Project Summary HIV-1 presents a severe global health challenge. Due to the high genetic variability of HIV and the lifelong duration of the standard treatment, resistant mutations pose an acute challenge. As such, understanding the mechanisms of resistance is crucial for the rational design of antivirals. The current approach for understanding drug resistance focuses on identifying important interactions in the protein-drug complex based on intuitions. These insights have led to intriguing structure-based drug design strategies. However, resistance for drugs designed by these strategies readily developed, reflecting their limitations. This is due to two major gaps in the current approach: (1) It does not consider the conformational dynamics inherent to ligand binding, which are vital to decoding drug resistance. For example, the interplay between active-site and non-active site mutations in PR cannot be understood from structures alone. (2) This empirical, qualitative approach lacks a rigorous method to quantify how different residues and interactions individually and collectively contribute to binding affinity. We propose to fill these two gaps with a physics-based rigorous approach centered on protein conformational dynamics that control ligand binding, the process at the heart of drug potency and resistance. We will leverage a novel method we developed for identifying the exact reaction coordinates, the few essential coordinates of a protein that control its conformational dynamics and ligand binding. We will develop a rigorous method for decomposing the ligand binding free energy into contributions from individual residue-residue interactions. This method will enable us to identify residues and interactions critical for drug resistance. We will apply it to HIV-1 protease inhibitors, aiming to elucidate the mechanisms of resistance. We will also develop protocols for adjusting protein-protein and protein-ligand interactions to manipulate protein dynamics and combat drug resistance. To verify our understanding of resistance mechanisms and protocols for manipulating protein interactions and dynamics, we will test two types of computational predictions in infection assays. 1) We will design mutations that confer stronger resistance than current variants, aiming to establish the limits of drug resistance. 2) We will introduce additional mutations to existing mutants to neutralize their resistance, aiming to establishing the range for countering resistance. These will be achieved through two specific aims. The goal of this project is to develop a computational toolkit for rigorously and systematically dissecting protein drug resistance mechanisms that will enable rationale design of effective counterstrategies and validate it with virology assays. The insights from this project will fuel our long-term goal: to design the next-generation HIV antivirals that not only neutralize current resistant mutants but also minimize chances of new resistant mut...