Multicomplex-based pharmacophore modeling in conjunction with multi-target docking and molecular dynamics simulations for the identification of PfDHFR inhibitors

Abstract

Plasmodium falciparum dihydrofolate reductase enzyme (PfDHFR) is counted as one of the attractive and validated antimalarial drug targets. However, the point mutations in the active site of wild-type PfDHFR have developed resistance against the well-known antifolates. Therefore, there is a dire need for the development of inhibitors that can inhibit both wild-type and mutant-type DHFR enzyme. In the present contribution, we have constructed the common feature pharmacophore models from the available PfDHFR. A representative hypothesis was prioritized and then employed for the screening of natural product library to search for the molecules with complementary features responsible for the inhibition. The screened candidates were processed via drug-likeness filters and molecular docking studies. The docking was carried out on the wild-type PfDHFR (3QGT); double-mutant PfDHFR (3UM5 and 1J3J) and quadruple-mutant PfDHFR (1J3K) enzymes. A total of eight common hits were obtained from the docking calculations that could be the potential inhibitors for both wild and mutant type DHFR enzymes. Eventually, the stability of these candidates with the selected proteins was evaluated via molecular dynamics simulations. Except for SPECS14, all the prioritized candidates were found to be stable throughout the simulation run. Overall, the strategy employed in the present work resulted in the retrieval of seven candidates that may show inhibitory activity against PfDHFR and could be further exploited as a scaffold to develop novel antimalarials.

Communicated by Ramaswamy H. Sarma     

Understanding the relative affinity and specificity of the substrate binding site of protein kinase B for substrate-mimetic inhibitors

Designing selective inhibitor of protein kinase B (PKB/Akt) is an area of intense research to develop potential anticancer drugs. As a general point of strategy, the peptide substrate-binding site only responds to a highly specific sequence of amino acids. Targeting the substrate-mimetic inhibitors to the peptide substrate-binding site has the potential for better selectivity. It is therefore of great interest to understand the peptide substrate binding mode of PKB, as well as its specificity and affinity for different substrate-mimetic inhibitors. In the present study, we used molecular dynamic simulations to better understand the interactions of the PKB substrate-binding site with the substrate-mimetic inhibitors. Our computational models successfully mirrored PKB’s selectivity for the substrate-mimetic inhibitors. Furthermore, the key residues interacting with the substrate-mimetic inhibitor were discussed by analysing the different interaction modes of these inhibitors, with different inhibitory potencies, binding to PKB and by comparing the different binding free energy contributions of corresponding residues around the binding pocket. The pharmacophoric requirements were then also summarised for the substrate-mimetic inhibitor binding to PKB. It is expected that this work will provide useful chemical or biochemical informatics for the design of novel and potent substrate-mimetic inhibitors of PKB.     

Zika virus NS5 protein potential inhibitors: an enhanced in silico approach in drug discovery

The re-emerging Zika virus (ZIKV) is an arthropod-borne virus that has been described to have explosive potential as a worldwide pandemic. The initial transmission of the virus was through a mosquito vector, however, evolving modes of transmission has allowed the spread of the disease over continents. The virus has already been linked to irreversible chronic central nervous system conditions. The concerns of the scientific and clinical community are the consequences of Zika viral mutations, thus suggesting the urgent need for viral inhibitors. There have been large strides in vaccine development against the virus but there are still no FDA approved drugs available. Rapid rational drug design and discovery research is fundamental in the production of potent inhibitors against the virus that will not just mask the virus, but destroy it completely. In silico drug design allows for this prompt screening of potential leads, thus decreasing the consumption of precious time and resources. This study demonstrates an optimized and proven screening technique in the discovery of two potential small molecule inhibitors of ZIKV Methyltransferase and RNA dependent RNA polymerase. This in silico ‘per-residue energy decomposition pharmacophore’ virtual screening approach will be critical in aiding scientists in the discovery of not only effective inhibitors of Zika viral targets, but also a wide range of anti-viral agents.     

