Inhibitory potential of phytochemicals from Chromolaena odorata L. against apoptosis signal-regulatory kinase 1: A computational model against colorectal cancer
Damilola A. Omoboyowa , Muhammad N. Iqbal , Toheeb A. Balogun , Damilola S. Bodun , John O. Fatoki , Oluwatoba E. Oyeneyin
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引用次数: 15
Abstract
Apoptosis signal kinase 1 (ASK 1) is a member of the mitogen-activated protein kinase (MAPK) family that induces cells apoptosis including colorectal cancer (CRC). CRC is the second most common type of malignancy globally. Hence, ASK 1 plays an essential role in the pathogenesis of CRC and therefore, is an exclusive target in drug design and discovery for CRC. Herein, applied computational approaches including molecular docking, molecular mechanics/generalized born surface area calculation and pharmacokinetic models were performed to propose putative ASK 1 antagonists from natural compounds. Seven (7) ligands were identified as potent inhibitors and two top hit compounds were validated using molecular dynamics (MD) simulation studies. The density function theory (DFT) of the hits were performed at the Becke three Lee Yang Parr/6-31G(d) level of theory to understand their molecular reactivity. Seven compounds identified as ASK 1 antagonists have docking score ranging from −9.10 to −8.14 kcal/mol which is comparable to the reference ligand camptosar (-7.03 kcal/mol). One of the compounds, odoratin has finally emerged as the structurally stable compound with −9.10 kcal/mol and MD simulation over 50 ns indicated that odoratin forms stable interaction with key amino acid residues such as LEU 686, VAL 757 and PRO 758. DFT study showed that the studied compounds have proton donating and accepting ability hence, potent inhibitory and solubility effects. The findings from this study suggest that, odoratin could be considered a potent ASK 1 inhibitor and could be experimentally verified as a lead compound for search of MAPK inhibitors for colorectal cancer.
期刊介绍:
Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs