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Exploring the limits of the usefulness of mutagenesis in studies of allosteric mechanisms
Author(s) -
Tang Qingling,
Alontaga Aileen Y.,
Holyoak Todd,
Fenton Aron W.
Publication year - 2017
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.23239
Subject(s) - allosteric regulation , mutagenesis , mechanism (biology) , allosteric enzyme , biology , computational biology , phosphoenolpyruvate carboxykinase , function (biology) , mutation , alanine , alanine scanning , biochemistry , genetics , amino acid , enzyme , gene , philosophy , epistemology
The outcome of structure‐guided mutational analyses is often used in support of postulated mechanisms of protein allostery. However, the limits of how informative mutations can be in understanding allosteric mechanisms are not completely clear. Here, we report an exercise to evaluate whether mutational data can support a simplistic mechanistic model, developed with minimal data inputs. Due to the lack of a mechanism to explain how alanine allosterically modifies the affinity of human liver pyruvate kinase (approved symbol PKLR) for its substrate, phosphoenolpyruvate, we proposed a speculative allosteric mechanism for this system. Within the allosteric amino‐acid‐binding site (something in the effector site must, of necessity, contribute to the allosteric mechanism), we implemented multiple mutational strategies: (1) site‐directed random mutagenesis at positions that contact bound alanine and (2) mutations to probe specific questions. Despite acknowledged inadequacies used to formulate the speculative mechanism, many mutations modified the allosteric coupling constant ( Q ax ) consistent with that mechanism. The observed support for this speculative mechanism leaves us to ponder the best use of mutational data in structure–function studies of allosteric mechanisms. The mutational databank derived from this exercise has an independent value for training and testing algorithms specific to allostery.