A comparative study of AutoDock and PMF scoring performances,and SAR of 2-substituted pyrazolotriazolopyrimidines and 4-substituted pyrazolopyrimidines as potent xanthine oxidase inhibitors

4-Alkylidenehydrazino-1H-pyrazolo[3,4-d]pyrimidines, 4-arylmethylidenehydrazino-1H-pyrazolo[3,4-d]pyrimidines, and 2-substituted 7H-pyrazolo[4,3-e]-1,2,4-triazolo-[1,5-c]-pyrimidines as potential xanthine oxidase inhibitors were docked into the active site of the bovine milk xanthine dehydrogenase using two scoring functions involved in AutoDock 3.05 and the CAChe 6.1.10. The correlation coefficiency obtained between the AutoDock binding energy and IC₅₀ of the inhibitors was better than that obtained by the CAChe-PMF docking score. Many ligands exhibited one to four hydrogen bonds within the active site, where the detected hydrogen bonds by CAChe was identified quantitatively in the docked conformation by using MOPAC 2002. These ligands were docked into a long, narrow channel of the enzyme leading to the molybdopterin active moiety, with hydrogen bonding and electrostatic interaction between the planar aromatic moiety of the ligand and the enzyme. Furthermore, SAR among inhibitors was investigated, which revealed that the oxo group of pyrazolopyrimidine analogs is essential for its activity and the tricyclic derivatives are shown to be more potent than bicyclic ones. The mode of interaction of the docked inhibitors was described in details.     

Evaluation of docking/scoring approaches: A comparative study based on MMP3 inhibitors

An increasing number of docking/scoring programs are available that use different sampling and scoring algorithms. A reliable scoring function is the crucial element of such approaches. Comparative studies are needed to evaluate their current capabilities. DOCK4 with force field and PMF scoring as well as FlexX were used to evaluate the predictive power of these docking/scoring approaches to identify the correct binding mode of 61 MMP-3 inhibitors in a crystal structure of stromelysin and also to rank them according to their different binding affinities. It was found that DOCK4/PMF scoring performs significantly better than FlexX and DOCK4/FF in both ranking ligands and predicting their binding modes. Most notably, DOCK4/PMF was the only scoring/docking approach that found a significant correlation between binding affinity and predicted score of the docked inhibitors. However, comparing only those cases where the correct binding mode was identified (scoring highest among sampled poses), FlexX showed the best `fine tuning' (lowest rmsd) in predicted binding modes. The results suggest that not so much the sampling procedure but rather the scoring function is the crucial element of a docking program.     

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.     

ELECT++: Faster conformational search method for docking flexible molecules using molecular similarity

We have developed a program, ELECT++ (Effective LEssening of Conformations by Template molecules in C++), to speed up the conformational search for small flexible molecules using the similar property principle. We apply this principle to molecular shape and, importantly, to molecular flexibility. After molecules in a database are clustered according to flexibility and shape (FCLUST++), additional reagents are generated to screen the conformational space of molecules in each cluster (TEMPLATE++). We call these representative reagents of each cluster template reagents. Template reagents and clustered reagents produce, after reaction, template molecules and clustered molecules, respectively (tREACT++). The conformations of a template molecule are searched in the context of a macromolecular target. Acceptable conformational choices are then applied to all molecules in its cluster, thus effectively biasing conformational space to speed up conformational searches (tSEARCH++). In our incremental search method, it is necessary to calculate the root-mean-square deviations (RMSD) matrix of distances between different conformations of the same molecule to reduce the number of conformations. Instead of calculating the RMSD matrix for all molecules in a cluster, the RMSD matrix of a template molecule is chosen as a reference and applied to all the molecules in its cluster. We demonstrate that FCLUST++ clusters the primary amine reagents from the Available Chemicals Directory (ACD) successfully. The program tSEARCH++ was applied to dihydrofolate reductase with virtual molecules generated by tREACT++ using clustered primary amine reagents. The conformational search by the program tSEARCH++ was about 4.8 times faster than by SEARCH++, with an acceptable range of errors. © 1998 John Wiley & Sons, Inc. J Comput Chem 19: 1834–1852, 1998     

