AIMC Journal:
Journal of chemical information and modeling

Showing 521 to 530 of 953 articles

Beyond Woodward-Fieser Rules: Design Principles of Property-Oriented Chromophores Based on Explainable Deep Learning Optical Spectroscopy.

Journal of chemical information and modeling Apr 27, 2022
An adequate understanding of molecular structure-property relationships is important for developing new molecules with desired properties. Although deep learning optical spectroscopy (DLOS) has been successfully applied to predict the optical and pho...
Deep Learning Molecular Structure Solvents Spectrum Analysis Chemical Phenomena
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Pose Classification Using Three-Dimensional Atomic Structure-Based Neural Networks Applied to Ion Channel-Ligand Docking.

Journal of chemical information and modeling Apr 21, 2022
The identification of promising lead compounds showing pharmacological activities toward a biological target is essential in early stage drug discovery. With the recent increase in available small-molecule databases, virtual high-throughput screening...
Neural Networks, Computer Molecular Docking Simulation Protein Binding Ligands Ion Channels
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Accurate Prediction of Aqueous Free Solvation Energies Using 3D Atomic Feature-Based Graph Neural Network with Transfer Learning.

Journal of chemical information and modeling Apr 14, 2022
Graph neural network (GNN)-based deep learning (DL) models have been widely implemented to predict the experimental aqueous solvation free energy, while its prediction accuracy has reached a plateau partly due to the scarcity of available experimenta...
Neural Networks, Computer Machine Learning Water Molecular Dynamics Simulation Entropy
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Improving Predictions with a Multitask Convolutional Siamese Network.

Journal of chemical information and modeling Apr 5, 2022
The lead optimization phase of drug discovery refines an initial hit molecule for desired properties, especially potency. Synthesis and experimental testing of the small perturbations during this refinement can be quite costly and time-consuming. Rel...
Neural Networks, Computer Drug Discovery Proteins Ligands Entropy
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Accurate Sampling of Macromolecular Conformations Using Adaptive Deep Learning and Coarse-Grained Representation.

Journal of chemical information and modeling Mar 30, 2022
Conformational sampling of protein structures is essential for understanding biochemical functions and for predicting thermodynamic properties such as free energies. Where previous approaches rely on sequential sampling procedures, recent development...
Deep Learning Proteins Molecular Dynamics Simulation Macromolecular Substances Molecular Conformation Thermodynamics
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Observing Noncovalent Interactions in Experimental Electron Density for Macromolecular Systems: A Novel Perspective for Protein-Ligand Interaction Research.

Journal of chemical information and modeling Mar 29, 2022
We report for the first time the use of experimental electron density (ED) in the Protein Data Bank for modeling of noncovalent interactions (NCIs) for protein-ligand complexes. Our methodology is based on reduced electron density gradient (RDG) theo...
Artificial Intelligence Databases, Protein Electrons Macromolecular Substances Ligands
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DeLA-Drug: A Deep Learning Algorithm for Automated Design of Druglike Analogues.

Journal of chemical information and modeling Mar 16, 2022
In this paper, we present a deep learning algorithm for automated design of druglike analogues (DeLA-Drug), a recurrent neural network (RNN) model composed of two long short-term memory (LSTM) layers and conceived for data-driven generation of simila...
Neural Networks, Computer Algorithms Databases, Factual Deep Learning
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Prediction of Maximum Absorption Wavelength Using Deep Neural Networks.

Journal of chemical information and modeling Mar 15, 2022
Fluorescent molecules are important tools in biological detection, and numerous efforts have been made to develop compounds to meet the desired photophysical properties. For example, tuning the wavelength allows an appropriate penetration depth with ...
Humans Neural Networks, Computer Machine Learning Fluorescent Dyes Solvents
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Unified Deep Learning Model for Multitask Reaction Predictions with Explanation.

Journal of chemical information and modeling Mar 10, 2022
There is significant interest and importance to develop robust machine learning models to assist organic chemistry synthesis. Typically, task-specific machine learning models for distinct reaction prediction tasks have been developed. In this work, w...
Machine Learning Deep Learning Natural Language Processing Chemistry Techniques, Synthetic
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AI-Driven Synthetic Route Design Incorporated with Retrosynthesis Knowledge.

Journal of chemical information and modeling Mar 8, 2022
Computer-aided synthesis planning (CASP) aims to assist chemists in performing retrosynthetic analysis for which they utilize their experiments, intuition, and knowledge. Recent breakthroughs in machine learning (ML) techniques, including deep neural...
Humans Neural Networks, Computer Machine Learning Software
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