Electrostatic potential as a reactivity scoring function in computer‐assisted enzyme engineering DOI Creative Commons
Aitor Vega, Antoni Planas, Xevi Biarnés

et al.

FEBS Journal, Journal Year: 2025, Volume and Issue: unknown

Published: May 5, 2025

The high catalytic efficiency of enzymes is attained, in part, by their capacity to stabilize electrostatically the transition state chemical reaction. High‐throughput protocols for measuring this electrostatic contribution computer‐assisted enzyme design are limited. We present here an easy‐to‐compute metric that captures complementarity charge distribution substrate at state. demonstrate such a representative dataset glycoside hydrolases, large family responsible hydrolytic cleavage glycosidic bonds oligosaccharides, polysaccharides, and glycoconjugates. have implemented BindScan , computer‐based mutational analysis protocol assist protein engineering. predictive power with two mechanistically distinct hydrolases: Spodoptera frugiperda β‐glucosidase ( Sf βgly, operates via nucleophile catalysis) Bifidobacterium bifidum lacto‐ N ‐biosidase Bb LnbB, substrate‐assisted catalysis). correctly predicts sequence positions sensible modulation k cat / K M upon mutation from experimental benchmark 51 mutants βgly 77% classification identifies variants LnbB improved transglycosylation yields (up 32%). Based on potential ligand affinity calculations, as we propose rational strategy hydrolase synthesis added‐value new reactivity may contribute expanding range computational available engineering campaigns aimed optimizing relevant properties.

Language: Английский

Insilico Mining of Metagenomic Datasets for Novel PET Hydrolase Homologs: Enhancing Enzyme Discovery for Circular Bioeconomy DOI Creative Commons
Shubham Kumar,

R. L. Bhardwaj,

Km Shivangi

et al.

Sustainable Chemistry for the Environment, Journal Year: 2025, Volume and Issue: unknown, P. 100253 - 100253

Published: May 1, 2025

Language: Английский

Citations

0
Electrostatic potential as a reactivity scoring function in computer‐assisted enzyme engineering DOI Creative Commons
Aitor Vega, Antoni Planas, Xevi Biarnés

et al.

FEBS Journal, Journal Year: 2025, Volume and Issue: unknown

Published: May 5, 2025

The high catalytic efficiency of enzymes is attained, in part, by their capacity to stabilize electrostatically the transition state chemical reaction. High‐throughput protocols for measuring this electrostatic contribution computer‐assisted enzyme design are limited. We present here an easy‐to‐compute metric that captures complementarity charge distribution substrate at state. demonstrate such a representative dataset glycoside hydrolases, large family responsible hydrolytic cleavage glycosidic bonds oligosaccharides, polysaccharides, and glycoconjugates. have implemented BindScan , computer‐based mutational analysis protocol assist protein engineering. predictive power with two mechanistically distinct hydrolases: Spodoptera frugiperda β‐glucosidase ( Sf βgly, operates via nucleophile catalysis) Bifidobacterium bifidum lacto‐ N ‐biosidase Bb LnbB, substrate‐assisted catalysis). correctly predicts sequence positions sensible modulation k cat / K M upon mutation from experimental benchmark 51 mutants βgly 77% classification identifies variants LnbB improved transglycosylation yields (up 32%). Based on potential ligand affinity calculations, as we propose rational strategy hydrolase synthesis added‐value new reactivity may contribute expanding range computational available engineering campaigns aimed optimizing relevant properties.

Language: Английский

Citations

0