ArticleMetabolic engineering communications2020
Improving protein solubility and activity by introducing small peptide tags designed with machine learning models.
Article in Metabolic engineering communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Directed evolution of functional intrinsically disordered proteins.Nature chemical biology · 2026Article
- Integrative structural and physicochemical characterization of chalcone synthase enzymes from medicinal plants using AlphaFold, molecular docking, and molecular dynamics.Scientific reports · 2026Article
- Deep learning on protein language model embeddings unlocks accurate prediction of protein solubility.Frontiers in microbiology · 2026Article
- Enzyme sequence optimisation via Gromov-Wasserstein Autoencoders integrating MSA techniques.Journal of enzyme inhibition and medicinal chemistry · 2025Article
- SUMO-G5C23-D208G@ZIF-F: A Novel Immobilized Enzyme with Enhanced Stability and Reusability for Organophosphorus Hydrolysis.International journal of molecular sciences · 2025Article
- A review on computational models for predicting protein solubility.Journal of microbiology (Seoul, Korea) · 2025Review
- ProSol-multi: Protein solubility prediction via amino acids multi-level correlation and discriminative distribution.Heliyon · 2024Article
- ThermoLink: Bridging disulfide bonds and enzyme thermostability through database construction and machine learning prediction.Protein science : a publication of the Protein Society · 2024Article
- Organelle-dependent polyprotein designs enable stoichiometric expression of nitrogen fixation components targeted to mitochondria.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- The Versatile Biocatalyst of Cytochrome P450 CYP102A1: Structure, Function, and Engineering.Molecules (Basel, Switzerland) · 2023Review
- Protein expression/secretion boost by a novel unique 21-mer cis-regulatory motif (Exin21) via mRNA stabilization.Molecular therapy : the journal of the American Society of Gene Therapy · 2023Article
- Directed Evolution of Soluble α-1,2-Fucosyltransferase Using Kanamycin Resistance Protein as a Phenotypic Reporter for Efficient Production of 2'-Fucosyllactose.Journal of microbiology and biotechnology · 2022Article
- Protein Design: From the Aspect of Water Solubility and Stability.Chemical reviews · 2022Review
- Protein Function Analysis through Machine Learning.Biomolecules · 2022Review
- Fusion Tag Design Influences Soluble Recombinant Protein Production inInternational journal of molecular sciences · 2022Article
- In silico screening and heterologous expression of soluble dimethyl sulfide monooxygenases of microbial origin in Escherichia coli.Applied microbiology and biotechnology · 2022Article
- Charged Polypeptide Tail Boosts the Salt Resistance of Enzyme-Containing Complex Coacervate Micelles.Biomacromolecules · 2022Article
- Solution NMR and racemic crystallography provide insights into a novel structural class of cyclic plant peptides.RSC chemical biology · 2021Article
- Trehalose treatment alters carbon partitioning and reduces the accumulation of individual metabolites but does not affect salt tolerance in the green microalgaPhysiology and molecular biology of plants : an international journal of functional plant biology · 2021Article
- Enhanced Production of a Thermostable Carbonic Anhydrase inMolecules (Basel, Switzerland) · 2021Article
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5 authors.
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Abstract
Improving catalytic ability of enzymes is critical to the success of many metabolic engineering projects, but the search space of possible protein mutants is too large to explore exhaustively through experiments. To some extent, highly soluble enzymes tend to exhibit high activity due to their better folding quality. Here, we demonstrate that an optimization algorithm based on a regression model can effectively design short peptide tags to improve solubility of a few model enzymes. Based on the protein sequence information, a support vector regression model we recently developed was used to evaluate protein solubility after small peptide tags were introduced to a target protein. The optimization algorithm guided the sequences of the tags to evolve towards variants that had higher solubility. The optimization results were validated successfully by measuring solubility and activity of the model enzyme with and without the identified tags. The solubility of one protein (tyrosine ammonia lyase) was more than doubled and its activity was improved by 250%. This strategy successfully increased solubility of another two enzymes (aldehyde dehydrogenase and 1-deoxy-D-xylulose-5-phosphate synthase) we tested. The presented optimization methodology thus provides a valuable tool for improving enzyme performance for metabolic engineering and other biotechnology projects.
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