Computational study of chalcone-cyanopyrimidine hybrids as LSD1 inhibitors: Assessing the influence of FAD on binding affinity and inhibition
Year: 2025
Type: article
Abstract: The inhibition of lysine-specific demethylase 1 (LSD1) has emerged as a promising therapeutic strategy for cancer treatment due to its critical role in epigenetic regulation. In this study, we conducted an in-silico investigation to explore the potential of chalcone-cyanopyrimidine hybrids as LSD1 inhibitors. Chalcones and cyanopyrimidine derivatives are known for their anticancer properties, making them an ideal combination for targeting LSD1. A library of novel chalcone-cyanopyrimidine hybrids were evaluated using molecular docking, ADMET, MM-GBSA, and molecular dynamics simulations against LSD1, with a particular focus on the role and effect of flavin adenine dinucleotide (FAD), a cofactor integral to LSD1 activity. The molecular docking results revealed that the chalcone-cyanopyrimidine hybrids demonstrate strong binding affinities with LSD1. Additionally, the results revealed that several compounds within the library in comparison to the reference standards exhibited strong binding affinities towards LSD1. When we evaluated these docking results, it was found that despite the highest binding affinity observed in competitive docking approach, their MD results depicted their instability inside the binding pocket, whereas the MD simulation done in presence of FAD represented a stable RMSF and RMSD profile. It suggests that FAD is an integral part in modulating LSD1 inhibition. This study lays the groundwork for future experimental validation and optimization of chalcone-cyanopyrimidine hybrids as potent LSD1 inhibitors with promising therapeutic implications. • A novel library of 2912 novel chalcone-cyanopyrimidine hybrids were designed. • The in-silico screening was done by docking, MM-GBSA, ADMET, and MD simulation. • The FAD is an integral cofactor for the binding and inhibition of LSD1. • The interactions that observed in docking were visualized after MD simulation.
Institutions: Jamia Hamdard, Qassim University
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,700
Awards: G7549639023, G8433663102
OpenAlex ID: W4416574364
