AIMC Topic: Models, Molecular

Clear Filters Showing 501 to 510 of 759 articles

Recent applications of machine learning in medicinal chemistry.

Bioorganic & medicinal chemistry letters Jun 28, 2018
In recent decades, artificial intelligence and machine learning have played a significant role in increasing the efficiency of processes across a wide spectrum of industries. When it comes to the pharmaceutical and biotechnology sectors, numerous too...
Models, Molecular Quantitative Structure-Activity Relationship Chemistry, Pharmaceutical Humans Machine Learning Animals
View on PubMed DOI

Perturbation Theory/Machine Learning Model of ChEMBL Data for Dopamine Targets: Docking, Synthesis, and Assay of New l-Prolyl-l-leucyl-glycinamide Peptidomimetics.

ACS chemical neuroscience Jun 25, 2018
Predicting drug-protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning (ML) models for one specific protein...
Software Molecular Docking Simulation Deep Learning Models, Molecular Humans Neural Networks, Computer Peptidomimetics Nonlinear Dynamics Machine Learning Receptors, Dopamine D2 Databases, Chemical Dopamine Allosteric Regulation MSH Release-Inhibiting Hormone
View on PubMed DOI

Computational design of thermostabilizing point mutations for G protein-coupled receptors.

eLife Jun 21, 2018
Engineering of GPCR constructs with improved thermostability is a key for successful structural and biochemical studies of this transmembrane protein family, targeted by 40% of all therapeutic drugs. Here we introduce a comprehensive computational ap...
Humans Machine Learning Gene Expression Kinetics Amino Acid Sequence Protein Stability Animals Protein Binding Models, Molecular Sequence Homology, Amino Acid Protein Interaction Domains and Motifs Protein Conformation, alpha-Helical Serotonin 5-HT2 Receptor Agonists Serotonin 5-HT2 Receptor Antagonists Protein Conformation, beta-Strand Point Mutation Receptor, Serotonin, 5-HT2C Protein Engineering Crystallography, X-Ray Thermodynamics Binding Sites Sequence Alignment
View on PubMed DOI

Visualizing convolutional neural network protein-ligand scoring.

Journal of molecular graphics & modelling Jun 18, 2018
Protein-ligand scoring is an important step in a structure-based drug design pipeline. Selecting a correct binding pose and predicting the binding affinity of a protein-ligand complex enables effective virtual screening. Machine learning techniques c...
Ligands Molecular Conformation Protein Binding Proteins Models, Molecular Deep Learning ROC Curve Neural Networks, Computer Algorithms
View on PubMed DOI

Redefining the Protein Kinase Conformational Space with Machine Learning.

Cell chemical biology May 31, 2018
Protein kinases are dynamic, adopting different conformational states that are critical for their catalytic activity. We assess a range of structural features derived from the conserved αC helix and DFG motif to define the conformational space of the...
Ligands Humans Protein Conformation Machine Learning Protein Kinase Inhibitors Models, Molecular Small Molecule Libraries Protein Kinases
View on PubMed DOI

DPP-PseAAC: A DNA-binding protein prediction model using Chou's general PseAAC.

Journal of theoretical biology May 16, 2018
A DNA-binding protein (DNA-BP) is a protein that can bind and interact with a DNA. Identification of DNA-BPs using experimental methods is expensive as well as time consuming. As such, fast and accurate computational methods are sought for predicting...
Protein Domains Amino Acids DNA-Binding Proteins Amino Acid Sequence Nucleic Acid Conformation Databases, Protein DNA Models, Molecular Reproducibility of Results Computational Biology Support Vector Machine Algorithms
View on PubMed DOI

Sequentially distant but structurally similar proteins exhibit fold specific patterns based on their biophysical properties.

Computational biology and chemistry May 16, 2018
The Three-dimensional structure of a protein depends on the interaction between their amino acid residues. These interactions are in turn influenced by various biophysical properties of the amino acids. There are several examples of proteins that sha...
Bayes Theorem Support Vector Machine Protein Conformation Protein Folding Proteins Models, Molecular
View on PubMed DOI

Reliable and Performant Identification of Low-Energy Conformers in the Gas Phase and Water.

Journal of chemical information and modeling May 16, 2018
Prediction of compound properties from structure via quantitative structure-activity relationship and machine-learning approaches is an important computational chemistry task in small-molecule drug research. Though many such properties are dependent ...
Gases Informatics Thermodynamics Drug Discovery Water Models, Molecular Molecular Conformation Pharmaceutical Preparations Machine Learning Quantitative Structure-Activity Relationship Solvents
View on PubMed DOI

Fingerprint-Based Machine Learning Approach to Identify Potent and Selective 5-HTR Ligands.

Molecules (Basel, Switzerland) May 10, 2018
The identification of subtype-selective GPCR (G-protein coupled receptor) ligands is a challenging task. In this study, we developed a computational protocol to find compounds with 5-HTR versus 5-HTR selectivity. Our approach employs the hierarchical...
Humans Machine Learning Models, Molecular Binding Sites Drug Evaluation, Preclinical Receptor, Serotonin, 5-HT2B Serotonin Ligands
View on PubMed DOI

Agonists of G-Protein-Coupled Odorant Receptors Are Predicted from Chemical Features.

The journal of physical chemistry letters Apr 17, 2018
Predicting the activity of chemicals for a given odorant receptor is a longstanding challenge. Here the activity of 258 chemicals on the human G-protein-coupled odorant receptor (OR)51E1, also known as prostate-specific G-protein-coupled receptor 2 (...
Neoplasm Proteins Receptors, Odorant Humans Protein Binding Models, Molecular Fatty Acids Machine Learning Mice Drug Evaluation, Preclinical Ligands Animals Receptors, G-Protein-Coupled
View on PubMed DOI
Popular Topics
Recent Journals