Multiobjective heuristic algorithm for de novo protein design in a quantified continuous sequence space.

ABSTRACT: Protein design usually involves sequence search process and evaluation criteria. Commonly used methods primarily implement the Monte Carlo or simulated annealing algorithm with a single-energy function to obtain ideal solutions, which is often highly time-consuming and limited by the accuracy of the energy function. In this report, we introduce a multiobjective algorithm named Hydra for protein design, which employs two different energy functions to optimize solutions simultaneously and makes use of the latent quantitative relationship between different amino acid types to facilitate the search process. The framework uses two kinds of prior information to transform the original disordered discrete sequence space into a relatively ordered space, and decoy sequences are searched in this orde

SUBMITTER: Li RX 

PROVIDER: S-EPMC8114120 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature