Correlation between the conformation space and the sequence space of Peptide chain

The influence of the hydrogen-bond network on the structure and dynamics of the RAPRKKG heptapeptide and its mutants

The structural behaviour of the RAPRKKG heptapeptide after individual or multiple mutations was inspected through molecular dynamics simulation. The nature of the mutations provided information on the flexibility of the heptapeptide and on how water molecules establish hydrogen bonds with it. The structural behaviour of the wild-type and the mutated structures were measured through the analysis of protein‒protein and protein‒solvent hydrogen bonds. The conformational behaviours of the different structures were analysed through free energy landscape analysis. The flexibility characteristics of the mutants seem to depend on the reorganization of water molecules and their static or dynamic behaviour around amino acid side chains.

Biophysical Models of Protein Evolution: Understanding the Patterns of Evolutionary Sequence Divergence

For decades, rates of protein evolution have been interpreted in terms of the vague concept of functional importance. Slowly evolving proteins or sites within proteins were assumed to be more functionally important and thus subject to stronger selection pressure. More recently, biophysical models of protein evolution, which combine evolutionary theory with protein biophysics, have completely revolutionized our view of the forces that shape sequence divergence. Slowly evolving proteins have been found to evolve slowly because of selection against toxic misfolding and misinteractions, linking their rate of evolution primarily to their abundance. Similarly, most slowly evolving sites in proteins are not directly involved in function, but mutating these sites has a large impact on protein structure and stability. In this article, we review the studies in the emerging field of biophysical protein evolution that have shaped our current understanding of sequence divergence patterns. We also propose future research directions to develop this nascent field.

Correlation between evolutionary structural development and protein folding

Evolution should have played important roles in determining folding mechanisms and structures of proteins. In this article we discuss how the folding mechanisms had been affected by the early stage of evolution through which the uniqueness of structure had developed. Although the process of such early-time evolution has remained a mystery, a plausible scenario is that the evolution of proteins toward the ordered structures was guided by functional selection pressure as demonstrated in vitro and in silico. We examine the in silico functional selection of sequences and show that there is a significant correlation between two different processes toward the unique 3D structure, the evolutionary development of structure through sequence selection, and the folding process of the resultant sequence. This finding could be rephrased as protein folding recapitulates the emergence of topology in the molecular evolution. The correlation suggests a guideline for engineering foldable proteins.

Simulating protein evolution in sequence and structure space

Naturally occurring proteins comprise a special subset of all plausible sequences and structures selected through evolution. Simulating protein evolution with simplified and all-atom models has shed light on the evolutionary dynamics of protein populations, the nature of evolved sequences and structures, and the extent to which today's proteins are shaped by selection pressures on folding, structure and function. Extensive mapping of the native structure, stability and folding rate in sequence space using lattice proteins has revealed organizational principles of the sequence/structure map important for evolutionary dynamics. Evolutionary simulations with lattice proteins have highlighted the importance of fitness landscapes, evolutionary mechanisms, population dynamics and sequence space entropy in shaping the generic properties of proteins. Finally, evolutionary-like simulations with all-atom models, in particular computational protein design, have helped identify the dominant selection pressures on naturally occurring protein sequences and structures.