Introducing folding stability into the score function for computational design of RNA‐binding peptides boosts the probability of success |
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Authors: | Xingqing Xiao Paul F. Agris Carol K. Hall |
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Affiliation: | 1. Chemical and Biomolecular Engineering Department, North Carolina State University, Raleigh, North Carolina;2. The RNA Institute, University at Albany, State University of New York, Albany, New York |
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Abstract: | 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 (ASLLys3) of human for 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 ASLLys3. 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 ASLLys3. 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. |
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Keywords: | peptide design search algorithm atomistic molecular dynamics simulation tRNALys3UUU binding affinity and specificity |
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