Molecular modeling studies on nucleoside hydrolase from the biological warfare agent Brucella suis

Brucella suis is a dangerous biological warfare agent already used for military purposes. This bacteria cause brucellosis, a zoonosis highly infective and difficult to fight. An important selective target for chemotherapy against this disease is nucleoside hydrolase (NH), an enzyme still not found in mammals. We present here the first three-dimensional structure of B. suis NH (BsNH) and propose this enzyme as a molecular target to the drug design in the fight against brucellosis. In addition, we performed molecular docking studies, aiming to analyze the three-dimensional positioning of nine known inhibitors of Chritidia fasciculata NH (CfNH) in the active sites of BsNH and CfNH. We also analyzed the main interactions of some of these compounds inside the active site of BsNH and the relevant factors to biological activity. These results, together with further molecular dynamics (MD) simulations, pointed out to the most promising compound as lead for the design of potential inhibitors of BsNH. Most of the docking and MD results corroborated to each other and the docking results also suggested a good correlation with experimental data.     

Design of new chemotherapeutics against the deadly anthrax disease. Docking and molecular dynamics studies of inhibitors containing pyrrolidine and riboamidrazone rings on nucleoside hydrolase from Bacillus anthracis

Anthrax is a disease caused by Bacillus anthracis, a dangerous biological warfare agent already used for both military and terrorist purposes. An important selective target for chemotherapy against this disease is nucleoside hydrolase (NH), an enzyme still not found in mammals. Having this in mind we have performed molecular docking studies, aiming to analyze the three-dimensional positioning of six known inhibitors of Trypanosoma vivax NH (TvNH) in the active site of B. anthracis NH (BaNH). We also analyzed the main interactions of these compounds with the active site residues of BaNH and the relevant factors to biological activity. These results, together with further molecular dynamics (MD) simulations, pointed out to the most promising compounds as lead for the design of potential inhibitors of BaNH. Most of the docking and MD results obtained corroborated to each other. Additionally, the docking results also suggested a good correlation with experimental data.     

Analysis of Bacillus anthracis nucleoside hydrolase via in silico docking with inhibitors and molecular dynamics simulation

As the enzyme nucleoside hydrolase (NH) is widely found in nature but has not yet been detected in mammals, it is considered an ideal target in the development of chemotherapy against parasitic diseases and bacterial infections like anthrax. Considering the risk that this biological warfare agent represents nowadays, the search for new drugs and new molecular targets in the development of chemotherapy against anthrax is imperative. On this basis, we performed docking studies of six known NH inhibitors at the active site of NH from Bacillus anthracis (BaNH). Subsequently, molecular dynamics (MD) simulations of these compounds inside BaNH were carried out in order to complement the docking studies and select the most promising compounds as leads for the design of potential BaNH inhibitors. Most of the docking and MD results obtained agreed well with each other and showed good correlation with experimental data.     

Virtual screening,docking, and dynamics of potential new inhibitors of dihydrofolate reductase from Yersinia pestis

In the present work, we propose to design drugs that target the enzyme dihydrofolate redutase (DHFR) as a means of a novel drug therapy against plague. Potential inhibitors of DHFR from Yersinia pestis (YpDHFR) were selected by virtual screening and subjected to docking, molecular dynamics (MD) simulations, and Poisson–Boltzmann surface area method, in order to evaluate their interactions in the active sites of YpDHFR and human DHFR (HssDHFR). The results suggested selectivity for three compounds that were further used to propose the structures of six new potential selective inhibitors for YpDHFR.     

Preventing the return of smallpox: molecular modeling studies on thymidylate kinase from Variola virus

Smallpox was one of the most devastating diseases in the human history and still represents a serious menace today due to its potential use by bioterrorists. Considering this threat and the non-existence of effective chemotherapy, we propose the enzyme thymidylate kinase from Variola virus (VarTMPK) as a potential target to the drug design against smallpox. We first built a homology model for VarTMPK and performed molecular docking studies on it in order to investigate the interactions with inhibitors of Vaccinia virus TMPK (VacTMPK). Subsequently, molecular dynamics (MD) simulations of these compounds inside VarTMPK and human TMPK (HssTMPK) were carried out in order to select the most promising and selective compounds as leads for the design of potential VarTMPK inhibitors. Results of the docking and MD simulations corroborated to each other, suggesting selectivity towards VarTMPK and, also, a good correlation with the experimental data.     

