AIMC Topic: Models, Molecular

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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...
Protein Conformation Databases, Protein Models, Molecular Internet Amino Acid Sequence Data Mining Intrinsically Disordered Proteins Reproducibility of Results Computational Biology Membrane Proteins Neural Networks, Computer
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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...
Models, Molecular Quantitative Structure-Activity Relationship Phosphodiesterase 5 Inhibitors Machine Learning
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Improved Protein Structure Prediction Using a New Multi-Scale Network and Homologous Templates.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Oct 31, 2021
The accuracy of de novo protein structure prediction has been improved considerably in recent years, mostly due to the introduction of deep learning techniques. In this work, trRosettaX, an improved version of trRosetta for protein structure predicti...
Neural Networks, Computer Deep Learning Computational Biology Models, Molecular Datasets as Topic Protein Conformation Sequence Analysis, Protein
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The AlphaFold Database of Protein Structures: A Biologist's Guide.

Journal of molecular biology Oct 29, 2021
AlphaFold, the deep learning algorithm developed by DeepMind, recently released the three-dimensional models of the whole human proteome to the scientific community. Here we discuss the advantages, limitations and the still unsolved challenges of the...
Databases, Factual Deep Learning Computational Biology Protein Conformation Humans Protein Folding Algorithms Proteome Molecular Biology Models, Molecular
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Disease variant prediction with deep generative models of evolutionary data.

Nature Oct 27, 2021
Quantifying the pathogenicity of protein variants in human disease-related genes would have a marked effect on clinical decisions, yet the overwhelming majority (over 98%) of these variants still have unknown consequences. In principle, computational...
Selection, Genetic Genetic Fitness Unsupervised Machine Learning Models, Molecular Bayes Theorem Biological Assay Genetic Variation Disease Humans Genetic Predisposition to Disease Phenotype Evolution, Molecular Proteins
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Quantum Artificial Neural Network Approach to Derive a Highly Predictive 3D-QSAR Model for Blood-Brain Barrier Passage.

International journal of molecular sciences Oct 12, 2021
A successful passage of the blood-brain barrier (BBB) is an essential prerequisite for the drug molecules designed to act on the central nervous system. The logarithm of blood-brain partitioning (LogBB) has served as an effective index of molecular B...
Pharmaceutical Preparations Neural Networks, Computer Quantitative Structure-Activity Relationship Biological Transport Blood-Brain Barrier Models, Molecular Quantum Theory
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MANORAA: A machine learning platform to guide protein-ligand design by anchors and influential distances.

Structure (London, England : 1993) Oct 5, 2021
The MANORAA platform uses structure-based approaches to provide information on drug design originally derived from mapping tens of thousands of amino acids on a grid. In-depth analyses of the pockets, frequently occurring atoms, influential distances...
Drug Design Protein Binding Computational Biology Pandemics COVID-19 SARS-CoV-2 Protein Domains Ligands Crystallography, X-Ray Proteins Databases, Protein Models, Molecular Humans Machine Learning Trimethoprim Tetrahydrofolate Dehydrogenase
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In silico formulation prediction of drug/cyclodextrin/polymer ternary complexes by machine learning and molecular modeling techniques.

Carbohydrate polymers Sep 29, 2021
Ternary cyclodextrin (CD) complexes (drug/CD/polymer) can effectively improve the solubility of water-insoluble drugs with large size than binary CD formulations. However, ternary formulations are screened by a trial-and-error approach, which is labo...
Cyclodextrins Drug Compounding Benzimidazoles Polymers Hydrocortisone Quinolones Machine Learning Models, Molecular
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XENet: Using a new graph convolution to accelerate the timeline for protein design on quantum computers.

PLoS computational biology Sep 27, 2021
Graph representations are traditionally used to represent protein structures in sequence design protocols in which the protein backbone conformation is known. This infrequently extends to machine learning projects: existing graph convolution algorith...
Neural Networks, Computer Proteins Machine Learning Algorithms Models, Molecular Protein Conformation Computers Computer-Aided Design Computational Biology Computer Graphics
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