Analysis of Ah receptor binding affinities of polybrominated diphenyl ethers via in silico molecular docking and 3D-QSAR

Polybrominated diphenyl ethers (PBDEs) have become ubiquitous contaminations due to their use as flame retardants. The structural similarity of PBDE to some dioxin-like compounds suggested that they may share similar toxicological effects: they might activate the aryl hydrocarbon receptor (AhR) signal transduction pathway and thus might have adverse effects on wildlife and humans. In this study, in silico computational workflow combining molecular docking and three-dimensional quantitative structure–activity relationship (3D-QSAR) was performed to investigate the binding interactions between PBDEs and AhR and the structural features affecting the AhR binding affinity of PBDE. The molecular docking showed that hydrogen-bond and hydrophobic interactions were the major driving forces for the binding of ligands to AhR, and several key amino acid residues were also identified. The CoMSIA model was developed from the conformations obtained from molecular docking and exhibited satisfactory results as q ² of 0.605 and r ² of 0.996. Furthermore, the derived model had good robustness and statistical significance in both internal and external validations. The 3D contour maps generated from CoMSIA provided important structural features influence the binding affinity. The obtained results were beneficial to better understand the toxicological mechanism of PBDEs.     

CoMFA 3D-QSAR Analysis of Epothilones Based on Docking Conformation and Alignment

Epothilones belong to a class of novel microtubule stabilizing and anti-mitotic agents, which have a paclitaxel-like mechanism of action. A three-dimensional quantitative structure-activity relationship （3D-QSAR） model was built for epothilones by the method of comparative molecular field analysis （CoMFA） combined with the flexible docking technology. The docking CoMFA model gave a good cross-validated value of q2=0.784 with an optimized component of 6 and the conventional correlation coefficient of r^2=0.985. The statistical results show that the model has good ability to predict the activity of the studied compounds. At last, the docking CoMFA model was analyzed through contour maps complemented with MOLCAD-generated active site potential surface in the α,β-tubulin receptor, which can provide important information for the structure-based drug design.     

Virtual screening using docking and molecular dynamics of cannabinoid analogs against CB1 and CB2 receptors

BackgroundCannabis sativa has been attributed to different pharmacological properties. A number of secondary metabolites such as tetrahydrocannabinol (THC), cannabinol (CBD), and different analogs, with highly promising biological activity on CB₁ and CB₂ receptors, have been identified.MethodsThus, this study aimed was to evaluate the activity of THC, CBD, and their analogs using molecular docking and molecular dynamics simulations (MD) methods. Initially, the molecules (ligands) were selected by bioinformatics searches in databases. Subsequently, CB₁ and CB₂ receptors were retrieved from the protein data bank database. Afterward, each receptor and its ligands were optimized to perform molecular docking. Then, MD Simulation was performed with the most stable ligand-receptor complexes. Finally, the Molecular Mechanics-Generalized Born Surface Area (MM-PBSA) method was applied to analyze the binding free energy between ligands and cannabinoid receptors.ResultsThe results obtained showed that ligand LS-61176 presented the best affinity in the molecular docking analysis. Also, this analog could be a CB₁ negative allosteric modulator like CBD and probably an agonist in CB₂ like THC and CBD according to their dynamic behavior in silico. The possibility of having a THC and a CBD analog (LS-61176) as a promising molecule for experimental evaluation since it could have no central side-effects on CB₁ and have effects of CB₂ useful in pain, inflammation, and some immunological disorders. Docking results were validate using ROC curve for both cannabinoids receptor where AUC for CB1 receptor was 0.894±0.024, and for CB2 receptor AUC was 0.832±0032, indicating good affinity prediction.     

