AIMC Topic: Serine Proteases

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Long-Range Electrostatics in Serine Proteases: Machine Learning-Driven Reaction Sampling Yields Insights for Enzyme Design.

Journal of chemical information and modeling Feb 10, 2025
Computational enzyme design is a promising technique for producing novel enzymes for industrial and clinical needs. A key challenge that this technique faces is to consistently achieve the desired activity. Fundamental studies of natural enzymes reve...
Quantum Theory Biocatalysis Models, Molecular Static Electricity Protein Engineering Catalytic Domain Serine Proteases Machine Learning
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A genetic programming-based approach to identify potential inhibitors of serine protease of .

Future medicinal chemistry Nov 15, 2019
We applied genetic programming approaches to understand the impact of descriptors on inhibitory effects of serine protease inhibitors of () and the discovery of new inhibitors as drug candidates. The experimental dataset of serine protease inhibit...
Serine Proteases Serine Proteinase Inhibitors Models, Molecular Mycobacterium tuberculosis Machine Learning
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Elucidating the druggability of the human proteome with eFindSite.

Journal of computer-aided molecular design Mar 19, 2019
Identifying the viability of protein targets is one of the preliminary steps of drug discovery. Determining the ability of a protein to bind drugs in order to modulate its function, termed the druggability, requires a non-trivial amount of time and r...
Serine Proteases Binding Sites 5-Aminolevulinate Synthetase Proteins Supervised Machine Learning Proteome Software Drug Design Drug Discovery Protein Binding Humans
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Data-driven supervised learning of a viral protease specificity landscape from deep sequencing and molecular simulations.

Proceedings of the National Academy of Sciences of the United States of America Dec 26, 2018
Biophysical interactions between proteins and peptides are key determinants of molecular recognition specificity landscapes. However, an understanding of how molecular structure and residue-level energetics at protein-peptide interfaces shape these l...
Antiviral Agents Metabolomics Structure-Activity Relationship Models, Molecular Energy Metabolism Drug Resistance, Viral Serine Proteases Viral Nonstructural Proteins Hepacivirus High-Throughput Nucleotide Sequencing Supervised Machine Learning Peptide Hydrolases Substrate Specificity
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QSAR studies of the bioactivity of hepatitis C virus (HCV) NS3/4A protease inhibitors by multiple linear regression (MLR) and support vector machine (SVM).

Bioorganic & medicinal chemistry letters May 3, 2017
In this study, quantitative structure-activity relationship (QSAR) models using various descriptor sets and training/test set selection methods were explored to predict the bioactivity of hepatitis C virus (HCV) NS3/4A protease inhibitors by using a ...
Molecular Structure Hepacivirus Linear Models Serine Proteases Support Vector Machine Dose-Response Relationship, Drug Antiviral Agents Viral Nonstructural Proteins Protease Inhibitors Quantitative Structure-Activity Relationship
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Purification and biochemical properties of SDS-stable low molecular weight alkaline serine protease from Citrullus colocynthis.

Natural product research Sep 1, 2015
A low molecular weight serine protease from seeds of Citrullus colocynthis was purified to electrophoretic homogeneity with high level of catalytic efficiency (22,945 M(-1) S(-1)). The enzyme was a monomer with molecular mass of 25 kDa estimated by S...
Molecular Weight Enzyme Stability Hydrogen-Ion Concentration Substrate Specificity Citrullus colocynthis Serine Proteases Electrophoresis, Polyacrylamide Gel Temperature Seeds
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