AIMC Journal:
Journal of chemical information and modeling

Showing 361 to 370 of 934 articles

From Proteins to Ligands: Decoding Deep Learning Methods for Binding Affinity Prediction.

Journal of chemical information and modeling Nov 20, 2023
Accurate in silico prediction of protein-ligand binding affinity is important in the early stages of drug discovery. Deep learning-based methods exist but have yet to overtake more conventional methods such as giga-docking largely due to their lack o...
Neural Networks, Computer Deep Learning Protein Binding Proteins Ligands
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Opinion Mining by Convolutional Neural Networks for Maximizing Discoverability of Nanomaterials.

Journal of chemical information and modeling Nov 20, 2023
The scientific literature contains valuable information that can be used for future applications, but manual analysis presents challenges due to its size and disciplinary boundaries. The prevailing solution involves natural language processing (NLP) ...
Neural Networks, Computer Information Storage and Retrieval Sentiment Analysis
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Identification of High-Reliability Regions of Machine Learning Predictions Based on Materials Chemistry.

Journal of chemical information and modeling Nov 20, 2023
Progress in the application of machine learning (ML) methods to materials design is hindered by the lack of understanding of the reliability of ML predictions, in particular, for the application of ML to small data sets often found in materials scien...
Machine Learning Reproducibility of Results
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Calculation of Protein Folding Thermodynamics Using Molecular Dynamics Simulations.

Journal of chemical information and modeling Nov 13, 2023
Despite advances in artificial intelligence methods, protein folding remains in many ways an enigma to be solved. Accurate computation of protein folding energetics could help drive fields such as protein and drug design and genetic interpretation. H...
Artificial Intelligence Proteins Molecular Dynamics Simulation Thermodynamics Protein Folding
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Data-Driven Score-Based Models for Generating Stable Structures with Adaptive Crystal Cells.

Journal of chemical information and modeling Nov 10, 2023
The discovery of new functional and stable materials is a big challenge due to its complexity. This work aims at the generation of new crystal structures with desired properties, such as chemical stability and specified chemical composition, by using...
Machine Learning
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Anatomy of Potency Predictions Focusing on Structural Analogues with Increasing Potency Differences Including Activity Cliffs.

Journal of chemical information and modeling Nov 9, 2023
Potency predictions are popular in compound design and optimization but are complicated by intrinsic limitations. Moreover, even for nonlinear methods, activity cliffs (ACs, formed by structural analogues with large potency differences) represent cha...
Artificial Intelligence Machine Learning Structure-Activity Relationship
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Deep Generative Models in Drug Molecule Generation.

Journal of chemical information and modeling Nov 7, 2023
The discovery of new drugs has important implications for human health. Traditional methods for drug discovery rely on experiments to optimize the structure of lead molecules, which are time-consuming and high-cost. Recently, artificial intelligence ...
Humans Artificial Intelligence Databases, Factual Drug Design Drug Discovery Benchmarking
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DeepMPSF: A Deep Learning Network for Predicting General Protein Phosphorylation Sites Based on Multiple Protein Sequence Features.

Journal of chemical information and modeling Nov 6, 2023
Phosphorylation, as one of the most important post-translational modifications, plays a key role in various cellular physiological processes and disease occurrences. In recent years, computer technology has been gradually applied to the prediction of...
Humans Animals Deep Learning Mice Rats Protein Processing, Post-Translational Proteins Phosphorylation Amino Acid Sequence
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Small-Molecule Conformer Generators: Evaluation of Traditional Methods and AI Models on High-Quality Data Sets.

Journal of chemical information and modeling Oct 26, 2023
Small-molecule conformer generation (SMCG) is an extremely important task in both ligand- and structure-based computer-aided drug design, especially during the hit discovery phase. Recently, a multitude of artificial intelligence (AI) models tailored...
Artificial Intelligence Drug Design Models, Molecular Ligands Molecular Conformation
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Deep Learning with Geometry-Enhanced Molecular Representation for Augmentation of Large-Scale Docking-Based Virtual Screening.

Journal of chemical information and modeling Oct 26, 2023
Structure-based virtual screening has been a crucial tool in drug discovery for decades. However, as the chemical space expands, the existing structure-based virtual screening techniques based on molecular docking and scoring struggle to handle billi...
Humans Molecular Docking Simulation Drug Discovery Deep Learning
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