Konaté, Plata, Park, Usmanova, Wang, and Vitkup (eLife 2019) showed that orthologous proteins that strictly conserve the same molecular function do not diverge indefinitely: after roughly 1–2 billion years of independent evolution, the decline of sequence and structural similarity slows sharply, leaving an effective divergence limit above 25% sequence identity (typically about 40%), with protein structures kept within about 3 Å Cα RMSD and, on average, fewer than four amino acid types accepted per site. The paper proposes this as a mechanistic hypothesis—functional pressure preserves the positions and dynamics of key residues, which in turn preserves overall structural optimality and restricts per-site amino acid acceptance—but explicitly leaves the mechanism to be elucidated. The open problem is that mechanism: how biochemical, biophysical, and cellular constraints jointly enforce functional maintenance over planetary timescales, whether the limit generalizes beyond precisely annotated enzyme families, and what drives the substantially accelerated divergence observed, for example, in mitochondrial ribosomal proteins.

Background

Proteins that descend from a common ancestral gene (homologs) and were separated by a speciation event are called orthologs; when such orthologs conserve the same molecular function over billions of years, they offer a natural experiment in how long-term functional constraint shapes sequence and structure. Sequence divergence between two proteins is usually quantified as percent sequence identity (the fraction of aligned positions occupied by the same amino acid), and structural divergence as the root-mean-square deviation (RMSD, in Ångströms) between the Cα atoms of the best superposition of the two folded backbones. A classical result of Chothia and Lesk (1986) established that structure diverges more slowly than sequence, and proteins sharing the same fold can remain below 10–15% sequence identity, so fold conservation alone is a weak constraint. Povolotskaya and Kondrashov (2010) showed that the protein universe is still expanding, with even ancient orthologs continuing to diverge from each other. Konaté et al. (2019) refined this picture by restricting attention to orthologs that strictly conserve their molecular function (for enzymes, the same fully specified EC number, the hierarchical Enzyme Commission annotation of catalyzed reactions). They found that the decline of sequence and structural similarity between such orthologs markedly slows after ~1–2 billion years, approaching an effective divergence limit of more than 25% sequence identity (~40% typically), with structures confined within about 3 Å Cα RMSD—the 'structural optimality' the function demands. The limit is not created by universally conserved sites (positions identical across nearly all lineages; only 10–20% of sites, with a median near 13%); instead, on average fewer than four amino acid types are accepted per site. That per-site number is a model-derived quantity rather than a direct count of observed residues: in the paper's divergence model with allowed back substitutions, the asymptotic fraction of identical sites is Y0 = 1/a, with R0 = 2λa/(a−1), so a is interpreted as the average number of amino acid types accepted per site during long-term protein evolution and Y0 as its inverse; the authors note that this low average does not contradict the observation of more than four amino acid types at a given site at low frequencies. Different lineages are identical at different sites—an observation the authors attribute to epistasis, meaning that the fitness effect of a mutation depends on the sequence context in which it occurs. As a mechanistic model, they hypothesize that conserving the substrates and interaction partners of a function forces preservation of the spatial positions and dynamics of key residues, which forces preservation of the overall structure, which in turn restricts acceptable substitutions. The model rests on fitness-effect assignments at sites and on a two-stage divergence dynamics (fast divergence at sites with mild fitness effects that saturates, plus persistently slow divergence at sites with large fitness effects), but the authors state it as a belief requiring further analysis of biochemical, biophysical, and cellular constraints, and they note that functional annotations for non-enzymatic protein families are too imprecise to ascertain strict functional conservation.

Problem Statement

Elucidate the mechanism by which strict conservation of a molecular function enforces the observed divergence limit of protein evolution on billion-year timescales. The mechanism is to be resolved through the four sub-questions below.

  1. Explain—quantitatively and with evidence—how (i) the restriction to a small set of acceptable amino acid types per site (fewer than four on average) and (ii) the requirement of structural optimality (conservation of the overall fold to within roughly 3 Å Cα RMSD), together with the underlying biochemical, biophysical, and cellular constraints, jointly produce the observed saturation of sequence and structural divergence between orthologs that conserve their function. This quantitative account must cover two named conditions: the two-stage divergence dynamics (saturation of substitution at sites with mild fitness effects, persistent slow divergence at sites with large fitness effects) and the degradation of functional efficiency by deleterious mutations near the limit. Because the source's own model already renders a small per-site acceptance number mathematically equivalent to a nonzero asymptotic identity (Y0 = 1/a), what is sought is the causal content—biochemical, biophysical, and cellular—that fixes the acceptance number and the structural ceiling in real proteins, not a restatement of that equivalence.

  2. Determine whether the effective number of acceptable amino acid types per site, in the model-derived sense defined above, varies systematically across structural or functional classes of proteins.

  3. Establish whether this limit and its per-site amino acid acceptance statistics generalize beyond enzyme families with precise EC annotations to non-enzymatic protein families, whose functional annotations are currently too imprecise to ascertain strict functional conservation (the paper reports an effective limit above 25% identity for 23 of the 29 non-enzymatic families it analyzed, so what remains open is the rigor of the functional annotation and the per-site acceptance statistics rather than the existence of a limit).

  4. Determine what drives divergence that is substantially accelerated relative to the limit—of the kind the paper illustrates with mitochondrial ribosomal proteins and mitochondrial translation initiation factors, for which it suggests either co-evolution with changing interaction partners or relaxation of selection pressures—and how frequently such acceleration occurs.

References

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  2. Konaté MM, Plata G, Park J, Usmanova DR, Wang H, Vitkup D. Molecular function limits divergent protein evolution on planetary timescales. bioRxiv preprint, posted 2017-10-05. doi:10.1101/198663, https://doi.org/10.1101/198663
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