Pharmacoinformatics analysis to identify inhibitors of Mtb-ASADH

Aspartate-semialdehyde dehydrogenase (ASADH; EC 1.2.1.11) is a key enzyme in the biosynthesis of essential amino acids in prokaryotes and fungi, inhibition of ASADH leads to the development of novel antitubercular agents. In the present work, a combined structure and ligand-based pharmacophore modeling, molecular docking, and molecular dynamics (MD) approaches were employed to identify potent inhibitors of mycobacterium tuberculosis (Mtb)-ASADH. The structure-based pharmacophore hypothesis consists of three hydrogen bond acceptor (HBA), two negatively ionizable, and one positively ionizable center, while ligand-based pharmacophore consists of additional one HBA and one hydrogen bond donor features. The validated pharmacophore models were used to screen the chemical databases (ZINC and NCI). The screened hits were subjected to ADME and toxicity filters, and subsequently to the molecular docking analysis. Best-docked 25 compounds carry the characteristics of highly electronegative functional groups (–COOH and –NO₂) on both sides and exhibited the H-bonding interactions with highly conserved residues Arg99, Arg249, and His256. For further validation of docking results, MD simulation studies were carried out on two representative compounds NSC51108 and ZINC04203124. Both the compounds remain bound to the key active residues of Mtb-ASADH during the MD simulations. These identified hits can be further used for lead optimization and in the design more potent inhibitors against Mtb-ASADH.     

Understanding microscopic binding of macrophage migration inhibitory factor with phenolic hydrazones by molecular docking, molecular dynamics simulations and free energy calculations

Macrophage migration inhibitory factor (MIF), an immunoregulatory protein, is a potential target for a number of inflammatory diseases. In the current work, the interactions between MIF and a series of phenolic hydrazones were studied by molecular docking, molecular dynamics (MD) simulations, binding free energy calculations, and binding energy decomposition analysis to determine the structural requirement for achieving favorable biological activity of phenolic hydrazones. First, molecular docking was used to predict the binding modes of inhibitors in the binding site of MIF. The good correlation between the predicted docking scores and the experimental activities shows that the binding conformations of the inhibitors in the active site of MIF are well predicted. Moreover, our results suggest that the flexibility of MIF is essential in ligand binding process. Then, MD simulations and MM/GBSA free energy calculations were employed to determine the dynamic binding process and compare the binding modes of the inhibitors with different activities. The predicted binding free energies given by MM/GBSA are not well correlated with the experimental activities for the two subsets of the inhibitors; however, for each subset, a good correlation between the predicted binding free energies and the experimental activities is achieved. The MM/GBSA free energy decomposition analysis highlights the importance of hydrophobic residues for the MIF binding of the studied inhibitors. Based on the essential factors for MIF-inhibitor interactions derived from the theoretical predictions, some derivatives were designed and the higher inhibitory activities of several candidates were confirmed by molecular docking studies. The structural insights obtained from our study are useful for designing potent inhibitors of MIF.     

Molecular docking and 3D-QSAR-based virtual screening of flavonoids as potential aromatase inhibitors against estrogen-dependent breast cancer

Aromatase, catalyzing final step of estrogen biosynthesis, is considered a key target for the development of drug against estrogen-dependent breast cancer (EDBC). Identification and development of naturally occurring compounds, such as flavonoids, as drugs against EDBC is in demand due to their lesser toxicity when compared to those of synthetic ones. Thus, a three-dimensional quantitative structure–activity relationship, using comparative molecular field analysis (CoMFA) was done on a series of 45 flavonoids against human aromatase. A significant cross-validated correlation coefficient (q²) of 0.827 was obtained. The best predictive CoMFA model explaining the biological activity of the training and test sets with correlation coefficient values (r²) of 0.916 and 0.710, respectively, when used for virtual screening of a flavanoids database following molecular docking revealed a flavanone namely, 7-hydroxyflavanone beta-D-glucopyranoside showing highest predicted activity of 1.09?μM. In comparison to a well-established inhibitor of aromatase, namely 7-hydroxyflavanone (IC₅₀: 3.8?μM), the derivative identified in the present study, namely 7-hydroxyflavanone beta-D-glucopyranoside exhibited about 3.5 folds higher inhibitory activity against aromatase. The result of virtual screening was further validated using molecular dynamics (MD) simulation analysis. Thus, a 25 ns MD simulation analysis revealed high stability and effective binding of 7-hydroxyflavanone beta-D-glucopyranoside within the active site of aromatase. To the best of our knowledge, this is the first report of CoMFA-based QSAR model for virtual screening of flavonoids as inhibitors of aromatase.     

