AIMC Topic: Models, Molecular

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Nuclear Quantum Effect and Its Temperature Dependence in Liquid Water from Random Phase Approximation via Artificial Neural Network.

The journal of physical chemistry letters Jul 7, 2021
We report structural and dynamical properties of liquid water described by the random phase approximation (RPA) correlation together with the exact exchange energy (EXX) within density functional theory. By utilizing thermostated ring polymer molecul...
Quantum Theory Molecular Conformation Neural Networks, Computer Temperature Water Models, Molecular
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In silico prediction of chemical-induced hematotoxicity with machine learning and deep learning methods.

Molecular diversity Jul 1, 2021
Chemical-induced hematotoxicity is an important concern in the drug discovery, since it can often be fatal when it happens. It is quite useful for us to give special attention to chemicals which can cause hematotoxicity. In the present study, we focu...
Machine Learning Databases, Chemical Deep Learning Humans Algorithms Blood Cells Reproducibility of Results Quantitative Structure-Activity Relationship Drug Discovery Cheminformatics ROC Curve Models, Molecular Drug-Related Side Effects and Adverse Reactions
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A multi-conformational virtual screening approach based on machine learning targeting PI3Kγ.

Molecular diversity Jun 23, 2021
Nowadays, more and more attention has been attracted to develop selective PI3Kγ inhibitors, but the unique structural features of PI3Kγ protein make it a very big challenge. In the present study, a virtual screening strategy based on machine learning...
Molecular Docking Simulation Drug Discovery ROC Curve Phosphoinositide-3 Kinase Inhibitors Protein Binding Databases, Pharmaceutical Class Ib Phosphatidylinositol 3-Kinase Machine Learning Molecular Dynamics Simulation Ligands Molecular Conformation Structure-Activity Relationship Binding Sites Models, Molecular Molecular Structure
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Discovery of novel DGAT1 inhibitors by combination of machine learning methods, pharmacophore model and 3D-QSAR model.

Molecular diversity Jun 23, 2021
DGAT1 plays a crucial controlling role in triglyceride biosynthetic pathways, which makes it an attractive therapeutic target for obesity. Thus, development of DGAT1 inhibitors with novel chemical scaffolds is desired and important in the drug discov...
Molecular Docking Simulation Drug Discovery ROC Curve Models, Molecular Molecular Structure Molecular Dynamics Simulation Enzyme Inhibitors Cheminformatics Humans Machine Learning Algorithms Databases, Chemical Reproducibility of Results Quantitative Structure-Activity Relationship Diacylglycerol O-Acyltransferase
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MULTICOM2 open-source protein structure prediction system powered by deep learning and distance prediction.

Scientific reports Jun 23, 2021
Protein structure prediction is an important problem in bioinformatics and has been studied for decades. However, there are still few open-source comprehensive protein structure prediction packages publicly available in the field. In this paper, we p...
Software Sequence Alignment Deep Learning Protein Structure, Tertiary Structure-Activity Relationship Models, Molecular Amino Acid Sequence
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Learning the Exciton Properties of Azo-dyes.

The journal of physical chemistry letters Jun 22, 2021
The determination of electronic excited state (ES) properties is the cornerstone of theoretical photochemistry. Yet, traditional ES methods become impractical when applied to fairly large molecules, or when used on thousands of systems. Machine lear...
Coloring Agents Machine Learning Azo Compounds Models, Molecular Molecular Conformation Quantum Theory
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Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations.

Cell reports methods Jun 21, 2021
Structure prediction for proteins lacking homologous templates in the Protein Data Bank (PDB) remains a significant unsolved problem. We developed a protocol, C-I-TASSER, to integrate interresidue contact maps from deep neural-network learning with t...
Models, Molecular Protein Conformation SARS-CoV-2 Humans Deep Learning COVID-19 Computational Biology Algorithms Proteins
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Machine learning differentiates enzymatic and non-enzymatic metals in proteins.

Nature communications Jun 17, 2021
Metalloenzymes are 40% of all enzymes and can perform all seven classes of enzyme reactions. Because of the physicochemical similarities between the active sites of metalloenzymes and inactive metal binding sites, it is challenging to differentiate b...
Binding Sites Enzymes Metalloproteins Catalysis Machine Learning Catalytic Domain Algorithms Static Electricity Metals Databases, Protein Models, Molecular
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Machine learning models to select potential inhibitors of acetylcholinesterase activity from SistematX: a natural products database.

Molecular diversity Jun 16, 2021
Alzheimer's disease is the most common form of dementia, representing 60-70% of dementia cases. The enzyme acetylcholinesterase (AChE) cleaves the ester bonds in acetylcholine and plays an important role in the termination of acetylcholine activity a...
Molecular Dynamics Simulation Acetylcholinesterase Cholinesterase Inhibitors Cheminformatics Area Under Curve Models, Molecular Workflow Databases, Pharmaceutical Machine Learning Algorithms Molecular Docking Simulation Drug Discovery ROC Curve Biological Products Structure-Activity Relationship Humans
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Applications of artificial intelligence to drug design and discovery in the big data era: a comprehensive review.

Molecular diversity Jun 10, 2021
Artificial intelligence (AI) renders cutting-edge applications in diverse sectors of society. Due to substantial progress in high-performance computing, the development of superior algorithms, and the accumulation of huge biological and chemical data...
Algorithms Drug Design Drug Discovery Big Data Humans Artificial Intelligence Protein Interaction Mapping Protein Folding Databases, Pharmaceutical Structure-Activity Relationship Models, Molecular Workflow Data Mining Protein Binding Models, Theoretical Proteins
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