Reliable In Silico Ranking of Engineered Therapeutic TCR Binding Affinities with MMPB/GBSA.

ABSTRACT: Accurate and efficient in silico ranking of protein-protein binding affinities is useful for protein design with applications in biological therapeutics. One popular approach to rank binding affinities is to apply the molecular mechanics Poisson-Boltzmann/generalized Born surface area (MMPB/GBSA) method to molecular dynamics (MD) trajectories. Here, we identify protocols that enable the reliable evaluation of T-cell receptor (TCR) variants binding to their target, peptide-human leukocyte antigens (pHLAs). We suggest different protocols for variant sets with a few (≤4) or many mutations, with entropy corrections important for the latter. We demonstrate how potential outliers could be identified in advance and that just 5-10 replicas of short (4 ns) MD simulations may be sufficient fo

SUBMITTER: Crean RM 

PROVIDER: S-EPMC9097153 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature