Development and assessment of methods for membrane protein structure prediction

National Institute Of Neurological Disorders And Stroke

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Abstract

The ability to reliably align the amino acid sequences of proteins is a key requirement for confirming evolutionary relationships, identifying conserved elements, and enabling homology-based structural modeling. However, the more dissimilar the sequences, the more challenging it is to compute their alignments accurately, and the challenge is particularly acute for membrane proteins due to their largely greasy composition. This year, we continued to develop our software for alignment of membrane protein sequences. In collaboration with Dr. Staritzbichler (U. Leipzig), we added several new structurally-oriented features to our online server for AlignMe, available at http://www.bioinfo.mpg.de/AlignMe (Staritzbichler R, Yaklich E, Sarti E, Ristic N, Hildebrand PW, Forrest LR, 2022, Nucleic Acids Res 50:W29). Protein function has traditionally been interpreted largely in the context of "snapshots" of structural data that reflect single frames in a movie of molecular behavior. To facilitate incorporation of biophysical data into representations of proteins, we have developed an approach together with the Faraldo-Gomez lab (NHLBI) to combine rates of exchange between hydrogen and deuterium (HDX) with molecular dynamics simulations. We developed a comprehensive tutorial for this method (Lee SP, Bradshaw RT, Marinelli F, Kihn KC, Smith AK, Wintrode PL, Deredge DJ, Faraldo-Gomez JD, Forrest LR, 2022, Living Journal of Computational Molecular Science 3:1521) and illustrated the application of the method to the problem of rare-event sampling in an antibacterial target called PhuS (Kihn KC, Wilson T, Smith AK, Bradshaw RT, Wintrode PL, Forrest LR, Wilks A, Deredge DJ, 2021, Biophys J 120:5141) in collaboration with the Deredge and Wintrode labs (U. Maryland).