Identification of some novel AHAS inhibitors via molecular docking and virtual screening approach

Acetohydroxyacid synthase (AHAS; EC 2.2.1.6) catalyzes the first common step in branched-chain amino acid biosynthesis. This enzyme is an important target for the design of environmental-benign herbicides. Based on the crystal structure of AHAS/sulfonylurea complex, we have carried out computational screening of the ACD-3D database in order to look for novel non-sulfonylurea inhibitors of AHAS for the first time. Three novel compounds were found to inhibit plant AHAS in vitro among 14 procured compounds. One compound showed promising activity in vivo for rape root growth inhibition bioassay. This research provided useful clues for further design and discovery of AHAS inhibitors.     

Identification of novel urease inhibitors: pharmacophore modeling,virtual screening and molecular docking studies

Abstract

Pharmacophore modeling and atom-based three-dimensional quantitative structure–activity relationship (3D-QSAR) have been developed on N-acylglycino- and hippurohydroxamic acid derivatives, which are known potential inhibitors of urease. This is followed by virtual screening and ADMET (absorption, distribution, metabolism, excretion and toxicity) studies on a large library of known drugs in order to get lead molecules as Helicobacter pylori urease inhibitors. A suitable three-featured pharmacophore model comprising one H-bond acceptor and two H-bond donor features (ADD.10) has been found to be the best QSAR model. An external library of compounds (～3000 molecules), pre-filtered using Lipinski’s rule of five, has been further screened using the pharmacophore model ADD.10. By analyzing the fitness of the hits with respect to the pharmacophore model and their binding interaction inside the urease active site, four molecules have been predicted to be extremely good urease inhibitors. Two of these have significant potential and should be taken up for further drug-designing process.     

Docking based virtual screening and molecular dynamics study to identify potential monoacylglycerol lipase inhibitors

Monoacylglycerol lipase (MAGL) is one of the key enzymes of the endocannabinoid system (ECS). It hydrolyzes one of the major endocannabinoid, 2-arachidonoylglycerol (2-AG), an endogenous full agonist at G protein coupled cannabinoid receptors CB1 and CB2. Numerous studies showed that MGL inhibitors are potentially useful for the treatment of pain, inflammation, cancer and CNS disorders. These provocative findings suggested that pharmacological inhibition of MAGL function may confer significant therapeutic benefits. In this study, we presented hybrid ligand and structure-based approaches to obtain a novel set of virtual leads as MAGL inhibitors. The constraints used in this study, were Glide score, binding free energy estimates and ADME properties to screen the ZINC database, containing approximately 21 million compounds. A total of seven virtual hits were obtained, which showed significant binding affinity towards MAGL protein. Ligand, ZINC24092691 was employed in complex form with the protein MAGL, for molecular dynamics simulation study, because of its excellent glide score, binding free energy and ADME properties. The RMSD of ZINC24092691 was observed to stay at 0.1 nm (1 Å) in most of the trajectories, which further confirmed its ability to inhibit the protein MAGL. The hits were then evaluated for their ability to inhibit human MAGL. The compound ZINC24092691 displayed the noteworthy inhibitory activity reducing MAGL activity to 21.15% at 100 nM concentration, with an IC₅₀ value of 10 nM.     

Pharmacophore based virtual screening,molecular docking and biological evaluation to identify novel PDE5 inhibitors with vasodilatory activity

Prompted by the role of PDE5 and its closely associated cAMP and cGMP in hypertension, we have attempted to discover novel PDE5 inhibitors through ligand based virtual screening. Rigorously validated model comprising of one HBA, one HY and one RA was used as a query to search the NCI database leading to retrieval of many compounds which were screened on the basis of estimated activity, fit value and Lipinski’s violation. Selected compounds were subjected to docking studies which resulted into visualization of potential interaction capabilities of NCI compounds in line to pharmacophoric features. Finally three compounds were subjected to in vitro evaluation using the isolated rat aortic model. The results showed that all three compounds are potent and novel PDE5 inhibitors with vasodilatory activity range from 10⁻² to 10⁻⁵ M.     

Identification of potent virtual leads to design novel PLK1 inhibitors: pharmacophore modelling,virtual screening and molecular docking studies

The aim of this study was to identify novel scaffolds and utilise them in designing potent PLK1 inhibitors. Three-dimensional pharmacophore models on the basis of chemical features were developed for PLK1 on the basis of the known inhibitors. The best pharmacophore model, Hypo 1, which has the highest correlation (0.96), the highest cost difference (75.7494), the lowest total cost and RMSD (75.7494, 0.5458), contains two hydrophobics, one ring aromatic and one hydrogen donor. Hypo 1 was validated by the test set, decoy set and the Fischer's randomisation method. Then it was used for chemical database virtual screening. The hit compounds were filtered by Lipinski's rule of five and absorption, distribution, metabolism, elimination and toxicity properties. Finally, 24 compounds with good estimated activity values were used for docking studies. These results will be used to develop new inhibitors of PLK1 as leads.     

Discovery of potential novel microsomal triglyceride transfer protein inhibitors via virtual screening of pharmacophore modelling and molecular docking

In order to identify potential natural inhibitors against the microsomal triglyceride transfer protein (MTP), HipHop models were generated using 20 known inhibitors from the Binding Database. Using evaluation indicators, the best hypothesis model, Hypo1, was selected and utilised to screen the Traditional Chinese Medicine Database, which resulted in a hit list of 58 drug-like compounds. A homology model of MTP was built by MODELLER and was minimised by CHARMm force field. It was then validated by Ramachandran plot and Verify-3D so as to obtain a stable structure, which was further used to refine the 58 hits using molecular docking studies. Then, five compounds with higher docking scores which satisfied the docking requirements were discovered. Among them, Ginkgetin and Dauricine were most likely to be candidates that exhibition inhibiting effect on MTP. The screening strategy in this study is relatively new to the discovery of MTP inhibitors in medicinal chemistry. Moreover, it is important to note that, lomitapide, an approved MTP inhibitor, fits well with Hypo1 as well as our homology model of MTP, which confirmed the rationality of our studies. The results indicated the applicability of molecular modeling for the discovery of potential natural MTP inhibitors from traditional Chinese herbs.     

Shape-based virtual screening,docking, and molecular dynamics simulations to identify Mtb-ASADH inhibitors

Aspartate β-semialdehyde dehydrogenase (ASADH) is a key enzyme for the biosynthesis of essential amino acids and several important metabolites in microbes. Inhibition of ASADH enzyme is a promising drug target strategy against Mycobacterium tuberculosis (Mtb). In this work, in silico approach was used to identify potent inhibitors of Mtb-ASADH. Aspartyl β-difluorophosphonate (β-AFP), a known lead compound, was used to understand the molecular recognition interactions (using molecular docking and molecular dynamics analysis). This analysis helped in validating the computational protocol and established the participation of Arg99, Glu224, Cys130, Arg249, and His256 amino acids as the key amino acids in stabilizing ligand–enzyme interactions for effective binding, an essential feature is H-bonding interactions with the two arginyl residues at the two ends of the ligand. Best binding conformation of β-AFP was selected as a template for shape-based virtual screening (ZINC and NCI databases) to identify compounds that competitively inhibit the Mtb-ASADH. The top rank hits were further subjected to ADME and toxicity filters. Final filter was based on molecular docking analysis. Each screened molecule carries the characteristics of the highly electronegative groups on both sides separated by an average distance of 6?Å. Finally, the best predicted 20 compounds exhibited minimum three H-bonding interactions with Arg99 and Arg249. These identified hits can be further used for designing the more potent inhibitors against ASADH family. MD simulations were also performed on two selected compounds (NSC4862 and ZINC02534243) for further validation. During the MD simulations, both compounds showed same H-bonding interactions and remained bound to key active residues of Mtb-ASADH.     

面向虚拟筛选的GPU加速的分子对接方法

虚拟筛选是在计算机上对化合物分子进行模拟预筛选,找出容易和药物靶标结合的小分子(配体),从而降低实际实验测试次数,提高药物先导化合物的发现效率。常用的分子对接软件可以用于基于结构的虚拟筛选,寻找配体与靶标的最佳的作用模式和结合构象,并通过打分函数来筛选出潜在的配体。现有的对接软件如AutoDock Vina等在分子对接过程中需要耗费大量时间和计算资源,特别是面对大规模分子对接时,过长的筛选时间不能满足应用需求,因此,本文在最高效的QVina2对接软件基础上,提出一种基于GPU的QVina 2并行化方法QVina2-GPU,利用GPU硬件高度并行体系加速分子对接。具体包括增加初始化分子构象数量,以扩展蒙特卡罗的迭代局部搜索中线程的并行规模,增加蒙特卡罗的迭代搜索的广度以减少每次蒙特卡罗迭代搜索深度,并利用Wolfe-Powell准则改进局部搜索算法,提高了对接精度,进一步减少蒙特卡罗迭代搜索深度,最后,在NVIDIA Geforce RTX 3090平台上在公开的配体数据库上验证了QVina2-GPU的性能,实验表明在保证分子对接精度的基础上,我们提出的QVina2-GPU对Qvina2的平均加速比达到5.18倍,最大加速比达到12.28倍。     

