ABSTRACT
The unprecedented performance of Deepmind’s Alphafold2 in predicting protein structure in CASP XIV and the creation of a database of structures for multiple proteomes is reshaping structural biology. Moreover, the availability of Alphafold2’s architecture and code has stimulated a number of questions on how to harness the capabilities of this remarkable tool. A question of central importance is whether Alphafold2’s architecture is amenable to predict the intrinsic conformational heterogeneity of proteins. A general approach presented here builds on a simple manipulation of the multiple sequence alignment, via in silico mutagenesis, and subsequent modeling by Alphafold2. The approach is based in the concept that the multiple sequence alignment encodes for the structural heterogeneity, thus its rational manipulation will enable Alphafold2 to sample alternate conformations and potentially structural alterations due to point mutations. This modeling pipeline is benchmarked against canonical examples of protein conformational flexibility and applied to interrogate the conformational landscape of membrane proteins. This work broadens the applicability of Alphafold2 by generating multiple protein conformations to be tested biologically, biochemically, biophysically, and for use in structure-based drug design.
Competing Interest Statement
The authors have declared no competing interest.
