AIMC Topic: Computational Chemistry

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Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives.

Journal of chemical information and modeling Jan 31, 2024
Solute carrier transporters (SLCs) are a class of important transmembrane proteins that are involved in the transportation of diverse solute ions and small molecules into cells. There are approximately 450 SLCs within the human body, and more than a ...
Humans Artificial Intelligence Membrane Transport Proteins Computational Chemistry Drug Design Drug Discovery
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Deep learning algorithms applied to computational chemistry.

Molecular diversity Dec 27, 2023
Recently, there has been a significant increase in the use of deep learning techniques in the molecular sciences, which have shown high performance on datasets and the ability to generalize across data. However, no model has achieved perfect performa...
Deep Learning Computational Chemistry Algorithms Drug Discovery
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Hit Identification Driven by Combining Artificial Intelligence and Computational Chemistry Methods: A PI5P4K-β Case Study.

Journal of chemical information and modeling Aug 7, 2023
Computer-aided drug design (CADD), especially artificial intelligence-driven drug design (AIDD), is increasingly used in drug discovery. In this paper, a novel and efficient workflow for hit identification was developed within the drug discovery pla...
Drug Discovery Computational Chemistry Artificial Intelligence Drug Design
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Feedback-AVPGAN: Feedback-guided generative adversarial network for generating antiviral peptides.

Journal of bioinformatics and computational biology Dec 14, 2022
In this study, we propose , a system that aims to computationally generate novel antiviral peptides (AVPs). This system relies on the key premise of the Generative Adversarial Network (GAN) model and the Feedback method. GAN, a generative modeling ap...
Feedback Deep Learning Algorithms Antimicrobial Peptides Computational Chemistry Antiviral Agents Amino Acid Sequence Network Pharmacology
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Improving Molecular Contrastive Learning via Faulty Negative Mitigation and Decomposed Fragment Contrast.

Journal of chemical information and modeling May 31, 2022
Deep learning has been a prevalence in computational chemistry and widely implemented in molecular property predictions. Recently, self-supervised learning (SSL), especially contrastive learning (CL), has gathered growing attention for the potential ...
Neural Networks, Computer Machine Learning Cheminformatics Computational Chemistry
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Introducing a Chemically Intuitive Core-Substituent Fingerprint Designed to Explore Structural Requirements for Effective Similarity Searching and Machine Learning.

Molecules (Basel, Switzerland) Apr 4, 2022
Fingerprint (FP) representations of chemical structure continue to be one of the most widely used types of molecular descriptors in chemoinformatics and computational medicinal chemistry. One often distinguishes between two- and three-dimensional (2D...
Chemistry, Pharmaceutical Computational Chemistry Molecular Conformation Machine Learning
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Differentiable biology: using deep learning for biophysics-based and data-driven modeling of molecular mechanisms.

Nature methods Oct 4, 2021
Deep learning using neural networks relies on a class of machine-learnable models constructed using 'differentiable programs'. These programs can combine mathematical equations specific to a particular domain of natural science with general-purpose, ...
Neural Networks, Computer Deep Learning Protein Conformation Models, Chemical Computational Biology Computational Chemistry Biophysics Pattern Recognition, Automated Proteins
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Beyond Tripeptides Two-Step Active Machine Learning for Very Large Data sets.

Journal of chemical theory and computation Apr 27, 2021
Self-assembling peptide nanostructures have been shown to be of great importance in nature and have presented many promising applications, for example, in medicine as drug-delivery vehicles, biosensors, and antivirals. Being very promising candidates...
Protein Conformation Computational Chemistry Supervised Machine Learning Datasets as Topic Nanostructures Algorithms Oligopeptides Programming Languages
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OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug Design.

Journal of chemical information and modeling Jan 4, 2021
Deep learning models have demonstrated outstanding results in many data-rich areas of research, such as computer vision and natural language processing. Currently, there is a rise of deep learning in computational chemistry and materials informatics,...
Deep Learning Support Vector Machine Drug Design Computational Chemistry Machine Learning
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ChemBoost: A Chemical Language Based Approach for Protein - Ligand Binding Affinity Prediction.

Molecular informatics Dec 14, 2020
Identification of high affinity drug-target interactions is a major research question in drug discovery. Proteins are generally represented by their structures or sequences. However, structures are available only for a small subset of biomolecules an...
Computational Biology Drug Discovery Computational Chemistry Machine Learning Ligands Protein Binding
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