Characterization of binding site of closed-state KCNQ1 potassium channel by homology modeling, molecular docking, and pharmacophore identification

This investigation was performed to assess the importance of interaction in the binding of blockers to KCNQ1 potassium using molecular modeling. This work could be considered made up by three main steps: (1) the construction of closed-state structure of KCNQ1 through homology modeling; (2) the automated docking of three blockers: IKS-142, L-735821, and BMS-IKS, using DOCK program; (3) the generation and validation of pharmacophore for KCNQ1 ligands using Catalyst/HypoGen. The obtained results highlight the hydrophobic or aromatic residues involved in S6 transmembrane domain and the base of the pore helix of KCNQ1, confirming the mutagenesis data and pharmacophore model, and giving new suggestions for the rational design of novel KCNQ1 ligands.     

Binding site analysis of full-length alpha1a adrenergic receptor using homology modeling and molecular docking

The recent availability of crystal structure of bovine rhodopsin offers new opportunities in order to approach the construction of G protein coupled receptors. This study focuses the attention on the modeling of full-length alpha(1a) adrenergic receptor (alpha(1a)-AR) due to its biological role and significant implications in pharmacological treatment of benign prostate hyperplasia. This work could be considered made up by two main steps: (a) the construction of full structure of alpha(1a)-AR, through homology modeling methods; (b) the automated docking of an endogenous agonist, norepinephrine, and of an antagonist, WB-4101, using BioDock program. The obtained results highlight the key residues involved in binding sites of both agonists and antagonists, confirming the mutagenesis data and giving new suggestions for the rational design of selective ligands.     

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。     

GEMDOCK: a generic evolutionary method for molecular docking

We have developed an evolutionary approach for flexible ligand docking. This approval, GEMDOCK, uses a Generic Evolutionary Method for molecular DOCKing and an empirical scoring function. The former combines both discrete and continuous global search strategies with local search strategies to speed up convergence, whereas the latter results in rapid recognition of potential ligands. GEMDOCK was tested on a diverse data set of 100 protein-ligand complexes from the Protein Data Bank. In 79% of these complexes, the docked lowest energy ligand structures had root-mean-square derivations (RMSDs) below 2.0 A with respect to the corresponding crystal structures. The success rate increased to 85% if the structure water molecules were retained. We evaluated GEMDOCK on two cross-docking experiments in which each ligand of a protein ensemble was docked into each protein of the ensemble. Seventy-six percent of the docked structures had RMSDs below 2.0 A when the ligands were docked into foreign structures. We analyzed and validated GEMDOCK with respect to various search spaces and scoring functions, and found that if the scoring function was perfect, then the predicted accuracy was also essentially perfect. This study suggests that GEMDOCK is a useful tool for molecular recognition and may be used to systematically evaluate and thus improve scoring functions.     

A hierarchical method for molecular docking using cloud computing

Discovering small molecules that interact with protein targets will be a key part of future drug discovery efforts. Molecular docking of drug-like molecules is likely to be valuable in this field; however, the great number of such molecules makes the potential size of this task enormous. In this paper, a method to screen small molecular databases using cloud computing is proposed. This method is called the hierarchical method for molecular docking and can be completed in a relatively short period of time. In this method, the optimization of molecular docking is divided into two subproblems based on the different effects on the protein–ligand interaction energy. An adaptive genetic algorithm is developed to solve the optimization problem and a new docking program (FlexGAsDock) based on the hierarchical docking method has been developed. The implementation of docking on a cloud computing platform is then discussed. The docking results show that this method can be conveniently used for the efficient molecular design of drugs.     

Automatic identification and representation of protein binding sites for molecular docking.

