Prediction of estrogen receptor β ligands potency and selectivity by docking and MM-GBSA scoring methods using three different scaffolds

This study aimed to identify the docking and molecular mechanics-generalized born surface area (MM-GBSA) re-scoring parameters which can correlate the binding affinity and selectivity of the ligands towards oestrogen receptor β (ERβ). Three different series of ERβ ligands were used as dataset and the compounds were docked against ERβ (protein data bank (PDB) ID: 1QKM) using Glide and ArgusLab. Glide docking showed superior results when compared with ArgusLab. Docked poses were then rescored using Prime-MM-GBSA to calculate free energy binding. Correlations were made between observed activities of ERβ ligands with computationally predicted values from docking, binding energy parameters. ERβ ligands experimental binding affinity/selectivity did not correlate well with Glide and ArgusLab score. Whereas calculated Glide energy (coulomb-van der Waal interaction energy) correlated significantly with binding affinity of ERβ ligands (r²?=?0.66). MM-GBSA re-scoring showed correlation of r²?=?0.74 with selectivity of ERβ ligands. These results will aid the discovery of novel ERβ ligands with isoform selectivity.     

Efficient docking of peptides to proteins without prior knowledge of the binding site

Reliability in docking of ligand molecules to proteins or other targets is an important challenge for molecular modeling. Applications of the docking technique include not only prediction of the binding mode of novel drugs, but also other problems like the study of protein-protein interactions. Here we present a study on the reliability of the results obtained with the popular AutoDock program. We have performed systematical studies to test the ability of AutoDock to reproduce eight different protein/ligand complexes for which the structure was known, without prior knowledge of the binding site. More specifically, we look at factors influencing the accuracy of the final structure, such as the number of torsional degrees of freedom in the ligand. We conclude that the Autodock program package is able to select the correct complexes based on the energy without prior knowledge of the binding site. We named this application blind docking, as the docking algorithm is not able to "see" the binding site but can still find it. The success of blind docking represents an important finding in the era of structural genomics.     

In silico investigation of ACE2 and the main protease of SARS-CoV-2 with phytochemicals from Myristica fragrans (Houtt.) for the discovery of a novel COVID-19 drug

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19), is a new coronavirus strain that was first reported in December 2019 in Wuhan, China. A specific treatment for COVID-19 has yet to be identified. Potential therapeutic targets include SARS-CoV-2 main protease (Mpro) and the SARS-CoV-2 spike-ACE2 interaction. Molecular docking, molecular dynamics (MD), solvent screening for the extraction of the specified compounds, and prediction of the drug properties of certain molecules were the methods used in this study to investigate compounds from the medicinal plant Myristica fragrans, which is one of twelve herbs in Prasachandaeng remedy (PSD). ArgusLab, AutoDock Vina, and AutoDock were used to perform docking tasks. The examined ligands were compared with panduratin A as a standard (Kanjanasirirat et al., 2020), which is a promising medicinal plant molecule for the treatment of COVID-19. Molecular docking revealed that malabaricones B and C and licarins A, B and C bound to SARS-CoV-2/ACE2 and SARS-CoV-2 Mpro with low binding energies compared to that of the standard ligand. Furthermore, appropriate solvent usage is important. Acetone was selected by COSMOquick software for compound extraction in this investigation because it can extract large amounts of all five of the abovementioned M. fragrans compounds. Furthermore, the drug-like properties of these compounds were studied utilizing the Lipinski, Veber, and Ghose criteria. The results revealed that these M. fragrans compounds have potential as effective medicines to combat the COVID-19 pandemic. However, to assess the therapeutic potential of these ligands, additional research is needed, which will use our findings as a foundation.     

Molecular docking analysis of known flavonoids as duel COX-2 inhibitors in the context of cancer

Cyclooxygenase-2 (COX-2) catalyzed synthesis of prostaglandin E2 and it associates with tumor growth, infiltration, and metastasis in preclinical experiments. Known inhibitors against COX-2 exhibit toxicity. Therefore, it is of interest to screen natural compounds like flavanoids against COX-2. Molecular docking using 12 known flavanoids against COX-2 by FlexX and of ArgusLab were performed. All compounds showed a favourable binding energy of >-10 KJ/mol in FlexX and > -8 kcal/mol in ArgusLab. However, this data requires in vitro and in vivo verification for further consideration.     