3D-QSAR,molecular docking,and molecular dynamic simulations for prediction of new Hsp90 inhibitors based on isoxazole scaffold

Heat shock protein 90(Hsp90), as a molecular chaperone, play a crucial role in folding and proper function of many proteins. Hsp90 inhibitors containing isoxazole scaffold are currently being used in the treatment of cancer as tumor suppressers. Here in the present studies, new compounds based on isoxazole scaffold were predicted using a combination of molecular modeling techniques including three-dimensional quantitative structure–activity relationship (3D-QSAR), molecular docking and molecular dynamic (MD) simulations. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were also done. The steric and electrostatic contour map of CoMFA and CoMSIA were created. Hydrophobic, hydrogen bond donor and acceptor of CoMSIA model also were generated, and new compounds were predicted by CoMFA and CoMSIA contour maps. To investigate the binding modes of the predicted compounds in the active site of Hsp90, a molecular docking simulation was carried out. MD simulations were also conducted to evaluate the obtained results on the best predicted compound and the best reported Hsp90 inhibitors in the 3D-QSAR model. Findings indicate that the predicted ligands were stable in the active site of Hsp90.     

Searching the conformational complexity and binding properties of HDAC6 through docking and molecular dynamic simulations

Histone deacetylases (HDACs) are a family of proteins involved in the deacetylation of histones and other non-histones substrates. HDAC6 belongs to class II and shares similar biological functions with others of its class. Nevertheless, its three-dimensional structure that involves the catalytic site remains unknown for exploring the ligand recognition properties. Therefore, in this contribution, homology modeling, 100-ns-long Molecular Dynamics (MD) simulation and docking calculations were combined to explore the conformational complexity and binding properties of the catalytic domain 2 from HDAC6 (DD2-HDAC6), for which activity and affinity toward five different ligands have been reported. Clustering analysis allowed identifying the most populated conformers present during the MD simulation, which were used as starting models to perform docking calculations with five DD2-HDAC6 inhibitors: Cay10603 (CAY), Rocilinostat (RCT), Tubastatin A (TBA), Tubacin (TBC), and Nexturastat (NXT), and then were also submitted to 100-ns-long MD simulations. Docking calculations revealed that the five inhibitors bind at the DD2-HDAC6 binding site with the lowest binding free energy, the same binding mode is maintained along the 100-ns-long MD simulations. Overall, our results provide structural information about the molecular flexibility of apo and holo DD2-HDAC6 states as well as insight of the map of interactions between DD2-HDAC6 and five well-known DD2-HDAC6 inhibitors allowing structural details to guide the drug design. Finally, we highlight the importance of combining different theoretical approaches to provide suitable structural models for structure-based drug design.     

Molecular modeling studies of Yersinia pestis dihydrofolate reductase

Considering the risk represented by plague today as a potential biological warfare agent, we propose cytosolic Yersinia pestis dihydrofolate reductase (YpDHFR) as a new target to the design of selective plague chemotherapy. This enzyme has a low homology with the human enzyme and its crystallographic structure has been recently deposited in the Protein Data Bank (PDB). Comparisons of the docking energies and molecular dynamic behaviors of five known DHFR inhibitors inside a 3D model of YpDHFR (adapted from the crystallographic structure) and human DHFR (HssDHFR), revealed new potential interactions and suggested insights into the design of more potent HssDHFR inhibitors as well as selective inhibitors for YpDHFR.     