Molecular docking is a popular way to screen for novel drug compounds. The method involves aligning small molecules to a protein structure and estimating their binding affinity. To do this rapidly for tens of thousands of molecules requires an effective representation of the binding region of the target protein. This paper presents an algorithm for representing a protein's binding site in a way that is specifically suited to molecular docking applications. Initially the protein's surface is coated with a collection of molecular fragments that could potentially interact with the protein. Each fragment, or probe, serves as a potential alignment point for atoms in a ligand, and is scored to represent that probe's affinity for the protein. Probes are then clustered by accumulating their affinities, where high affinity clusters are identified as being the "stickiest" portions of the protein surface. The stickiest cluster is used as a computational binding "pocket" for docking. This method of site identification was tested on a number of ligand-protein complexes; in each case the pocket constructed by the algorithm coincided with the known ligand binding site. Successful docking experiments demonstrated the effectiveness of the probe representation.     

Hydrophobic docking: A proposed enhancement to molecular recognition techniques

In the classical procedures for predicting the structure of protein complexes two molecules are brought in contact at multiple relative positions, the extent of complementarity (geometric and/or energy) at the surface of contact is assessed at each position, and the best fits are retrieved. In view of the higher occurrence of hydrophobic groups at contact sites, their contribution results in more intermolecular atom–atom contacts per unit area for correct matches than for false positive fits. The hydrophobic groups are also potentially less flexible at the surface. Thus, from a practical point of view, a partial representation of the molecules based on hydrophobic groups should improve the quality of the results in finding molecular recognition sites, as compared to full representation. We tested this proposal by applying the idea to an existing geometric fit procedure and compared the results obtained with full vs. hydrophobic representations of molecules in known molecular complexes. The hydrophobic docking yielded distinctly higher signal-to-noise ratio so that the correct match is discriminated better from false positive fits. It appears that nonhydrophobic groups contribute more to false matches. The results are discussed in terms of their relevance to molecular recognition techniques as compared to energy calculations. © 1994 Wiley-Liss, Inc.     

Structural studies,homology modeling and molecular docking of novel non-competitive antagonists of GluK1/GluK2 receptors

Non-competitive ligands of kainate receptors have focused significant attention as medicinal compounds because they seem to be better tolerated than competitive antagonists and uncompetitive blocker of these receptors. Here we present structural studies (X-ray structure determination, NMR and MS spectra) of novel indole-derived non-competitive antagonists of GluK1/GluK2 receptors, homology models of GluK1 and GluK2 receptors based on novel AMPA receptor template as well as molecular docking of ligands to their molecular targets. We find that the allosteric site is in the receptor transduction domain, in one receptor subunit, not between the two subunits as it was indicated by our earlier studies.     

Identification of nonplanar small molecule for G-quadruplex grooves: molecular docking and molecular dynamic study

DNA G-quadruplex is an attractive drug target for anticancer therapy. Most G-quadruplex ligands have little selectivity, due to π-stacking interaction with common G-tetrads surface. Thanks to the varieties of G-quadruplex grooves, the groove-binding ligand is expected to create high selectivity. Therefore, developing novel molecular geometries that target G-quadruplex groove has been paid growing attention. In this work, steroid FG, a special nonplanar and nonaromatic small molecule, interacting with different conformations of G-quadruplexes has been studied by molecular docking and molecular dynamics simulations. The results showed the selectivity of the hydrophobic group of steroid FG for the wide groove of antiparallel G-quadruplex. The methyl groups on the tetracyclic ring of steroid represent the specific binding ability for the small hydrophobic cavity formed by reversed stacking of G-tetrads in antiparallel G-quadruplex groove. This work provides new insight for developing new classes of G-quadruplex groove-binding ligands.     

Probing the structure of falcipain-3, a cysteine protease from Plasmodium falciparum: comparative protein modeling and docking studies

Increasing resistance of malaria parasites to conventional antimalarial drugs is an important factor contributing to the persistence of the disease as a major health threat. The ongoing search for novel targets has resulted in identification and expression of several enzymes including cysteine proteases that are implicated in hemoglobin degradation. Falcipain-2 and falcipain-3 are considered to be the two principal cysteine proteases in this degradation, and hence, are potential drug targets. A homology model of falcipain-3 was built and validated by various structure/geometry verification tools as well as docking studies of known substrates. The correlation coefficient of 0.975 between interaction energies and K(m) values of these substrates provided additional support for the model. On comparison with the previously reported falcipain-2 homology model, the currently constructed falcipain-3 structure showed important differences between the S2 pockets that might explain the variations in the K(m) values of various substrates for these enzymes. Further, docking studies also provided insight into possible binding modes and interactions of ligands with falcipain-3. Results of the current study could be employed in de novo drug design leading to development of new antimalarial agents.     