Identifying the binding mode of a molecular scaffold

We describe a method for docking of a scaffold-based series and present its advantages over docking of individual ligands, for determining the binding mode of a molecular scaffold in a binding site. The method has been applied to eight different scaffolds of protein kinase inhibitors (PKI). A single analog of each of these eight scaffolds was previously crystallized with different protein kinases. We have used FlexX to dock a set of molecules that share the same scaffold, rather than docking a single molecule. The main mode of binding is determined by the mode of binding of the largest cluster among the docked molecules that share a scaffold. Clustering is based on our 'nearest single neighbor' method [J. Chem. Inf. Comput. Sci., 43 (2003) 208-217]. Additional criteria are applied in those cases in which more than one significant binding mode is found. Using the proposed method, most of the crystallographic binding modes of these scaffolds were reconstructed. Alternative modes, that have not been detected yet by experiments, could also be identified. The method was applied to predict the binding mode of an additional molecular scaffold that was not yet reported and the predicted binding mode has been found to be very similar to experimental results for a closely related scaffold. We suggest that this approach be used as a virtual screening tool for scaffold-based design processes.     

Docking-based comparative intermolecular contacts analysis as new 3-D QSAR concept for validating docking studies and in silico screening: NMT and GP inhibitors as case studies

The significant role played by docking algorithms in drug discovery combined with their serious pitfalls prompted us to envisage a novel concept for validating docking solutions, namely, docking-based comparative intermolecular contacts analysis (dbCICA). This novel approach is based on the number and quality of contacts between docked ligands and amino acid residues within the binding pocket. It assesses a particular docking configuration on the basis of its ability to align a set of ligands within a corresponding binding pocket in such a way that potent ligands come into contact with binding site spots distinct from those approached by low-affinity ligands and vice versa. In other words, dbCICA evaluates the consistency of docking by assessing the correlation between ligands' affinities and their contacts with binding site spots. Optimal dbCICA models can be translated into valid pharmacophore models that can be used as 3-D search queries to mine structural databases for new bioactive compounds. dbCICA was implemented to search for new inhibitors of candida N-myristoyl transferase as potential antifungal agents and glycogen phosphorylase (GP) inhibitors as potential antidiabetic agents. The process culminated in five selective micromolar antifungal leads and nine GP inhibitory leads.     

Discovery of a novel serine protease inhibitor utilizing a structure-based and experimental selection of fragments technique

We report a set of strategies to develop novel ligands (Structure Based and Experimental Selection of Fragments: SbE-SF). First, a docking simulation utilizing DOCK3.5 is performed in order to screen the fragment database, which was generated with the in-house program FRAGMENT++ specifically for docking simulation purposes. Although the affinity of these small molecules (fragments) is expected to be low, the affinity of fragments selected by computation is assayed by experiment to determine which ones can be potent inhibitors. After determining such key fragments, additional fragments are attached to the key ones in order to increase the binding affinity,taking into account the binding modes predicted by computation. This method has been applied to a thrombin inhibitor study, resulting in the discovery of a novel inhibitor exhibiting pIC₅₀ = 7.9.     

Automated flexible ligand docking method and its application for database search

We have developed a new docking program that explores ligand flexibility. This program can be applied to database searches. The program is similar in concept to earlier efforts, but it has been automated and improved. The algorithm begins by selecting an anchor fragment of a ligand. This fragment is protonated, as needed, and then placed in the receptor by the DOCK algorithm, followed by minimization using a simplex method. Finally, the conformations of the remaining parts of the putative ligands are searched by a limited backtrack method and minimized to get the most stable conformation. To test the efficiency of this method, the program was used to regenerate ten ligand–protein complex structures. In all cases, the docked ligands basically reproduced the crystallographic binding modes. The efficiency of this method was further tested by a database search. Ten percent of molecules from the Available Chemicals Directory (ACD) were docked to a dihydrofolate reductase structure. Most of the top-ranking molecules (7 of the top 13 hits) are dihydrofolate or methotrexate derivatives, which are known to be DHFR inhibitors, demonstrating the suitability of this program for screening molecular databases. © 1997 John Wiley & Sons, Inc. J Comput Chem 18 : 1812–1825, 1997     