Molecular modeling study for the design of novel acetyl-CoA carboxylase inhibitors using 3D QSAR,molecular docking and dynamic simulations

Acetyl-CoA carboxylase (ACC) enzyme plays an important role in the regulation of biosynthesis and oxidation of fatty acids. ACC is a recognized drug target for the treatment of obesity and diabetes. Combination of ligand and structure-based in silico methods along with activity and toxicity prediction provides best lead compounds in the drug discovery process. In this study, a data-set of 100 ACC inhibitors were used for the development of comparative molecular field analysis (CoMFA) and comparative molecular similarity index matrix analysis (CoMSIA) models. The generated contour maps were used for the design of novel ACC inhibitors. CoMFA and CoMSIA models were used for the predication of activity of designed compounds. In silico toxicity risk prediction study was carried out for the designed compounds. Molecular docking and dynamic simulations studies were performed to know the binding mode of designed compounds with the ACC enzyme. The designed compounds showed interactions with key amino acid residues important for catalysis, and good correlation was observed between binding free energy and inhibition of ACC.     

Pharmacophore and structure-based drug design,molecular dynamics and admet/tox studies to design novel potential pad4 inhibitors

We have used docking (GLIDE), pharmacophore modeling (Discovery Studio), long trajectory molecular dynamics (Discovery Studio) and ADMET/Tox (QikProp and DEREK) to investigate PAD4 in order to determine potential novel inhibitors and hits. We have carried out virtual screening in the ZINC natural compounds database. Pharmacokinetics and Toxicity of the best hits were assessed using databases implemented in softwares that create models based on chemical structures taking into account consideration about the toxicophoric groups. A wide variety of pharmaceutical relevant properties are determined in order to make decisions about molecular suitability. After screening and analysis, the 6 most promising PAD4 inhibitors are suggested, with strong interactions (pi-stacking, hydrogen bonds, hydrophobic contacts) and suitable pharmacotherapeutic profile as well.     

Molecular docking and pharmacophore model studies of Rho kinase inhibitors

Molecular docking and pharmacophore model approaches were used to characterise the binding features of four different series of Rho kinase (ROCK) inhibitors. Docking simulation of 20 inhibitors with ROCK was performed. The binding conformations and binding affinities of these inhibitors were obtained using AutoDock 4.0 software. The predicted binding affinities correlate well with the activities of these inhibitors (R ² = 0.904). 3D pharmacophore models were generated for ROCK based on highly active inhibitors implemented in Catalyst 4.11 program. The best pharmacophore model consists of one hydrogen bond acceptor feature and two hydrophobic features, and they all seemed to be essential for inhibitors in terms of their binding activities. It is anticipated that the findings reported in this paper may provide very useful information for designing new ROCK inhibitors.     

Identification of potential inhibitors for HCV NS5b of genotype 4a by combining dynamic simulation,protein–ligand interaction fingerprint, 3D pharmacophore,docking and 3D QSAR

Abstract

HCV NS5B polymerase has been one of the most attractive targets for developing new drugs for HCV infection and many drugs were successfully developed, but all of them were designed for targeting Hepatitis C Virus genotype 1 (HCV GT1). Hepatitis C virus genotype 4a (HCV GT4a) dominant in Egypt has paid less attention. Here, we describe our protocol of virtual screening in identification of novel potential potent inhibitors for HCV NS5B polymerase of GT4a using homology modeling, protein–ligand interaction fingerprint (PLIF), docking, pharmacophore, and 3D CoMFA quantitative structure activity relationship (QSAR). Firstly, a high-quality 3D model of HCV NS5B polymerase of GT4a was constructed using crystal structure of HCV NS5B polymerase of GT1 (PDB ID: 3hkw) as a template. Then, both the model and the template were simulated to compare conformational stability. PLIF was generated using five crystal structures of HCV NS5B (PDB ID: 4mia, 4mib, 4mk9, 4mka, and 4mkb), which revealed the most important residues and their interactions with the co-crystalized ligands. After that, a 3D pharmacophore model was developed from the generated PLIF data and then used as a screening filter for 17000328 drug-like zinc database compounds. 900 compounds passed the pharmacophore filter and entered the docking-based virtual screening stage. Finally, a 3D CoMFA QSAR was developed using 42 compounds as a training and 19 compounds as a test set. The 3D CoMFA QSAR was used to design and screen some potential inhibitors, these compounds were further evaluated by the docking stage. The highest ranked five hits from docking result (compounds (p1–p4) and compound q1) were selected for further analysis.