MADAMM: a multistaged docking with an automated molecular modeling protocol

Dealing with receptor flexibility in docking methodology is still a problem. The main reason behind this difficulty is the large number of degrees of freedom that have to be considered in this kind of calculations. In this paper, we present an automated procedure, called MADAMM, that allows flexibilization of both the receptor and the ligand during a multistaged docking with an automated molecular modeling protocol. We show that the orientation of particular residues at the interface between the protein and the ligand have a crucial influence on the way they interact during the docking process, and the standard docking methodologies failed to predict their correct mode of binding. We present some examples that demonstrate the capabilities of this approach when compared with traditional docking methodologies.     

Homology modeling, active site prediction, and targeting the anti hypertension activity through molecular docking on endothelin - B receptor domain

In cardiovascular system, activation of Endothelin receptors causes vasoconstriction which leads to Pulmonary Arterial Hypertension (PAH). Endothelin receptor antagonism has emerged as an important therapeutic strategy in pulmonary arterial hypertension. Bosentan is intended to affect vasoconstriction, hypertrophic and fibrotic effects by blocking the actions of receptors ET(A) and ET(B). In this study we identified the action of Bosentan on endothelin B receptor using docking studies with homology modeled endothelin B receptor. Through the modeled protein, the flexible Docking study was performed with Bosentan and its derivatives with theoretically predicted active sites. The results indicated that amino acid ARG82, ARG84 and HIS197 present in endothelin B receptor are core important for binding activities and these residues are having strong hydrogen bond interactions with Bosentan. We have investigated the Bosentan and its derivatives interactions and scoring parameters using gold docking package. Among the docked compounds, one of the Bosentan derivatives BD(6) shows better interaction than Bosentan with endothelin B receptor. Our results may be helpful for further investigations in both in vivo and in vitro conditions.     

Computational active site analysis of molecular pathways to improve functional classification of enzymes

This study describes a method to computationally assess the function of homologous enzymes through small molecule binding interaction energy. Three experimentally determined X-ray structures and four enzyme models from ornithine cyclo-deaminase, alanine dehydrogenase, and mu-crystallin were used in combination with nine small molecules to derive a function score (FS) for each enzyme-model combination. While energy values varied for a single molecule-enzyme combination due to differences in the active sites, we observe that the binding energies for the entire pathway were proportional for each set of small molecules investigated. This proportionality of energies for a reaction pathway appears to be dependent on the amino acids in the active site and their direct interactions with the small molecules, which allows a function score (FS) to be calculated to assess the specificity of each enzyme. Potential of mean force (PMF) calculations were used to obtain the energies, and the resulting FS values demonstrate that a measurement of function may be obtained using differences between these PMF values. Additionally, limitations of this method are discussed based on: (a) larger substrates with significant conformational flexibility; (b) low homology enzymes; and (c) open active sites. This method should be useful in accurately predicting specificity for single enzymes that have multiple steps in their reactions and in high throughput computational methods to accurately annotate uncharacterized proteins based on active site interaction analysis.     

