Involvement of Bioinformatics in Solving Protein Folding Problem

There are lots of facts that have been revealed on protein folding problem since last decade. Most importantly, energy landscape theory and funnel concept have greatly evolved the field which describes protein folding is proceeded by progressive ensemble of partially folded structures leading to a completely folded native structure [123]. Protein folding is controlled by the shape of free energy landscape and the roughness on it arising due to various interactions which stabilize the folded state. Theoretical and experimental advances have found that designing of certain motifs can be done but there are various other motifs present in the protein which cannot be designed. This is due to fact that foldability of those motifs is independent of energetic frustrations. Further, prediction of order of native contact formation during folding is another challenge to be looked [124]. However, collective studies by theoretical folding studies, all-atom simulations, and experimental evidence have suggested that the real proteins, particularly small, fast-folding two-state like proteins have sequences with a sufficiently reduced level of energetic frustration with transition state ensemble primarily determined by topological constraints. Topology is one of the dominant factors governing transition state structure and thus helpful in prediction of fold from the given sequence [125]. Recent observations have revealed that there is substantial correlation between the average sequence separation between contacting residues in the native structure and the folding rates for single domain proteins [126].