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

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.

Multicomplex-based pharmacophore modeling coupled with molecular dynamics simulations: An efficient strategy for the identification of novel inhibitors of PfDHODH.

Enormous efforts have been made in the past to identify novel scaffolds against the potential therapeutic target, Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH). Fourteen different organic molecules have been crystallized to understand the structural basis of the inhibition. However, the pharmacophoric studies carried out so far, have not exploited all the structural information simultaneously to identify the novel inhibitors. Therefore, an attempt was made to construct the pharmacophore hypotheses from the available PfDHODH structural proteome. Among the generated hypotheses, a representative hypothesis was employed as a primary filter to list the molecules with complimentary features accountable for inhibition. Moreover, the auxiliary evaluations of the filtered molecules were accomplished via docking and drug-likeness studies. Subsequently, the stability of the protein-ligand complex was evaluated by using molecular dynamics simulations (MDs). The molecular details of binding interactions of the potential hits were compared with the highly active experimental structure (5FI8) to seek the more potent candidates that can be targeted against PfDHODH. Overall, the combination of screening and stability procedures resulted in the identification of three potent candidates. The drug-likeness of these molecules lie within the acceptable range and consequently increased the opportunities for their development to new anti-malarials.

Structural Investigation of Vinca Domain Tubulin Binders by Pharmacophore, Atom based QSAR, Docking and Molecular Dynamics Simulations.

AIM AND OBJECTIVE: Vinca domain of tubulin protein is the potential target for different microtubule targeting drugs (MTD). However, its binding mechanism and structure-activityrelationship (SAR) is not well understood in terms of ligand-receptor interactions and structure functionality requirements. This limits the exploitation of vinca domain for developing novel clinical leads. Herein, as a progressive step towards the exploration of this target, we rendered the in-silico insight through the development of a robust pharmacophore model followed by the QSAR, Molecular Docking and Molecular Dynamics (MD) simulations. Furthermore, the study was undertaken to identify potent inhibitors that can inhibit vinca domain of tubulin. MATERIALS AND METHODS: Utilizing the well-defined tubulin polymerization inhibition activities, common pharmacophore hypotheses were constructed and scored for their rankings. The hypotheses were validated by 3D-Atom based QSAR and tested for various statistically relevant metrices. Thereafter, virtual screening was performed with ZINC natural product database and the screened hits were evaluated for structure-based studies via molecular docking and molecular dynamics simulations. RESULTS: The predictive 3D-QSAR based pharmacophore model consists of two hydrogen bond acceptors (A), two hydrogen bond donors (D) and one hydrophobic (H) group. Significance of the model was reflected from the statistical parameters viz. r2 = 0.98, q2 = 0.72, F = 562.9, RMSE = 0.11 and Pearson-R = 0.87. Further, the docking scores of the retrieved hits deciphered that the ligands were adequately bound in the pocket. Moreover, RMSD fluctuations of protein (1.0 to 1.75A) and ligand (0.3 to 2.3 Å) in molecular dynamics simulations insinuate towards the conformational and interactions stability of the complexes. CONCLUSION: The quantitative pharmacophore model was developed from range of natural product scaffolds in order to incorporate all the complimentary features accountable for inhibition. The obtained hits were found to occupy similar binding region and superimpose well over the reference ligand. Therefore, it can be concluded that hierarchical combination of methods exploited in this study can steer the identification of novel scaffolds. Moreover, the rendered hit molecules could serve as potential inhibitory leads for the development of improved inhibitors targeting Vinca domain.