Probing the Mutational Interplay between Primary and Promiscuous Protein Functions: A Computational-Experimental Approach

Protein promiscuity is of considerable interest due its role in adaptive metabolic plasticity, its fundamental connection with molecular evolution and also because of its biotechnological applications. Current views on the relation between primary and promiscuous protein activities stem largely from laboratory evolution experiments aimed at increasing promiscuous activity levels. Here, on the other hand, we attempt to assess the main features of the simultaneous modulation of the primary and promiscuous functions during the course of natural evolution. The computational/experimental approach we propose for this task involves the following steps: a function-targeted, statistical coupling analysis of evolutionary data is used to determine a set of positions likely linked to the recruitment of a promiscuous activity for a new function; a combinatorial library of mutations on this set of positions is prepared and screened for both, the primary and the promiscuous activities; a partial-least-squares reconstruction of the full combinatorial space is carried out; finally, an approximation to the Pareto set of variants with optimal primary/promiscuous activities is derived. Application of the approach to the emergence of folding catalysis in thioredoxin scaffolds reveals an unanticipated scenario: diverse patterns of primary/promiscuous activity modulation are possible, including a moderate (but likely significant in a biological context) simultaneous enhancement of both activities. We show that this scenario can be most simply explained on the basis of the conformational diversity hypothesis, although alternative interpretations cannot be ruled out. Overall, the results reported may help clarify the mechanisms of the evolution of new functions. From a different viewpoint, the partial-least-squares-reconstruction/Pareto-set-prediction approach we have introduced provides the computational basis for an efficient directed-evolution protocol aimed at the simultaneous enhancement of several protein features and should therefore open new possibilities in the engineering of multi-functional enzymes. Author Summary: Interpretations of evolutionary processes at the molecular level have been determined to a significant extent by the concept of “trade-off”, the idea that improving a given feature of a protein molecule by mutation will likely bring about deterioration in other features. For instance, if a protein is able to carry out two different molecular tasks based on the same functional site (competing tasks), optimization for one task could be naively expected to impair its performance for the other task. In this work, we report a computational/experimental approach to assess the potential patterns of modulation of two competing molecular tasks in the course of natural evolution. Contrary to the naïve expectation, we find that diverse modulation patterns are possible, including the simultaneous optimization of the two tasks. We show, however, that this simultaneous optimization is not in conflict with the trade-offs expected for two competing tasks: using the language of the theory of economic efficiency, trade-offs are realized in the Pareto set of optimal variants for the two tasks, while most protein variants do not belong to such Pareto set. That is, most protein variants are not Pareto-efficient and can potentially be improved in terms of several features.