal role in the proliferation and differentiation of T cells. IDO1 has been proven to be an attractive target for many diseases, such as breast cancer, lung cancer, colon cancer, prostate cancer, etc. In this study, docking-based virtual screening and bioassays were conducted to identify novel inhibitors of IDO1. The cellular assay demonstrated that 24 compounds exhibited potent inhibitory activity against IDO1 at micromolar level, including 8 compounds with IC₅₀ values below 10 μM and the most potent one (compound 1) with IC₅₀ of 1.18?±?0.04 μM. Further lead optimization based on similarity searching strategy led to the discovery of compound 28 as an excellent inhibitor with IC₅₀ of 0.27?±?0.02 μM. Then, the structure–activity relationship of compounds 1, 2, 8 and 14 analogues is discussed. The interaction modes of two compounds against IDO1 were further explored through a Python Based Metal Center Parameter Builder (MCPB.py) molecular dynamics simulation, binding free energy calculation and electrostatic potential analysis. The novel IDO1 inhibitors of compound 1 and its analogues could be considered as promising scaffold for further development of IDO1 inhibitors.

     

Discovery of novel Pim-1 kinase inhibitors by a hierarchical multistage virtual screening approach based on SVM model, pharmacophore, and molecular docking

In this investigation, we describe the discovery of novel potent Pim-1 inhibitors by employing a proposed hierarchical multistage virtual screening (VS) approach, which is based on support vector machine-based (SVM-based VS or SB-VS), pharmacophore-based VS (PB-VS), and docking-based VS (DB-VS) methods. In this approach, the three VS methods are applied in an increasing order of complexity so that the first filter (SB-VS) is fast and simple, while successive ones (PB-VS and DB-VS) are more time-consuming but are applied only to a small subset of the entire database. Evaluation of this approach indicates that it can be used to screen a large chemical library rapidly with a high hit rate and a high enrichment factor. This approach was then applied to screen several large chemical libraries, including PubChem, Specs, and Enamine as well as an in-house database. From the final hits, 47 compounds were selected for further in vitro Pim-1 inhibitory assay, and 15 compounds show nanomolar level or low micromolar inhibition potency against Pim-1. In particular, four of them were found to have new scaffolds which have potential for the chemical development of Pim-1 inhibitors.     

Discovery of novel human acrosin inhibitors by virtual screening

Human acrosin is an attractive target for the discovery of male contraceptive drugs. For the first time, structure-based drug design was applied to discover structurally diverse human acrosin inhibitors. A parallel virtual screening strategy in combination with pharmacophore-based and docking-based techniques was used to screen the SPECS database. From 16 compounds selected by virtual screening, a total of 10 compounds were found to be human acrosin inhibitors. Compound 2 was found to be the most potent hit (IC₅₀ = 14 μM) and its binding mode was investigated by molecular dynamics simulations. The hit interacted with human acrosin mainly through hydrophobic and hydrogen-bonding interactions, which provided a good starting structure for further optimization studies.     

A virtual screening approach for thymidine monophosphate kinase inhibitors as antitubercular agents based on docking and pharmacophore models

Docking and pharmacophore screening tools were used to examine the binding of ligands in the active site of thymidine monophosphate kinase of Mycobacterium tuberculosis. Docking analysis of deoxythymidine monophosphate (dTMP) analogues suggests the role of hydrogen bonding and other weak interactions in enzyme selectivity. Water-mediated hydrogen-bond networks and a halogen-bond interaction seem to stabilize the molecular recognition. A pharmacophore model was developed using 20 dTMP analogues. The pharmacophoric features were complementary to the active site residues involved in the ligand recognition. On the basis of these studies, a composite screening model that combines the features from both the docking analysis and the pharmacophore model was developed. The composite model was validated by screening a database spiked with 47 known inhibitors. The model picked up 42 of these, giving an enrichment factor of 17. The validated model was used to successfully screen an in-house database of about 500,000 compounds. Subsequent screening with other filters gave 186 hit molecules.     

Discovery of novel checkpoint kinase 1 inhibitors by virtual screening based on multiple crystal structures

Incorporating receptor flexibility is considered crucial for improvement of docking-based virtual screening. With an abundance of crystallographic structures freely available, docking with multiple crystal structures is believed to be a practical approach to cope with protein flexibility. Here we describe a successful application of the docking of multiple structures to discover novel and potent Chk1 inhibitors. Forty-six Chk1 structures were first compared in single structure docking by predicting the binding mode and recovering known ligands. Combinations of different protein structures were then compared by recovery of known ligands and an optimal ensemble of Chk1 structures were selected. The chosen structures were used in the virtual screening of over 60?000 diverse compounds for Chk1 inhibitors. Six novel compounds ranked at the top of the hits list were tested experimentally, and two of these compounds inhibited Chk1 activity-the best with an IC(50) value of 9.6 μM. Further study indicated that achieving a better enrichment and identifying more diverse compounds was more likely using multiple structures than using only a single structure even when protein structures were randomly selected. Taking into account conformational energy difference did not help to improve enrichment in the top ranked list.     

Evaluation of potential inhibitors of squalene synthase based on virtual screening and in vitro studies

Squalene synthase (SQS) is a potential target for hyperlipidemia treatment. To identify novel chemical scaffolds of SQS inhibitors, we generated 3D-QSAR pharmacophore models using HypoGen. The best quantitative pharmacophore model, Hypo 1, was selected for virtual screening using two chemical databases, Specs and Traditional Chinese Medicine database (TCM). The best-mapped hit compounds were then subjected to filtering by Lipinski^’s rule of five and docking studies to refine the hits. Finally, five compounds were selected from the top-ranked hit compounds for SQS inhibitory assay in vitro. Three of these compounds could inhibit SQS in vitro, and should be further evaluated pre-clinically as a treatment for hyperlipidemia.     

Novel virtual screening protocol based on the combined use of molecular modeling and electron-ion interaction potential techniques to design HIV-1 integrase inhibitors

HIV-1 integrase (IN) is an essential enzyme for viral replication and represents an intriguing target for the development of new drugs. Although a large number of compounds have been reported to inhibit IN in biochemical assays, no drug active against this enzyme has been approved by the FDA so far. In this study, we report, for the first time, the use of the electron-ion interaction potential (EIIP) technique in combination with molecular modeling approaches for the identification of new IN inhibitors. An innovative virtual screening approach, based on the determination of both short- and long-range interactions between interacting molecules, was employed with the aim of identifying molecules able to inhibit the binding of IN to viral DNA. Moreover, results from a database screening on the commercial Asinex Gold Collection led to the selection of several compounds. One of them showed a significant inhibitory potency toward IN in the overall integration assay. Biological investigations also showed, in agreement with modeling studies, that these compounds prevent recognition of DNA by IN in a fluorescence fluctuation assay, probably by interacting with the DNA binding domain of IN.     

Discovery of potential inhibitors targeting the kinase domain of polynucleotide kinase/phosphatase (PNKP): Homology modeling,virtual screening based on multiple conformations,and molecular dynamics simulation

In recent years, the level of interest has been increased in developing the DNA-repair inhibitors, to enhance the cytotoxic effects in the treatment of cancers. Polynucleotide kinase/phosphatase (PNKP) is a critical human DNA repair enzyme that repairs DNA strand breaks by catalyzing the restoration of 5’-phosphate and 3’-hydroxyl termini that are required for subsequent processing by DNA ligases and polymerases. PNKP is the only protein that repairs the 3′-hydroxyl group and 5′-phosphate group, which depicts PNKP as a potential therapeutic target. Besides, PNKP is the only DNA-repair enzyme that contains the 5′-kinase activity, therefore, targeting this kinase domain would motivate the development of novel PNKP-specific inhibitors. However, there are neither crystal structures of human PNKP nor the kinase inhibitors reported so far. Thus, in this present study, a sequential molecular docking-based virtual screening with multiple PNKP conformations integrating homology modeling, molecular dynamics simulation, and binding free energy calculation was developed to discover novel PNKP kinase inhibitors, and the top-scored molecule was finally submitted to molecular dynamics simulation to reveal the binding mechanism between the inhibitor and PNKP. Taken together, the current study could provide some guidance for the molecular docking based-virtual screening of novel PNKP kinase inhibitors.     