Communicated by Ramaswamy H. Sarma     

Multi-stage structure-based virtual screening approach towards identification of potential SARS-CoV-2 NSP13 helicase inhibitors

On account of its crucial role in the virus life cycle, SARS-COV-2 NSP13 helicase enzyme was exploited as a promising target to identify a novel potential inhibitor using multi-stage structure-based drug discovery approaches. Firstly, a 3D pharmacophore was generated based on the collected data from a protein-ligand interaction fingerprint (PLIF) study using key interactions between co-crystallised fragments and the NSP13 helicase active site. The ZINC database was screened through the generated 3D-pharmacophore retrieving 13 potential hits. All the retrieved hits exceeded the benchmark score of the co-crystallised fragments at the molecular docking step and the best five-hit compounds were selected for further analysis. Finally, a combination between molecular dynamics simulations and MM-PBSA based binding free energy calculations was conducted on the best hit (compound FWM-1) bound to NSP13 helicase enzyme, which identified FWM-1 as a potential potent NSP13 helicase inhibitor with binding free energy equals −328.6 ± 9.2 kcal/mol.     

Exploration of potential RSK2 inhibitors by pharmacophore modelling,structure-based 3D-QSAR,molecular docking study and molecular dynamics simulation

Abstract

The p90 ribosomal s6 kinase 2 (RSK2) is a promising target because of its over expression and activation in human cancer cells and tissues. Over the last few years, significant efforts have been made in order to develop RSK2 inhibitors to treat myeloma, prostatic cancer, skin cancer and etc., but with limited success so far. In this paper, pharmacophore modelling, molecular docking study and molecular dynamics (MD) simulation have been performed to explore the novel inhibitors of RSK2. Pharmacophore models were developed by 95 molecules having pIC₅₀ ranging from 4.577 to 9.000. The pharmacophore model includes one hydrogen bond acceptor (A), one hydrogen bond donor (D), one hydrophobic feature (H) and one aromatic ring (R). It is the best pharmacophore hypothesis that has the highest correlation coefficient (R² = 0.91) and cross validation coefficient (Q² = 0.71) at 5 component PLS factor. It was evaluated using enrichment analysis and the best model was used for virtual screening. The constraints used in this study were docking score, ADME properties, binding free energy estimates and IFD Score to screen the database. Ultimately, 12 hits were identified as potent and novel RSK2 inhibitors. A 15 ns molecular dynamics (MD) simulation was further employed to validate the reliability of the docking results.     

Identification of two natural compound inhibitors of Leishmania donovani Spermidine Synthase (SpdS) through molecular docking and dynamic studies

Visceral leishmaniasis caused by the protozoan Leishmania donovani is the most severe form of leishmaniasis and it is potentially lethal if untreated. Despite the availability of drugs for treating the disease, the current drug regime suffers from drawbacks like antibiotic resistance and toxicity. New drugs have to be discovered in order to overcome these limitations. Our aim is to identify natural compounds from plant sources as putative inhibitors considering the occurrence of structural diversity in plant sources. Spermidine Synthase (SpdS) was chosen as the target enzyme as it plays a vital role in growth, survival, and due to its contribution in virulence. Our initial investigation started with a literature survey in identifying natural compounds that showed antileishmanial activity. Subsequently, we identified two monoterpenoid compounds, namely Geraniol and Linalool, that were structurally analogous to one of the substrates (putrescine) of SpdS. In the present study, homology model of L. donovani SpdS was generated and the binding affinity of the identified compounds was analyzed and also compared with the putrescine through molecular docking and dynamic studies. The pharmacokinetic properties of the identified compounds were validated and the binding efficiency of these ligands over the original substrate has been demonstrated. Based on these studies, Geraniol and Linalool can be considered as lead molecules for future investigations targeting SpdS. This study further emphasizes the choice of natural compounds as a good source of therapeutic agents.     

