AIMC Topic: Substrate Specificity

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De novo design of luciferases using deep learning.

Nature Feb 22, 2023
De novo enzyme design has sought to introduce active sites and substrate-binding pockets that are predicted to catalyse a reaction of interest into geometrically compatible native scaffolds, but has been limited by a lack of suitable protein structur...
Deep Learning Oxidation-Reduction Luminescence Enzyme Stability Hot Temperature Substrate Specificity Luciferins Luciferases Biocatalysis Catalytic Domain
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Using Steady-State Kinetics to Quantitate Substrate Selectivity and Specificity: A Case Study with Two Human Transaminases.

Molecules (Basel, Switzerland) Feb 18, 2022
We examined the ability of two human cytosolic transaminases, aspartate aminotransferase (GOT1) and alanine aminotransferase (GPT), to transform their preferred substrates whilst discriminating against similar metabolites. This offers an opportunity ...
Alkyl and Aryl Transferases Kinetics Structure-Activity Relationship Protein Conformation Humans Models, Molecular Enzyme Activation Animals Amino Acids Transferases (Other Substituted Phosphate Groups) Cattle Binding Sites Transaminases Substrate Specificity
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Machine learning modeling of family wide enzyme-substrate specificity screens.

PLoS computational biology Feb 10, 2022
Biocatalysis is a promising approach to sustainably synthesize pharmaceuticals, complex natural products, and commodity chemicals at scale. However, the adoption of biocatalysis is limited by our ability to select enzymes that will catalyze their nat...
Proteins Amino Acid Sequence Substrate Specificity Machine Learning Drug Discovery
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Deep learning allows genome-scale prediction of Michaelis constants from structural features.

PLoS biology Oct 19, 2021
The Michaelis constant KM describes the affinity of an enzyme for a specific substrate and is a central parameter in studies of enzyme kinetics and cellular physiology. As measurements of KM are often difficult and time-consuming, experimental estima...
Deep Learning Kinetics Neural Networks, Computer Databases, Genetic Models, Biological Metabolomics Genome Substrate Specificity Enzymes
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Time-resolved in vivo ubiquitinome profiling by DIA-MS reveals USP7 targets on a proteome-wide scale.

Nature communications Sep 13, 2021
Mass spectrometry (MS)-based ubiquitinomics provides system-level understanding of ubiquitin signaling. Here we present a scalable workflow for deep and precise in vivo ubiquitinome profiling, coupling an improved sample preparation protocol with dat...
Time Factors Cell Line, Tumor Proteomics Humans Neural Networks, Computer HCT116 Cells Jurkat Cells Substrate Specificity Ubiquitin Proteome Signal Transduction Tandem Mass Spectrometry Ubiquitination Ubiquitin-Specific Peptidase 7
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A Machine Learning Study on the Thermostability Prediction of (R)--Selective Amine Transaminase from Aspergillus terreus.

BioMed research international Aug 16, 2021
Artificial intelligence technologies such as machine learning have been applied to protein engineering, with unique advantages in protein structure, function prediction, catalytic activity, and other issues in recent years. Screening better mutants i...
Models, Molecular Protein Stability Hot Temperature Machine Learning Transaminases Amines Aspergillus Protein Structural Elements Substrate Specificity Protein Engineering
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CYPstrate: A Set of Machine Learning Models for the Accurate Classification of Cytochrome P450 Enzyme Substrates and Non-Substrates.

Molecules (Basel, Switzerland) Aug 2, 2021
The interaction of small organic molecules such as drugs, agrochemicals, and cosmetics with cytochrome P450 enzymes (CYPs) can lead to substantial changes in the bioavailability of active substances and hence consequences with respect to pharmacologi...
Xenobiotics Humans Cytochrome P-450 Enzyme System Substrate Specificity Machine Learning Animals
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Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2.

BioMed research international May 25, 2021
A global pandemic has emerged following the appearance of the new severe acute respiratory virus whose official name is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), strongly affecting the health sector as well as the world econom...
Gene Expression Kinetics COVID-19 Drug Treatment Thermodynamics Protease Inhibitors Catalytic Domain Substrate Specificity Humans Antiviral Agents Neural Networks, Computer Protein Binding Biological Products SARS-CoV-2 Small Molecule Libraries Molecular Docking Simulation Coronavirus 3C Proteases Protein Structure, Secondary Drug Design Protein Interaction Domains and Motifs
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Integrating structure-based machine learning and co-evolution to investigate specificity in plant sesquiterpene synthases.

PLoS computational biology Mar 22, 2021
Sesquiterpene synthases (STSs) catalyze the formation of a large class of plant volatiles called sesquiterpenes. While thousands of putative STS sequences from diverse plant species are available, only a small number of them have been functionally ch...
Sequence Homology, Amino Acid Alkyl and Aryl Transferases Protein Conformation Cations Substrate Specificity Plants Amino Acid Sequence Sesquiterpenes Machine Learning Evolution, Molecular
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Enzyme Promiscuity Prediction Using Hierarchy-Informed Multi-Label Classification.

Bioinformatics (Oxford, England) Jan 30, 2021
MOTIVATION: As experimental efforts are costly and time consuming, computational characterization of enzyme capabilities is an attractive alternative. We present and evaluate several machine-learning models to predict which of 983 distinct enzymes, a...
Computational Biology Databases, Protein Neural Networks, Computer Enzyme Inhibitors Machine Learning Substrate Specificity Enzymes
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