Pharmacophore identification by molecular modeling and chemometrics: The case of HMG-CoA reductase inhibitors

Summary A methodology based on molecular modeling and chemometrics is applied to identify the geometrical pharmacophore and the stereoelectronic requirements for the activity in a series of inhibitors of 3-hydroxy 3-methylglutaryl coenzyme A (HMG-CoA) reductase, an enzyme involved in cholesterol biosynthesis. These inhibitors present two common structural features—a 3,5-dihydroxy heptanoic acid which mimics the active portion of the natural substrate HMG-CoA and a lipophilic region which carries both polar and bulky groups. A total of 432 minimum energy conformations of 11 homologous compounds showing different levels of biological activity are calculated by the molecular mechanics MM2 method. Five atoms are selected as representatives of the relevant fragments of these compounds and three interatomic distances, selected among 10 by means of a Principal Component Analysis (PCA), are used to describe the three-dimensional disposition of these atoms. A cluster analysis procedure, performed on the whole set of conformations described by these three distances, allows the selection of one cluster whose centroid represents a geometrical model for the HMG-CoA reductase pharmacophore and the conformations included are candidates as binding conformations. To obtain a refinement of the geometrical model and to have a better insight into the requirements for the activity of these inhibitors, the Molecular Electrostatic Potential (MEP) distributions are determined by the MNDO semiempirical method.     

A molecular docking study of potential inhibitors and repurposed drugs against SARS-CoV-2 main protease enzyme

COVID-19 has affected millions of people. Although many drugs are in use to combat disease, there is not any sufficient treatment yet. Having critical role in propagation of the novel coronavirus (SARS-CoV-2) works Main Protease up into a significant drug target. We have performed a molecular docking study to define possible inhibitor candidates against SARS-CoV-2 Main Protease enzyme. Besides docking Remdesivir, Ribavirin, Chloroquine and 28 other antiviral inhibitors (totally 31 inhibitors) to Main Protease enzyme, we have also performed a molecular docking study of 2177 ligands, which are used against Main Protease for the first time by using molecular docking program Autodock4. All ligands were successfully docked into Main Protease enzyme binding site. Among all ligands, EY16 coded ligand which previously used as EBNA1-DNA binding blocker candidate showed the best score for Main Protease with a binding free energy of −10.83 ​kcal/mol which was also lower than re-docking score of N3 ligand (−10.72 ​kcal/mol) contained in crystal structure of Main Protease. After analyzing the docking modes and docking scores we have found that our ligands have better binding free energy values than the inhibitors in use of treatment. We believe that further studies such as molecular dynamics or Molecular Mechanic Poisson Boltzmann Surface Area studies can make contribution that is more exhaustive to the docking results.     

Use of virtual screening, flexible docking, and molecular interaction fields to design novel HMG-CoA reductase inhibitors for the treatment of hypercholesterolemia

Dietary changes associated with drug therapy can reduce high serum cholesterol levels and dramatically decrease the risk of coronary artery disease, stroke, and overall mortality. Statins are hypolipemic drugs that are effective in the reduction of cholesterol serum levels, attenuating cholesterol synthesis in liver by competitive inhibition regarding the substrate or molecular target HMG-CoA reductase. We have herewith used computer-aided molecular design tools, i.e., flexible docking, virtual screening in large data bases, molecular interaction fields to propose novel potential HMG-CoA reductase inhibitors that are promising for the treatment of hypercholesterolemia.     

DOX: A new computational protocol for accurate prediction of the protein–ligand binding structures

Molecular docking techniques have now been widely used to predict the protein–ligand binding modes, especially when the structures of crystal complexes are not available. Most docking algorithms are able to effectively generate and rank a large number of probable binding poses. However, it is hard for them to accurately evaluate these poses and identify the most accurate binding structure. In this study, we first examined the performance of some docking programs, based on a testing set made of 15 crystal complexes with drug statins for the human 3‐hydroxy‐3‐methylglutaryl coenzyme A reductase (HMGR). We found that most of the top ranking HMGR–statin binding poses, predicted by the docking programs, were energetically unstable as revealed by the high theoretical‐level calculations, which were usually accompanied by the large deviations from the geometric parameters of the corresponding crystal binding structures. Subsequently, we proposed a new computational protocol, DOX, based on the joint use of molecular Docking, ONIOM, and eXtended ONIOM (XO) methods to predict the accurate binding structures for the protein–ligand complexes of interest. Our testing results demonstrate that the DOX protocol can efficiently predict accurate geometries for all 15 HMGR‐statin crystal complexes without exception. This study suggests a promising computational route, as an effective alternative to the experimental one, toward predicting the accurate binding structures, which is the prerequisite for all the deep understandings of the properties, functions, and mechanisms of the protein–ligand complexes. © 2015 Wiley Periodicals, Inc.     