Postprocessing of docked protein-ligand complexes using implicit solvation models

Molecular docking plays an important role in drug discovery as a tool for the structure-based design of small organic ligands for macromolecules. Possible applications of docking are identification of the bioactive conformation of a protein-ligand complex and the ranking of different ligands with respect to their strength of binding to a particular target. We have investigated the effect of implicit water on the postprocessing of binding poses generated by molecular docking using MM-PB/GB-SA (molecular mechanics Poisson-Boltzmann and generalized Born surface area) methodology. The investigation was divided into three parts: geometry optimization, pose selection, and estimation of the relative binding energies of docked protein-ligand complexes. Appropriate geometry optimization afforded more accurate binding poses for 20% of the complexes investigated. The time required for this step was greatly reduced by minimizing the energy of the binding site using GB solvation models rather than minimizing the entire complex using the PB model. By optimizing the geometries of docking poses using the GB(HCT+SA) model then calculating their free energies of binding using the PB implicit solvent model, binding poses similar to those observed in crystal structures were obtained. Rescoring of these poses according to their calculated binding energies resulted in improved correlations with experimental binding data. These correlations could be further improved by applying the postprocessing to several of the most highly ranked poses rather than focusing exclusively on the top-scored pose. The postprocessing protocol was successfully applied to the analysis of a set of Factor Xa inhibitors and a set of glycopeptide ligands for the class II major histocompatibility complex (MHC) A(q) protein. These results indicate that the protocol for the postprocessing of docked protein-ligand complexes developed in this paper may be generally useful for structure-based design in drug discovery.     

Development of energetic pharmacophore for the designing of 1,2,3,4-tetrahydropyrimidine derivatives as selective cyclooxygenase-2 inhibitors

We present here the Energetic pharmacophore model representing complementary features of the 1,2,3,4-tetrahydropyrimidine for selective cyclooxygenase-2 (COX-2) inhibition. For the development of pharmacophore hypothesis, a total of 43 previously reported compounds were docked on active site of COX-2 enzyme. The generated pharmacophore features were ranked using energetic terms of Glide XP docking for 1,2,3,4-tetrahydropyrimidine scaffold to optimize its structure requirement for COX-2 inhibition. The thirty new 4,5,6-triphenyl-1,2,3,4-tetrahydropyrimidine derivatives were synthesized and assessed for selective COX-2 inhibitory activity. Two compounds 4B1 and 4B11 were found to be potent and selective COX-2 inhibitors. The molecular docking studies revealed that the newly synthesized compounds can be docked into COX-2 binding site and also provide the molecular basis for their activity.     

Query generation to search for inhibitors of enzymatic reactions

A method for the generation of intermediates of enzyme-catalyzed reactions is presented. These intermediates can be used as three-dimensional structural queries for searching for inhibitors of enzymatic reactions. The intermediates can be considered as being structurally quite close to transition-state analogues. For this application, a database containing detailed chemical information on metabolic reactions is used. The likely three-dimensional structure of the intermediates of enzyme-catalyzed reactions can be generated from the information in the database. For three reactions catalyzed by the enzymes AMP deaminase (EC code 3.5.4.6), triose phosphate isomerase (EC code 5.3.1.1), and arginase II (EC code 3.5.3.1), we show how a 3D model of these intermediates can be superimposed onto known inhibitors of these enzymes by a program that uses a genetic algorithm. For this, we test different methods for the superimposition using information on the enzymatic binding site, using information on physicochemical properties calculated from the molecular structure, or without having any information in the superimposition process. We show that these inhibitors are most similar to the corresponding intermediates regarding the 3D structure.     

