AIMC Topic: Peptide Hydrolases
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The Proteasix Ontology.
Journal of biomedical semantics
Jun 4, 2016
BACKGROUND: The Proteasix Ontology (PxO) is an ontology that supports the Proteasix tool; an open-source peptide-centric tool that can be used to predict automatically and in a large-scale fashion in silico the proteases involved in the generation of...
Protease engineering: Approaches, tools, and emerging trends.
Biotechnology advances
Sep 1, 2025
Engineered proteases with bespoke substrate specificities and activities can empower broad and innovative applications in biomedicine, mass spectrometry-based proteomics, and chemical and synthetic biology. This review provides an authoritative, topi...
Single-Walled Carbon Nanotube Probes for Protease Characterization Directly in Cell-Free Expression Reactions.
Analytical chemistry
May 27, 2025
Proteins can be rapidly prototyped with cell-free expression (CFE) but in most cases there is a lack of probes or assays to measure their function directly in the cell lysate, thereby limiting the throughput of these screens. Increased throughput is ...
Cell-Free Protein Synthesis as a Method to Rapidly Screen Machine Learning-Generated Protease Variants.
ACS synthetic biology
May 16, 2025
Machine learning (ML) tools have revolutionized protein structure prediction, engineering, and design, but the best ML tool is only as good as the training data it learns from. To obtain high-quality structural or functional data, protein purificatio...
Determination of Novel SARS-CoV-2 Inhibitors by Combination of Machine Learning and Molecular Modeling Methods.
Medicinal chemistry (Shariqah (United Arab Emirates))
Jan 1, 2024
INTRODUCTION: Within the scope of the project, this study aimed to find novel inhibitors by combining computational methods. In order to design inhibitors, it was aimed to produce molecules similar to the RdRp inhibitor drug Favipiravir by using the ...
ProsperousPlus: a one-stop and comprehensive platform for accurate protease-specific substrate cleavage prediction and machine-learning model construction.
Briefings in bioinformatics
Sep 22, 2023
Proteases contribute to a broad spectrum of cellular functions. Given a relatively limited amount of experimental data, developing accurate sequence-based predictors of substrate cleavage sites facilitates a better understanding of protease functions...
Transfer learning for drug-target interaction prediction.
Bioinformatics (Oxford, England)
Jun 30, 2023
MOTIVATION: Utilizing AI-driven approaches for drug-target interaction (DTI) prediction require large volumes of training data which are not available for the majority of target proteins. In this study, we investigate the use of deep transfer learnin...
[The Effects of All-trans Retinoic Acid on the Expression of Inflammatory Cytokines and Cartilage Damage Related Protease in Rats with Collagen Induced Arthritis].
Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
Jul 1, 2016
OBJECTIVES: To investigate the effects of all-trans retinoic acid (ATRA) on arthritis and the expressions of inflammatory cytokines and cartilage damage related proteases of the collagen-induced arthritis model (CIA) rats .
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