A comprehensive protein design protocol to identify resistance mutations and signatures of adaptation in pathogens.

The article focuses on a high-throughput computational protein design protocol developed to identify hotspot residues, drug resistance mutations, and signatures of adaptation in pathogen proteins under drug pressure. This protocol, exemplified by the "ResScan-design" method implemented in the Molecular Operating Environment (MOE) software, predicts single-point mutations that reduce binding affinity between a protein and a bound drug, indicating potential resistance. Case studies on SARS-CoV-2 proteins, including the main protease (Mpro) in complex with the FDA-approved drug narlaprevir, demonstrate the protocol's ability to rapidly screen mutations and its validation through correlation with real-world viral genomic data. The approach offers a faster alternative to experimental methods for monitoring evolving resistance and can aid in surveillance and therapeutic strategy development against infectious diseases.