Viper venom hyaluronidase and its potential inhibitor analysis: a multipronged computational investigation

Viper venom hyaluronidase (VV-HYA) inhibitors have long been used as therapeutic agents for arresting the local and systemic effects caused during its envenomation. Henceforth, to understand its structural features and also to identify the best potential inhibitor against it the present computational study was undertaken. Structure-based homology modeling of VV-HYA followed by its docking and free energy-based ranking analysis of ligand, the MD simulations of the lead complex was also performed. The sequence analysis and homology modeling of VV-HYA revealed a distorted (β/α)₈ folding as in the case of hydrolases family of proteins. Molecular docking of the resultant 3D structure of VV-HYA with known inhibitors (compounds 1–25) revealed the importance of molecular recognition of hotspot residues (Tyr 75, Arg 288, and Trp 321) other than that of the active site residues. It also revealed that Trp 321 of VV-HYA is highly important for mediating π–π interactions with ligands. In addition, the molecular docking and comparative free energy binding analysis was investigated for the VV-HYA inhibitors (compounds 1–25). Both molecular docking and relative free energy binding analysis clearly confirmed the identification of sodium chromoglycate (compound 1) as the best potential inhibitor against VV-HYA. Molecular dynamics simulations additionally confirmed the stability of their binding interactions. Further, the information obtained from this work is believed to serve as an impetus for future rational designing of new novel VV-HYA inhibitors with improved activity and selectivity.     

Elucidating the molecular interaction of sinigrin,a potent anticancer glucosinolate from cruciferous vegetables with bovine serum albumin: effect of methylglyoxal modification

The present study employed the spectroscopic techniques, i.e. fluorescence, and circular dichroism (CD) and the molecular docking approach to investigate the mechanism of interaction of a potent anticancer glucosinolate, sinigrin (SIN), with bovine serum albumin (BSA). SIN binding to BSA resulted in the quenching of intrinsic fluorescence, and the analysis of results revealed the presence of static quenching mechanism. Based on the results, it was evident that the interaction of SIN with BSA was mainly stabilized by hydrogen bonding. Results from CD analysis revealed that the binding of SIN does not induce significant conformational changes in BSA. Molecular docking studies showed that four hydrogen bonds stabilize the binding of SIN in the site I of BSA with a binding energy of ?6.2 kcal mol^?1. These findings will not only provide insights about the mechanism of interaction of sinigrin but also showed the effect of methylglyoxal-mediated glycation on ligand binding with BSA.     

Molecular interaction between 4-aminoantipyrine and catalase reveals a potentially toxic mechanism of the drug

4-Aminoantipyrine (AAP) is scarcely administered as an analgesic drug because of the potential side effects. The residue of AAP in the environment possesses a potential threat to human health. In this article, the binding mode of AAP with the important antioxidant enzyme catalase (CAT) was investigated using spectroscopic and molecular docking methods. AAP can interact with CAT to form an AAP-CAT complex. The binding constant, number of binding sites and thermodynamic parameters were measured, which indicated that AAP could spontaneously bind with CAT through electrostatic forces with one binding site. Molecular docking results revealed that AAP bound into the CAT central cavity. UV-visible absorption, synchronous fluorescence and circular dichroism (CD) results provide data concerning conformational and some microenvironmental changes of CAT. Furthermore, the binding of AAP can inhibit CAT activity in erythrocytes. The present study provides direct evidence at a molecular level to show that exposure to AAP could induce changes in the enzyme CAT structure and function. The estimated methods in this work can be applied to characterize interactions of enzyme systems and other pollutants and drugs.     

Atomic insight into designed carbamate-based derivatives as acetylcholine esterase (AChE) inhibitors: a computational study by multiple molecular docking and molecular dynamics simulation

Over 100 variants have been designed and studied, using multiple docking methods such as Autodock Vina, ArgusLab, Molegro Virtual Docker, and Hex-Cuda, to study the effect of alteration in the structure of carbamate-based acetylcholyne esterase (AChE) inhibitors. Sixteen selected systems were then subjected to 14 ns molecular dynamics (MD) simulations. Results from all the docking methods are in agreement. Variants that involved biphenyl substituents possess the most negative binding energies in the ?37.64 to ?39.31 kJ mol^?1 range due to their π–π interactions with AChE aromatic residues. The root mean square deviation values showed that all of these components achieved equilibration after 6 ns. Gyration radius (R_g) and solvent accessibility surface area were calculated to further investigate the AChE conformational changes in the presence of these components. MD simulation results suggested that these components might interact with AChE, possibly with no major changes in AChE secondary and tertiary structures.     

