In silico prediction of novel phosphodiesterase type-5 inhibitors derived from Sildenafil, Vardenafil and Tadalafil

A series of drug-like compounds derived from Sildenafil, Vardenafil and Tadalafil analogues were modelled through the MIA-QSAR (multivariate image analysis applied to quantitative structure-activity relationships) ligand-based approach. A highly predictive model was achieved and novel compounds, miscellany of substructures of these three representative phosphodiesterase type-5 (PDE-5) inhibitors were predicted using the calibration parameters obtained through partial least squares (PLS) regression. The high bioactivities of eight promising compounds were corroborated by docking evaluation. Calculated ADME-Tox (absorption, distribution, metabolism, excretion and toxicity) profiles for such compounds suggest advantages of some of them over the currently available, most common drugs used for the treatment of erectile dysfunction.     

MIA-QSAR,PCA-ranking and least-squares support-vector machines in the accurate prediction of the activities of phosphodiesterase type 5 (PDE-5) inhibitors

Phosphodiesterase type-5 (PDE-5) is a key enzyme involved in the erection process. PDE-5 inhibitors, such as Sildenafil (Viagra^TM), Vardenafil (Levitra^TM) and Tadalafil (Cialis^TM), are used for the treatment of erectile dysfunction. Computer-assisted modelling of biological activities of PDE-5 inhibitors may make quantitative structure–activity relationship (QSAR) models useful for the development of safer (low side effects) and more potent drugs. The multivariate image analysis applied to QSAR (MIA-QSAR) method, coupled to partial least-squares (PLS) regression, has provided highly predictive QSAR models. Nevertheless, regression methods which take into account nonlinearity, such as least-squares support-vector machines (LS-SVMs), are supposed to predict biological activities more accurately than the usual linear methods. Thus, together with prior variable selection using principal component analysis ranking, MIA-QSAR and LS-SVM regression were applied to model the bioactivities of a series of cyclic guanine derivatives (PDE-5 inhibitors), and the results were compared with those based on linear methodologies. MIA-QSAR/LS-SVM was found to improve greatly the prediction performance when compared with MIA-QSAR/PLS, MIA-QSAR/N-PLS, CoMFA/PLS and CoMSIA/PLS models.     

The discovery of steroids and other novel FKBP inhibitors using a molecular docking program

The molecular docking computer program SANDOCK was used to screen small molecule three-dimensional databases in the hunt for novel FKBP inhibitors. Spectroscopic measurements confirmed binding of over 20 compounds to the target protein, some with dissociation constants in the low micromolar range. The discovery that FK506 binding protein is a steroid binding protein may be of wider biological significance. Two-dimensional NMR was used to determine the steroid binding mode and confirmed the interactions predicted by the docking program.     

Ligand‐based pharmacophore modelling and screening of DNA minor groove binders targeting Staphylococcus aureus

The recognition of DNA by small molecules is of special importance in the design of new drugs. Many natural and synthetic compounds have the ability to interact with the minor groove of DNA. In the present study, identification of minor groove binding compounds was attained by the combined approach of pharmacophore modelling, virtual screening and molecular dynamics approach. Experimentally reported 32 minor groove binding compounds were used to develop the pharmacophore model. Based on the fitness score, best three pharmacophore hypotheses were selected and used as template for screening the compounds from drug bank database. This pharmacophore‐based screening provides many compounds with the same pharmacological properties. All these compounds were subjected to four phases of docking protocols with combined Glide‐quantum‐polarized ligand docking approach. Molecular dynamics results indicated that selected compounds are more active and showed good interaction in the binding site of DNA. Based on the scoring parameters and energy values, the best compounds were selected, and antibacterial activity of these compounds was identified using in vitro antimicrobial techniques. Copyright © 2014 John Wiley & Sons, Ltd.     

Exploration of Virtual Candidates for Human HMG-CoA Reductase Inhibitors Using Pharmacophore Modeling and Molecular Dynamics Simulations

3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) is a rate-controlling enzyme in the mevalonate pathway which involved in biosynthesis of cholesterol and other isoprenoids. This enzyme catalyzes the conversion of HMG-CoA to mevalonate and is regarded as a drug target to treat hypercholesterolemia. In this study, ten qualitative pharmacophore models were generated based on chemical features in active inhibitors of HMGR. The generated models were validated using a test set. In a validation process, the best hypothesis was selected based on the statistical parameters and used for virtual screening of chemical databases to find novel lead candidates. The screened compounds were sorted by applying drug-like properties. The compounds that satisfied all drug-like properties were used for molecular docking study to identify their binding conformations at active site of HMGR. The final hit compounds were selected based on docking score and binding orientation. The HMGR structures in complex with the hit compounds were subjected to 10 ns molecular dynamics simulations to refine the binding orientation as well as to check the stability of the hits. After simulation, binding modes including hydrogen bonding patterns and molecular interactions with the active site residues were analyzed. In conclusion, four hit compounds with new structural scaffold were suggested as novel and potent HMGR inhibitors.     