Electrostatic Interactions in Docking a 3D Model of Bovine Testicular Hyaluronidase with a Chondroitin Sulfate Trimer and a Heparin Tetramer

The molecular docking of a 3D-model of bovine testicular hyaluronidase with glycosaminoglycan ligands is performed. A chondroitin sulfate trimer and a heparin tetramer were used as ligands. Methods of computational chemistry are applied to elucidate the regulation of hyaluronidase functioning in an organism when the heparin ligand inactivates the biocatalyst, and the chondroitin sulfate ligand protects the enzyme structure. Eight ligand binding sites are identified on the molecular surface of the enzyme, each of which is equally capable of interacting with chondroitin sulfate trimers and heparin tetramers via electrostatic interactions. It is found that reversible and irreversible conformational changes in the enzyme 3D structure can occur depending on the positioning of negatively charged ligands on its globule (under different conditions, they can either stabilize or inactivate the biocatalyst). Binding sites whose occupancy is sufficient for preventing irreversible deformations of the enzyme conformation upon introducing the heparin ligand into the active site are identified on the molecular surface of hyaluronidase. The interaction of glycosaminoglycan ligands with hyaluronidase is mainly determined by electrostatic forces.     

Docking of small molecules to farnesoid X receptors using AutoDock Vina with the Convex-PL potential: lessons learned from D3R Grand Challenge 2

The 2016 D3R Grand Challenge 2 provided an opportunity to test multiple protein–ligand docking protocols on a set of ligands bound to farnesoid X receptor that has many available experimental structures. We participated in the Stage 1 of the Challenge devoted to the docking pose predictions, with the mean RMSD value of our submission poses of 2.9 Å. Here we present a thorough analysis of our docking predictions made with AutoDock Vina and the Convex-PL rescoring potential by reproducing our submission protocol and running a series of additional molecular docking experiments. We conclude that a correct receptor structure, or more precisely, the structure of the binding pocket, plays the crucial role in the success of our docking studies. We have also noticed the important role of a local ligand geometry, which seems to be not well discussed in literature. We succeed to improve our results up to the mean RMSD value of 2.15–2.33 Å  dependent on the models of the ligands, if docking these to all available homologous receptors. Overall, for docking of ligands of diverse chemical series we suggest to perform docking of each of the ligands to a set of multiple receptors that are homologous to the target.     

Identification of 3-Methoxycarpachromene and Masticadienonic Acid as New Target Inhibitors against Trypanothione Reductase from Leishmania Infantum Using Molecular Docking and ADMET Prediction

Polyphenolic and Terpenoids are potent natural antiparasitic compounds. This study aimed to identify new drug against Leishmania parasites, leishmaniasis’s causal agent. A new in silico analysis was accomplished using molecular docking, with the Autodock vina program, to find the binding affinity of two important phytochemical compounds, Masticadienonic acid and the 3-Methoxycarpachromene, towards the trypanothione reductase as target drugs, responsible for the defense mechanism against oxidative stress and virulence of these parasites. There were exciting and new positive results: the molecular docking results show as elective binding profile for ligands inside the active site of this crucial enzyme. The ADMET study suggests that the 3-Methoxycarpachromene has the highest probability of human intestinal absorption. Through this work, 3-Methoxycarpachromene and Masticadienonic acid are shown to be potentially significant in drug discovery, especially in treating leishmaniasis. Hence, drug development should be completed with promising results.     