Construction of molecular assemblies via docking: modeling of tetramers with D2 symmetry

Comparative modeling methods are commonly used to construct models of homologous proteins or oligomers. However, comparative modeling may be inapplicable when the number of subunits in a modeled oligomer is different than in the modeling template. Thus, a dimer cannot be a template for a tetramer because a new monomer-monomer interface must be predicted. We present in this study a new prediction approach, which combines protein-protein docking with either of two tetramer-forming algorithms designed to predict the structures of tetramers with D2 symmetry. Both algorithms impose symmetry constraints. However, one of them requires identification of two of the C2 dimers within the tetramer in the docking step, whereas the other, less demanding algorithm, requires identification of only one such dimer. Starting from the structure of one subunit, the procedures successfully reconstructed 16 known D2 tetramers, which crystallize with either a monomer, a dimer or a tetramer in the asymmetric unit. In some cases we obtained clusters of native-like tetramers that differ in the relative rotation of the two identical dimers within the tetramer. The predicted structural pliability for concanavalin-A, phosphofructokinase, and fructose-1,6-bisphosphatase agrees semiquantitatively with the observed differences between the several experimental structures of these tetramers. Hence, our procedure identifies a structural soft-mode that allows regulation via relative rigid-body movements of the dimers within these tetramers. The algorithm also predicted three nearly correct tetramers from model structures of single subunits, which were constructed by comparative modeling from subunits of homologous tetrameric, dimeric, or hexameric systems.     

Molecular mechanism of Ferula asafoetida for the treatment of asthma: Network pharmacology and molecular docking approach

Asthma is a significant health-care burden that has great impact on the quality of life of patients and their families. The limited amount of previously reported data and complicated pathophysiology of asthma make it a difficult to treat and significant economic burden on public healthcare systems. Ferula asafoetida is an herbaceous, monoecious, perennial plant of the Umbelliferae family. In Asia, F. asafoetida is used to treat a range of diseases and disorders, including asthma. Several in vitro studies demonstrated the therapeutic efficacy of F. asafoetida against asthma. Nevertheless, the precise molecular mechanism is yet to be discovered. In the framework of current study, network pharmacology approach was used to identify the bioactive compounds of F. asafoetida in order to better understand its molecular mechanism for the treatment of asthma. In present work, we explored a compound-target-pathway network and discovered that assafoetidin, cynaroside, farnesiferol-B, farnesiferol-C, galbanic-acid, and luteolin significantly influenced the development of asthma by targeting MAPK3, AKT1 and TNF genes. Later, docking analysis revealed that active constituents of F. asafoetida bind stably with three target proteins and function as asthma repressor by regulating the expression of MAPK3, AKT1 and TNF genes. Thus, integration of network pharmacology with molecular docking revealed that F. asafoetida prevent asthma by modulating asthma-related signaling pathways. This study lays the basis for establishing the efficacy of multi-component, multi-target compound formulae, as well as investigating new therapeutic targets for asthma.     

Papaya fruit ripening: ROS metabolism,gene cloning,characterization and molecular docking of peroxidase

Climacteric fruit ripening has been characterized by oxidative burst and involve active oxidative metabolism with generation of reactive oxygen species (ROS). In the present paper, the papaya fruit ripening was found to be associated with increase in polygalacturonase (PG), pectate lyase (PEL), catalase (CAT), ascorbate peroxidase (APX), H₂O₂ and lipid peroxidation concomitant with decrease in the activities of superoxide dismutase (SOD) and guaiacol peroxidase (GPX). Furthermore, a cDNA (903 bp) of GPX from unripe papaya fruit pulp was isolated and cloned. On BLAST analysis, the deduced protein exhibited homology with various peroxidases and specific hits for plant heme peroxidase family namely heme and calcium binding domains. GPX of papaya was modeled and docked with various substrates and inhibitors among which guaiacol and cysteine were found to be the best substrate and inhibitor, respectively.     