Ligand-based pharmacophore modeling and docking studies on vitamin D receptor inhibitors

In recent years, pharmacophore modeling and molecular docking approaches have been extensively used to characterize the structural requirements and explore the conformational space of a ligand in the binding pocket of the selected target protein. Herein, we report a pharmacophore modeling and molecular docking of 45 compounds comprising of the indole scaffold as vitamin D receptor (VDR) inhibitors. Based on the selected best hypothesis (DRRRR.61), an atom-based three-dimensional quantitative structure-activity relationships model was developed to rationalize the structural requirement of biological activity modulating components. The developed model predicted the binding affinity for the training set and test set with R²_(training) = 0.8869 and R²_(test) = 0.8139, respectively. Furthermore, molecular docking and dynamics simulation were performed to understand the underpinning of binding interaction and stability of selected VDR inhibitors in the binding pocket. In conclusion, the results presented here, in the form of functional and structural data, agreed well with the proposed pharmacophores and provide further insights into the development of novel VDR inhibitors with better activity.     

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.     

Molecular mechanism study of several inhibitors binding to BRD9 bromodomain based on molecular simulations

Bromodomain-containing protein 9 (BRD9) has been employed as a potential target for anticancer drugs in recent years. In this work, molecular docking, molecular dynamics (MD) simulations, binding free energy calculations, and per residue energy decomposition approaches were performed to elucidate the different binding modes between four pyridinone-like scaffold inhibitors and BRD9 bromodomain. Analysis results indicate that non-polar contribution mainly deriving from van der Waals energy is a critical impact on binding affinity of inhibitors against BRD9. Some key residues Phe44, Phe47, Val49, and Ile53 (at ZA loop) enhance the binding energy of inhibitors in BRD9 by means of providing hydrophobic interactions. Moreover, it is observed that BRD9 is anchored by the formation of a stable hydrogen bond between the carbonyl of the inhibitors and the residue Asn100 (at BC loop), and a strong π–π stacking interaction formed between the residue Tyr106 (at BC loop) and the inhibitors. The existence of dimethoxyphenyl structure and the aromatic ring merged to pyridinone scaffold are useful to enhance the BRD9 binding affinity. These findings should guide the rational design of more prospective inhibitors targeting BRD9.

Communicated by Ramaswamy H. Sarma     

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     

Identification of novel natural inhibitors of Opisthorchis felineus cytochrome P450 using structure-based screening and molecular dynamic simulation

Opisthorchis felineus is the etiological agent of opisthorchiasis in humans. O. felineus cytochrome P450 (OfCYP450) is an important enzyme in the parasite xenobiotic metabolism. To identify the potential anti-opisthorchid compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,65,869) against the OfCYP450. The ligands were screened against OfCYP450 in four sequential docking modes that resulted in 361 ligands having better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 10 compounds were found to fit well with re-docking studies. After refinement by docking and drug-likeness analyses, four potential inhibitors (ZINC2358298, ZINC8790946, ZINC70707116, and ZINC85878789) were identified. These ligands with reference compounds (itraconazole and fluconazole) were further subjected to molecular dynamics simulation (MDS) and binding energy analyses to compare the dynamic structure of protein after ligand binding and the stability of the OfCYP450 and bound complexes. The binding energy analyses were also calculated. The results suggested that the compounds had a negative binding energy with ?259.41, ?110.09, ?188.25, ?163.30, ?202.10, and ?158.79 kJ mol^?1 for itraconazole, fluconazole, and compounds with IDs ZINC2358298, ZINC8790946, ZINC70707116, and ZINC85878789, respectively. These lead compounds displayed significant pharmacological and structural properties to be drug candidates. On the basis of MDS results and binding energy analyses, we concluded that ZINC8790946, ZINC70707116, and ZINC85878789 have excellent potential to inhibit OfCYP450.     

Position-resolved free energy of solvation for amino acids in lipid membranes from molecular dynamics simulations

Studies of insertion and interactions of amino acids in lipid membranes are pivotal to our understanding of membrane protein structure and function. Calculating the insertion cost as a function of transmembrane helix sequence is thus an important step towards improved membrane protein prediction and eventually drug design. Here, we present position-dependent free energies of solvation for all amino acid analogs along the membrane normal. The profiles cover the entire region from bulk water to hydrophobic core, and were produced from all-atom molecular dynamics simulations. Experimental differences corresponding to mutations and costs for entire segments match experimental data well, and in addition the profiles provide the spatial resolution currently not available from experiments. Polar side-chains largely maintain their hydration and assume quite ordered conformations, which indicates the solvation cost is mainly entropic. The cost of solvating charged side-chains is not only significantly lower than for implicit solvation models, but also close to experiments, meaning these could well maintain their protonation states inside the membrane. The single notable exception to the experimental agreement is proline, which is quite expensive to introduce in vivo despite its hydrophobicity--a difference possibly explained by kinks making it harder to insert helices in the translocon.     

