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.

Dihedral angle study in Hesperidin using NMR Spectroscopy.

Hesperidin is flavonoid molecule found in citrus fruits (Citrus reticulata), especially difficult to extract, classify and characterize. Present work is to study the unresolved relative configuration of Hesperidin through the dihedral angle, coupling constant and different NMR techniques. The Karplus equation and its modifications have been originated from the valence bond theory and associated with dihedral angle and coupling constant. The result data set of calculated dihedral angle can probe significant method to assign the virtual configuration of natural products and also resolved stereochemistry of Hesperidin at C-2 position in. Copyright © 2016 John Wiley & Sons, Ltd.

Synthesis, screening for antitubercular activity and 3D-QSAR studies of substituted N-phenyl-6-methyl-2-oxo-4-phenyl-1,2,3,4-tetrahydro-pyrimidine-5-carboxamides.

Multi-drug resistance to commonly used antitubercular drugs has propelled the development of new structural classes of antitubercular agents. This paper reports the synthesis, evaluation and 3D-QSAR analysis of a set of substituted N-phenyl-6-methyl-2-oxo-4-phenyl-1,2,3,4-tetrahydropyrimidine-5-carboxamides as antitubercular agents. Substituted acetoacetanilides were reacted with various aromatic aldehydes and urea which yielded the tetrahydropyrimidine derivatives with a phenyl carbamoyl group at C5 position, and with various substitutions on the 4-phenyl and the N-phenyl aromatic rings. All compounds were screened for antitubercular activity against Mycobacterium tuberculosis H37Rv strain. The QSAR models were generated on a training set of 23 molecules. The molecules were aligned using the atom-fit and field-fit techniques. The CoMFA and CoMSIA models generated on the molecules aligned by the atom-fit method show a correlation coefficient (r2) of 0.98 and 0.95 with cross-validated r2(q2) of 0.68 and 0.58, respectively. The 3D-QSAR models were externally validated against a test set of 7 molecules for which the predictive r2 (r(pred)2) is recorded as 0.41 and 0.32 for the CoMFA and CoMSIA models, respectively. The CoMFA and CoMSIA contours helped to design some new molecules with improved activity.