Biology subjects

Rakotoharisoa, R. V.

Publications and source records attributed to Rakotoharisoa, R. V..

4 recordsLinked to original sources

bioRxiv2026

Predictable adaptive evolution of a phage endolysin through substrate recognition optimization

Bacteriophages release progeny by producing endolysins that degrade the bacterial cell wall. While the frequent horizontal transfer of endolysins suggests substantial evolutionary plasticity, the mechanisms by which these enzymes adapt to new phage-host contexts remain poorly understood. Here, we investigated the evolutionary dynamics and structural mechanisms governing endolysin adaptation following experimental evolution of a chimeric phage generated via heterologous endolysin exchange between phages infecting different hosts. Using replicate experimental evolution and time-resolved PacBio sequencing, we identified a dominant, highly reproducible adaptive trajectory characterized by the stepwise fixation of three key mutations. This constrained mutational order correlated with incremental gains in enzymatic activity, reflecting a rugged yet predictable fitness landscape. High-resolution structural analyses revealed that these substitutions lie exclusively outside the catalytic site; instead, they enhance substrate recognition through electrostatic tuning, optimized hydrophobic packing, and local conformational refinement, resulting in significantly higher binding affinity. While the adaptive trajectory was largely conserved, one replicate followed an alternative path, highlighting the interplay between selection and historical contingency. Adaptation was further shaped by a functional trade-off, whereby increased lytic activity on the novel host was accompanied by reduced activity on the ancestral host, consistent with antagonistic pleiotropy. Genome-wide sequencing additionally identified a compensatory mutation in a lytic transglycosylase, suggesting coordinated evolution of the broader lysis machinery. Together, these results demonstrate that endolysins evolve through reproducible adaptive walks constrained by structure, selection, and trade-offs, providing a mechanistic framework for understanding enzyme evolution and informing rational protein engineering.

evolutionary biology↗

bioRxiv2025

Distal mutations enhance catalysis in designed enzymes by facilitating substrate binding and product release

The role of amino-acid residues distant from an enzymes active site in facilitating the complete catalytic cycle--including substrate binding, chemical transformation, and product release-- remains poorly understood. Here, we investigate how distal mutations promote the catalytic cycle by engineering mutants of three de novo Kemp eliminases containing either active-site or distal mutations identified through directed evolution. Kinetic analyses, X-ray crystallography, and molecular dynamics simulations reveal that while active-site mutations create preorganized catalytic sites for efficient chemical transformation, distal mutations enhance catalysis by facilitating substrate binding and product release through tuning structural dynamics to widen the active-site entrance and reorganize surface loops. These distinct contributions work synergistically to improve overall activity, demonstrating that a well-organized active site, though necessary, is not sufficient for optimal catalysis. Our findings reveal critical roles that distal residues play in shaping the catalytic cycle to enhance efficiency, yielding valuable insights for enzyme design.

biochemistry↗

bioRxiv2023

Design of efficient artificial enzymes using crystallographically-enhanced conformational sampling

The ability to create efficient artificial enzymes for any chemical reaction is of great interest. Here, we describe a computational design method for increasing catalytic efficiency of de novo enzymes to a level comparable to their natural counterparts without relying on directed evolution. Using structural ensembles generated from dynamics-based refinement against X-ray diffraction data collected from crystals of Kemp eliminases HG3 (kcat/KM 125 M-1 s-1) and KE70 (kcat/KM 57 M-1 s-1), we design from each enzyme [≤]10 sequences predicted to catalyze this reaction more efficiently. The most active designs display kcat/KM values improved by 100-250-fold, comparable to mutants obtained after screening thousands of variants in multiple rounds of directed evolution. Crystal structures show excellent agreement with computational models. Our work shows how computational design can generate efficient artificial enzymes by exploiting the true conformational ensemble to more effectively stabilize the transition state.

biochemistry↗

bioRxiv2020

Evolution of an enzyme conformational ensemble guides design of an efficient biocatalyst

The creation of artificial enzymes is a key objective of computational protein design. Although de novo enzymes have been successfully designed, these exhibit low catalytic efficiencies, requiring directed evolution to improve activity. Here, we used room-temperature X-ray crystallography to study changes in the conformational ensemble during evolution of the designed Kemp eliminase HG3 (kcat/KM 160 M-1s-1). We observed that catalytic residues were increasingly rigidified, the active site became better pre-organized, and its entrance was widened. Based on these observations, we engineered HG4, an efficient biocatalyst (kcat/KM 120,000 M-1s-1) containing active-site mutations found during evolution but not distal ones. HG4 structures revealed that its active site was pre-organized and rigidified for efficient catalysis. Our results show how directed evolution circumvents challenges inherent to enzyme design by shifting conformational ensembles to favor catalytically-productive sub-states, and suggest improvements to the design methodology that incorporate ensemble modeling of crystallographic data.

biophysics↗