ReviewACS catalysis2023
Accelerating Biocatalysis Discovery with Machine Learning: A Paradigm Shift in Enzyme Engineering, Discovery, and Design.
Review in ACS catalysis, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
29 citing papers in PubMed, 80 citations in OpenAlex.
- Next-Generation Manufacturing: The Evolving Role of Biocatalysis in AstraZeneca.Chembiochem : a European journal of chemical biology · 2026Review
- Application and Molecular Modification of Enzyme in Textile Degumming.Applied biochemistry and biotechnology · 2026Review
- Biosynthesis and Microbial Production of Carminic Acid: From Pathway Elucidation to Synthetic Biology.Microorganisms · 2026Review
- Geometric Deep Learning-Based Drug Design Models for Small-Molecule Drug Discovery.Molecular informatics · 2026Review
- Structure-Guided Extremophile Genome Mining Expands the PETase Landscape and Reveals PET-Hydrolysing True Lipase Lineages.Microbial biotechnology · 2026Article
- How far can you go? Extrapolating values of catalytic activity from known protein landscapes in natural and directed evolution.Chemical Society reviews · 2026Review
- The BAHD Acyltransferase Gene Family: Evolutionary Dynamics, Biochemical Mechanisms, and Roles in Plant Stress Adaptation.Plant biotechnology journal · 2026Review
- High-level production of vitamin K2 inSynthetic and systems biotechnology · 2026Article
- Fast analysis and engineering of protein function by microbe-independent deep assembly and screening.Molecular systems biology · 2026Article
- Advances in Machine Learning Models for Predicting Enzyme Kinetic Parameters.Journal of chemical information and modeling · 2026Review
- Machine learning for enzyme catalytic activity: current progress and future horizons.Briefings in bioinformatics · 2026Review
- Protein Design Enters the Artificial Intelligence Era: Foundations, Tools, and Emerging Paradigms.Computational and structural biotechnology journal · 2026Review
- Unlocking Enzyme Discovery: Leveraging Multi-Omics, Machine Learning, and De Novo Design.Methods in molecular biology (Clifton, N.J.) · 2026Article
- AI-Driven Enzyme Engineering: Emerging Models and Next-Generation Biotechnological Applications.Molecules (Basel, Switzerland) · 2025Review
- Machine learning-guided discovery of thermophilic carbonic anhydrases from environmental metagenomes.Scientific reports · 2025Article
- Of Revolutions and Roadblocks: The Emerging Role of Machine Learning in Biocatalysis.ACS central science · 2025Review
- Deep-Learning Driven Identification of Novel Antimicrobial Peptides.Chemistry (Weinheim an der Bergstrasse, Germany) · 2025Article
- Substrate Activation Efficiency in Active Sites of Hydrolases Determined by QM/MM Molecular Dynamics and Neural Networks.International journal of molecular sciences · 2025Article
- A mini review on revolutionizing hydrogenation catalysis: unleashing transformative power of artificial intelligence.Journal of molecular modeling · 2025Review
- Unraveling the molecular basis of substrate specificity and halogen activation in vanadium-dependent haloperoxidases.Nature communications · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Emerging computational tools promise to revolutionize protein engineering for biocatalytic applications and accelerate the development timelines previously needed to optimize an enzyme to its more efficient variant. For over a decade, the benefits of predictive algorithms have helped scientists and engineers navigate the complexity of functional protein sequence space. More recently, spurred by dramatic advances in underlying computational tools, the promise of faster, cheaper, and more accurate enzyme identification, characterization, and engineering has catapulted terms such as artificial intelligence and machine learning to the must-have vocabulary in the field. This Perspective aims to showcase the current status of applications in pharmaceutical industry and also to discuss and celebrate the innovative approaches in protein science by highlighting their potential in selected recent developments and offering thoughts on future opportunities for biocatalysis. It also critically assesses the technology's limitations, unanswered questions, and unmet challenges.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.