Predictions and experimental validation of fold-switching proteins

National Library Of Medicine

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Abstract

No introductory-level biochemistry textbook is complete without a chapter about how a proteins primary sequence of amino acids determines its fold. So far, nearly all computational work has focused on predicting a single protein structure from the proteins amino acid sequence. Our research challenges the one-sequence-one-structure paradigm. In 2018, we found nearly 100 examples of proteins that can adopt more than one stable fold. The structural heterogeneity of these fold-switching proteins allows them either to perform more than one function or to be highly regulated in cells. These functional changes appear to have significant relevance to human health as several fold-switching proteins are associated with human diseases such as cancer and bacterial infections. Now we are taking this research to the next level by (1) developing computational approaches to predict which amino acid sequences can switch folds and (2) testing our predictions experimentally. This year, we have furthered objective by (1) applying our JPred4-based predictive approach to the universally conserved family of NusG transcriptional regulators. Our method predicts that 24% of the proteins in this family have domains that switch completely from alpha helix to beta sheet, and our predictions were consistent with circular dichroism and nuclear magnetic resonance experiments for 10/10 sequence-dissimilar NusGs. Importantly, state-of-the-art methods, such as AlphaFold2, missed fold switching in these variants. This paper was recently published in Nature Communications. (2). We showed that AlphaFold2 systematically fails to predict fold switching in a dataset of diverse fold-switching proteins. This finding underscores the need to continue developing computational approaches that predict fold switching. Additionally, we have identified potential fold evolution in a large family of bacterial response regulators. We have identified an evolutionary path by which alpha helices morphed to beta sheets through stepwise mutations. Furthermore, we have been developing a coevolutionary approach to predict not only whether a protein switches folds but what conformations it assumes. We plan to submit both the evolution and response regulator projects for publication by the end of summer 2022.