AIMC Topic: Molecular Structure

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Design of (quinolin-4-ylthio)carboxylic acids as new Escherichia coli DNA gyrase B inhibitors: machine learning studies, molecular docking, synthesis and biological testing.

Computational biology and chemistry Jan 24, 2020
Spread of multidrug-resistant Escherichia coli clinical isolates is a main problem in the treatment of infectious diseases. Therefore, the modern scientific approaches in decision this problem require not only a prevention strategy, but also the deve...
Quantitative Structure-Activity Relationship Quinolines DNA Gyrase Computational Biology Escherichia coli Machine Learning Molecular Structure Anti-Bacterial Agents Molecular Docking Simulation Topoisomerase II Inhibitors Drug Design Microbial Sensitivity Tests
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Deep Learning to Generate Chemical Property Libraries and Candidate Molecules for Small Molecule Identification in Complex Samples.

Analytical chemistry Jan 6, 2020
Comprehensive and unambiguous identification of small molecules in complex samples will revolutionize our understanding of the role of metabolites in biological systems. Existing and emerging technologies have enabled measurement of chemical properti...
Metabolomics Computer Simulation Molecular Structure Deep Learning Small Molecule Libraries
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Synthesis and in vitro activity of asymmetric indole-based bisamidine compounds against Gram-positive and Gram-negative pathogens.

Bioorganic & medicinal chemistry letters Dec 13, 2019
A series of new asymmetric bisamidine was designed, synthesized, and tested for their in-vitro antibacterial activity using a range of Gram-positive and Gram-negative pathogens. Most compounds demonstrated powerful antibacterial activity, and interes...
Molecular Structure Escherichia coli Pseudomonas aeruginosa Citrobacter freundii Anti-Bacterial Agents Microbial Sensitivity Tests Indoles Furans Klebsiella Dose-Response Relationship, Drug Structure-Activity Relationship
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Artificial intelligence and big data facilitated targeted drug discovery.

Stroke and vascular neurology Nov 7, 2019
Different kinds of biological databases publicly available nowadays provide us a goldmine of multidiscipline big data. The Cancer Genome Atlas is a cancer database including detailed information of many patients with cancer. DrugBank is a database in...
Pharmacokinetics Computer-Aided Design Toxicology Drug Design Pharmaceutical Preparations Drug Discovery Humans Big Data Data Mining Artificial Intelligence Structure-Activity Relationship Molecular Targeted Therapy Databases, Factual Molecular Structure
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LightGBM: An Effective and Scalable Algorithm for Prediction of Chemical Toxicity-Application to the Tox21 and Mutagenicity Data Sets.

Journal of chemical information and modeling Oct 9, 2019
Machine learning algorithms have attained widespread use in assessing the potential toxicities of pharmaceuticals and industrial chemicals because of their faster speed and lower cost compared to experimental bioassays. Gradient boosting is an effect...
Machine Learning Software Algorithms Mutagens Molecular Structure Reproducibility of Results Drug-Related Side Effects and Adverse Reactions Drug Development Datasets as Topic
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Graph Classification of Molecules Using Force Field Atom and Bond Types.

Molecular informatics Oct 7, 2019
Classification of the biological activities of chemical substances is important for developing new medicines efficiently. Various machine learning methods are often employed to screen large libraries of compounds and predict the activities of new sub...
Machine Learning Molecular Structure Molecular Dynamics Simulation Quantitative Structure-Activity Relationship Benzenesulfonates Azepines
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Development and Application of a Data-Driven Reaction Classification Model: Comparison of an Electronic Lab Notebook and Medicinal Chemistry Literature.

Journal of chemical information and modeling Sep 26, 2019
Reaction classification has often been considered an important task for many different applications, and has traditionally been accomplished using hand-coded rule-based approaches. However, the availability of large collections of reactions enables d...
Chemistry, Pharmaceutical Machine Learning Molecular Structure Models, Chemical Databases, Chemical
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Toxicity Prediction Method Based on Multi-Channel Convolutional Neural Network.

Molecules (Basel, Switzerland) Sep 17, 2019
Molecular toxicity prediction is one of the key studies in drug design. In this paper, a deep learning network based on a two-dimension grid of molecules is proposed to predict toxicity. At first, the van der Waals force and hydrogen bond were calcul...
Molecular Structure Algorithms Neural Networks, Computer Quantitative Structure-Activity Relationship Deep Learning Data Interpretation, Statistical
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Deep learning enables rapid identification of potent DDR1 kinase inhibitors.

Nature biotechnology Sep 2, 2019
We have developed a deep generative model, generative tensorial reinforcement learning (GENTRL), for de novo small-molecule design. GENTRL optimizes synthetic feasibility, novelty, and biological activity. We used GENTRL to discover potent inhibitors...
Enzyme Inhibitors Protein Conformation Discoidin Domain Receptor 1 Rats Models, Molecular Animals Molecular Structure Deep Learning Dogs Mice Drug Evaluation, Preclinical Humans Microsomes, Liver
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Energy-Geometry Dependency of Molecular Structures: A Multistep Machine Learning Approach.

ACS combinatorial science Aug 21, 2019
There is growing interest in estimating quantum observables while circumventing expensive computational overhead for facile in silico materials screening. Machine learning (ML) methods are implemented to perform such calculations in shorter times. He...
Molecular Structure Models, Chemical Quantum Theory Small Molecule Libraries Ions Machine Learning Inorganic Chemicals Databases, Chemical Computer Simulation Thermodynamics Organic Chemicals
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