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Structural Investigation of Vinca Domain Tubulin Binders by Pharmacophore, Atom based QSAR, Docking and Molecular Dynamics Simulations.
Comb Chem High Throughput Screen. 2017; 20(8):682-695.CC

Abstract

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.

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Authors+Show Affiliations

Athar M
School of Chemical Sciences, Central University of Gujarat, Gandhinagar 382030, Gujarat, India.
Lone MY
School of Chemical Sciences, Central University of Gujarat, Gandhinagar 382030, Gujarat, India.
Khedkar VM
School of Health Sciences, Discipline of Pharmaceutical Sciences, University of KwaZulu-Natal, Westville, Durban 4000. South Africa.
Radadiya A
National Facility for Drug Discovery Complex, Department of Chemistry, Saurashtra University, Rajkot 360005, Gujarat, India.
Shah A
National Facility for Drug Discovery Complex, Department of Chemistry, Saurashtra University, Rajkot 360005, Gujarat, India.
Jha PC
Centre for Applied Chemistry, Central University of Gujarat, Gandhinagar 382030, Gujarat, India.

MeSH

Biological ProductsDose-Response Relationship, DrugDrug Evaluation, PreclinicalHumansMolecular Docking SimulationMolecular Dynamics SimulationMolecular StructurePolymerizationQuantitative Structure-Activity RelationshipTubulinVinca

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

28486912

Citation

Athar, Mohd, et al. "Structural Investigation of Vinca Domain Tubulin Binders By Pharmacophore, Atom Based QSAR, Docking and Molecular Dynamics Simulations." Combinatorial Chemistry & High Throughput Screening, vol. 20, no. 8, 2017, pp. 682-695.
Athar M, Lone MY, Khedkar VM, et al. Structural Investigation of Vinca Domain Tubulin Binders by Pharmacophore, Atom based QSAR, Docking and Molecular Dynamics Simulations. Comb Chem High Throughput Screen. 2017;20(8):682-695.
Athar, M., Lone, M. Y., Khedkar, V. M., Radadiya, A., Shah, A., & Jha, P. C. (2017). Structural Investigation of Vinca Domain Tubulin Binders by Pharmacophore, Atom based QSAR, Docking and Molecular Dynamics Simulations. Combinatorial Chemistry & High Throughput Screening, 20(8), 682-695. https://doi.org/10.2174/1386207320666170509151253
Athar M, et al. Structural Investigation of Vinca Domain Tubulin Binders By Pharmacophore, Atom Based QSAR, Docking and Molecular Dynamics Simulations. Comb Chem High Throughput Screen. 2017;20(8):682-695. PubMed PMID: 28486912.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Structural Investigation of Vinca Domain Tubulin Binders by Pharmacophore, Atom based QSAR, Docking and Molecular Dynamics Simulations. AU - Athar,Mohd, AU - Lone,Mohsin Y, AU - Khedkar,Vijay M, AU - Radadiya,Ashish, AU - Shah,Anamik, AU - Jha,Prakash C, PY - 2016/11/12/received PY - 2017/03/02/revised PY - 2017/05/04/accepted PY - 2017/5/11/pubmed PY - 2018/12/13/medline PY - 2017/5/11/entrez KW - Pharmacophore KW - QSAR KW - antimitotic KW - microtubules KW - molecular docking KW - natural products KW - virtual screening SP - 682 EP - 695 JF - Combinatorial chemistry & high throughput screening JO - Comb Chem High Throughput Screen VL - 20 IS - 8 N2 - 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. SN - 1875-5402 UR - https://www.unboundmedicine.com/medline/citation/28486912/Structural_Investigation_of_Vinca_Domain_Tubulin_Binders_by_Pharmacophore_Atom_based_QSAR_Docking_and_Molecular_Dynamics_Simulations_ L2 - https://www.eurekaselect.com/152290/article DB - PRIME DP - Unbound Medicine ER -