MCDOCK: A Monte Carlo simulation approach to the molecular docking problem

Prediction of the binding mode of a ligand (a drug molecule) to its macromolecular receptor, or molecular docking, is an important problem in rational drug design. We have developed a new docking method in which a non-conventional Monte Carlo (MC) simulation technique is employed. A computer program, MCDOCK, was developed to carry out the molecular docking operation automatically. The current version of the MCDOCK program (version 1.0) allows for the full flexibility of ligands in the docking calculations. The scoring function used in MCDOCK is the sum of the interaction energy between the ligand and its receptor, and the conformational energy of the ligand. To validate the MCDOCK method, 19 small ligands, the binding modes of which had been determined experimentally using X-ray diffraction, were docked into their receptor binding sites. To produce statistically significant results, 20 MCDOCK runs were performed for each protein–ligand complex. It was found that a significant percentage of these MCDOCK runs converge to the experimentally observed binding mode. The root-mean-square (rms) of all non-hydrogen atoms of the ligand between the predicted and experimental binding modes ranges from 0.25 to 1.84 Å for these 19 cases. The computational time for each run on an SGI Indigo2/R10000 varies from less than 1 min to 15 min, depending upon the size and the flexibility of the ligands. Thus MCDOCK may be used to predict the precise binding mode of ligands in lead optimization and to discover novel lead compounds through structure-based database searching.     

Large scale free energy calculations for blind predictions of protein–ligand binding: the D3R Grand Challenge 2015

We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein–ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.     

Design and pharmacophoric identification of flavonoid scaffold-based aromatase inhibitors

Aromatase is a crucial enzyme for the catalysis of aromatization reaction at the last and rate-limiting step involved in the conversion of androgenic substrates to an estrogenic substrate. A hormone-dependent breast cancer in postmenopausal woman can be cured by inhibition of estrogen biosynthesis by the help of aromatase inhibitors (AIs). The mode of interactions of flavonones with the active site of aromatase has been studied in search of potent and selective AIs as a substitute of the natural steroidal ligand. Structure-based computational approach namely, molecular docking simulations were performed to investigate the structural features of the docked complex of aromatase and flavonoid ligands. A nonsteroidal flavonoid pharmacophore showing electrostatic and steric features for selective binding within the main pocket of the catalytic active site of aromatase has been identified as an outcome of the study. The binding affinity of quercetin and isoflavone were predicted within aromatase. Isoflavone was used as a negative control to compare its binding affinities with the selected dataset. The predicted binding affinity of negative control isoflavone was in accordance with its in vitro AI efficacy. Isoflavone showed poor binding affinity and ranked last in terms of MolDock score (−86.309 kcal/molÅ) compared to dataset molecules. The generated pharmacophoric information will be helpful for the synthetic chemist to design and synthesize selective AIs with comparable binding affinity to the natural steroidal ligand.     

Pharmacophore anchor models of ATAT1 to discover potential inhibitors and lead optimization

Post-translation modification of microtubules is associated with many diseases like cancer. Alpha Tubulin Acetyltransferase 1 (ATAT1) is a major enzyme that acetylates ‘Lys-40’ in alpha-tubulin on the luminal side of microtubules and is a drug target that lacks inhibitors. Here, we developed pharmacophore anchor models of ATAT1 which were constructed statistically using thousands of docked compounds, for drug design and investigating binding mechanisms. Our models infer the compound moiety preferences with the physico-chemical properties for the ATAT1 binding site. The results from the pharmacophore anchor models show the three main sub-pockets, including S1 acetyl site, S2 adenine site, and S3 diphosphate site with anchors, where conserved moieties interact with respective sub-pocket residues in each site and help in guiding inhibitor discovery. We validated these key anchors by analyzing 162 homologous protein sequences (>99 species) and over 10 structures with various bound ligands and mutations. Our results were consistent with previous works also providing new interesting insights. Our models applied in virtual screening predicted several ATAT1 potential inhibitors. We believe that our model is useful for future inhibitor discovery and for guiding lead optimization.     

Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking,MM/GBSA,QM/MM,and free-energy simulations

We have estimated the binding affinity of three sets of ligands of the heat-shock protein 90 in the D3R grand challenge blind test competition. We have employed four different methods, based on five different crystal structures: first, we docked the ligands to the proteins with induced-fit docking with the Glide software and calculated binding affinities with three energy functions. Second, the docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method (molecular mechanics combined with generalised Born and solvent-accessible surface area solvation). Third, the docked structures were re-optimised by combined quantum mechanics and molecular mechanics (QM/MM) calculations. Then, interaction energies were calculated with quantum mechanical calculations employing 970–1160 atoms in a continuum solvent, combined with energy corrections for dispersion, zero-point energy and entropy, ligand distortion, ligand solvation, and an increase of the basis set to quadruple-zeta quality. Fourth, relative binding affinities were estimated by free-energy simulations, using the multi-state Bennett acceptance-ratio approach. Unfortunately, the results were varying and rather poor, with only one calculation giving a correlation to the experimental affinities larger than 0.7, and with no consistent difference in the quality of the predictions from the various methods. For one set of ligands, the results could be strongly improved (after experimental data were revealed) if it was recognised that one of the ligands displaced one or two water molecules. For the other two sets, the problem is probably that the ligands bind in different modes than in the crystal structures employed or that the conformation of the ligand-binding site or the whole protein changes.     

QXP: Powerful, rapid computer algorithms for structure-based drug design

New methods for docking, template fitting and building pseudo-receptors are described. Full conformational searches are carried out for flexible cyclic and acyclic molecules. QXP (quick explore) search algorithms are derived from the method of Monte Carlo perturbation with energy minimization in Cartesian space. An additional fast search step is introduced between the initial perturbation and energy minimization. The fast search produces approximate low-energy structures, which are likely to minimize to a low energy. For template fitting, QXP uses a superposition force field which automatically assigns short-range attractive forces to similar atoms in different molecules. The docking algorithms were evaluated using X-ray data for 12 protein–ligand complexes. The ligands had up to 24 rotatable bonds and ranged from highly polar to mostly nonpolar. Docking searches of the randomly disordered ligands gave rms differences between the lowest energy docked structure and the energy-minimized X-ray structure, of less than 0.76 Å for 10 of the ligands. For all the ligands, the rms difference between the energy-minimized X-ray structure and the closest docked structure was less than 0.4 Å, when parts of one of the molecules which are in the solvent were excluded from the rms calculation. Template fitting was tested using four ACE inhibitors. Three ACE templates have been previously published. A single run using QXP generated a series of templates which contained examples of each of the three. A pseudo-receptor, complementary to an ACE template, was built out of small molecules, such as pyrrole, cyclopentanone and propane. When individually energy minimized in the pseudo-receptor, each of the four ACE inhibitors moved with an rms of less than 0.25 Å. After random perturbation, the inhibitors were docked into the pseudo-receptor. Each lowest energy docked structure matched the energy-minimized geometry with an rms of less than 0.08 Å. Thus, the pseudo-receptor shows steric and chemical complementarity to all four molecules. The QXP program is reliable, easy to use and sufficiently rapid for routine application in structure-based drug design.     

Multiple ligand docking by Glide: implications for virtual second-site screening

Performance of Glide was evaluated in a sequential multiple ligand docking paradigm predicting the binding modes of 129 protein-ligand complexes crystallized with clusters of 2-6 cooperative ligands. Three sampling protocols (single precision-SP, extra precision-XP, and SP without scaling ligand atom radii-SP hard) combined with three different scoring functions (GlideScore, Emodel and Glide Energy) were tested. The effects of ligand number, docking order and druglikeness of ligands and closeness of the binding site were investigated. On average 36?% of all structures were reproduced with RMSDs lower than 2??. Correctly docked structures reached 50?% when docking druglike ligands into closed binding sites by the SP hard protocol. Cooperative binding to metabolic and transport proteins can dramatically alter pharmacokinetic parameters of drugs. Analyzing the cytochrome P450 subset the SP hard protocol with Emodel ranking reproduced two-thirds of the structures well. Multiple ligand binding is also exploited by the fragment linking approach in lead discovery settings. The HSP90 subset from real life fragment optimization programs revealed that Glide is able to reproduce the positions of multiple bound fragments if conserved water molecules are considered. These case studies assess the utility of Glide in sequential multiple docking applications.