Prediction of HIV-1 entry inhibitors neomycin-arginine conjugates interaction with the CD4-gp120 binding site by molecular modeling and multistep docking procedure

Developing of multi-target HIV-1 entry inhibitors represents an important avenue of drug therapy. Two such inhibitors are hexa-arginine-neomycin-conjugate (NeoR6) and nona-d-arginine-neomycin-conjugate (Neo-r9). Our findings that NeoR6-resistant mutations appear in the gp120 constant regions; and NeoR6 is not CCR5 antagonist, but inhibits CXCR4 and CCR5 HIV-1 using isolates, led us to suggest that NeoR6 may inhibit HIV-1 entry by interfering with the CD4-gp120 binding. To support this notion, we constructed a homology model of unliganded HIV-1_IIIB gp120 and docked NeoR6 and Neo-r9 to it, using a multistep docking procedure: geometric-electrostatic docking by MolFit; flexible ligand docking by Autodock3 and final refinement of the obtained complexes by Discover3. Binding free energies were calculated by MM-PBSA methodology. The model predicts competitive inhibition of CD4-gp120 binding by NeoR6 and Neo-r9. We determined plausible binding sites between constructed CD4-bound gp120 trimer and homology modeled membranal CXCR4, and tested NeoR6 and Neo-r9 interfering with this interaction. These models support our notion that another mechanism of anti-HIV-1 activity of NeoR6 is inhibition of gp120-CXCR4 binding. These structural models and interaction of NeoR6 and Neo-r9 with gp120 and CXCR4 provide a powerful approach for structural based drug design for selective targeting of HIV-1 entry and/or for inhibition of other retroviruses with similar mechanism of entry.     

Pharmacophore modeling,molecular docking and molecular dynamics studies on natural products database to discover novel skeleton as non-purine xanthine oxidase inhibitors

Gout is a common inflammatory arthritis caused by the deposition of urate crystals within joints. It is increasingly in prevalence during the past few decades as shown by the epidemiological survey results. Xanthine oxidase (XO) is a key enzyme to transfer hypoxanthine and xanthine to uric acid, whose overproduction leads to gout. Therefore, inhibiting the activity of xanthine oxidase is an important way to reduce the production of urate. In the study, in order to identify the potential natural products targeting XO, pharmacophore modeling was employed to filter databases. Here, two methods, pharmacophore based on ligand and pharmacophore based on receptor-ligand, were constructed by Discovery Studio. Then GOLD was used to refine the potential compounds with higher fitness scores. Finally, molecular docking and dynamics simulations were employed to analyze the interactions between compounds and protein. The best hypothesis was set as a 3D query to screen database, returning 785 and 297 compounds respectively. A merged set of the above 1082 molecules was subjected to molecular docking, which returned 144 hits with high-fitness scores. These molecules were clustered in four main kinds depending on different backbones. What is more, molecular docking showed that the representative compounds established key interactions with the amino acid residues in the protein, and the RMSD and RMSF of molecular dynamics results showed that these compounds can stabilize the protein. The information represented in the study confirmed previous reports. And it may assist to discover and design new backbones as potential XO inhibitors based on natural products.     

Protein-protein docking with a reduced protein model accounting for side-chain flexibility

A protein-protein docking approach has been developed based on a reduced protein representation with up to three pseudo atoms per amino acid residue. Docking is performed by energy minimization in rotational and translational degrees of freedom. The reduced protein representation allows an efficient search for docking minima on the protein surfaces within. During docking, an effective energy function between pseudo atoms has been used based on amino acid size and physico-chemical character. Energy minimization of protein test complexes in the reduced representation results in geometries close to experiment with backbone root mean square deviations (RMSDs) of approximately 1 to 3 A for the mobile protein partner from the experimental geometry. For most test cases, the energy-minimized experimental structure scores among the top five energy minima in systematic docking studies when using both partners in their bound conformations. To account for side-chain conformational changes in case of using unbound protein conformations, a multicopy approach has been used to select the most favorable side-chain conformation during the docking process. The multicopy approach significantly improves the docking performance, using unbound (apo) binding partners without a significant increase in computer time. For most docking test systems using unbound partners, and without accounting for any information about the known binding geometry, a solution within approximately 2 to 3.5 A RMSD of the full mobile partner from the experimental geometry was found among the 40 top-scoring complexes. The approach could be extended to include protein loop flexibility, and might also be useful for docking of modeled protein structures.