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Molecular Conformation

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Study of Structure-active Relationship for Inhibitors of HIV-1 Integrase LEDGF/p75 Interaction by Machine Learning Methods.

Molecular informatics Feb 28, 2017
HIV-1 integrase (IN) is a promising target for anti-AIDS therapy, and LEDGF/p75 is proved to enhance the HIV-1 integrase strand transfer activity in vitro. Blocking the interaction between IN and LEDGF/p75 is an effective way to inhibit HIV replicati...
Machine Learning Computer Simulation Reproducibility of Results Humans Intercellular Signaling Peptides and Proteins HIV Integrase Inhibitors Molecular Conformation HIV Integrase Structure-Activity Relationship Models, Molecular Molecular Structure ROC Curve Protein Binding
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An ensemble micro neural network approach for elucidating interactions between zinc finger proteins and their target DNA.

BMC genomics Dec 22, 2016
BACKGROUND: The ability to engineer zinc finger proteins binding to a DNA sequence of choice is essential for targeted genome editing to be possible. Experimental techniques and molecular docking have been successful in predicting protein-DNA interac...
DNA-Binding Proteins Protein Binding Binding Sites Molecular Conformation Zinc Fingers DNA Neural Networks, Computer Models, Molecular Algorithms
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Beyond Rotatable Bond Counts: Capturing 3D Conformational Flexibility in a Single Descriptor.

Journal of chemical information and modeling Dec 6, 2016
A new molecular descriptor, nConf, based on chemical connectivity, is presented which captures the accessible conformational space of a molecule. Currently the best available two-dimensional descriptors for quantifying the flexibility of a particular...
Algorithms Drug Design Models, Molecular Machine Learning Crystallization Molecular Conformation
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Synergies Between Quantum Mechanics and Machine Learning in Reaction Prediction.

Journal of chemical information and modeling Oct 25, 2016
Machine learning (ML) and quantum mechanical (QM) methods can be used in two-way synergy to build chemical reaction expert systems. The proposed ML approach identifies electron sources and sinks among reactants and then ranks all source-sink pairs. T...
Thermodynamics Machine Learning Models, Molecular Quantum Theory Molecular Conformation
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In Silico Calculation of Infinite Dilution Activity Coefficients of Molecular Solutes in Ionic Liquids: Critical Review of Current Methods and New Models Based on Three Machine Learning Algorithms.

Journal of chemical information and modeling Jul 20, 2016
The aim of the paper is to address all the disadvantages of currently available models for calculating infinite dilution activity coefficients (γ(∞)) of molecular solutes in ionic liquids (ILs)-a relevant property from the point of view of many appli...
Molecular Conformation Solutions Models, Molecular Ionic Liquids Linear Models Computer Simulation Support Vector Machine Neural Networks, Computer Machine Learning
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Neural-Network Scoring Functions Identify Structurally Novel Estrogen-Receptor Ligands.

Journal of chemical information and modeling Sep 4, 2015
The magnitude of the investment required to bring a drug to the market hinders medical progress, requiring hundreds of millions of dollars and years of research and development. Any innovation that improves the efficiency of the drug-discovery proces...
Humans Neural Networks, Computer Models, Biological Ligands Drug Discovery Receptors, Estrogen Databases, Factual Molecular Conformation Protein Binding Computer Simulation Estradiol
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Development of 3D-QSAR Model for Acetylcholinesterase Inhibitors Using a Combination of Fingerprint, Molecular Docking, and Structure-Based Pharmacophore Approaches.

Toxicological sciences : an official journal of the Society of Toxicology Jul 21, 2015
Acetylcholinesterase (AChE), a serine hydrolase vital for regulating the neurotransmitter acetylcholine in animals, has been used as a target for drugs and pesticides. With the increasing availability of AChE crystal structures, with or without ligan...
Quantitative Structure-Activity Relationship Binding Sites Peptide Mapping Nootropic Agents Expert Systems Catalytic Domain Molecular Conformation Acetylcholinesterase Cholinesterase Inhibitors Molecular Docking Simulation Imaging, Three-Dimensional Computational Biology Humans Artificial Intelligence GPI-Linked Proteins Animals Insecticides Databases, Protein Ligands Nerve Tissue Proteins Models, Molecular
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GTAM: a molecular pretraining model with geometric triangle awareness.

Bioinformatics (Oxford, England) Sep 2, 2024
MOTIVATION: Molecular representation learning is pivotal for advancing deep learning applications in quantum chemistry and drug discovery. Existing methods for molecular representation learning often fall short of fully capturing the intricate intera...
Deep Learning Models, Molecular Molecular Conformation Drug Discovery
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Integrating AlphaFold and deep learning for atomistic interpretation of cryo-EM maps.

Briefings in bioinformatics Sep 22, 2023
Interpretation of cryo-electron microscopy (cryo-EM) maps requires building and fitting 3D atomic models of biological molecules. AlphaFold-predicted models generate initial 3D coordinates; however, model inaccuracy and conformational heterogeneity o...
Deep Learning Models, Molecular Molecular Conformation Protein Conformation Cryoelectron Microscopy
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Modern semiempirical electronic structure methods and machine learning potentials for drug discovery: Conformers, tautomers, and protonation states.

The Journal of chemical physics Mar 28, 2023
Modern semiempirical electronic structure methods have considerable promise in drug discovery as universal "force fields" that can reliably model biological and drug-like molecules, including alternative tautomers and protonation states. Herein, we c...
Isomerism Molecular Conformation Machine Learning Drug Discovery
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