Synthesis,molecular docking and biological evaluation of some benzimidazole derivatives as potent pancreatic lipase inhibitors

In this study, a new series of benzimidazole and bisbenzimidazole derivatives were prepared via the reaction of iminoester hydrochlorides and o-phenylenediamines and then screened for their lipase inhibition properties. Among the synthesized molecules, compounds 7a, 8a and 8c showed the best inhibitory effect against lipase enzyme with IC₅₀ values of 1.72 ± 0.12 µM, 1.92 ± 0.28 and 0.98 ± 0.07 µM, respectively. Moreover, molecular modeling studies were performed in order to understand to the inhibitory activity of the molecules. Binding poses of the studied compounds were determined at the target sites using induced fit docking (IFD) algorithms.     

Identification of some novel pyrazolo[1,5-a]pyrimidine derivatives as InhA inhibitors through pharmacophore-based virtual screening and molecular docking

The InhA inhibitors play key role in mycolic acid synthesis by preventing the fatty acid biosynthesis pathway. In this present article, Pharmacophore modelling and molecular docking study followed by in silico virtual screening could be considered as effective strategy to identify newer enoyl-ACP reductase inhibitors. Pyrrolidine carboxamide derivatives were opted to generate pharmacophore models using HypoGen algorithm in Discovery studio 2.1. Further it was employed to screen Zinc and Minimaybridge databases to identify and design newer potent hit molecules. The retrieved newer hits were further evaluated for their drug likeliness and docked against enoyl acyl carrier protein reductase. Here, novel pyrazolo[1,5-a]pyrimidine analogues were designed and synthesized with good yields. Structural elucidation of synthesized final molecules was perform through IR, MASS, ¹H-NMR, ¹³C-NMR spectroscopy and further tested for its in vitro anti-tubercular activity against H37Rv strain using Microplate Alamar blue assay (MABA) method. Most of the synthesized compounds displayed strong anti-tubercular activities. Further, these potent compounds were gauged for MDR-TB, XDR-TB and cytotoxic study.     

Identification of novel acetylcholinesterase inhibitors through e-pharmacophore-based virtual screening and molecular dynamics simulations

Alzheimer’s disease (AD), a progressive neurodegenerative disorder is the most common cause of dementia among elderly people. To date, the successful therapeutic strategy to treat AD is maintaining the levels of acetylcholine via inhibiting acetylcholinesterase (AChE). The present study involves identification of newer AChE inhibitors by dual approach of e-pharmacophore and structure-based virtual screening of Asinex library. Robustness of docking protocol was validated by enrichment calculation with ROC value .71 and BEDROC value .028. Among 11 selected hits, ZINC72338524 with best MM-GBSA dG binding shows optimal range of CNS properties and ligand–AChE complex stability. Further, molecular dynamics study revealed its molecular interactions with Trp86, Phe338, and Tyr341 amino acid residues of catalytic anionic site and Tyr124, Ser125, and Trp286 amino acid residues of peripheral anionic site. Physicochemical properties and ADMET risk prediction indicates their potential in druggability and safety.     

Identification of novel CDK2 inhibitors by a multistage virtual screening method based on SVM,pharmacophore and docking model

Abstract

Cyclin-dependent kinase 2 (CDK2) is the family of Ser/Thr protein kinases that has emerged as a highly selective with low toxic cancer therapy target. A multistage virtual screening method combined by SVM, protein-ligand interaction fingerprints (PLIF) pharmacophore and docking was utilised for screening the CDK2 inhibitors. The evaluation of the validation set indicated that this method can be used to screen large chemical databases because it has a high hit-rate and enrichment factor (80.1% and 332.83 respectively). Six compounds were screened out from NCI, Enamine and Pubchem database. After molecular dynamics and binding free energy calculation, two compounds had great potential as novel CDK2 inhibitors and they also showed selective inhibition against CDK2 in the kinase activity assay.     

New potential inhibitors of mTOR: a computational investigation integrating molecular docking,virtual screening and molecular dynamics simulation

The mTOR (mammalian or mechanistic Target Of Rapamycin), a complex metabolic pathway that involves multiple steps and regulators, is a major human metabolic pathway responsible for cell growth control in response to multiple factors and that is dysregulated in various types of cancer. The classical inhibition of the mTOR pathway is performed by rapamycin and its analogs (rapalogs). Considering that rapamycin binds to an allosteric site and performs a crucial role in the inhibition of the mTOR complex without causing the deleterious side effects common to ATP-competitive inhibitors, we employ ligand-based drug design strategies, such as virtual screening methodology, computational determination of ADME/Tox properties of selected molecules, and molecular dynamics in order to select molecules with the potential to become non-ATP-competitive inhibitors of the mTOR enzymatic complex. Our findings suggest five novel potential mTOR inhibitors, with similar or better properties than the classic inhibitor complex, rapamycin.     

