AIMC Topic: Substrate Specificity
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A generalized platform for artificial intelligence-powered autonomous enzyme engineering.
Nature communications
Jul 1, 2025
Proteins are the molecular machines of life with numerous applications in energy, health, and sustainability. However, engineering proteins with desired functions for practical applications remains slow, expensive, and specialist-dependent. Here we r...
Data-driven protease engineering by DNA-recording and epistasis-aware machine learning.
Nature communications
Jul 1, 2025
Protein engineering has recently seen tremendous transformation due to machine learning (ML) tools that predict structure from sequence at unprecedented precision. Predicting catalytic activity, however, remains challenging, restricting our capabilit...
Charting γ-secretase substrates by explainable AI.
Nature communications
Jul 1, 2025
Proteases recognize substrates by decoding sequence information-an essential cellular process elusive when recognition motifs are absent. Here, we unravel this problem for γ-secretase, an intramembrane-cleaving protease associated with Alzheimer's di...
Substrate Specificity of the Organic Cation Transporters MATE1 and MATE2K and Functional Overlap with OCT1 and OCT2.
Journal of medicinal chemistry
Jun 13, 2025
The multidrug and toxin extrusion proteins MATE1 and MATE2K may determine the pharmacokinetics and drug-drug interactions of many drugs. However, their substrate spectrum and synergy with organic cation transporters OCT1 and OCT2 remain incompletely ...
Substrate Activation Efficiency in Active Sites of Hydrolases Determined by QM/MM Molecular Dynamics and Neural Networks.
International journal of molecular sciences
May 26, 2025
The active sites of enzymes are able to activate substrates and perform chemical reactions that cannot occur in solutions. We focus on the hydrolysis reactions catalyzed by enzymes and initiated by the nucleophilic attack of the substrate's carbonyl ...
Deciphering the dark cancer phosphoproteome using machine-learned co-regulation of phosphosites.
Nature communications
Mar 20, 2025
Mass spectrometry-based phosphoproteomics offers a comprehensive view of protein phosphorylation, yet our limited knowledge about the regulation and function of most phosphosites hampers the extraction of meaningful biological insights. To address th...
Geometry-encoded molecular dynamics enables deep learning insights into P450 regiospecificity control.
Scientific reports
Mar 3, 2025
Cytochrome P450 1A2, as many isoenzymes, can generate multiple metabolites from a single substrate. A loose coupling between substrate binding and oxygen activation makes possible substrate reorientations at the active site prior to catalysis. In the...
A novel interpretability framework for enzyme turnover number prediction boosted by pre-trained enzyme embeddings and adaptive gate network.
Methods (San Diego, Calif.)
Feb 26, 2025
It is a vital step to identify the enzyme turnover number (kcat) in synthetic biology and early-stage drug discovery. Recently, deep learning methods have achieved inspiring process to predict kcat with the development of multi-species enzyme-substra...
Accelerated enzyme engineering by machine-learning guided cell-free expression.
Nature communications
Jan 20, 2025
Enzyme engineering is limited by the challenge of rapidly generating and using large datasets of sequence-function relationships for predictive design. To address this challenge, we develop a machine learning (ML)-guided platform that integrates cell...
HIV OctaScanner: A Machine Learning Approach to Unveil Proteolytic Cleavage Dynamics in HIV-1 Protease Substrates.
Journal of chemical information and modeling
Jan 14, 2025
The rise of resistance to antiretroviral drugs due to mutations in human immunodeficiency virus-1 (HIV-1) protease is a major obstacle to effective treatment. These mutations alter the drug-binding pocket of the protease and reduce the drug efficacy ...
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