Roles of mutation and recombination in the evolution of protein thermodynamics

Abstract

We present a comprehensive study of the evolutionary origin of the thermodynamic behavior of proteins. With the use of a simplified model, we exhaustively enumerate the space of all sequences and the space of all structures, simulate the evolutionary relationship between sequences and structures, and characterize the steady-state sequence distribution for all structures in terms of several thermodynamic variables. We assess the effects of two major forces of evolution: mutation and recombination. Three simplifications are made. First, a two-dimensional lattice model is used to represent protein sequences and structures. Second, proteins undergo neutral evolution so that the fitness landscape has a flat allowed region inside of which all sequences are equally fit. Third, we ignore otherwise important factors such as finite population size and evolutionary time. Two scenarios emerge from our study. The first occurs when evolution is dominated by mutation events. Even though the prototype sequence that is most mutationally robust is preferred by evolution, the preference is not strong enough to offset the huge size of sequence space. Most native sequences are located near the boundary of the fitness region and are marginally compatible with the native structure. The second scenario occurs when evolution is dominated by recombination events. Now evolutionary preference for prototype sequence is strong enough to overcome the size of sequence space so that most native sequences are located near the center of sequence-structure compatibility. We conclude that the relative frequency of mutation and recombination events is a major determinant of how optimal protein sequences are for their structures. U nderstanding the relationship between protein sequences and structures is a central theme in modern molecular biology. Such an understanding can be partially achieved by predicting the folded structure from the amino acid sequence, and by predicting the compatible sequences from a known structure, using physical principles or protein-specific knowledge. However, a better understanding requires a global view of the space of all sequences and the space of all structures and its dynamics as a result of evolution. Because proteins are building blocks of life and a direct result of evolution, it is crucial to understand how evolution shapes the global relationship between protein sequences and structures by simulating the process of evolution in a direct way.Molecular evolution is often simulated as an adaptive walk over a fitness landscape (1) of connected network of all sequences (2). Simulation of molecular evolution has been used to study RNA sequence-secondary structure relationship (3, 4). Simple tractable models such as lattice and spin-glass models are often used to understand physical principles of protein folding (5-7), because these models are often simple enough to allow for precise statistical mechanical characterization, yet are able to capture the dominant forces in protein folding (8). Recently, simple tractable...

Biophysics of protein evolution and evolutionary protein biophysics

“…This theoretical prediction is consistent with subsequent experiments on b-lactamase indicating that for a given number of amino acid substitutions, recombined variants are much more likely to retain function than variants generated by random point mutations [339]. In another simulation study, evolutionary dynamics that admits both point mutations and recombination leads to a much higher concentration of population in the prototype sequence than if evolution proceeds via point mutations alone, suggesting a significant role of recombination in the prototype-like behaviours of natural proteins [152].…”

“…These sequences are often also thermodynamically most stable [137]. But random mutations alone-in the absence of a fitness drive towards higher native stability-are not sufficient to produce a highly concentrated population at the most stable 'prototype' sequence at the bottom of the sequence-space superfunnel because of the large number of sequences that are less stable [40,137,152,153]. Therefore, the experimental observation that natural proteins are often a nearly most stable sequence that behaves like a prototype sequence suggests strongly that they are results of positive selection for higher native stability (see further discussion in §3.2.3).…”

Neutralism and selectionism: a network-based reconciliation

“…The germ of this concept originated with Maynard-Smith 108 , and it was further developed by Schuster and collaborators 58 , who showed that the neutral networks associated with many individual minimum free energy RNA secondary structures are vast and span sequence space. Neutral networks were later characterized in proteins [109][110][111][112] , and the concept can even be applied to higher-order molecular systems, such as regulatory networks 47 . The biological importance of this concept is underscored by molecular evolution studies showing that very different RNA or protein molecules and their intermediates can have identical structure or function.…”

Complexity through Recombination: From Chemistry to Biology

“…Xia and Levitt [80] used a 5 × 5 two-dimensional square lattice model of proteins to test for the effects of recombination and mutation in the evolution of protein thermodynamics. They explored all the sequences in the lattice assuming that the protein sequences that fold into the same structure and that differ by a single mutation constituted a neutral network.…”