Supercomputer docking with a large number of degrees of freedom

ABSTRACT

Docking represents one of the most popular computational approaches in drug design. It has reached popularity owing to capability of identifying correct conformations of a ligand within an active site of the target-protein and of estimating the binding affinity of a ligand that is immensely helpful in prediction of compound activity. Despite many success stories, there are challenges, in particular, handling with a large number of degrees of freedom in solving the docking problem. Here, we show that SOL-P, the docking program based on the new Tensor Train algorithm, is capable to dock successfully oligopeptides having up to 25 torsions. To make the study comparative we have performed docking of the same oligopeptides with the SOL program which uses the same force field as that utilized by SOL-P and has common features of many docking programs: the genetic algorithm of the global optimization and the grid approximation. SOL has managed to dock only one oligopeptide. Moreover, we present the results of docking with SOL-P ligands into proteins with moveable atoms. Relying on visual observations we have determined the common protein atom groups displaced after docking which seem to be crucial for successful prediction of experimental conformations of ligands.     

In silico study of porphyrin-anthraquinone hybrids as CDK2 inhibitor

Cyclin-Dependent Kinases (CDKs) are known to play crucial roles in controlling cell cycle progression of eukaryotic cell and inhibition of their activity has long been considered as potential strategy in anti-cancer drug research. In the present work, a series of porphyrin-anthraquinone hybrids bearing meso-substituents, i.e. either pyridine or pyrazole rings were designed and computationally evaluated for their Cyclin Dependent Kinase-2 (CDK2) inhibitory activity using molecular docking, molecular dynamics simulation, and binding free energy calculation. The molecular docking simulation revealed that all six porphyrin hybrids were able to bind to ATP-binding site of CDK2 and interacted with key residues constituted the active cavity of CDK2, while molecular dynamics simulation indicated that all porphyrins bound to CDK2 were stable for 6 ns. The binding free energies predicted by MM-PBSA method showed that most compounds exhibited higher affinity than that of native ligand (4-anilinoquinazoline, DTQ) and the affinity of mono-H₂PyP-AQ was about three times better than that of DTQ, indicating its potential to be advanced as a new CDK2 inhibitor.     

Metadynamics Simulations Rationalise the Conformational Effects Induced by N‐Methylation of RGD Cyclic Hexapeptides

We combined metadynamics, docking and molecular mechanics/generalised born surface area (MM/GBSA) re‐scoring methods to investigate the impact of single and multiple N‐methylation on a set of RGD cyclopeptides displaying different affinity for integrin αIIbβ3. We rationalised the conformational effects induced by N‐methylation and its interplay with receptor affinity, obtaining good agreement with experimental data. This approach can be exploited before entering time‐consuming and expensive synthesis and binding experiments.     

Multiple ligand simultaneous docking: Orchestrated dancing of ligands in binding sites of protein

Present docking methodologies simulate only one single ligand at a time during docking process. In reality, the molecular recognition process always involves multiple molecular species. Typical protein–ligand interactions are, for example, substrate and cofactor in catalytic cycle; metal ion coordination together with ligand(s); and ligand binding with water molecules. To simulate the real molecular binding processes, we propose a novel multiple ligand simultaneous docking (MLSD) strategy, which can deal with all the above processes, vastly improving docking sampling and binding free energy scoring. The work also compares two search strategies: Lamarckian genetic algorithm and particle swarm optimization, which have respective advantages depending on the specific systems. The methodology proves robust through systematic testing against several diverse model systems: E. coli purine nucleoside phosphorylase (PNP) complex with two substrates, SHP2NSH2 complex with two peptides and Bcl‐xL complex with ABT‐737 fragments. In all cases, the final correct docking poses and relative binding free energies were obtained. In PNP case, the simulations also capture the binding intermediates and reveal the binding dynamics during the recognition processes, which are consistent with the proposed enzymatic mechanism. In the other two cases, conventional single‐ligand docking fails due to energetic and dynamic coupling among ligands, whereas MLSD results in the correct binding modes. These three cases also represent potential applications in the areas of exploring enzymatic mechanism, interpreting noisy X‐ray crystallographic maps, and aiding fragment‐based drug design, respectively. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Synthesis,Molecular Docking and Potential Antioxidant Activity of Di/Trisubstituted Pyridazinone Derivatives

