Allostery and protein evolution through protein conformational dynamics

Proteins are the most efficient nano-machines and perform a broad range of functions. All of the information necessary for function is encoded in 1-D sequences. Proteins exquisitely translate this code to fold and function, yet deciphering this encoded information remains an open challenge. With the advancement in sequencing techniques, inferring evolutionary record of extant proteins offers a tractable and highly effective solution to better understand the relation between sequence and protein function in order to decipher the 1-D sequence code. This is because evolution in itself has been a single massive ongoing experiment in diversification and optimization of protein sequence-structure-function relation occurring over billions of years. We have developed a physics-based metric called the Dynamic Flexibility Index (DFI) to study protein evolution. DFI quantifies the resilience of a given position to the perturbations occurring at various parts of a protein using linear response theory, mimicking the multidimensional response when the protein’s conformational space is probed upon interaction with small molecules or other cellular constituents. DFI provides us with an opportunity to retrace evolutionary steps which, in turn, have led to structural dynamics analysis of resurrected ancestral proteins. We demonstrated that protein static structures do not need to be modified in order for new function or molecular adaptation to emerge. Proteins may evolve and adapt new function by fine tuning their native state conformational dynamics. These studies provide us a molecular mechanism: Nature utilizes minimum perturbation-maximum response as a principle through the allosteric alteration of the dynamics of the active/catalytic sites by mutating distal positions, rather than introducing mutations on active sites. We also showed that this principle can be used to design proteins with desired function.

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https://search.asu.edu/profile/977700