Exploration of a binding mode of indole amide analogues as potent histone deacetylase inhibitors and 3D-QSAR analyses

Docking simulations and three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses were conducted on a series of indole amide analogues as potent histone deacetylase inhibitors. The studies include comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Selected ligands were docked into the active site of human HDAC1. Based on the docking results, a novel binding mode of indole amide analogues in the human HDAC1 catalytic core is presented, and enzyme/inhibitor interactions are discussed. The indole amide group is located in the open pocket, and anchored to the protein through a pair of hydrogen bonds with Asp99 O-atom and amide NH group on ligand. Based on the binding mode, predictive 3D-QSAR models were established, which had conventional r2 and cross-validated coefficient values (r(cv)2) up to 0.982 and 0.601 for CoMFA and 0.954 and 0.598 for CoMSIA, respectively. A comparison of the 3D-QSAR field contributions with the structural features of the binding site showed good correlation between the two analyses. The results of 3D-QSAR and docking studies validate each other and provided insight into the structural requirements for activity of this class of molecules as HDAC inhibitors. The CoMFA and CoMSIA PLS contour maps and MOLCAD-generated active site electrostatic, lipophilicity, and hydrogen-bonding potential surface maps, as well as the docking studies, provided good insights into inhibitor-HDAC interactions at the molecular level. Based on these results, novel molecules with improved activity can be designed.     

Shape-based virtual screening,docking, and molecular dynamics simulations to identify Mtb-ASADH inhibitors

Aspartate β-semialdehyde dehydrogenase (ASADH) is a key enzyme for the biosynthesis of essential amino acids and several important metabolites in microbes. Inhibition of ASADH enzyme is a promising drug target strategy against Mycobacterium tuberculosis (Mtb). In this work, in silico approach was used to identify potent inhibitors of Mtb-ASADH. Aspartyl β-difluorophosphonate (β-AFP), a known lead compound, was used to understand the molecular recognition interactions (using molecular docking and molecular dynamics analysis). This analysis helped in validating the computational protocol and established the participation of Arg99, Glu224, Cys130, Arg249, and His256 amino acids as the key amino acids in stabilizing ligand–enzyme interactions for effective binding, an essential feature is H-bonding interactions with the two arginyl residues at the two ends of the ligand. Best binding conformation of β-AFP was selected as a template for shape-based virtual screening (ZINC and NCI databases) to identify compounds that competitively inhibit the Mtb-ASADH. The top rank hits were further subjected to ADME and toxicity filters. Final filter was based on molecular docking analysis. Each screened molecule carries the characteristics of the highly electronegative groups on both sides separated by an average distance of 6?Å. Finally, the best predicted 20 compounds exhibited minimum three H-bonding interactions with Arg99 and Arg249. These identified hits can be further used for designing the more potent inhibitors against ASADH family. MD simulations were also performed on two selected compounds (NSC4862 and ZINC02534243) for further validation. During the MD simulations, both compounds showed same H-bonding interactions and remained bound to key active residues of Mtb-ASADH.     

Insight into the structural requirements of aminopyrimidine derivatives for good potency against both purified enzyme and whole cells of M. tuberculosis: combination of HQSAR,CoMSIA, and MD simulation studies

The Mycobacterium tuberculosis protein kinase B (PknB) is critical for growth and survival of M. tuberculosis within the host. The series of aminopyrimidine derivatives show impressive activity against PknB (IC₅₀ < .5 μM). However, most of them show weak or no cellular activity against M. tuberculosis (MIC > 63 μM). Consequently, the key structural features related to activity against of both PknB and M. tuberculosis need to be investigated. Here, two- and three-dimensional quantitative structure–activity relationship (2D and 3D QSAR) analyses combined with molecular dynamics (MD) simulations were employed with the aim to evaluate these key structural features of aminopyrimidine derivatives. Hologram quantitative structure–activity relationship (HQSAR) and CoMSIA models constructed from IC₅₀ and MIC values of aminopyrimidine compounds could establish the structural requirements for better activity against of both PknB and M. tuberculosis. The NH linker and the R₁ substituent of the template compound are not only crucial for the biological activity against PknB but also for the biological activity against M. tuberculosis. Moreover, the results obtained from MD simulations show that these moieties are the key fragments for binding of aminopyrimidine compounds in PknB. The combination of QSAR analysis and MD simulations helps us to provide a structural concept that could guide future design of PknB inhibitors with improved potency against both the purified enzyme and whole M. tuberculosis cells.     

Molecular design of new aggrecanases-2 inhibitors

Aggrecanases-2 is a very important potential drug target for the treatment of osteoarthritis. In this study, a series of known aggrecanases-2 inhibitors was analyzed by the technologies of three-dimensional quantitative structure–activity relationships (3D-QSAR) and molecular docking. Two 3D-QSAR models, which based on comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) methods, were established. Molecular docking was employed to explore the details of the interaction between inhibitors and aggrecanases-2 protein. According to the analyses for these models, several new potential inhibitors with higher activity predicted were designed, and were supported by the simulation of molecular docking. This work propose the fast and effective approach to design and prediction for new potential inhibitors, and the study of the interaction mechanism provide a better understanding for the inhibitors binding into the target protein, which will be useful for the structure-based drug design and modifications.     

