AIMC Journal:
Journal of chemical information and modeling

Showing 431 to 440 of 934 articles

Molecular Generation with Reduced Labeling through Constraint Architecture.

Journal of chemical information and modeling May 15, 2023
In the past few years, a number of machine learning (ML)-based molecular generative models have been proposed for generating molecules with desirable properties, but they all require a large amount of label data of pharmacological and physicochemical...
Neural Networks, Computer Machine Learning Drug Discovery Models, Molecular
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Exploring the Advantages of Quantum Generative Adversarial Networks in Generative Chemistry.

Journal of chemical information and modeling May 12, 2023
De novo drug design with desired biological activities is crucial for developing novel therapeutics for patients. The drug development process is time- and resource-consuming, and it has a low probability of success. Recent advances in machine learni...
Humans Neural Networks, Computer Artificial Intelligence Pharmaceutical Preparations Quantum Theory Computing Methodologies
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Predicting Protein-Peptide Interactions: Benchmarking Deep Learning Techniques and a Comparison with Focused Docking.

Journal of chemical information and modeling May 11, 2023
The accurate prediction of protein structures achieved by deep learning (DL) methods is a significant milestone and has deeply impacted structural biology. Shortly after its release, AlphaFold2 has been evaluated for predicting protein-peptide intera...
Software Peptides Molecular Docking Simulation Deep Learning Protein Binding Proteins Protein Conformation
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Fingerprint-Enhanced Graph Attention Network (FinGAT) Model for Antibiotic Discovery.

Journal of chemical information and modeling May 11, 2023
Artificial Intelligence (AI) techniques are of great potential to fundamentally change antibiotic discovery industries. Efficient and effective molecular featurization is key to all highly accurate learning models for antibiotic discovery. In this pa...
Neural Networks, Computer Artificial Intelligence Anti-Bacterial Agents Learning
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A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening.

Journal of chemical information and modeling May 11, 2023
Over the past few years, many machine learning-based scoring functions for predicting the binding of small molecules to proteins have been developed. Their objective is to approximate the distribution which takes two molecules as input and outputs th...
Machine Learning Molecular Docking Simulation Protein Binding Proteins Databases, Protein Ligands
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RPI-EDLCN: An Ensemble Deep Learning Framework Based on Capsule Network for ncRNA-Protein Interaction Prediction.

Journal of chemical information and modeling May 9, 2023
Noncoding RNAs (ncRNAs) play crucial roles in many cellular life activities by interacting with proteins. Identification of ncRNA-protein interactions (ncRPIs) is key to understanding the function of ncRNAs. Although a number of computational methods...
Neural Networks, Computer Animals Deep Learning Mice Proteins RNA, Untranslated
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Basis for Accurate Protein p Prediction with Machine Learning.

Journal of chemical information and modeling May 5, 2023
pH regulates protein structures and the associated functions in many biological processes via protonation and deprotonation of ionizable side chains where the titration equilibria are determined by p's. To accelerate pH-dependent molecular mechanism ...
Artificial Intelligence Machine Learning Proteins Hydrogen-Ion Concentration Staphylococcal Protein A
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Building Machine Learning Small Molecule Melting Points and Solubility Models Using CCDC Melting Points Dataset.

Journal of chemical information and modeling May 1, 2023
Predicting solubility of small molecules is a very difficult undertaking due to the lack of reliable and consistent experimental solubility data. It is well known that for a molecule in a crystal lattice to be dissolved, it must, first, dissociate fr...
Machine Learning Water Solubility Octanols
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Enhancing Molecular Representations Via Graph Transformation Layers.

Journal of chemical information and modeling Apr 27, 2023
Molecular representation learning is an essential component of many molecule-oriented tasks, such as molecular property prediction and molecule generation. In recent years, graph neural networks (GNNs) have shown great promise in this area, represent...
Neural Networks, Computer
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Artificial Intelligence in Drug Toxicity Prediction: Recent Advances, Challenges, and Future Perspectives.

Journal of chemical information and modeling Apr 26, 2023
Toxicity prediction is a critical step in the drug discovery process that helps identify and prioritize compounds with the greatest potential for safe and effective use in humans, while also reducing the risk of costly late-stage failures. It is esti...
Humans Artificial Intelligence Machine Learning Algorithms Drug Discovery Biological Assay
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