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A Fast and Precise Approach for Computational Saturation Mutagenesis and its Experimental Validation by Using an Artificial (βα) 8 ‐Barrel Protein
Author(s) -
Fischer Andre,
Seitz Tobias,
Lochner Adriane,
Sterner Reinhard,
Merkl Rainer,
Bocola Marco
Publication year - 2011
Publication title -
chembiochem
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.05
H-Index - 126
eISSN - 1439-7633
pISSN - 1439-4227
DOI - 10.1002/cbic.201100051
Subject(s) - saturated mutagenesis , mutagenesis , amino acid , point mutation , energy minimization , side chain , chemistry , protein engineering , mutant , biological system , molecular dynamics , protein design , stereochemistry , computational chemistry , protein structure , biochemistry , biology , gene , organic chemistry , enzyme , polymer
We present a computational saturation mutagenesis protocol (CoSM) that predicts the impact on stability of all possible amino acid substitutions for a given site at an internal protein interface. CoSM is an efficient algorithm that uses a combination of rotamer libraries, side‐chain flips, energy minimization, and molecular dynamics equilibration. Because CoSM considers full side‐chain and backbone flexibility in the local environment of the mutated position, amino acids larger than the wild‐type residue are also modeled in a proper manner. To assess the performance of CoSM, the effect of point mutations on the stability of an artificial (βα) 8 ‐barrel protein that has been designed from identical (βα) 4 ‐half barrels, was studied. In this protein, position 234 N is a previously identified stability hot‐spot that is located at the interface of the two half barrels. By using CoSM, changes in protein stability were predicted for all possible single point mutations replacing wild‐type Val234 N . In parallel, the stabilities of 14 representative mutants covering all amino acid classes were experimentally determined. A linear correlation of computationally and experimentally determined energy values yielded an R 2 value of 0.90, which is statistically significant. This degree of coherence is stronger than the ones we obtained for established computational methods of mutational analysis.