Discover potential inhibitors for PFKFB3 using 3D-QSAR,virtual screening,molecular docking and molecular dynamics simulation

Abstract

The 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase-3 (PFKFB3) is a master regulator of glycolysis in cancer cells by synthesizing fructose-2,6-bisphosphate (F-2,6-BP), a potent allosteric activator of phosphofructokinase-1 (PFK-1), which is a rate-limiting enzyme of glycolysis. PFKFB3 is an attractive target for cancer treatment. It is valuable to discover promising inhibitors by using 3D-QSAR pharmacophore modeling, virtual screening, molecular docking and molecular dynamics simulation. Twenty molecules with known activity were used to build 3D-QSAR pharmacophore models. The best pharmacophore model was ADHR called Hypo1, which had the highest correlation value of 0.98 and the lowest RMSD of 0.82. Then, the Hypo1 was validated by cost value method, test set method and decoy set validation method. Next, the Hypo1 combined with Lipinski's rule of five and ADMET properties were employed to screen databases including Asinex and Specs, total of 1,048,159 molecules. The hits retrieved from screening were docked into protein by different procedures including HTVS, SP and XP. Finally, nine molecules were picked out as potential PFKFB3 inhibitors. The stability of PFKFB3-lead complexes was verified by 40?ns molecular dynamics simulation. The binding free energy and the energy contribution of per residue to the binding energy were calculated by MM-PBSA based on molecular dynamics simulation.     

Pharmacophore modeling and virtual screening for designing potential 5-Lipoxygenase inhibitors

Inhibitors of the 5-Lipoxygenase (5-LOX) pathway have a therapeutic potential in a variety of inflammatory disorders such as asthma. In this study, chemical feature based pharmacophore models of inhibitors of 5-LOX have been developed with the aid of HipHop and HypoGen modules within Catalyst program package. The best quantitative pharmacophore model, Hypo1, which has the highest correlation coefficient (0.97), consists of two hydrogen-bond acceptors, one hydrophobic feature and one ring aromatic feature. Hypo1 was further validated by test set and cross validation method. The application of the model shows great success in predicting the activities of 65 known 5-LOX inhibitors in our test set with a correlation coefficient of 0.85 with a cross validation of 95% confidence level, proving that the model is reliable in identifying structurally diverse compounds for inhibitory activity against 5-LOX. Furthermore, Hypo1 was used as a 3D query for screening Maybridge and NCI databases within catalyst and also drug like compounds obtained from Enamine Ltd, which follow Lipinski’s rule of five. The hit compounds were subsequently subjected to filtering by docking and visualization, to identify the potential lead molecules. Finally 5 potential lead compounds, identified in the above process, were evaluated for their inhibitory activities. These studies resulted in the identification of two compounds with potent inhibition of 5-LOX activity with IC₅₀ of 14 μM and 35 μM, respectively. These studies thus validate the pharmacophore model generated and suggest the usefulness of the model in screening of various small molecule libraries and identification of potential lead compounds for 5-LOX inhibition.     

Pharmacophore modeling and virtual screening for designing potential PLK1 inhibitors

Pharmacophore models of Polo-like kinase-1 (PLK1) inhibitors have been established by using the HipHop and HypoGen algorithms implemented in the Catalyst software package. The best quantitative pharmacophore model, Hypo1, which has the highest correlation coefficient (0.9895), consists of one hydrogen bond acceptor, one hydrogen bond donor, one hydrophobic feature, and one hydrophobic aliphatic feature. Hypo1 was further validated by test set and cross validation method. Then Hypo1 was used as a 3D query to screen several databases including Specs, NCI, Maybridge, and Chinese Nature Product Database (CNPD). The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking study to refine the retrieved hits and as a result to reduce the rate of false positive. Finally, a total of 20 compounds were selected and have been shifted to in vitro and in vivo studies. As far as we know, this is the first report on the pharmacophore modeling even the first publicly reported virtual screening study of PLK1 inhibitors.     