The human olfactory receptor 17-40: requisites for fitting into the binding pocket

To gain structural insight on the interactions between odorants and the human olfactory receptor, we did homology modelling of the receptor structure, followed by molecular docking simulation with ligands. Molecular dynamics simulation on the structures resulting from docking served to estimate the binding free energy of the various odorant families. A correlation with the odorous properties of the ligands is proposed. We also investigated which residues were involved in the binding of a set of properly synthesised ligands and which were required for fitting inside the binding pocket. Olfactive stimulation of the olfactory receptor with odorous molecules was also investigated, using calcium imaging or electrophysiological recordings.     

Normalizing molecular docking rankings using virtually generated decoys

Drug discovery research often relies on the use of virtual screening via molecular docking to identify active hits in compound libraries. An area for improvement among many state-of-the-art docking methods is the accuracy of the scoring functions used to differentiate active from nonactive ligands. Many contemporary scoring functions are influenced by the physical properties of the docked molecule. This bias can cause molecules with certain physical properties to incorrectly score better than others. Since variation in physical properties is inevitable in large screening libraries, it is desirable to account for this bias. In this paper, we present a method of normalizing docking scores using virtually generated decoy sets with matched physical properties. First, our method generates a set of property-matched decoys for every molecule in the screening library. Each library molecule and its decoy set are docked using a state-of-the-art method, producing a set of raw docking scores. Next, the raw docking score of each library molecule is normalized against the scores of its decoys. The normalized score represents the probability that the raw docking score was drawn from the background distribution of nonactive property-matched decoys. Assuming that the distribution of scores of active molecules differs from the nonactive score distribution, we expect that the score of an active compound will have a low probability of having been drawn from the nonactive score distribution. In addition to the use of decoys in normalizing docking scores, we suggest that decoy sets may be a useful tool to evaluate, improve, or develop scoring functions. We show that by analyzing docking scores of library molecules with respect to the docking scores of their virtually generated property-matched decoys, one can gain insight into the advantages, limitations, and reliability of scoring functions.     

Importance of accurate charges in molecular docking: quantum mechanical/molecular mechanical (QM/MM) approach

The extent to which accuracy of electric charges plays a role in protein-ligand docking is investigated through development of a docking algorithm, which incorporates quantum mechanical/molecular mechanical (QM/MM) calculations. In this algorithm, fixed charges of ligands obtained from force field parameterization are replaced by QM/MM calculations in the protein environment, treating only the ligands as the quantum region. The algorithm is tested on a set of 40 cocrystallized structures taken from the Protein Data Bank (PDB) and provides strong evidence that use of nonfixed charges is important. An algorithm, dubbed "Survival of the Fittest" (SOF) algorithm, is implemented to incorporate QM/MM charge calculations without any prior knowledge of native structures of the complexes. Using an iterative protocol, this algorithm is able in many cases to converge to a nativelike structure in systems where redocking of the ligand using a standard fixed charge force field exhibits nontrivial errors. The results demonstrate that polarization effects can play a significant role in determining the structures of protein-ligand complexes, and provide a promising start towards the development of more accurate docking methods for lead optimization applications.     

Interpretation of scoring functions using 3D molecular fields. Mapping the diacyl-hydrazine-binding pocket of an insect ecdysone receptor

A method is presented for the interpretation of receptor docking score values (rough measures of binding affinities) of ligands in terms of 3D molecular field interaction contributions. The FlexX and FlexX-Pharm methods were used to dock the structures of designed sets of ligands into the ligand-binding pocket of a selected receptor. In the next step the relationship was investigated between the FlexX and CScore scores and 3D molecular fields obtained for the docked conformations of the ligands, using the CoMFA (Comparative Molecular Field Analysis) and CoMSIA (Comparative Molecular Similarity Indices Analysis) methods. The approach yielded highly significant CoMFA and CoMSIA models demonstrating that a high portion of the variance in the docking score values of the ligands can be explained by steric, electrostatic, hydrophobic, and hydrogen bond donor and acceptor molecular field interaction contributions. The approach was exemplified by using the crystal structure of the ligand-binding domain of the ecdysone receptor (EcR) of the moth Heliotis virescens as well as virtual molecule libraries of analogues of known diacyl-hydrazine (DAH) type ecdysteroid agonists. By docking appropriately designed virtual compound libraries into the DAH binding pocket of EcR followed by CoMFA and CoMSIA of the docked conformations, hitherto unexplored regions of the receptor cavity could be mapped. By mapping the significant molecular field interaction contributions onto the model of the receptor-ligand complex, important receptor-ligand interactions could be highlighted that may help the design of novel highly scored receptor ligands. An advantage of the method is that no experimental biological activity data are required to exhaustively map the receptor-binding site.     