In silico guided development of imine-based inhibitors for resistance-deriving kinases

Two major mechanisms involved in resistant NSCLC (non-small cell lung cancer) include secondary acquired mutation in EGFR (epidermal growth factor receptor), that is, EGFR T790M and amplification of c-MET (hepatocyte growth factor receptor). Thus, already established pharmacophore models of EGFR T790M and c-MET were employed to filter-out an in-house database. Further fitness score led to the selection of imino-pyrimidine scaffold. Followed by sketching of imino-pyrimidine derivatives having varied aryl substitutions, which were then docked and subjected to molecular dynamic simulations, to study the orientations and conformations of the designed molecules in the catalytic domain. Molecules with hydrophobic interaction with mutant residue M790 were selected. Finally, MM-GBSA (Molecular Mechanics‐Generalized Born Surface Area) calculations were performed, to study the effect of substitutions on the binding affinity of the double mutant EGFR towards these small molecules. Finally, the designed compounds were synthesized and evaluated for their kinase inhibitory potential using in-vitro experiments. Two compounds were found to possess sub-micromolar range inhibitory potential against EGFR (T790M), while one of the compound showed significant selective inhibitory potential against c-MET. Additionally, one compound was found to possess significant dual inhibitory potential against these target kinases.

Communicated by Ramaswamy H. Sarma     

In silico design and molecular basis for the selectivity of Olinone toward the first over the second bromodomain of BRD4

Bromodomains (BrDs), a conserved structural module in chromatin-associated proteins, are well known for recognizing ε-N-acetyl lysine residues on histones. One of the most relevant BrDs is BRD4, a tandem BrD containing protein (BrD1 and BrD2) that plays a critical role in numerous diseases including cancer. Growing evidence shows that the two BrDs of BRD4 have different biological functions; hence selective ligands that can be used to study their functions are of great interest. Here, as a follow-up of our previous work, we first provide a detailed characterization study of the in silico rational design of Olinone as part of a series of five tetrahydropyrido indole-based compounds as BRD4 BrD1 inhibitors. Additionally, we investigated the molecular basis for Olinone's selective recognition by BrD1 over BrD2. Molecular dynamics simulations, free energy calculations, and conformational analyses of the apo-BRD4-BrD1|2 and BRD4-BrD1|2/Olinone complexes showed that Olinone's selectivity is facilitated by five key residues: Leu92 in BrD1|385 in BrD2 of ZA loop, Asn140|433, Asp144|His437 and Asp145|Glu438 of BC loop, and Ile146|Val49 of helix C. Furthermore, the difference in hydrogen bonds number and in mobility of the ZA and BC loops of the acetyl-lysine binding site between BRD4 BrD1/Olinone and BrD2/Olinone complexes also contribute to the difference in Olinone's binding affinity and selectivity toward BrD1 over BrD2. Altogether, our computer-aided molecular design techniques can effectively guide the development of small-molecule BRD4 BrD1 inhibitors, explain their selectivity origin, and further open doors to the design of new therapeutically improved derivatives.     

The discovery of novel and selective fatty acid binding protein 4 inhibitors by virtual screening and biological evaluation

Adipocyte fatty acid binding protein (AFABP, FABP4) has been proven to be a potential therapeutic target for diabetes, atherosclerosis and inflammation-related diseases. In this study, a series of new scaffolds of small molecule inhibitors of FABP4 were identified by virtual screening and were validated by a bioassay. Fifty selected compounds were tested, which led to the discovery of seven hits. Structural similarity-based searches were then performed based on the hits and led to the identification of one high affinity compound 33b (K_i = 0.29 ± 0.07 μM, ΔT_m = 8.5 °C). This compound’s effective blockade of inflammatory response was further validated by its ability to suppress pro-inflammatory cytokines induced by lipopolysaccharide (LPS) stimulation. Molecular dynamics simulation (MD) and mutagenesis studies validated key residues for its inhibitory potency and thus provide an important clue for the further development of drugs.