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Cheminformatics

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Novel Molecular Representations Using Neumann-Cayley Orthogonal Gated Recurrent Unit.

Journal of chemical information and modeling
Advances in deep neural networks (DNNs) have made a very powerful machine learning method available to researchers across many fields of study, including the biomedical and cheminformatics communities, where DNNs help to improve tasks such as protein...

Exploring proteasome inhibition using atomic weighted vector indices and machine learning approaches.

Molecular diversity
Ubiquitin-proteasome system (UPS) is a highly regulated mechanism of intracellular protein degradation and turnover. The UPS is involved in different biological activities, such as the regulation of gene transcription and cell cycle. Several research...

PREFER: A New Predictive Modeling Framework for Molecular Discovery.

Journal of chemical information and modeling
Machine-learning and deep-learning models have been extensively used in cheminformatics to predict molecular properties, to reduce the need for direct measurements, and to accelerate compound prioritization. However, different setups and frameworks a...

Artificial intelligence and cheminformatics tools: a contribution to the drug development and chemical science.

Journal of biomolecular structure & dynamics
In the ever-evolving field of drug discovery, the integration of Artificial Intelligence (AI) and Machine Learning (ML) with cheminformatics has proven to be a powerful combination. Cheminformatics, which combines the principles of computer science a...

Fragments quantum descriptors in classification of bio-accumulative compounds.

Journal of molecular graphics & modelling
The aim of the following research is to assess the applicability of calculated quantum properties of molecular fragments as molecular descriptors in machine learning classification task. The research is based on bio-concentration and QM9-extended dat...

Cheminformatics and machine learning approaches for repurposing anti-viral compounds against monkeypox virus thymidylate kinase.

Molecular diversity
One of the emerging epidemic concerns is Monkeypox disease which is spreading globally. This disease is caused by the monkeypox virus (MPXV), with an increasing global incidence with an outbreak in 2022. One of the novel targets for monkeypox disease...

Cheminformatics and Machine Learning Approaches to Assess Aquatic Toxicity Profiles of Fullerene Derivatives.

International journal of molecular sciences
Fullerene derivatives (FDs) are widely used in nanomaterials production, the pharmaceutical industry and biomedicine. In the present study, we focused on the potential toxic effects of FDs on the aquatic environment. First, we analyzed the binding af...

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
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...

When Yield Prediction Does Not Yield Prediction: An Overview of the Current Challenges.

Journal of chemical information and modeling
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...