紫锥菊提取物及酚酸化合物体外抗血小板聚集活性研究

为探究紫锥菊提取物及酚酸化合物体外抗血小板聚集活性,体外抗血小板聚集实验采用Born比浊法,以聚集抑制率和半数抑制浓度为指标评价。同时采用分子对接方法,选择凝血因子V(F5)、凝血因子VIII(F8)及凝血因子XI(F11)与酚酸类化合物进行虚拟对接,研究其抗血小板聚集的分子作用靶点。结果表明化合物S-1～S-10及其提取物对体外ADP诱导的血小板聚集有抑制作用,抑制率呈浓度依赖性,S-6与靶点的结合位点更多,选择性更强。紫锥菊中酚酸类化合物及其提取物在体外均显现出抗ADP诱导的血小板聚集活性,为紫锥菊体内研究提供依据。     

Blind docking of drug-sized compounds to proteins with up to a thousand residues

Blind docking was introduced for the detection of possible binding sites and modes of peptide ligands by scanning the entire surface of protein targets. In the present study, the method is tested on a group of drug-sized compounds and proteins with up to a thousand amino acid residues. Both proteins from complex structures and ligand-free proteins were used as targets. Robustness, limitations and future perspectives of the method are discussed. It is concluded that blind docking can be used for unbiased mapping of the binding patterns of drug candidates.     

Modeling the binding modes of stilbene analogs to cyclooxygenase-2: a molecular docking study

Stilbene analogs are a new class of anti-inflammatory compounds that effectively inhibit COX-2, which is the major target in the treatment of inflammation and pain. In this study, docking simulations were conducted using AutoDock 4 software that focused on the binding of this class of compounds to COX-2 protein. Our aim was to better understand the structural and chemical features responsible for the recognition mechanism of these compounds, and to explore their binding modes of interaction at the active site by comparing them with COX-2 co-crystallized with SC-558. The docking results allowed us to provide a plausible explanation for the different binding affinities observed experimentally. These results show that important conserved residues, in particular Arg513, Phe518, Trp387, Leu352, Leu531 and Arg120, could be essential for the binding of the ligands to COX-2 protein. The quality of the docking model was estimated based on the binding energies of the studied compounds. A good correlation was obtained between experimental logAr values and the predicted binding energies of the studied compounds.     

Identification of selective MMP-9 inhibitors through multiple e-pharmacophore,ligand-based pharmacophore,molecular docking,and density functional theory approaches

Matrix metalloproteinase-9 (MMP-9) is a significant target for the development of drugs for the treatment of arthritis, CNS disorders, and cancer metastasis. The structure-based and ligand-based methods were used for the virtual screening (VS) of database compounds to obtain potent and selective MMP-9 inhibitors. Experimentally known MMP-9 inhibitors were used to grow up ligand-based three pharmacophore models utilizing Schrodinger suite. The X-ray crystallographic structures of MMP-9 with different inhibitors were used to develop five energy-optimized structure-based (e-pharmacophore) models. All developed pharmacophores were validated and applied to screen the Zinc database. Pharmacophore matched compounds were subjected to molecular docking to retrieve hits with novel scaffolds. The molecules with diverse structures, high docking scores and low binding energies for various crystal structures of MMP-9, were selected as final hits. The Induced fit docking (IFD) analysis provided significant information about the driving of inhibitor to approve a suitable bioactive conformational position in the active site of protein. Since charge transfer reaction occurs during receptor–ligand interaction, therefore, electronic features of hits (ligands) are interesting parameters to explain the binding interactions. Density functional theory (DFT) at B3LYP/6-31G* level was utilized to explore electronic features of hits. The docking study of hits using AutoDock was helpful to establish the binding interactions. The study illustrates that the combined pharmacophore approach is advantageous to identify diverse hits which have better binding affinity to the active site of the enzyme for all possible bioactive conformations. The approach used in the study is worthy to design drugs for other targets.     

