PREDICTING CONFORMATIONAL SWITCHES IN PROTEINS

University Of California San Francisco, San Francisco CA

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Abstract

We are developing a new computational technique to predict conformationally switching elements in proteins from their amino acid sequences. The method, called ASP (Ambivalent Structure Predictor) analyzes results from a secondary structure prediction algorithm to identify regions of conformational ambivalence. ASP identifies ambivalent regions in test protein sequences for which function involves substantial backbone rearrangements. Sites previously described as conformational switches are correctly predicted to be part of structurally ambivalent regions. ASP can also identify putative pathways of allosteric communication between the nucleotide, actin binding and fulcrum sites of myosin. The facilities at the Computer Graphics Laboratory are used to acquire sequence data and secondary structure predictions. Molecular graphics are integral to data analysis, as we map predictions of structural ambivalence onto the 3D crystal structures of the proteins. Further development of our algorithm may provide a tool for guiding experimental studies on protein function and motion in the absence of detailed three-dimensional structural data.