Identification of potential influenza virus endonuclease inhibitors through virtual screening based on the 3D-QSAR model

Influenza endonucleases have appeared as an attractive target of antiviral therapy for influenza infection. With the purpose of designing a novel antiviral agent with enhanced biological activities against influenza endonuclease, a three-dimensional quantitative structure-activity relationships (3D-QSAR) model was generated based on 34 influenza endonuclease inhibitors. The comparative molecular similarity index analysis (CoMSIA) with a steric, electrostatic and hydrophobic (SEH) model showed the best correlative and predictive capability (q ² = 0.763, r ² = 0.969 and F = 174.785), which provided a pharmacophore composed of the electronegative moiety as well as the bulky hydrophobic group. The CoMSIA model was used as a pharmacophore query in the UNITY search of the ChemDiv compound library to give virtual active compounds. The 3D-QSAR model was then used to predict the activity of the selected compounds, which identified three compounds as the most likely inhibitor candidates.     

Discovery of novel cathepsin S inhibitors by pharmacophore-based virtual high-throughput screening

The cysteine protease cathepsin S (CatS) is involved in the pathogenesis of autoimmune disorders, atherosclerosis, and obesity. Therefore, it represents a promising pharmacological target for drug development. We generated ligand-based and structure-based pharmacophore models for noncovalent and covalent CatS inhibitors to perform virtual high-throughput screening of chemical databases in order to discover novel scaffolds for CatS inhibitors. An in vitro evaluation of the resulting 15 structures revealed seven CatS inhibitors with kinetic constants in the low micromolar range. These compounds can be subjected to further chemical modifications to obtain drugs for the treatment of autoimmune disorders and atherosclerosis.     

基于药效团的BRD4靶向小分子抑制剂虚拟筛选

BRD4靶点和多种肿瘤密切相关,是具有良好成药性的热门靶点.本文选取活性较好且结构差异较大的BRD4小分子抑制剂作为训练集分子,基于配体小分子共同特征(HipHop)方法使用Discovery Studio 3.0分子模拟软件构建了药效团.药效团通过测试集验证、ROC曲线验证(SE(sensitivity)=0.937...     

Combination of pharmacophore modeling and 3D-QSAR analysis of potential glyoxalase-I inhibitors as anticancer agents

Glyoxalase system is an ubiquitous system in human cells which has been examined thoroughly for its role in different diseases. It comprises two enzymes; Glyoxalase I (Glo-I) and Glyoxalase II (Glo-II) which perform detoxifying endogenous harmful metabolites, mainly methylglyoxal (MG) into non-toxic bystanders. In silico computer Aided Drug Design approaches were used and ninety two diverse pharmacophore models were generated from eighteen Glyoxalase I crystallographic complexes. Subsequent QSAR modeling followed by ROC evaluation identified a single pharmacophore model which was able to predict the expected Glyoxalase I inhibition. Screening of the National Cancer Institute (NCI) database using the optimal pharmacophore Hypo(3VW9) identified several promising hits. Thirty eight hits were successfully predicted then ordered and evaluated in vitro. Seven hits out of the thirty eight tested compounds showed more than 50% inhibition with low micromolar IC₅₀.     

In silico based virtual screening and mixed mode QM/MM calculation identifies caffeine scaffold for designing potential inhibitors for tyrosyl tRNA synthetase of Mycobacterium tuberculosis

Aminoacyl tRNA synthetases are novel antibacterial drug target because of their important role in protein synthesis. In this study, we performed high throughput virtual screening of 205883 compounds from Asinex ligand database to identify potential specific inhibitors for Tyrosyl tRNA synthetase of Mycobacterium tuberculosis (MtbTyrRS). Compounds are ranked based on the glide extra precision docking score. It is noted that the top ranked compounds have caffeine scaffold. The top five caffeine analogs are further evaluated for other drug‐like properties. The binding energies of caffeine analogs are estimated using mixed mode quantum mechanics/molecular mechanics calculation. The results show that these caffeine analogs have good absorption, distribution, metabolism, and excretion properties and high binding affinity to the MtbTyrRS. This suggests that caffeine could be a new scaffold for designing inhibitors against Tyrosyl tRNA synthetase of M. tuberculosis. The top five caffeine analogs are also subjected to docking calculations with human cytosolic and mitochondrial Tyrosyl tRNA synthetases to ascertain their specificities toward MtbTyrRS. The comparative docking studies indicate that the top five caffeine analogs are specific for MtbTyrRS. © 2014 Wiley Periodicals, Inc.