In Silico Screening Of Small Molecules Targeting Protein Kinases
Year: 2024
Type: article
Abstract: Background: Computational modeling and simulation serve as valuable adjunct tools to traditional methodologies for evidence collection, including in-vitro and in-vivo studies, subject to FDA regulations. Over the past decades, a multitude of FDA-approved drugs with substantial anticancer efficacy have been discovered, primarily through the inhibition of various protein kinases. Methods: In the current investigation, five derivatives featuring a Benzamide moiety were selected, and in silico methodologies were employed to assess their potential as anticancer agents. These compounds underwent thorough scrutiny for their absorption, distribution, metabolism, excretion (ADME) properties, and drug-likeness characteristics. This study sought to identify novel compounds with anticancer potential, and their attributes were compared to those of the FDA-approved drug Cobimetinib. Results: It is seen that there is marginal shift after the energy minimization. In Errat value, it enhanced from 94.702 to 96.358. In protein analysis, Ramachandran plot showed 90.9% of amino acids resided in the most favored region. Z-score also shown a effective results. Ligand 5 has shown the similar binding energy, hydrogen bonds, halogen and Pi bond interactions with the standard drug. Conclusion: One of the derivatives that is Ligand 5 has shown greater resemblances in its interactions, encompassing hydrogen bonding, pi bonding, and halogen bonding with standard drug Cobimetinib.
Author: K. Pallavi, I. Tabssum, P. Bebi*, Shankar Patil
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6930430738
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