FitDockApp：基于模板的分子对接PyMOL插件图形化计算软件

目的 分子对接在预测分子之间的结合模式和亲和力方面起着至关重要的作用,是计算结构生物学和计算机辅助药物设计研究的重要方法。本研究团队近期开发了一款基于模板的新型对接方法FitDock,当存在近似的蛋白质配体模板时,它在准确性和速度方面都超过了业界常用的分子对接方法。为了增强FitDock方法的可用性,使其在分子模拟领域得到更广泛的应用,很有必要发展图像化的软件工具。方法 基于Python图像化编程,本文开发了FitDockApp,这是分子可视化软件PyMOL的插件软件。结果 FitDockApp能够通过操作窗口界面,实现基于模板的分子对接和配体结构比对,实时显示预测三维结构,并提供将对接文件上传到实验室服务器获取最优模板的便利。此外,FitDockApp还具备批量对接功能。结论 FitDockApp通过用户友好的界面简化了对接过程,并提供丰富的功能,帮助研究人员获得精确的对接结果。FitDockApp是一款免费软件,兼容Windows和Linux系统,可在http://cao.labshare.cn/fitdock/下载。     

Combining Machine Learning Systems and Multiple Docking Simulation Packages to Improve Docking Prediction Reliability for Network Pharmacology

Increased availability of bioinformatics resources is creating opportunities for the application of network pharmacology to predict drug effects and toxicity resulting from multi-target interactions. Here we present a high-precision computational prediction approach that combines two elaborately built machine learning systems and multiple molecular docking tools to assess binding potentials of a test compound against proteins involved in a complex molecular network. One of the two machine learning systems is a re-scoring function to evaluate binding modes generated by docking tools. The second is a binding mode selection function to identify the most predictive binding mode. Results from a series of benchmark validations and a case study show that this approach surpasses the prediction reliability of other techniques and that it also identifies either primary or off-targets of kinase inhibitors. Integrating this approach with molecular network maps makes it possible to address drug safety issues by comprehensively investigating network-dependent effects of a drug or drug candidate.     

Improved Ligand-Protein Binding Affinity Predictions Using Multiple Binding Modes

Accurate ligand-protein binding affinity prediction, for a set of similar binders, is a major challenge in the lead optimization stage in drug development. In general, docking and scoring functions perform unsatisfactorily in this application. Docking calculations, followed by molecular dynamics simulations and free energy calculations can be applied to improve the predictions. However, for targets with large, flexible binding sites, with no experimentally determined binding modes for a set of ligands, insufficient sampling can decrease the accuracy of the free energy calculations. Cytochrome P450s, a protein family of major importance for drug metabolism, is an example of a challenging target for binding affinity predictions. As a result, the choice of starting structure from the docking solutions becomes crucial. In this study, an iterative scheme is introduced that includes multiple independent molecular dynamics simulations to obtain weighted ensemble averages to be used in the linear interaction energy method. The proposed scheme makes the initial pose selection less crucial for further simulation, as it automatically calculates the relative weights of the various poses. It also properly takes into account the possibility that multiple binding modes contribute similarly to the overall affinity, or of similar compounds occupying very different poses. The method was applied to a set of 12 compounds binding to cytochrome P450 2C9 and it displayed a root mean-square error of 2.9 kJ/mol.     

Spectroscopic,electrochemical, docking and molecular dynamics studies on the interaction of three oxovanadium (IV) Schiff base complexes with bovine serum albumin and their cytotoxicity against cancer

This study was designed to investigate the interaction of three oxovanadium (IV) Schiff base complexes with bovine serum albumin (BSA) by means of various spectroscopic and electrochemical methods along with molecular docking study and molecular dynamics simulations. Binding constants were estimated by fluorescence and UV-Vis spectroscopy. The results indicated a good affinity of the complexes for BSA in which furyl derivative had more activity. Molecular docking study showed that these complexes have the similar binding modes and located within subdomain IB in site III of BSA. The supporting of molecular docking and molecular dynamics results by experimental data, confirms the validity of the interactions data obtained by these methods. Biological activity against cancer cell showed that furyl derivative has higher activity than other complexes. Pharmaceutical analysis also showed that, these complexes potentially can be used as anticancer agents.     

Molecular docking study of the interactions between the thioesterase domain of human fatty acid synthase and its ligands

Human fatty acid synthase (hFAS) thioesterase domain (TE) is an attractive drug target to treat obesity and cancer. On the basis of the recently published crystal structure of TE domain of hFAS, we performed molecular surface analysis and docking study to characterize the molecular interactions between the enzyme and its various ligands. Surface analysis identified the ligand-binding pocket of TE domain that encompasses the catalytic triad of Ser2308, His2481, Asp2338. Docking of palmitate, the main biological product of hFAS, into this pocket revealed the ligand-binding mode, in which the hydrophobic interactions are the dominant driving forces. The catalytic mechanism of TE domain can also be well explained based on the generated TE-palmitate complex structure. Moreover, the comparison of the binding modes of five fatty acids with chain lengths ranging from 12 to 20 carbons confirmed that the ligand binding pocket of TE domain is a decisive factor in chain length specificity. In addition, docking of two known TE inhibitors, c75 and orlistat revealed the pharmacophore of these hFAS TE inhibitors, which will prove useful in structure-based drug design against this important target.     

Identification of novel, less toxic PTP-LAR inhibitors using in silico strategies: pharmacophore modeling, SADMET-based virtual screening and docking

Human leukocyte antigen-related (PTP-LAR) is a receptor-like transmembrane phosphatase and a potential target for diabetes, obesity and cancer. In the present study, a sequence of in silico strategies (pharmacophore mapping, a 3D database searching, SADMET screening, and docking and toxicity studies) was performed to identify eight novel nontoxic PTP-LAR inhibitors. Twenty different pharmacophore hypotheses were generated using two methods; the best (hypothesis 2) consisted of three hydrogen-bond acceptor (A), one ring aromatic (R), and one hydrophobic aliphatic (Z) features. This hypothesis was used to screen molecules from several databases, such as Specs, IBS, MiniMaybridge, NCI, and an in-house PTP inhibitor database. In order to overcome the general bioavailability problem associated with phosphatases, the hits obtained were filtered by Lipinski’s rule of five and SADMET properties and validated by molecular docking studies using the available crystal structure 1LAR. These docking studies suggested the ligand binding pattern and interactions required for LAR inhibition. The docking analysis also revealed that sulfonylurea derivatives with an isoquinoline or naphthalene scaffold represent potential LAR drugs. The screening protocol was further validated using ligand pharmacophore mapping studies, which showed that the abovementioned interactions are indeed crucial and that the screened molecules can be presumed to possess potent inhibitory activities.     

Spermine as a porcine pancreatic elastase activator: spectroscopic and molecular simulation studies

Abstract

The aim of this study was to investigate the spermine effect on the thermal denaturation, conformation and activity of elastase at three temperatures of 303, 313 and 323?K in the Tris buffer, at pH 8.5, using UV–vis spectrophotometry, spectrofluorometry and circular dichroism as well as molecular docking and molecular simulation. The increased absorption of elastase in the presence of spermine suggested a change in the environment of tryptophan. It was found that under the influence of spermine, the emission intensity of elastase extremely was reduced, and the use of the Stern-Volmer equation showed that some static quenching had occurred. The thermodynamic parameters values (enthalpy and entropy) and the molecular docking technique also revealed that van der Waals forces or hydrogen bonding interactions played an important role in the binding process. The spermine–elastase complex formation led to increasing the value of the catalytic constant (k_cat). So it could be considered as an activator. Slight changes were observed in the second structure of elastase (1.06% increase for the α-helix and 0.048% decrease the β-sheet) and the thermal stability effect. Molecular docking results also demonstrated that spermine could bind to porcine pancreatic elastase, and van der Waals forces or hydrogen bonding interactions played the major role in the binding process. Overall, our results showed that spermine could induce structural alterations in elastase, acting as a partial stabilizer and an activator for the enzyme.

