Motivation: There is a need for an efficient and accurate computational method to identify the effects of single- and multiple-residue mutations on the stability and reactivity of proteins. Such a method should ideally be consistent and yet applicable in a widespread manner, i.e. it should be applied to various proteins under the same parameter settings, and have good predictive power for all of them. Results: We develop a Delaunay tessellation-based four-body scoring function to predict the effects of single- and multiple-residue mutations on the stability and reactivity of proteins. We test our scoring function on sets of single-point mutations used by several previous studies. We also assemble a new, diverse set of 237 single- and multiple-residue mutations, from over 24 different publications. The four-body scoring function correctly predicted the changes to the stability of 169 out of 210 mutants (80.5%), and the changes to the reactivity of 17 out of 27 mutants (63%). For the mutants that had the changes in stability/reactivity quantified (using reaction rates, temperatures, etc.), an average Spearman rank correlation coefficient of 0.67 was achieved with the four-body scores. We also develop an efficient method for screening huge numbers of mutants of a protein, called combinatorial mutagenesis. In one study, 64 million mutants of a cold-shock nucleus binding domain protein 1CSQ, with six of its residues being changed to all possible (20) amino acids, were screened within a few hours on a PC, and all five stabilizing mutants reported were correctly identified as stabilizing by combinatorial mutagenesis.
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