Identification of small-molecule inhibitors of the steroidogenic acute regulatory protein (STARD1) by structure-based design

A homology model of the steroidogenic acute regulatory protein (STAR)-related lipid transfer (START) domain of STARD1 was built, and the cholesterol binding site was identified. Structure-based design studies were performed to identify small molecule inhibitors of the START domain. The lead compounds were selected based on cAMP-induced, but not 22R-hydroxycholesterol-supported, inhibition of steroid synthesis by 50% at 10 μM. The results obtained by molecular docking & dynamics show a good correlation between bioactivity, docking scores and calculated binding energies of ligand-protein complexes. The best active compounds will be optimized further and used to develop potential drugs to control excessive steroid formation.     

Discovery of new MurA inhibitors using induced-fit simulation and docking

We report on the successful application of ProBiS-CHARMMing web server in the discovery of new inhibitors of MurA, an enzyme that catalyzes the first committed cytoplasmic step of bacterial peptidoglycan synthesis. The available crystal structures of Escherichia coli MurA in the Protein Data Bank have binding sites whose small volume does not permit the docking of drug-like molecules. To prepare the binding site for docking, the ProBiS-CHARMMing web server was used to simulate the induced-fit effect upon ligand binding to MurA, resulting in a larger, more holo-like binding site. The docking of a filtered ZINC compound library to this enlarged binding site was then performed and resulted in three compounds with promising inhibitory potencies against MurA. Compound 1 displayed significant inhibitory potency with IC₅₀ value of 1 μM. All three compounds have novel chemical structures, which could be used for further optimization of small-molecule MurA inhibitors.     

Exploring docking methods for virtual screening: application to the identification of neuraminidase and Ftsz potential inhibitors

Virtual screenings based on molecular docking play a major role in medicinal chemistry for the identification of new bioactive molecules. For this purpose, several docking methods can be used. Here, using Arguslab as software and a Gold Platinum subset library of commercially available compounds from Asinex, two docking methods associated to the scoring function Ascore were employed to investigate virtual screenings. One method is based on a genetic algorithm and the other based on a shape-based method. As case studies, both docking techniques were explored by targeting the PC190723 binding site of FtsZ protein from Staphylococcus aureus and the active site of N8 neuraminidase from Influenza virus. Following four docking sequences for each docking engine, the genetic algorithm led to multiple docking results, whereas the shape-based method gave reproducible results. The present study shows that the stochastic nature of the genetic algorithm will require the biological evaluation of more compounds than the shape-based method. This study showed that both methods are complementary and also led to the identification of neuraminidase and FtsZ potential inhibitors.     

New inhibitors of VEGFR-2 targeting the extracellular domain dimerization process

We are reporting the discovery of small molecule inhibitors for vascular endothelial growth factor receptor type 2 (VEGFR-2) extracellular domain. The VEGFR-2 extracellular domain is responsible for the homo-dimerization process, which has been recently reported as a main step in VEGFR signal transduction cascade. This cascade is essential for the vascularization and survival of most types of cancers. Two main design strategies were used; Molecular docking-based Virtual Screening and Fragment Based Design (FBD). A virtual library of drug like compounds was screened using a cascade of docking techniques in order to discover an inhibitor that binds to this new binding site. Rapid docking methodology was used first to filter the large number of compounds followed by more accurate and slow ones. Fragment based molecular design was adopted afterwards due to unsatisfactory results of screening process. Screening and design process resulted in a group of inhibitors with superior binding energies exceeding that of the natural substrate. Molecular dynamics simulation was used to test the stability of binding of these inhibitors and finally the drug ability of these compounds was assisted using Lipinski rule of five. By this way the designed compounds have shown to possess high pharmacologic potential as novel anticancer agents.     

Modeling of human M1 aminopeptidases for in silico screening of potential Plasmodium falciparum alanine aminopeptidase (PfA-M1) specific inhibitors

Plasmodium falciparum alanine M1-aminopeptidase (PfA-M1) is a validated target for anti-malarial drug development. Presence of significant similarity between PfA-M1 and human M1-aminopeptidases, particularly within regions of enzyme active site leads to problem of non-specificity and off-target binding for known aminopeptidase inhibitors. Molecular docking based in silico screening approach for off-target binding has high potential but requires 3D-structure of all human M1-aminopeptidaes. Therefore, in the present study 3D structural models of seven human M1-aminopeptidases were developed. The robustness of docking parameters and quality of predicted human M1-aminopeptidases structural models was evaluated by stereochemical analysis and docking of their respective known inhibitors. The docking scores were in agreement with the inhibitory concentrations elucidated in enzyme assays of respective inhibitor enzyme combinations (r2≈0.70). Further docking analysis of fifteen potential PfA-M1 inhibitors (virtual screening identified) showed that three compounds had less docking affinity for human M1-aminopeptidases as compared to PfA-M1. These three identified potential lead compounds can be validated with enzyme assays and used as a scaffold for designing of new compounds with increased specificity towards PfA-M1.     

