AIMC Topic: Structure-Activity Relationship

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Machine Learning Approaches for Metalloproteins.

Molecules (Basel, Switzerland) Feb 14, 2022
Metalloproteins are a family of proteins characterized by metal ion binding, whereby the presence of these ions confers key catalytic and ligand-binding properties. Due to their ubiquity among biological systems, researchers have made immense efforts...
Machine Learning Drug Design Protein Binding Protein Stability Proteolysis Binding Sites Metalloproteins Structure-Activity Relationship Models, Molecular Amino Acid Sequence
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Interpretation of Structure-Activity Relationships in Real-World Drug Design Data Sets Using Explainable Artificial Intelligence.

Journal of chemical information and modeling Jan 26, 2022
In silico models based on Deep Neural Networks (DNNs) are promising for predicting activities and properties of new molecules. Unfortunately, their inherent black-box character hinders our understanding, as to which structural features are important ...
Neural Networks, Computer Structure-Activity Relationship Artificial Intelligence Computer Simulation Drug Design
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Ensemble learning from ensemble docking: revisiting the optimum ensemble size problem.

Scientific reports Jan 10, 2022
Despite considerable advances obtained by applying machine learning approaches in protein-ligand affinity predictions, the incorporation of receptor flexibility has remained an important bottleneck. While ensemble docking has been used widely as a so...
Machine Learning Molecular Docking Simulation Protein Binding Cyclin-Dependent Kinase 2 Crystallography, X-Ray Protein Conformation Binding Sites Support Vector Machine Structure-Activity Relationship Ligands
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Computational identification of 4-carboxyglutamate sites to supplement physiological studies using deep learning.

Scientific reports Jan 7, 2022
In biological systems, Glutamic acid is a crucial amino acid which is used in protein biosynthesis. Carboxylation of glutamic acid is a significant post-translational modification which plays important role in blood coagulation by activating prothrom...
Glutamic Acid Models, Molecular Amino Acid Sequence Reproducibility of Results Protein Conformation Deep Learning Proteins Structure-Activity Relationship Computational Biology Protein Processing, Post-Translational
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A computer-aided drug design approach to discover tumour suppressor p53 protein activators for colorectal cancer therapy.

Bioorganic & medicinal chemistry Nov 27, 2021
Colorectal cancer (CRC) is the third most detected cancer and the second foremost cause of cancer deaths in the world. Intervention targeting p53 provides potential therapeutic strategies, but thus far no p53-based therapy has been successfully trans...
Tumor Suppressor Protein p53 Dihydroergotoxine Drug Screening Assays, Antitumor Structure-Activity Relationship Molecular Structure Molecular Docking Simulation Drug Discovery Antineoplastic Agents Dose-Response Relationship, Drug Cell Survival Cell Line, Tumor Cell Proliferation Humans Machine Learning Colorectal Neoplasms
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Application of Deep Neural Network Models in Drug Discovery Programs.

ChemMedChem Oct 18, 2021
In silico driven optimization of compound properties related to pharmacokinetics, pharmacodynamics, and safety is a key requirement in modern drug discovery. Nowadays, large and harmonized datasets allow to implement deep neural networks (DNNs) as a ...
Factor Xa Inhibitors Cytochrome P-450 CYP3A Cytochrome P-450 CYP3A Inhibitors Humans Drug Discovery Deep Learning Dose-Response Relationship, Drug Molecular Structure Structure-Activity Relationship Factor Xa
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Machine Learning Data Augmentation as a Tool to Enhance Quantitative Composition-Activity Relationships of Complex Mixtures. A New Application to Dissect the Role of Main Chemical Components in Bioactive Essential Oils.

Molecules (Basel, Switzerland) Oct 17, 2021
Scientific investigation on essential oils composition and the related biological profile are continuously growing. Nevertheless, only a few studies have been performed on the relationships between chemical composition and biological data. Herein, th...
Machine Learning Anti-Infective Agents Phylogeny Data Collection Microsporum Oils, Volatile Complex Mixtures Structure-Activity Relationship Arthrodermataceae
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Biomolecular simulation based machine learning models accurately predict sites of tolerability to the unnatural amino acid acridonylalanine.

Scientific reports Sep 15, 2021
The incorporation of unnatural amino acids (Uaas) has provided an avenue for novel chemistries to be explored in biological systems. However, the successful application of Uaas is often hampered by site-specific impacts on protein yield and solubilit...
Structure-Activity Relationship Models, Molecular Amino Acids Molecular Conformation Protein Biosynthesis Machine Learning Proteins
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CYPlebrity: Machine learning models for the prediction of inhibitors of cytochrome P450 enzymes.

Bioorganic & medicinal chemistry Aug 28, 2021
The vast majority of approved drugs are metabolized by the five major cytochrome P450 (CYP) isozymes, 1A2, 2C9, 2C19, 2D6 and 3A4. Inhibition of CYP isozymes can cause drug-drug interactions with severe pharmacological and toxicological consequences....
Cytochrome P-450 Enzyme Inhibitors Humans Models, Molecular Machine Learning Molecular Structure Cytochrome P-450 Enzyme System Dose-Response Relationship, Drug Structure-Activity Relationship
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Identification of kinase inhibitors that rule out the CYP27B1-mediated activation of vitamin D: an integrated machine learning and structure-based drug designing approach.

Molecular diversity Jul 16, 2021
CYP27B1, a cytochrome P450-containing hydroxylase enzyme, converts vitamin D precursor calcidiol (25-hydroxycholecalciferol) to its active form calcitriol (1α,25(OH)D). Tyrosine kinase inhibitor such as imatinib is reported to interfere with the acti...
Amino Acid Sequence Enzyme Inhibitors Binding Sites Metabolic Networks and Pathways Molecular Docking Simulation Small Molecule Libraries Models, Molecular Drug Design Databases, Pharmaceutical Molecular Dynamics Simulation Protein Binding Support Vector Machine Phosphotransferases Algorithms 25-Hydroxyvitamin D3 1-alpha-Hydroxylase Humans Vitamin D Structure-Activity Relationship Neural Networks, Computer Reproducibility of Results Machine Learning Animals
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