Structural Investigations of Aroylindole Derivatives through 3D-QSAR and Multiple Pharmacophore Modeling for the Search of Novel Colchicines Inhibitor

Title:Structural Investigations of Aroylindole Derivatives through 3D-QSAR and Multiple Pharmacophore Modeling for the Search of Novel Colchicines Inhibitor

Volume: 18 Issue: 2

Author(s): Vijay Kumar Patel and Harish Rajak*

Affiliation:

• Medicinal Chemistry Research Laboratory, SLT Institute of Pharmaceutical Sciences, Guru Ghasidas University, Bilaspur 495 009, (C.G.),India

Keywords: Ligand and structure based, combretastatin a-4, aroylindole derivatives, 3D-QSAR, docking, colchicine.

Abstract:

Background: The ligand and structure based integrated strategies are being repeatedly and effectively employed for the precise search and design of novel ligands against various disease targets. Aroylindole derivative has a similar structural analogy as Combretastatin A-4, and exhibited potent anticancer activity on several cancer cell lines.

Objective: To identify structural features of aroylindole derivatives through 3D-QSAR and multiple pharmacophore modelling for the search of novel colchicines inhibitor via virtual screening.

Methods: The present study utilizes ligand and structure based methodology for the establishment of structure activity correlation among trimethoxyaroylindole derivatives and the search of novel colchicines inhibitor via virtual screening. The 3D-QSAR studies were performed using Phase module and provided details of relationship between structure and biological activity. A single ligand based pharmacophore model was generated from Phase on compound 3 and compound 29 and three energetically optimized structure based pharmacophore models were generated from epharmacophore for co-crystallized ligand, compound 3 and compound 29 with protein PBD ID 1SA0, 5EYP and 5LYJ. These pharmacophoric features containing hit-like compounds were collected from commercially available ZINC database and screened using virtual screening workflow.

Results and Discussion: The 3D-QSAR model studies with good PLSs statistics for factor four was characterized by the best prediction coefficient Q² (0.8122), regression R² (0.9405), SD (0.2581), F (102.7), P (1.56e-015), RMSE (0.402), Stability (0.5411) and Pearson-r (0.9397). The generated epharmacophores have GH scores over 0.5 and AUAC ≥ 0.7 indicated that all the pharmacophores were suitable for pharmacophore-based virtual screening. The virtual screened compounds ZINC12323179, ZINC01642724, and ZINC14238006 have showed similar structural alignment as co-crystallized ligand and showed the hydrogen bonding of ligand with ASN101, SER178, THR179, VAL238, CYS241 amino acid of protein.

Conclusion: The study illustrates that the ligand and structure based pharmacophoric approach is beneficial for identification of structurally diverse hits, having better binding affinity on colchicines binding site as novel anticancer agents.

Cite this article as:

Patel Kumar Vijay and Rajak Harish *, Structural Investigations of Aroylindole Derivatives through 3D-QSAR and Multiple Pharmacophore Modeling for the Search of Novel Colchicines Inhibitor, Letters in Drug Design & Discovery 2021; 18 (2) . https://dx.doi.org/10.2174/1570180817999200905092444