A number of pyridazinone derivatives bearing substituted benzylidene and heterocyclic/aromatic rings at 4^th and 6^th positions, respectively were synthesized in good to moderate yields and screened for antioxidant activity. Antioxidant activity of pyridazinone derivatives was evaluated by using several in vitro radical scavenging methods such as 1,1‐diphenylpicrylhydrazyl (DPPH), hydrogen peroxide (H₂O₂), nitric oxide (NO), reducing power, and metal chelating assay etc. Molegro virtual docker software was used to study the binding affinity of the title compounds with the xanthine oxidoreductase enzyme. Amongst the tested compounds, 5a, 5d, 5g & 5j were found to exhibit excellent antioxidant activity at par with the positive control, ascorbic acid. The molecular docking studies of these compounds demonstrated a good selectivity profile with xanthine oxidoreductase receptors. A preliminary study of the structural‐activity relationship showed that the presence of electron withdrawing group and heterocyclic ring on pyridazinone nucleus are associated with the best potency and selectivity profile. It could be proposed that xanthine oxidoreductase receptor may be involved in observed antioxidant activity of pyridazinone derivatives bearing aromatic ring and benzylidene substituents and thus the synthesized compounds are worthy of further exploration.     

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.     

禽流感病毒HA蛋白与人受体的分子对接

血凝素(hemagglutinin,HA)是位于禽流感病毒表面的糖蛋白。在病毒感染过程中,HA与禽类宿主细胞表面受体结合,介导病毒膜与宿主核内体膜的融合,在传染过程中发挥关键作用。自然界中的禽流感病毒处于不断演化之中,其HA的禽受体结合位点常常发生氨基酸变异。因此,当HA变异体与人受体结合能力较强时,禽流感病毒往往会发生跨种传播而感染人。为预防禽流感的跨种传播,人们迫切需要发展大规模快速检测或预测HA变异体与人受体结合亲和力的方法,以评估各种新发禽流感病毒的跨种传播能力,提前筛选出有潜在危险的病毒株。针对此问题,本研究以H7N9亚型的HA蛋白H7为研究对象,发展了一种运用分子对接的计算方法,预测HA变异体与人受体的结合亲和力。该方法的计算结果表明,H7与人受体的结合亲和力普遍弱于有较强传染人能力的H1,说明H7N9亚型病毒的跨种传播能力普遍较弱;但是,计算分析也揭示,部分新发的H7N9毒株的HA有强的人受体结合亲和力,提示在自然演化过程中,H7N9病毒有可能演化出具有较强的感染人能力的新毒株,这与2013年禽流感疫情的实际发生情况相一致。因此,本文所发展的计算方法可用于快速预测新发禽流感病毒HA与人受体的结合亲和力,为新发禽流感病毒的跨种传播风险评估提供理论依据。     

From Shape Similarity to Shape Complementarity: Toward a Docking Theory

Formal relations between similarity and docking are analyzed, and a general docking theory is proposed for colored mixtures of multivariate distributions. X and Y being two colored mixtures with given marginal distributions, their shape complementarity coefficient is defined as the lower bound of the variance of (X–Y)· (X-Y), taken over the set of joint distributions of X and Y. The docking is performed via minimization of the shape complementarity coefficient for all translations and rotations of the mixtures. The properties of the docking criterion are derived, and are shown to satisfy the practical requirements encountered in molecular shape analysis.     

