Identification of TBK1 inhibitors against breast cancer using a computational approach supported by machine learning

Discussion: All these four molecules displayed solvent based free energy values of −48.78, −47.56, −46.78 and −45.47 Kcal/mol and glide docking score of −10.4, −9.84, −10.03, −10.06 Kcal/mol respectively. The molecules displayed highly stable RMSD plots, hydrogen bond patterns and MMPBSA score close to or higher than BX795 molecule. In future, all these compounds can be further refined or validated by in vitro as well as in vivo activity. Also, we have found two novel groups that have the potential to be utilized in a fragment-based design strategy for the discovery and development of novel inhibitors targeting TBK1. Our method for identifying small molecule inhibitors can be used to make fundamental advances in drug design methods for the TBK1 protein which will further help to reduce breast cancer incidence.
Source: Frontiers in Pharmacology - Category: Drugs & Pharmacology Source Type: research