Communicated by Ramaswamy H. Sarma     

SOFTDOCK application to protein-protein interaction benchmark and CAPRI

The success of molecular docking requires cooperation of sampling and scoring of various conformations. The SOFTDOCK package uses a coarse-grained docking method to sample all possible conformations of complexes. SOFTDOCK uses a new Voronoi molecular surface and calculates several grid-based scores. It is shown by the leave-one-out test that three geometry scores and an FTDOCK-like electrostatics score contribute the most to the discrimination of near-native conformations. However, an atom-based solvation score is shown to be ineffective. It is also found that an increased Voronoi surface thickness greatly increases the accuracy of docking results. Finally, the clustering procedure is shown to improve the overall ranking, but leads to less accurate docking results. The application of SOFTDOCK in Critical Assessment of PRedicted Interactions involves four steps: (i) sampling with INTELEF; (ii) clustering; (iii) AMBER energy minimization; and (iv) manual inspection. Biological information from literature is used as filters in some of the sampling and manual inspection according to different targets. Two of our submissions have L_rmsd around 10 A. Although they are not classified as acceptable solutions, they are considered successful because they are comparable to the accuracy of our method. Availability: SOFTDOCK is open source code and can be downloaded at http://bio.iphy.ac.cn     

Docking and DFT studies on ligand binding to Quercetin 2,3-dioxygenase

Simple molecular docking calculations on quercetin, kojic acid and diethylcarbamatodithoic acid using the software package MOE are shown to be close to the geometries reported in the X-ray crystal structures of the protein co-crystallized with the respective ligands. Furthermore, DFT optimization of the docked conformations is shown to reproduce the essential features of previous studies on quercetin, showing that docking can be used to provide good starting structures for mechanistic study. The flavone ligand, lacking the hydroxyl group of the quercetin is shown by docking to be unable to approach closely the copper atom, indicating the necessity of the presence of the hydroxyl group and providing a prediction of the likely binding environment of this ligand.     

Progress in molecular docking

Background: In recent years, since the molecular docking technique can greatly improve the efficiency and reduce the research cost, it has become a key tool in computer-assisted drug design to predict the binding affinity and analyze the interactive mode. Results: This study introduces the key principles, procedures and the widely-used applications for molecular docking. Also, it compares the commonly used docking applications and recommends which research areas are suitable for them. Lastly, it briefly reviews the latest progress in molecular docking such as the integrated method and deep learning. Conclusion: Limited to the incomplete molecular structure and the shortcomings of the scoring function, current docking applications are not accurate enough to predict the binding affinity. However, we could improve the current molecular docking technique by integrating the big biological data into scoring function.     

Insights into structure and function of SHIP2-SH2: homology modeling, docking, and molecular dynamics study

SRC homology 2 (SH2)-containing inositol 5′-phosphatase protein (SHIP2) is a potential target for type 2 diabetes. Its ability to dephosphorylate the lipid messenger phosphatidylinositol 3,4,5-trisphosphate [PtdIns(3,4,5)P3], important for insulin signaling, makes it an important target against type 2 diabetes. The insulin-induced SHIP2 interaction with Shc is very important for the membrane localization and functioning of SHIP2. There is a bidentate relationship between the two proteins where two domains each from SHIP2 and Shc are involved in mutual binding. However in the present study, the SHIP2-SH2 domain binding with the phosphorylated tyrosine 317 on the collagen-homology (CH) domain of Shc, has been studied due to the indispensability of this interaction in SHIP2 localization. In the absence of the crystal structure of SHIP2-SH2, its structural model was developed followed by tracking its molecular interactions with Shc through molecular docking and dynamics studies. This study revealed much about the structural interactions between the SHIP2-SH2 and Shc-CH. Finally, docking study of a nonpeptide inhibitor into the SHIP2-SH2 domain further confirmed the structural interactions involved in ligand binding and also proposed the inhibitor as a major starting point against SHIP2-SH2 inhibition. The insights gained from the current study should prove useful in the design of more potent inhibitors against type 2 diabetes.     

Studying the roles of W86, E202, and Y337 in binding of acetylcholine to acetylcholinesterase using a combined molecular dynamics and multiple docking approach

A combined molecular dynamics simulation and multiple ligand docking approach is applied to study the roles of the anionic subsite residues (W86, E202, Y337) in the binding of acetylcholine (ACh) to acetylcholinesterase (AChE). We find that E202 stabilizes docking of ACh via electrostatic interactions. However, we find no significant electrostatic contribution from the aromatic residues. Docking energies of ACh to mutant AChE show a more pronounced effect because of size/shape complementarity. Mutating to smaller residues results in poorer binding, both in terms of docking energy and statistical docking probability. Besides separating out electrostatics by turning off the partial charges from each residue and comparing it with the native, the mutations in this study are W86F, W86A, E202D, E202Q, E202A, Y337F, and Y337A. We also find that all perturbations result in a significant reduction in binding of extended ACh in the catalytically productive orientation. This effect is primarily caused by a small shift in preferred position of the quaternary tail.