The MM2QM tool for combining docking,molecular dynamics,molecular mechanics,and quantum mechanics†

The use of the MM2QM tool in a combined docking + molecular dynamics (MD) + molecular mechanics (MM) + quantum mechanical (QM) binding affinity prediction study is presented, and the tool itself is discussed. The system of interest is Mycobacterium tuberculosis (MTB) pantothenate synthetase in complexes with three highly similar sulfonamide inhibitors, for which crystal structures are available. Starting from the structure of MTB pantothenate synthetase in the “open” conformation and following the combined docking + MD + MM + QM procedure, we were able to capture the closing of the enzyme binding pocket and to reproduce the position of the ligands with an average root mean square deviation of 1.6 Å. Protein–ligand interaction energies were reproduced with an average error lower than 10%. The discussion on the MD part and a protein flexibility importance is carried out. The presented approach may be useful especially for finding analog inhibitors or improving drug candidates. © 2012 Wiley Periodicals, Inc.     

GAMPMS: Genetic algorithm managed peptide mutant screening

The prominence of endogenous peptide ligands targeted to receptors makes peptides with the desired binding activity good molecular scaffolds for drug development. Minor modifications to a peptide's primary sequence can significantly alter its binding properties with a receptor, and screening collections of peptide mutants is a useful technique for probing the receptor–ligand binding domain. Unfortunately, the combinatorial growth of such collections can limit the number of mutations which can be explored using structure‐based molecular docking techniques. Genetic algorithm managed peptide mutant screening (GAMPMS) uses a genetic algorithm to conduct a heuristic search of the peptide's mutation space for peptides with optimal binding activity, significantly reducing the computational requirements of the virtual screening. The GAMPMS procedure was implemented and used to explore the binding domain of the nicotinic acetylcholine receptor (nAChR) ‐isoform with a library of 64,000 α‐conotoxin (α‐CTx) MII peptide mutants. To assess GAMPMS's performance, it was compared with a virtual screening procedure that used AutoDock to predict the binding affinity of each of the α‐CTx MII peptide mutants with the ‐nAChR. The GAMPMS implementation performed AutoDock simulations for as few as 1140 of the 64,000 α‐CTx MII peptide mutants and could consistently identify a set of 10 peptides with an aggregated binding energy that was at least 98% of the aggregated binding energy of the 10 top peptides from the exhaustive AutoDock screening. © 2015 Wiley Periodicals, Inc.     

Discovery of the potential neuraminidase inhibitors from Polygonum cuspidatum by ultrafiltration combined with mass spectrometry guided by molecular docking

Neuraminidase is an important target in the treatment of the influenza A virus. Screening natural neuraminidase inhibitors from medicinal plants is crucial for drug research. This study proposed a rapid strategy for identifying neuraminidase inhibitors from different crude extracts (Polygonum cuspidatum, Cortex Fraxini, and Herba Siegesbeckiae) using ultrafiltration combined with mass spectrometry guided by molecular docking. Firstly, the main component library of the three herbs was established, followed by molecular docking between the components and neuraminidase. Only the crude extracts with numbers of potential neuraminidase inhibitors identified by molecular docking were selected for ultrafiltration. This guided approach reduced experimental blindness and improved efficiency. The results of molecular docking indicated that the compounds in Polygonum cuspidatum demonstrated good binding affinity with neuraminidase. Subsequently, ultrafiltration-mass spectrometry was employed to screen for neuraminidase inhibitors in Polygonum cuspidatum. A total of five compounds were fished out, and they were identified as trans-polydatin, cis-polydatin, emodin-1-O-β-D-glucoside, emodin-8-O-β-D-glucoside, and emodin. The enzyme inhibitory assay showed that they all had neuraminidase inhibitory effects. In addition, the key residues of the interaction between neuraminidase and fished compounds were predicted. In all, this study could provide a strategy for the rapid screening of the potential enzyme inhibitors from medicinal herbs.     

Computational design of novel cyclic urea as HIV-1 protease inhibitor

A series of novel cyclic urea molecules 5,6-dihydroxy-1,3-diazepane-2,4,7-trione as HIV-1 protease inhibitors were designed using computational techniques. The designed molecules were compared with the known cyclic urea molecules by performing docking studies, calculating their ADME (Absorption, Distribution, Metabolism, and Excretion) properties and protein ligand interaction energy. These novel molecules were designed by substituting the P ₁/P′ ₁ positions (4 ^th and 7 ^th position of 1, 3-diazepan-2-one) with double bonded oxygens. This reduces the molecular weight and increases the bioavailability, indicating better ADME properties. The docking studies showed good binding affinity towards HIV-1 protease. The biological activity of these inhibitors were predicted by a model equation generated by the regression analysis between biological activity (log 1/K ⁱ ) of known inhibitors and their protein ligand interaction energy. The synthetic studies are in progress.      

