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Introducing folding stability into the score function for computational design of RNA‐binding peptides boosts the probability of success
Author(s) -
Xiao Xingqing,
Agris Paul F.,
Hall Carol K.
Publication year - 2016
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.25021
Subject(s) - peptide , folding (dsp implementation) , molecular dynamics , sequence (biology) , function (biology) , stability (learning theory) , rational design , ww domain , protein folding , computational biology , computer science , chemistry , computational chemistry , biology , materials science , nanotechnology , biochemistry , genetics , engineering , machine learning , gene , electrical engineering
A computational strategy that integrates our peptide search algorithm with atomistic molecular dynamics simulation was used to design rational peptide drugs that recognize and bind to the anticodon stem and loop domain (ASL Lys3 ) of humantRNA UUU Lys 3for the purpose of interrupting HIV replication. The score function of the search algorithm was improved by adding a peptide stability term weighted by an adjustable factor λ to the peptide binding free energy. The five best peptide sequences associated with five different values of λ were determined using the search algorithm and then input in atomistic simulations to examine the stability of the peptides' folded conformations and their ability to bind to ASL Lys3 . Simulation results demonstrated that setting an intermediate value of λ achieves a good balance between optimizing the peptide's binding ability and stabilizing its folded conformation during the sequence evolution process, and hence leads to optimal binding to the target ASL Lys3 . Thus, addition of a peptide stability term significantly improves the success rate for our peptide design search. Proteins 2016; 84:700–711. © 2016 Wiley Periodicals, Inc.