Understanding the molecular interactions of different radical scavengers with ribonucleotide reductase M2 (hRRM2) domain: opening the gates and gaining access

We employed a combination of molecular docking and dynamics to understand the interaction of three different radical scavengers (SB-HSC21, ABNM13 and trimidox) with ribonucleotide reductase M2 (hRRM2) domain. On the basis of the observed results, we can propose how these ligands interact with the enzyme, and cease the radical transfer step from the di-iron center to TYR176. All the ligands alter the electron density over TYR176, -OH group by forming an extremely stable H-bond with either -NHOH group, or with phenolic hydroxyl group of the ligands. This change in electronic density disrupts the water bridge between TYR176, -OH and the di-iron center, which stops the single electron transfer process from TYR176, -OH to iron. As a consequence the enzyme is inhibited. Another interesting observation that we are reporting is the two stage gate keeping mechanism of the RR active site tunnel. We describe these as the outer Gate-1 controlled by ARG330, and the inner Gate-2 controlled by SER263, PHE240, and PHE236. We also observed a dynamic conformational shift in these residues, the incoming ligands can go through, and interact with the underlying TYR176, -OH group. From the study we found the active-site of hRRM2 is extremely flexible and shows a significant induced fit.     

Liquid Chromatographic Determination of 3-Hydroxy-3-methylglutaryl Coenzyme A Reductase Inhibitors

Reversed-phase high-performance liquid chromatography (RP-HPLC) was used as a tool to explore the retention behavior and separation of four 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors, namely compactin, lovastatin, simvastatin, and pravastatin in their hydroxy acid and lactone forms. The contribution of C-6 and C-2′ methyl groups and lactonization to the molecular hydrophobicity among these four structurally related HMG-CoA reductase inhibitors were elucidated. Eight components (four lactones and four hydroxy acids) could be resolved by RP-HPLC with isocratic elution. In a binary mobile phase system of acetonitrile-water containing 0.5% acetic acid, the free hydroxy acids and corresponding lactone forms remained intact and were completely separated. This study demonstrated that RP-HPLC is suitable for simultaneous determination of active and prodrug forms of these HMG-CoA reductase inhibitors.     

Theoretical studies of 1,4-dihydropyridine-3,5-dicarboxamides as possible inhibitors of Mycobacterium tuberculosis enoyl reductase

Abstract  

The binding affinity of some novel 1,4-dihydropyridine-3,5-dicarboxamides to enoyl-ACP reductase (InhA) from M. tuberculosis was studied by the docking method. A molecular dynamics simulation lasting 230 ns in total was performed for 19 ligand–enzyme complexes to calculate the binding free energies of these ligands to the enzyme. All of the studied compounds stayed in the active site. An energetics analysis revealed that the van der Waals share is more important than electrostatic in binding of all ligands to the active site.     

Binding affinity of substituted ureido‐benzenesulfonamide ligands to the carbonic anhydrase receptor: A theoretical study of enzyme inhibition

The binding properties of a series of benzenesulfonamide inhibitors (4‐substituted‐ureido‐benzenesulfonamides, UBSAs) of human carbonic anhydrase II (hCA II) enzyme with active site residues have been studied using a hybrid quantum mechanical/molecular mechanical (QM/MM) model. To account for the important docking interactions between the UBSAs ligand and hCA II enzyme, a molecular docking program AutoDock Vina is used. The molecular docking results obtained by AutoDock Vina revealed that the docked conformer has root mean square deviation value less than 1.50 Å compared to X‐ray crystal structures. The inhibitory activity of UBSA ligands against hCA II is found to be in good agreement with the experimental results. The thermodynamic parameters for inhibitor binding show that hydrogen bonding, hydrophilic, and hydrophobic interactions play a major role in explaining the diverse inhibitory range of these derivatives. Additionally, natural bond orbital analysis is performed to characterize the ligand–metal charge transfer stability. The insights gained from this study have great potential to design new hCA‐II inhibitor, 4‐[3‐(1‐p‐Tolyl‐4‐trifluoromethyl‐1H‐pyrazol‐3‐yl)‐ureido]‐benzenesulfonamide, which belongs to the family of UBSA inhibitors and shows similar type of inhibitor potency with hCA II. This work also reveals that a QM/MM model and molecular docking method are computationally feasible and accurate for studying substrate–protein inhibition. © 2013 Wiley Periodicals, Inc.     

3C-like蛋白酶抑制剂的构效关系、分子对接和分子动力学

3C-like蛋白酶是中东呼吸综合征冠状病毒（MERS-CoV）等其它冠状病毒的繁殖过程中极为重要的蛋白酶。它已成为人类在抗冠状病毒领域中的研究热点。本文基于计算生物学方法对与MERS-CoV同属的蝙蝠冠状病毒HKU4（HKU4-CoV）的43个肽类3C-like蛋白酶抑制剂分子,建立三维定量构效关系（3D-QSAR）模型。在基于配体叠合的基础上,发现比较分子相似性指数分析法（CoMSIA）中的四个场组合（位阻场、静电场、氢键供体场与氢键受体场）为最优的模型（Q²=0.522,R_ncv²=0.996,R_pre²=0.904;Q²：交叉验证相关系数,R_ncv²：非交叉验证相关系数,R_pre²：验证集分子的预测值相关系数）,并借助该模型通过分子对接（docking）与分子动力学（MD）方法阐明了配受体结合作用。实验结果表明：（1）基于最优的CoMSIA模型基础上的三维等势图形象地说明了分子基团的位阻作用、静电作用、氢键供体与氢键受体作用对分子生物活性的影响;（2）分子对接研究结果显示了疏水性以及结晶水、氨基酸His166和Glu169在配体和受体结合过程中产生重要作用;（3）分子动力学模拟进一步验证了分子对接模型的可靠性,并发现了两个新的关键氨基酸Ser24与Gln192,它们与配体产生了两个较强的氢键。此外,根据这些结果,一些新的具有潜在抑制活性的肽类化合物作为3C-like蛋白酶抑制剂被获得。以上结果能够帮助深入了解3C-like蛋白酶与肽类抑制剂的作用机理,并且能够为今后的抗MERS-CoV药物设计提供有价值的参考。     

HMG-CoA还原酶抑制剂三维药效团的构建

以作用于鼠肝脏细胞的21个3-羟基-3-甲基戊二酰辅酶A(HMG-CoA)还原酶抑制剂(RI)为训练集, 训练集化合物具备结构多样性, 来源于相同药理模型, 活性值IC50范围在0.3-8000 nmol·L-1. 利用Catalyst 计算HMG-CoA还原酶抑制剂最优药效团由一个氢键受体, 一个氢键给体, 一个疏水基团和一个芳香环特征组成. 药效团模型Fixed cost值, Total cost值和Configuration cost值分别为88.75、111.5 和16.98. 训练集化合物活性计算值与实测值相关系数为0.8883, 偏差值为1.269, 交叉验证结果表明, 药效团模型具有较高的置信度, 对测试集化合物活性值的预测结果显示有较好的预测能力, 可用于数据库搜索发现新的具有该活性的化合物, 也可用于中药或天然产物药物的研究开发.     

Placement of medium-sized molecular fragments into active sites of proteins

Summary We present an algorithm for placing molecular fragments into the active site of a receptor. A molecular fragment is defined as a connected part of a molecule containing only complete ring systems. The algorithm is part of a docking tool, called FlexX, which is currently under development at GMD. The overall goal is to provide means of automatically computing low-energy conformations of the ligand within the active site, with an accuracy approaching the limitations of experimental methods for resolving molecular structures and within a run time that allows for docking large sets of ligands. The methods by which we plan to achieve this goal are the explicit exploitation of molecular flexibility of the ligand and the incorporation of physicochemical properties of the molecules. The algorithm for fragment placement, which is the topic of this paper, is based on pattern recognition techniques and is able to predict a small set of possible positions of a molecular fragment with low flexibility within seconds on a workstation. In most cases, a placement with rms deviation below 1.0 Å with respect to the X-ray structure is found among the 10 highest ranking solutions, assuming that the receptor is given in the bound conformation.     

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.