Molecular docking and 3D-QSAR on 2-(oxalylamino) benzoic acid and its analogues as protein tyrosine phosphatase 1B inhibitors

In this paper, molecular docking technique was used to investigate the binding conformation of twelve 2-(oxalylamino) benzoic acid (OBA) inhibitors in the active site of PTP1B. The predicted binding affinities are linearly correlated to the experimental values (r² = 0.859). Furthermore, comparative molecular field analysis (CoMFA) was conducted based on the binding conformation predicted by molecular docking. The predicted CoMFA model has satisfactory statistical significance and good actual predicted power. The information from molecular docking and CoMFA may give us some valuable hints to the optimization of lead compounds.     

Discovery of promising FtsZ inhibitors by E-pharmacophore, 3D-QSAR,molecular docking study,and molecular dynamics simulation

Filamentous temperature-sensitive protein Z (FtsZ), playing a key role in bacterial cell division, is regarded as a promising target for the design of antimicrobial agent. This study is looking for potential high-efficiency FtsZ inhibitors. Ligand-based pharmacophore and E-pharmacophore, virtual screening and molecular docking were used to detect promising FtsZ inhibitors, and molecular dynamics simulation was used to study the stability of protein-ligand complexes in this paper. Sixty-three inhibitors from published literatures with pIC₅₀ ranging from 2.483 to 5.678 were collected to develop ligand-based pharmacophore model. 4DXD bound with 9PC was selected to develop the E-pharmacophore model. The pharmacophore models validated by test set method and decoy set were employed for virtual screening to exclude inactive compounds against ZINC database. After molecular docking, ADME analysis, IFD docking and MM-GBSA, 8 hits were identified as potent FtsZ inhibitors. A 50?ns molecular dynamics simulation was implemented on the compounds to assess the stability between potent inhibitors and FtsZ. The results indicated that the candidate compounds had a high docking score and were strongly combined with FtsZ by forming hydrogen bonding interactions with key amino acid residues, and van der Waals forces and hydrophobic interactions had significant contribution to the stability of the binding. Molecular dynamics simulation results showed that the protein-ligand compounds performed well in both the stability and flexibility of the simulation process.     

Analysis of binding modes of ligands to multiple conformations of CYP3A4

Cytochromes P450 (CYPs) are extremely versatile enzymes capable of catalyzing a vast number of compounds, and CYP3A4 is no exception metabolizing approximately half of the currently marketed drugs, besides endogenous compounds. To metabolize such a variety of compounds, CYP3A4 has to be extremely flexible, which makes interaction studies difficult. We employ a multi-conformational docking setup where conformations are generated by several molecular dynamics simulations to analyze the binding modes of various ligands, and the docking is considered successful if the ligand site of catalysis (SOC) is within 6.0 Å of the haem Fe. While docking with the X-ray structure proved unsuccessful with all ligands, the multi-conformational docking achieved successful binding of each ligand to at least one protein conformation. Analysis of the docked solutions highlights residues in the active site cavity that may have an important role in access, binding and stabilization of the ligand.     

E-pharmacophore-based virtual screening to identify GSK-3β inhibitors

Glycogen synthase kinase-3β (GSK-3β) is a serine/threonine kinase which has attracted significant attention during recent years in drug design studies. The deregulation of GSK-3β increased the loss of hippocampal neurons by triggering apoptosis-mediating production of neurofibrillary tangles and alleviates memory deficits in Alzheimer’s disease (AD). Given its role in the formation of neurofibrillary tangles leading to AD, it has been a major therapeutic target for intervention in AD, hence was targeted in the present study. Twenty crystal structures were refined to generate pharmacophore models based on energy involvement in binding co-crystal ligands. Four common e-pharmacophore models were optimized from the 20 pharmacophore models. Shape-based screening of four e-pharmacophore models against nine established small molecule databases using Phase v3.9 had resulted in 1800 compounds having similar pharmacophore features. Rigid receptor docking (RRD) was performed for 1800 compounds and 20 co-crystal ligands with GSK-3β to generate dock complexes. Interactions of the best scoring lead obtained through RRD were further studied with quantum polarized ligand docking (QPLD), induced fit docking (IFD) and molecular mechanics/generalized Born surface area. Comparing the obtained leads to 20 co-crystal ligands resulted in 18 leads among them, lead1 had the lowest docking score, lower binding free energy and better binding orientation toward GSK-3β. The 50?ns MD simulations run confirmed the stable nature of GSK-3β-lead1 docking complex. The results from RRD, QPLD, IFD and MD simulations confirmed that lead1 might be used as a potent antagonist for GSK-3β.