Binding mode of inhibitors and Cryptosporidium parvum IMP dehydrogenase: A combined ligand- and receptor-based study

A combined ligand- and target-based approach was used to analyse the interaction models of Cryptosporidium parvum inosine 5’-monophosphate dehydrogenase (CpIMPDH) with selective inhibitors. First, a ligand-based pharmacophore model was generated from 20 NAD⁺ competitive CpIMPDH inhibitors with the HipHop module. The characteristic of the NAD⁺ binding site of CpIMPDH was then described, and the binding modes of the representative inhibitors were studied by molecular docking. The combination of the pharmacophore model and the docking results allowed us to evaluate the pharmacophore features and structural information of the NAD⁺ binding site of CpIMPDH. This research supports the proposal of an interaction model inside the NAD⁺ binding site of CpIMPDH, consisting of four key interaction points: two hydrophobic-aromatic groups, a hydrophobic-aliphatic group and a hydrogen bond donor. This study also provides guidance for the design of more potent CpIMPDH inhibitors for the treatment of Cryptosporidium infections.     

Assessment of programs for ligand binding affinity prediction

The prediction of the binding free energy between a ligand and a protein is an important component in the virtual screening and lead optimization of ligands for drug discovery. To determine the quality of current binding free energy estimation programs, we examined FlexX, X-Score, AutoDock, and BLEEP for their performance in binding free energy prediction in various situations including cocrystallized complex structures, cross docking of ligands to their non-cocrystallized receptors, docking of thermally unfolded receptor decoys to their ligands, and complex structures with "randomized" ligand decoys. In no case was there a satisfactory correlation between the experimental and estimated binding free energies over all the datasets tested. Meanwhile, a strong correlation between ligand molecular weight-binding affinity correlation and experimental predicted binding affinity correlation was found. Sometimes the programs also correctly ranked ligands' binding affinities even though native interactions between the ligands and their receptors were essentially lost because of receptor deformation or ligand randomization, and the programs could not decisively discriminate randomized ligand decoys from their native ligands; this suggested that the tested programs miss important components for the accurate capture of specific ligand binding interactions.     

Evaluation of the performance of four molecular docking programs on a diverse set of protein‐ligand complexes

Many molecular docking programs are available nowadays, and thus it is of great practical value to evaluate and compare their performance. We have conducted an extensive evaluation of four popular commercial molecular docking programs, including Glide, GOLD, LigandFit, and Surflex. Our test set consists of 195 protein‐ligand complexes with high‐resolution crystal structures (resolution ≤2.5 Å) and reliable binding data [dissociation constant (K_d) or inhibition constant (K_i)], which are selected from the PDBbind database with an emphasis on diversity. The top‐ranked solutions produced by these programs are compared to the native ligand binding poses observed in crystal structures. Glide and GOLD demonstrate better accuracy than the other two on the entire test set. Their results are also less sensitive to the starting structures for docking. Comparison of the results produced by these programs at three different computation levels reveal that their accuracy are not always proportional to CPU cost as one may expect. The binding scores of the top‐ranked solutions produced by these programs are in low to moderate correlations with experimentally measured binding data. Further analyses on the outcomes of these programs on three suites of subsets of protein‐ligand complexes indicate that these programs are less capable to handle really flexible ligands and relatively flat binding sites, and they have different preferences to hydrophilic/hydrophobic binding sites. Our evaluation can help other researchers to make reasonable choices among available molecular docking programs. It is also valuable for program developers to improve their methods further. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010