ArticleJournal of chemical information and modeling2021
Computational Prediction of ω-Transaminase Specificity by a Combination of Docking and Molecular Dynamics Simulations.
Article in Journal of chemical information and modeling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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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.
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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.
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Who cites it
13 citing papers in PubMed, 34 citations in OpenAlex.
- A machine learning-based workflow for transaminase selection.Chemical science · 2026Article
- Engineering of ω-transaminases for advanced applications.Applied microbiology and biotechnology · 2026Review
- Engineering ω-transaminase for efficient dihydroxyacetone transamination in serinol biosynthesis starting from methanol.Synthetic and systems biotechnology · 2026Article
- The BAHD Acyltransferase Gene Family: Evolutionary Dynamics, Biochemical Mechanisms, and Roles in Plant Stress Adaptation.Plant biotechnology journal · 2026Review
- Computational approaches to enzymatic reaction assignment: a review of methods, validations, and future directions.Briefings in bioinformatics · 2025Review
- Advances in the Molecular Modification of Microbial ω-Transaminases for Asymmetric Synthesis of Bulky Chiral Amines.Microorganisms · 2025Review
- Article
- Article
- One substrate many enzymes virtual screening uncovers missing genes of carnitine biosynthesis in human and mouse.Nature communications · 2024Article
- Computational design of highly efficient thermostable MHET hydrolases and dual enzyme system for PET recycling.Communications biology · 2023Article
- EnzyHTP Computational Directed Evolution with Adaptive Resource Allocation.Journal of chemical information and modeling · 2023Article
- Super High-Throughput Screening of Enzyme Variants by Spectral Graph Convolutional Neural Networks.Journal of chemical theory and computation · 2023Article
- Computational prediction of ω-transaminase selectivity by deep learning analysis of molecular dynamics trajectories.QRB discovery · 2023Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
ω-Transaminases (ω-TAs) catalyze the conversion of ketones to chiral amines, often with high enantioselectivity and specificity, which makes them attractive for industrial production of chiral amines. Tailoring ω-TAs to accept non-natural substrates is necessary because of their limited substrate range. We present a computational protocol for predicting the enantioselectivity and catalytic selectivity of an ω-TA from
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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.