Prasanna, D. | Search bioRxiv

bioRxiv2026

Coevolution-informed Bayesian optimization for sample-efficient protein design

Protein engineering is limited less by generating variants than by the cost of evaluating them, so designing under a tight budget demands sequence features that let a model learn fitness from very few examples. We introduce ALSEBO (Active Learning Sequence Exploration via Bayesian Optimization), which couples a generative latent sequence landscape to Bayesian optimization and featurizes candidates with direct-coupling-analysis (DCA) coevolutionary statistics. This representation carries a specific inductive bias: it places the dominant organizer of the fitness landscape along a single linear coordinate, producing a smooth, funnel-like objective that a low-data surrogate navigates efficiently. On a virtual avGFP fluorescence benchmark, ALSEBO reaches the optimum in [~]40 evaluations and outpaces protein-language-model embeddings and raw latent coordinates; controls with representation-neutral oracles confirm that the advantage is intrinsic, not an artifact of the benchmark. Molecular dynamics of the optimized variant recovers structural hallmarks of fluorescence, and ALSEBO transfers to divergent GFP orthologs and to a non-GFP enzyme, establishing a data-efficient route to protein design.

biophysics↗

bioRxiv2022

NudF-boosted strategy to improve the yield of DXS pathway

BackgroundTerpenoids form a large pool of highly diverse organic compounds possessing several economically important properties, including nutritional, aromatic, and pharmacological properties. The DXP pathways end enzyme, nuclear distribution protein (NudF), interacting with isopentenyl pyrophosphate (IPP) and dimethylallyl pyrophosphate (DMAPP), is critical for the synthesis of isoprenol/prenol/downstream compounds. The enzyme is yet to be thoroughly investigated to increase the overall yield of terpenoids in the Bacillus subtilis, which is widely used in industry and is generally regarded as safe (GRAS) bacterium. The study aims to analyze the evolutionary conservation across the active site, and map the key residues for mutagenesis studies. The study would allow us customize the metabolic load towards the synthesis of prenol or isoprenol or any of the downstream molecules. ResultsThe 37-sequence dataset, extracted from 103 Bacillus subtilis entries, show a high phylogenetic divergence, and only six one-motif sequences ASB92783.1, ASB69297.1, ASB56714.1, AOR97677.1, AOL97023.1, and OAZ71765.1 show monophyly relationship, unlike a complete polyphyly relationship between the other 31 three-motif sequences. Further, only 47 of 179 residues of the representative sequence CUB50584.1 are observed to be significantly conserved. Docking analysis shows a preferential bias of ADP-ribose pyrophosphatase towards IPP, and a nearly 3-fold energetic difference is observed between IPP and DMAPP. Computational saturation mutagenesis of the seven hotspot residues identifies two key positions LYS78 and PHE116, encoded within loop1 and loop7, majorly interact with the ligands DMAPP and IPP, and their mutants K78I/K78L and PHE116D/PHE116E are found to stabilize the overall conformation. The loops are hereby shown to play a regulatory role in guiding the promiscuity of NudF towards a specific ligand. ConclusionThe study map the phylogenetic relationship between the 37 representative B.subtiis NudF sequences, and through sequence conservation, structural contact map, topological flexibility, and saturation mutagenesis of the active site residues, the essential residues regulating the interaction of NudF with IPP/DMAPP are deciphered. The study robustly screens its mutational landscape and localizes the two crucial residues LYS78 and PHE116 for directing the mutagenesis studies. The preliminary docking and simulation results also suggest a preferential bias of ADP-ribose pyrophosphatase towards IPP over DMAPP. The findings would pave the way for the development of novel enzyme variants with highly improved catalytic ability for the large-scale bioproduction of specific terpenoids with significant neutraceutical or commercial value.

bioengineering↗