PARCE: Protocol for Amino acid Refinement through Computational Evolution
The in silico design of peptides and proteins as binders is useful for diagnosis and therapeutics due to their low adverse effects and major specificity. To select the most promising candidates, a key matter is to understand their interactions with protein targets. In this work, we present PARCE, an open source Protocol for Amino acid Refinement through Computational Evolution that implements an advanced and promising method for the design of peptides and proteins. The protocol performs a random mutation in the binder sequence, then samples the bound conformations using molecular dynamics simulations, and evaluates the protein–protein interactions using multiple scoring functions. Finally, it accepts or rejects the mutation by applying a consensus criterion based on the binding scores. The procedure is iterated with the aim to explore efficiently novel sequences with potential better affinities towards their targets. We also provide a tutorial for running and reproducing the methodology.