AIMC Journal:
Journal of chemical information and modeling

Showing 381 to 390 of 934 articles

Machine Learning-Based Prediction of Activation Energies for Chemical Reactions on Metal Surfaces.

Journal of chemical information and modeling Sep 18, 2023
In computational surface catalysis, the calculation of activation energies of chemical reactions is expensive, which, in many cases, limits our ability to understand complex reaction networks. Here, we present a universal, machine learning-based appr...
Machine Learning Databases, Factual Metals Catalysis
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Data-Driven Prediction of Configurational Stability of Molecule-Adsorbed Heterogeneous Catalysts.

Journal of chemical information and modeling Sep 15, 2023
The design of new heterogeneous catalysts that convert small molecules into valuable chemicals is a key challenge for constructing sustainable energy systems. Density functional theory (DFT)-based design frameworks based on the understanding of molec...
Machine Learning Adsorption Density Functional Theory Catalysis
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NNP/MM: Accelerating Molecular Dynamics Simulations with Machine Learning Potentials and Molecular Mechanics.

Journal of chemical information and modeling Sep 11, 2023
Machine learning potentials have emerged as a means to enhance the accuracy of biomolecular simulations. However, their application is constrained by the significant computational cost arising from the vast number of parameters compared with traditio...
Neural Networks, Computer Machine Learning Molecular Dynamics Simulation Ligands
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Deep-Cloud: A Deep Neural Network-Based Approach for Analyzing Differentially Expressed Genes of RNA-seq Data.

Journal of chemical information and modeling Sep 8, 2023
Presently, the field of analyzing differentially expressed genes (DEGs) of RNA-seq data is still in its infancy, with new approaches constantly being proposed. Taking advantage of deep neural networks to explore gene expression information on RNA-seq...
Neural Networks, Computer Software Algorithms RNA-Seq
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Design of New Inorganic Crystals with the Desired Composition Using Deep Learning.

Journal of chemical information and modeling Sep 8, 2023
New solid-state materials have been discovered using various approaches from atom substitution in density functional theory (DFT) to generative models in machine learning. Recently, generative models have shown promising performance in finding new ma...
Machine Learning Databases, Factual Deep Learning Density Functional Theory Diffusion
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Combining SILCS and Artificial Intelligence for High-Throughput Prediction of the Passive Permeability of Drug Molecules.

Journal of chemical information and modeling Sep 8, 2023
Membrane permeability of drug molecules plays a significant role in the development of new therapeutic agents. Accordingly, methods to predict the passive permeability of drug candidates during a medicinal chemistry campaign offer the potential to ac...
Artificial Intelligence Permeability Ligands Chemistry, Pharmaceutical Cell Membrane Permeability
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VenomPred 2.0: A Novel Platform for an Extended and Human Interpretable Toxicological Profiling of Small Molecules.

Journal of chemical information and modeling Sep 7, 2023
The application of artificial intelligence and machine learning (ML) methods is becoming increasingly popular in computational toxicology and drug design; it is considered as a promising solution for assessing the safety profile of compounds, particu...
Humans Artificial Intelligence Machine Learning Animals
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CIRCE: Web-Based Platform for the Prediction of Cannabinoid Receptor Ligands Using Explainable Machine Learning.

Journal of chemical information and modeling Sep 7, 2023
The endocannabinoid system, which includes cannabinoid receptor 1 and 2 subtypes (CBR and CBR, respectively), is responsible for the onset of various pathologies including neurodegeneration, cancer, neuropathic and inflammatory pain, obesity, and inf...
Machine Learning Internet Ligands Receptors, Cannabinoid
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Integrating Reaction Schemes, Reagent Databases, and Virtual Libraries into Fragment-Based Design by Reinforcement Learning.

Journal of chemical information and modeling Sep 5, 2023
Lead optimization supported by artificial intelligence (AI)-based generative models has become increasingly important in drug design. Success factors are reagent availability, novelty, and the optimization of multiple properties. Directed fragment-re...
Artificial Intelligence Databases, Factual Learning Chemistry, Pharmaceutical Libraries, Digital
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Adaptive Ensemble Refinement of Protein Structures in High Resolution Electron Microscopy Density Maps with Radical Augmented Molecular Dynamics Flexible Fitting.

Journal of chemical information and modeling Sep 4, 2023
Recent advances in cryo-electron microscopy (cryo-EM) have enabled modeling macromolecular complexes that are essential components of the cellular machinery. The density maps derived from cryo-EM experiments are often integrated with manual, knowledg...
Artificial Intelligence Molecular Dynamics Simulation Microscopy, Electron Cryoelectron Microscopy Adenylate Kinase
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