{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Vega A"],"funding":["Ramon Llull University/Obra Social la Caixa","Ministry of Science and Innovation, Spain"],"pagination":["4211-4231"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12366256"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["292(16)"],"pubmed_abstract":["The high catalytic efficiency of enzymes is attained, in part, by their capacity to stabilize electrostatically the transition state of the chemical reaction. High-throughput protocols for measuring this electrostatic contribution in computer-assisted enzyme design are limited. We present here an easy-to-compute metric that captures the electrostatic complementarity of the enzyme to the charge distribution of the substrate at the transition state. We demonstrate such a complementarity for a representative dataset of glycoside hydrolases, a large family of enzymes responsible for the hydrolytic cleavage of glycosidic bonds in oligosaccharides, polysaccharides, and glycoconjugates. We have implemented this metric in BindScan, a computer-based mutational analysis protocol to assist protein engineering. We demonstrate the predictive power of BindScan with this metric for two mechanistically distinct glycoside hydrolases: Spodoptera frugiperda β-glucosidase (Sfβgly, operates via protein nucleophile catalysis) and Bifidobacterium bifidum lacto-N-biosidase (BbLnbB, operates via substrate-assisted catalysis). The metric correctly predicts sequence positions sensible to the modulation of k<sub>cat</sub>/K<sub>M</sub> upon mutation from an experimental benchmark of 51 mutants of Sfβgly with 77% classification efficiency and identifies variants of BbLnbB with improved transglycosylation yields (up to 32%). Based on electrostatic potential and ligand affinity calculations, as implemented in BindScan, we propose a rational strategy to design glycoside hydrolase variants with improved transglycosylation efficiency for the synthesis of added-value glycoconjugates. The new reactivity metric may contribute to expanding the range of computational protocols available to assist enzyme engineering campaigns aimed at optimizing mechanistically relevant properties."],"journal":["The FEBS journal"],"pubmed_title":["Electrostatic potential as a reactivity scoring function in computer-assisted enzyme engineering."],"pmcid":["PMC12366256"],"funding_grant_id":["GLYCODESIGN (PID2019-104350RB-I00)","BINDSCAN 2.0'2020","GLYCOENGIN (PID2022-138252OB-I00)"],"pubmed_authors":["Vega A","Planas A","Biarnes X"],"additional_accession":[]},"is_claimable":false,"name":"Electrostatic potential as a reactivity scoring function in computer-assisted enzyme engineering.","description":"The high catalytic efficiency of enzymes is attained, in part, by their capacity to stabilize electrostatically the transition state of the chemical reaction. High-throughput protocols for measuring this electrostatic contribution in computer-assisted enzyme design are limited. We present here an easy-to-compute metric that captures the electrostatic complementarity of the enzyme to the charge distribution of the substrate at the transition state. We demonstrate such a complementarity for a representative dataset of glycoside hydrolases, a large family of enzymes responsible for the hydrolytic cleavage of glycosidic bonds in oligosaccharides, polysaccharides, and glycoconjugates. We have implemented this metric in BindScan, a computer-based mutational analysis protocol to assist protein engineering. We demonstrate the predictive power of BindScan with this metric for two mechanistically distinct glycoside hydrolases: Spodoptera frugiperda β-glucosidase (Sfβgly, operates via protein nucleophile catalysis) and Bifidobacterium bifidum lacto-N-biosidase (BbLnbB, operates via substrate-assisted catalysis). The metric correctly predicts sequence positions sensible to the modulation of k<sub>cat</sub>/K<sub>M</sub> upon mutation from an experimental benchmark of 51 mutants of Sfβgly with 77% classification efficiency and identifies variants of BbLnbB with improved transglycosylation yields (up to 32%). Based on electrostatic potential and ligand affinity calculations, as implemented in BindScan, we propose a rational strategy to design glycoside hydrolase variants with improved transglycosylation efficiency for the synthesis of added-value glycoconjugates. The new reactivity metric may contribute to expanding the range of computational protocols available to assist enzyme engineering campaigns aimed at optimizing mechanistically relevant properties.","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Aug","modification":"2026-05-29T14:29:47.613Z","creation":"2026-04-08T05:05:23.825Z"},"accession":"S-EPMC12366256","cross_references":{"pubmed":["40322838"],"doi":["10.1111/febs.70121"]}}