AIMC Topic: Cheminformatics

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Cheminformatics analysis of indoleamine and tryptophan 2,3-dioxygenase inhibitors: A descriptor and fingerprint based machine learning approach to disclose selectivity measures.

Computers in biology and medicine Aug 1, 2024
Indoleamine 2,3-dioxygenase (IDO) and tryptophan 2,3-dioxygenase (TDO) are attractive drug targets for cancer immunotherapy. After disappointing results of the epacadostat as a selective IDO inhibitor in phase III clinical trials, there is much inter...
Indoleamine-Pyrrole 2,3,-Dioxygenase Cheminformatics Molecular Docking Simulation Enzyme Inhibitors Tryptophan Oxygenase Humans Machine Learning
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Versatile Deep Learning Pipeline for Transferable Chemical Data Extraction.

Journal of chemical information and modeling Jul 15, 2024
Chemical information disseminated in scientific documents offers an untapped potential for deep learning-assisted insights and breakthroughs. Automated extraction efforts have shifted from resource-intensive manual extraction toward applying machine ...
Cheminformatics Data Mining Deep Learning
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OpenChemIE: An Information Extraction Toolkit for Chemistry Literature.

Journal of chemical information and modeling Jul 1, 2024
Information extraction from chemistry literature is vital for constructing up-to-date reaction databases for data-driven chemistry. Complete extraction requires combining information across text, tables, and figures, whereas prior work has mainly inv...
Machine Learning Databases, Chemical Cheminformatics Algorithms Data Mining
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Stereoisomers Are Not Machine Learning's Best Friends.

Journal of chemical information and modeling Jul 1, 2024
This study addresses the challenge of accurately identifying stereoisomers in cheminformatics, which originates from our objective to apply machine learning to predict the association constant between cyclodextrin and a guest. Identifying stereoisome...
Stereoisomerism Cheminformatics Machine Learning Natural Language Processing Cyclodextrins
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Application of Transformers in Cheminformatics.

Journal of chemical information and modeling May 30, 2024
By accelerating time-consuming processes with high efficiency, computing has become an essential part of many modern chemical pipelines. Machine learning is a class of computing methods that can discover patterns within chemical data and utilize this...
Machine Learning Cheminformatics
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Python tools for structural tasks in chemistry.

Molecular diversity May 14, 2024
In recent decades, the use of computational approaches and artificial intelligence in the scientific environment has become more widespread. In this regard, the popular and versatile programming language Python has attracted considerable attention fr...
Programming Languages Cheminformatics Software
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Outline and background for the EU-OS solubility prediction challenge.

SLAS discovery : advancing life sciences R & D Mar 20, 2024
In June 2022, EU-OS came to the decision to make public a solubility data set of 100+K compounds obtained from several of the EU-OS proprietary screening compound collections. Leveraging on the interest of SLAS for screening scientific development it...
Cheminformatics Drug Discovery Solubility Machine Learning Humans
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Computational discovery of novel FYN kinase inhibitors: a cheminformatics and machine learning-driven approach to targeted cancer and neurodegenerative therapy.

Molecular diversity Feb 28, 2024
In this study, we explored the potential of novel inhibitors for FYN kinase, a critical target in cancer and neurodegenerative disorders, by integrating advanced cheminformatics, machine learning, and molecular simulation techniques. Our approach inv...
Neoplasms Molecular Docking Simulation Drug Discovery Antineoplastic Agents Humans Machine Learning Protein Kinase Inhibitors Cheminformatics Molecular Dynamics Simulation Proto-Oncogene Proteins c-fyn Neurodegenerative Diseases Piperidines
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When Yield Prediction Does Not Yield Prediction: An Overview of the Current Challenges.

Journal of chemical information and modeling Dec 20, 2023
Machine Learning (ML) techniques face significant challenges when predicting advanced chemical properties, such as yield, feasibility of chemical synthesis, and optimal reaction conditions. These challenges stem from the high-dimensional nature of th...
Cheminformatics Machine Learning
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Potent multi-target natural inhibitors against SARS-CoV-2 from medicinal plants of the Himalaya: a discovery from hybrid machine learning, chemoinformatics, and simulation assisted screening.

Journal of biomolecular structure & dynamics Sep 21, 2023
The emergence and immune evasion ability of SARS-CoV-2 Omicron strains, mainly BA.5.2 and BF.7 and other variants of concern have raised global apprehensions. With this context, the discovery of multitarget inhibitors may be proven more comprehensive...
Molecular Docking Simulation Molecular Dynamics Simulation Machine Learning Drug Discovery Plants, Medicinal Cheminformatics SARS-CoV-2 Phytochemicals Antiviral Agents COVID-19 Drug Treatment Humans India Virus Replication
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