Structure based virtual screening of novel inhibitors against multidrug resistant superbugs

Pathogenic microorganisms are persistently expressing resistance towards present generation antibiotics and are on the verge of joining the superbug family. Recent studies revealed that, notorious pathogens such as Salmonella typhi, Shigella dysenteriae and Vibrio cholerae have acquired multiple drug resistance and the treatment became a serious concern. This necessitates an alternative therapeutic solution. Present study investigates the utility of computer aided method to study the mechanism of receptor-ligand interactions and thereby inhibition of virulence factors (shiga toxin of Shigella dysenteriae, cholera toxin of Vibrio cholerae and hemolysin-E of Salmonella typhi) by novel phytoligands. The rational designs of improved therapeutics require the crystal structure for the drug targets. The structures of the virulent toxins were identified as probable drug targets. However, out of the three virulent factors, the structure for hemolysin-E is not yet available in its native form. Thus, we tried to model the structure by homology modeling using Modeller 9v9. After extensive literature survey, we selected 50 phytoligands based on their medicinal significance and drug likenesses. The receptor-ligands interactions between selected leads and toxins were studied by molecular docking using Auto Dock 4.0. We have identified two novel sesquiterpenes, Cadinane [(1S, 4S, 4aS, 6S, 8aS)- 4- Isopropyl- 1, 6- dimethyldecahydronaphthalene] and Cedrol [(8α)-Cedran-8-ol] against Shiga (binding energy -5.56 kcal/mol) and cholera toxins (binding energy -5.33 kcal/mol) respectively which have good inhibitory properties. Similarly, a natural Xanthophyll, Violaxanthin [3S, 3'S, 5R, 5'R, 6S, 6'S)-5, 5', 6, 6'-Tetrahydro-5, 6:5', 6'-diepoxy-β, β-carotene-3, 3'-diol] was identified as novel therapeutic lead for hemolysin-E (binding energy of -5.99 kcal/mol). This data provide an insight for populating the pool of novel inhibitors against various drug targets of superbugs when all current generation drugs seem to have failed.     

Accessible high-throughput virtual screening molecular docking software for students and educators

We survey low cost high-throughput virtual screening (HTVS) computer programs for instructors who wish to demonstrate molecular docking in their courses. Since HTVS programs are a useful adjunct to the time consuming and expensive wet bench experiments necessary to discover new drug therapies, the topic of molecular docking is core to the instruction of biochemistry and molecular biology. The availability of HTVS programs coupled with decreasing costs and advances in computer hardware have made computational approaches to drug discovery possible at institutional and non-profit budgets. This paper focuses on HTVS programs with graphical user interfaces (GUIs) that use either DOCK or AutoDock for the prediction of DockoMatic, PyRx, DockingServer, and MOLA since their utility has been proven by the research community, they are free or affordable, and the programs operate on a range of computer platforms.     

Discovery of novel low molecular weight inhibitors of IMPDH via virtual needle screening

Novel, low molecular weight inhibitors of IMPDH have been discovered through the application of a validated virtual screening protocol. A series of 21 IMPDH inhibitors were used to validate the docking procedure. Application of this procedure to the selection of compounds for screening from an in-house database resulted in a 50-fold reduction in the size of the screening set (3425 to 74 compounds) and gave a hit-rate of 10% on biological evaluation.     

Novel urushiol derivatives as HDAC8 inhibitors: rational design,virtual screening,molecular docking and molecular dynamics studies

Three series of novel urushiol derivatives were designed by introducing a hydroxamic acid moiety into the tail of an alkyl side chain and substituents with differing electronic properties or steric bulk onto the benzene ring and alkyl side chain. The compounds’ binding affinity toward HDAC8 was screened by Glide docking. The highest-scoring compounds were processed further with molecular docking, MD simulations, and binding free energy studies to analyze the binding modes and mechanisms. Ten compounds had Glide scores of ?8.2 to ?10.2, which revealed that introducing hydroxy, carbonyl, amino, or methyl ether groups into the alkyl side chain or addition of –F, –Cl, sulfonamide, benzamido, amino, or hydroxy substituents on the benzene ring could significantly increase binding affinity. Molecular docking studies revealed that zinc ion coordination, hydrogen bonding, and hydrophobic interactions contributed to the high calculated binding affinities of these compounds toward HDAC8. MD simulations and binding free energy studies showed that all complexes possessed good stability, as characterized by low RMSDs, low RMSFs of residues, moderate hydrogen bonding and zinc ion coordination and low values of binding free energies. Hie147, Tyr121, Phe175, Hip110, Phe119, Tyr273, Lys21, Gly118, Gln230, Leu122, Gly269, and Gly107 contributed favorably to the binding; and Van der Waals and electrostatic interactions provided major contributions to the stability of these complexes. These results show the potential of urushiol derivatives as HDAC8 binding lead compounds, which have great therapeutic potential in the treatment of various malignancies, neurological disorders, and human parasitic diseases.