AIMC Topic: Cheminformatics

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Virtual screening of anti-HIV1 compounds against SARS-CoV-2: machine learning modeling, chemoinformatics and molecular dynamics simulation based analysis.

Scientific reports Nov 23, 2020
COVID-19 caused by the SARS-CoV-2 is a current global challenge and urgent discovery of potential drugs to combat this pandemic is a need of the hour. 3-chymotrypsin-like cysteine protease (3CLpro) enzyme is the vital molecular target against the SAR...
SARS-CoV-2 Molecular Docking Simulation Humans COVID-19 Antiviral Agents Drug Repositioning Molecular Dynamics Simulation Deep Learning Anti-HIV Agents Cheminformatics Coronavirus 3C Proteases Infectious bronchitis virus COVID-19 Drug Treatment Protease Inhibitors Drug Evaluation, Preclinical HIV-1
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Machine-Learning and Chemicogenomics Approach Defines and Predicts Cross-Talk of Hippo and MAPK Pathways.

Cancer discovery Nov 18, 2020
Hippo pathway dysregulation occurs in multiple cancers through genetic and nongenetic alterations, resulting in translocation of YAP to the nucleus and activation of the TEAD family of transcription factors. Unlike other oncogenic pathways such as RA...
Signal Transduction MAP Kinase Signaling System Humans Genomics Machine Learning Computational Biology Cheminformatics Hippo Signaling Pathway
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Self-Optimizing Support Vector Elastic Net.

Analytical chemistry Nov 9, 2020
Chemometrics is widely used to solve various quantitative and qualitative problems in analytical chemistry. A self-optimizing chemometrics method facilitates scientists to exploit the advantages of chemometrics. In this report, a parameter-free suppo...
Support Vector Machine Linear Models Cheminformatics
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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...
Deep Learning Quantitative Structure-Activity Relationship Pharmaceutical Preparations Cheminformatics Algorithms Models, Biological Permeability Blood-Brain Barrier Databases, Chemical
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Hybrid Harris hawks optimization with cuckoo search for drug design and discovery in chemoinformatics.

Scientific reports Sep 2, 2020
One of the major drawbacks of cheminformatics is a large amount of information present in the datasets. In the majority of cases, this information contains redundant instances that affect the analysis of similarity measurements with respect to drug d...
Algorithms Drug Design Heuristics Cheminformatics Support Vector Machine Humans Machine Learning
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Impact of Chemist-In-The-Loop Molecular Representations on Machine Learning Outcomes.

Journal of chemical information and modeling Aug 18, 2020
The development of molecular descriptors is a central challenge in cheminformatics. Most approaches use algorithms that extract atomic environments or end-to-end machine learning. However, a looming question is that how do these approaches compare wi...
Machine Learning Algorithms Cheminformatics
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A Deep-Learning Approach toward Rational Molecular Docking Protocol Selection.

Molecules (Basel, Switzerland) May 27, 2020
While a plethora of different protein-ligand docking protocols have been developed over the past twenty years, their performances greatly depend on the provided input protein-ligand pair. In this study, we developed a machine-learning model that uses...
Molecular Docking Simulation Deep Learning Cheminformatics Databases, Protein Machine Learning
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TOP: A deep mixture representation learning method for boosting molecular toxicity prediction.

Methods (San Diego, Calif.) May 21, 2020
At the early stages of the drug discovery, molecule toxicity prediction is crucial to excluding drug candidates that are likely to fail in clinical trials. In this paper, we presented a novel molecular representation method and developed a correspond...
Datasets as Topic Toxicity Tests Drug Discovery Pharmacology, Clinical Humans Cheminformatics Deep Learning Forecasting
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The message passing neural networks for chemical property prediction on SMILES.

Methods (San Diego, Calif.) May 21, 2020
Drug metabolism is determined by the biochemical and physiological properties of the drug molecule. To improve the performance of a drug property prediction model, it is important to extract complex molecular dynamics from limited data. Recent machin...
Chemistry, Pharmaceutical Cheminformatics Forecasting Deep Learning Humans Pharmacology, Clinical
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Learning Molecular Representations for Medicinal Chemistry.

Journal of medicinal chemistry May 15, 2020
The accurate modeling and prediction of small molecule properties and bioactivities depend on the critical choice of molecular representation. Decades of informatics-driven research have relied on expert-designed molecular descriptors to establish qu...
Cheminformatics Quantitative Structure-Activity Relationship Chemistry, Pharmaceutical Organic Chemicals Deep Learning Models, Molecular Molecular Structure
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