AIMC Topic: Databases, Chemical

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Algebraic graph-assisted bidirectional transformers for molecular property prediction.

Nature communications Jun 10, 2021
The ability of molecular property prediction is of great significance to drug discovery, human health, and environmental protection. Despite considerable efforts, quantitative prediction of various molecular properties remains a challenge. Although s...
Databases, Chemical Molecular Conformation Blood-Brain Barrier Drug Discovery Drug-Related Side Effects and Adverse Reactions Hydrophobic and Hydrophilic Interactions Pharmaceutical Preparations Machine Learning Algorithms Computer Simulation Neural Networks, Computer
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In silico prediction of drug-induced ototoxicity using machine learning and deep learning methods.

Chemical biology & drug design Jun 7, 2021
Drug-induced ototoxicity has become a serious global problem, because of leading to deafness in hundreds of thousands of people every year. It always results from exposure to drugs or environmental chemicals that cause the impairment and degeneration...
Humans Machine Learning Drug Discovery Glucosides User-Computer Interface Databases, Chemical Models, Theoretical Ototoxicity Deep Learning
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Cluster Analysis of Medicinal Plants and Targets Based on Multipartite Network.

Biomolecules Apr 8, 2021
Network-based methods for the analysis of drug-target interactions have gained attention and rely on the paradigm that a single drug can act on multiple targets rather than a single target. In this study, we have presented a novel approach to analyze...
Neural Networks, Computer Algorithms Plants, Medicinal Databases, Chemical Receptors, Androgen Cluster Analysis Pharmaceutical Preparations 3-Oxo-5-alpha-Steroid 4-Dehydrogenase
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ClassicalGSG: Prediction of log P using classical molecular force fields and geometric scattering for graphs.

Journal of computational chemistry Mar 30, 2021
This work examines methods for predicting the partition coefficient (log P) for a dataset of small molecules. Here, we use atomic attributes such as radius and partial charge, which are typically used as force field parameters in classical molecular ...
Molecular Dynamics Simulation Databases, Chemical Neural Networks, Computer
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Epigenetic Target Fishing with Accurate Machine Learning Models.

Journal of medicinal chemistry Mar 26, 2021
Epigenetic targets are of significant importance in drug discovery research, as demonstrated by the eight approved epigenetic drugs for treatment of cancer and the increasing availability of chemogenomic data related to epigenetics. This data represe...
Proof of Concept Study Histone Deacetylases Structure-Activity Relationship Molecular Structure Databases, Chemical Epigenomics Transcription Factors Drug Discovery Organic Chemicals Machine Learning
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Identification of SARS-CoV-2 viral entry inhibitors using machine learning and cell-based pseudotyped particle assay.

Bioorganic & medicinal chemistry Mar 26, 2021
In response to the pandemic caused by SARS-CoV-2, we constructed a hybrid support vector machine (SVM) classification model using a set of publicly posted SARS-CoV-2 pseudotyped particle (PP) entry assay repurposing screen data to identify novel pote...
ROC Curve Antiviral Agents Drug Repositioning Area Under Curve Support Vector Machine Humans SARS-CoV-2 Microbial Sensitivity Tests Small Molecule Libraries HEK293 Cells Virus Internalization Databases, Chemical
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EDock-ML: A web server for using ensemble docking with machine learning to aid drug discovery.

Protein science : a publication of the Protein Society Mar 25, 2021
EDock-ML is a web server that facilitates the use of ensemble docking with machine learning to help decide whether a compound is worthwhile to be considered further in a drug discovery process. Ensemble docking provides an economical way to account f...
Databases, Chemical Drug Discovery Internet Software Molecular Docking Simulation Machine Learning
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Accurate predictions of aqueous solubility of drug molecules via the multilevel graph convolutional network (MGCN) and SchNet architectures.

Physical chemistry chemical physics : PCCP Oct 16, 2020
Deep learning based methods have been widely applied to predict various kinds of molecular properties in the pharmaceutical industry with increasingly more success. In this study, we propose two novel models for aqueous solubility predictions, based ...
Datasets as Topic Databases, Chemical Water Deep Learning Pharmaceutical Preparations Solubility
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Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning.

Biomolecules Sep 28, 2020
Microbial natural products (NPs) are an important source of drugs, however, their structural diversity remains poorly understood. Here we used our recently reported MinHashed Atom Pair fingerprint with diameter of four bonds (MAP4), a fingerprint sui...
Biological Products Databases, Chemical Machine Learning ROC Curve Area Under Curve Bacteria Fungi
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A Recurrent Neural Network model to predict blood-brain barrier permeability.

Computational biology and chemistry Sep 24, 2020
The rapid development of computational methods and the increasing volume of chemical and biological data have contributed to an immense growth in chemical research. This field of study is known as "chemoinformatics," which is a discipline that uses m...
Permeability Databases, Chemical Cheminformatics Algorithms Deep Learning Quantitative Structure-Activity Relationship Pharmaceutical Preparations Blood-Brain Barrier Models, Biological
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