AIMC Topic: Models, Molecular

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Harnessing protein folding neural networks for peptide-protein docking.

Nature communications Jan 10, 2022
Highly accurate protein structure predictions by deep neural networks such as AlphaFold2 and RoseTTAFold have tremendous impact on structural biology and beyond. Here, we show that, although these deep learning approaches have originally been develop...
Neural Networks, Computer Software Protein Conformation, beta-Strand Amino Acid Sequence Binding Sites Protein Interaction Mapping Protein Folding Protein Interaction Domains and Motifs Protein Conformation, alpha-Helical Peptides Molecular Docking Simulation Protein Binding Proteins Models, Molecular
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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...
Deep Learning Computational Biology Protein Processing, Post-Translational Reproducibility of Results Amino Acid Sequence Protein Conformation Glutamic Acid Proteins Structure-Activity Relationship Models, Molecular
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Protein structures for all.

Science (New York, N.Y.) Dec 16, 2021
AI-powered predictions reveal the shapes of proteins by the thousands.
Artificial Intelligence Software Proteins Databases, Protein Models, Molecular Protein Conformation Protein Folding
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Computed structures of core eukaryotic protein complexes.

Science (New York, N.Y.) Dec 10, 2021
Protein-protein interactions play critical roles in biology, but the structures of many eukaryotic protein complexes are unknown, and there are likely many interactions not yet identified. We take advantage of advances in proteome-wide amino acid coe...
Protein Biosynthesis Ribosomes Multiprotein Complexes Saccharomyces cerevisiae Proteins DNA Repair Ligases Acyltransferases Homologous Recombination Chromosome Segregation Models, Molecular Protein Conformation Saccharomyces cerevisiae Ubiquitin Protein Interaction Mapping Proteome Computer Simulation Membrane Proteins Deep Learning Evolution, Molecular Protein Interaction Maps Computational Biology
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Block-wise Exploration of Molecular Descriptors with Multi-block Orthogonal Component Analysis (MOCA).

Molecular informatics Dec 8, 2021
Data tables for machine learning and structure-activity relationship modelling (QSAR) are often naturally organized in blocks of data, where multiple molecular representations or sets of descriptors form the blocks. Multi-block Orthogonal Component A...
Machine Learning Models, Molecular Quantitative Structure-Activity Relationship
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Molecular modeling in cardiovascular pharmacology: Current state of the art and perspectives.

Drug discovery today Dec 1, 2021
Molecular modeling in pharmacology is a promising emerging tool for exploring drug interactions with cellular components. Recent advances in molecular simulations, big data analysis, and artificial intelligence (AI) have opened new opportunities for ...
Artificial Intelligence Models, Molecular Drug Discovery Big Data
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Structure-Based Drug Design Using Deep Learning.

Journal of chemical information and modeling Nov 18, 2021
In recent years, deep learning-based methods have emerged as promising tools for drug design. Most of these methods are ligand-based, where an initial target-specific ligand data set is necessary to design potent molecules with optimized properties....
Deep Learning Proteins Models, Molecular Ligands Drug Design
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MemDis: Predicting Disordered Regions in Transmembrane Proteins.

International journal of molecular sciences Nov 12, 2021
Transmembrane proteins (TMPs) play important roles in cells, ranging from transport processes and cell adhesion to communication. Many of these functions are mediated by intrinsically disordered regions (IDRs), flexible protein segments without a wel...
Models, Molecular Internet Amino Acid Sequence Protein Conformation Data Mining Intrinsically Disordered Proteins Computational Biology Membrane Proteins Databases, Protein Neural Networks, Computer Reproducibility of Results
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Proteome-Informed Machine Learning Studies of Cocaine Addiction.

The journal of physical chemistry letters Nov 9, 2021
No anti-cocaine addiction drugs have been approved by the Food and Drug Administration despite decades of effort. The main challenge is the intricate molecular mechanisms of cocaine addiction, involving synergistic interactions among proteins upstrea...
Protein Binding Proteome Models, Molecular Humans Machine Learning Antipsychotic Agents Cocaine-Related Disorders
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First molecular modelling report on tri-substituted pyrazolines as phosphodiesterase 5 (PDE5) inhibitors through classical and machine learning based multi-QSAR analysis.

SAR and QSAR in environmental research Nov 3, 2021
Phosphodiesterase 5 (PDE5) falls under a broad category of metallohydrolase enzymes responsible for the catalysis of the phosphodiesterase bond, and thus it can terminate the action of cyclic guanosine monophosphate (cGMP). Overexpression of this enz...
Phosphodiesterase 5 Inhibitors Machine Learning Models, Molecular Quantitative Structure-Activity Relationship
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