Literature DB >> 25936945

QSAR based docking studies of marine algal anticancer compounds as inhibitors of protein kinase B (PKBβ).

G Dicky John Davis1, A Hannah Rachel Vasanthi2.   

Abstract

Marine algae are prolific source of bioactive secondary metabolites and are found to be active against different cancer cell lines. QSAR studies will explicate the significance of a particular class of descriptor in eliciting anticancer activity against a cancer type. Marine algal compounds showing anticancer activity against six different cancer cell lines namely MCF-7, A431, HeLa, HT-29, P388 and A549 taken from Seaweed metabolite database were subjected to comprehensive QSAR modeling studies. A hybrid-GA (genetic algorithm) optimization technique for descriptor space reduction and multiple linear regression analysis (MLR) approach was used as fitness functions. Cell lines HeLa and MCF-7 showed good statistical quality (R(2)∼0.75, Q(2)∼0.65) followed by A431, HT29 and P388 cell lines with reasonable statistical values (R(2)∼0.70, Q(2)∼0.60). The models developed were interpretable, with good statistical and predictive significance. Molecular descriptor analyses revealed that Baumann's alignment-independent topological descriptors had a major role in variation of activity along with other descriptors. Incidentally, earlier QSAR analysis on a variety of chemically diverse PKBα inhibitors revealed Baumann's alignment-independent topological descriptors that differentiated the molecules binding to Protein kinase B (PKBα) kinase or PH domain, hence a docking study of two crystal structures of PKBβ was performed for identification of novel ATP-competitive inhibitors of PKBβ. Five compounds had a good docking score and Callophycin A showed better ligand efficiency than other PKBβ inhibitors. Furthermore in silico pharmacokinetic and toxicity studies also showed that Callophycin A had a high drug score (0.85) compared to the other inhibitors. These results encourages discovering novel inhibitors for cancer therapeutic targets by screening metabolites from marine algae.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Anticancer activity; Caespitol (PubChem CID: 14314413); Callophycin A; Callophycin A (PubChem CID: 57399101); Docking; In silico ADMET; Marine algae; Prevezol C (PubChem CID: 10046593); Protein kinase B; QSAR

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Year:  2015        PMID: 25936945     DOI: 10.1016/j.ejps.2015.04.026

Source DB:  PubMed          Journal:  Eur J Pharm Sci        ISSN: 0928-0987            Impact factor:   4.384


  4 in total

1.  QSAR analysis and molecular docking simulation of norepinephrine transporter (NET) inhibitors as anti-psychotic therapeutic agents.

Authors:  Sabitu Babatunde Olasupo; Adamu Uzairu; Gideon Shallangwa; Sani Uba
Journal:  Heliyon       Date:  2019-10-19

2.  Structural Investigation for Optimization of Anthranilic Acid Derivatives as Partial FXR Agonists by in Silico Approaches.

Authors:  Meimei Chen; Xuemei Yang; Xinmei Lai; Jie Kang; Huijuan Gan; Yuxing Gao
Journal:  Int J Mol Sci       Date:  2016-04-08       Impact factor: 5.923

Review 3.  Omics for Bioprospecting and Drug Discovery from Bacteria and Microalgae.

Authors:  Reuben Maghembe; Donath Damian; Abdalah Makaranga; Stephen Samwel Nyandoro; Sylvester Leonard Lyantagaye; Souvik Kusari; Rajni Hatti-Kaul
Journal:  Antibiotics (Basel)       Date:  2020-05-04

Review 4.  Computational Methodologies in the Exploration of Marine Natural Product Leads.

Authors:  Florbela Pereira; Joao Aires-de-Sousa
Journal:  Mar Drugs       Date:  2018-07-13       Impact factor: 5.118

  4 in total

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