From pixels to druggable leads: A CADD strategy for the design and synthesis of potent DDR1 inhibitors

Abstract

Background and objectiveWhile numerous in silico tools exist for target-based drug discovery, the inconsistent integration of in vitro data with predictive models hinders research and development productivity. This is particularly apparent during the Hit-to-Lead stage, where unreliable in-silico tools often lead to suboptimal lead selection. Herein, we address this challenge by presenting a CADD-guided pipeline that successfully integrates rational drug design with in-silico hits to identify a promising DDR1 lead. Methods2 × 1000 ns MD simulations along with their respective FEL and MMPBSA analyses were employed to guide the rational design and synthesis of 12 novel compounds which were evaluated for their DDR inhibition. ResultsThe molecular dynamics investigation of the initial hit led to the identification of key structural features within the DDR1 binding pocket. The identified key features were used to guide the rational design and synthesis of twelve novel derivatives. SAR analysis, biological evaluation, molecular dynamics, and free energy calculations were carried out for the synthesized derivatives to understand their mechanism of action. Compound 4c exhibited the strongest inhibition and selectivity for DDR1, with an IC50 of 0.11 µM. ConclusionsThe MD simulations led to the identification of a key hydrophobic groove in the DDR1 binding pocket. The integrated approach of SAR analysis with molecular dynamics led to the identification of compound 4c as a promising lead for further development of potent and selective DDR1 inhibitors. Moreover, this work establishes a protocol for translating in silico hits to real world bioactive druggable leads.