Molecular dynamics simulation study and hybrid pharmacophore model development in human LTA4H inhibitor design

Human leukotriene A4 hydrolase (hLTA4H) is a bi-functional enzyme catalyzes the hydrolase and aminopeptidase functions upon the fatty acid and peptide substrates, respectively, utilizing the same but overlapping binding site. Particularly the hydrolase function of this enzyme catalyzes the rate-limiting step of the leukotriene (LT) cascade that converts the LTA4 to LTB4. This product is a potent pro-inflammatory activator of inflammatory responses and thus blocking this conversion provides a valuable means to design anti-inflammatory agents. Four structurally very similar chemical compounds with highly different inhibitory profile towards the hydrolase function of hLTA4H were selected from the literature. Molecular dynamics (MD) simulations of the complexes of hLTA4H with these inhibitors were performed and the results have provided valuable information explaining the reasons for the differences in their biological activities. Binding mode analysis revealed that the additional thiophene moiety of most active inhibitor helps the pyrrolidine moiety to interact the most important R563 and K565 residues. The hLTA4H complexes with the most active compound and substrate were utilized in the development of hybrid pharmacophore models. These developed pharmacophore models were used in screening chemical databases in order to identify lead candidates to design potent hLTA4H inhibitors. Final evaluation based on molecular docking and electronic parameters has identified three compounds of diverse chemical scaffolds as potential leads to be used in novel and potent hLTA4H inhibitor design.     

Insights into the structure and inhibition of Giardia intestinalis arginine deiminase: homology modeling,docking, and molecular dynamics studies

Giardia intestinalis arginine deiminase (GiADI) is an important metabolic enzyme involved in the energy production and defense of this protozoan parasite. The lack of this enzyme in the human host makes GiADI an attractive target for drug design against G. intestinalis. One approach in the design of inhibitors of GiADI could be computer-assisted studies of its crystal structure, such as docking; however, the required crystallographic structure of the enzyme still remains unresolved. Because of its relevance, in this work, we present a three-dimensional structure of GiADI obtained from its amino acid sequence using the homology modeling approximation. Furthermore, we present an approximation of the most stable dimeric structure of GiADI identified through molecular dynamics simulation studies. An in silico analysis of druggability using the structure of GiADI was carried out in order to know if it is a good target for design and optimization of selective inhibitors. Potential GiADI inhibitors were identified by docking of a set of 3196 commercial and 19 in-house benzimidazole derivatives, and molecular dynamics simulation studies were used to evaluate the stability of the ligand–enzyme complexes.     

Computational investigations of gram-negative bacteria phosphopantetheine adenylyltransferase inhibitors using 3D-QSAR,molecular docking and molecular dynamic simulations

Abstract

Phosphopantetheine adenylyltransferase (PPAT) has been recognized as a promising target to develop novel antimicrobial agents, which is a hexameric enzyme that catalyzes the penultimate step in coenzyme A biosynthesis. In this work, molecular modeling study was performed with a series of PPAT inhibitors using molecular docking, three-dimensional qualitative structure-activity relationship (3D-QSAR) and molecular dynamic (MD) simulations to reveal the structural determinants for their bioactivities. Molecular docking study was applied to understand the binding mode of PPAT with its inhibitors. Subsequently, 3D-QSAR model was constructed to find the features required for different substituents on the scaffolds. For the best comparative molecular field analysis (CoMFA) model, the Q² and R² values of which were calculated as 0.702 and 0.989, while they were calculated as 0.767 and 0.983 for the best comparative molecular similarity index analysis model. The statistical data verified the significance and accuracy of our 3D-QSAR models. Furthermore, MD simulations were carried out to evaluate the stability of the receptor–ligand contacts in physiological conditions, and the results were consistent with molecular docking studies and 3D-QSAR contour map analysis. Binding free energy was calculated with molecular mechanics generalized born surface area approach, the result of which coincided well with bioactivities and demonstrated that van der Waals accounted for the largest portion. Overall, our study provided a valuable insight for further research work on the recognition of potent PPAT inhibitors.

Communicated by Ramaswamy H. Sarma