Computational protein design as an optimization problem
作者:
摘要
Proteins are chains of simple molecules called amino acids. The three-dimensional shape of a protein and its amino acid composition define its biological function. Over millions of years, living organisms have evolved a large catalog of proteins. By exploring the space of possible amino acid sequences, protein engineering aims at similarly designing tailored proteins with specific desirable properties. In Computational Protein Design (CPD), the challenge of identifying a protein that performs a given task is defined as the combinatorial optimization of a complex energy function over amino acid sequences.
论文关键词:Weighted constraint satisfaction problem,Soft constraints,Neighborhood substitutability,Constraint optimization,Graphical model,Cost function networks,Integer linear programming,Quadratic programming,Computational protein design,Bioinformatics,Maximum a posteriori inference,Maximum satisfiability
论文评审过程:Received 16 September 2013, Revised 22 February 2014, Accepted 10 March 2014, Available online 26 March 2014.
论文官网地址:https://doi.org/10.1016/j.artint.2014.03.005