AIMC Journal:
Journal of chemical information and modeling

Showing 531 to 540 of 958 articles

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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An Interpretable Convolutional Neural Network Framework for Analyzing Molecular Dynamics Trajectories: a Case Study on Functional States for G-Protein-Coupled Receptors.

Journal of chemical information and modeling Mar 8, 2022
Molecular dynamics (MD) simulations have made great contribution to revealing structural and functional mechanisms for many biomolecular systems. However, how to identify functional states and important residues from vast conformation space generated...
Neural Networks, Computer Software Receptors, G-Protein-Coupled Molecular Dynamics Simulation
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CateCom: A Practical Data-Centric Approach to Categorization of Computational Models.

Journal of chemical information and modeling Mar 1, 2022
The advent of data-driven science in the 21st century brought about the need for well-organized structured data and associated infrastructure able to facilitate the applications of artificial intelligence and machine learning. We present an effort ai...
Artificial Intelligence Machine Learning Software Databases, Factual Computer Simulation
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Structure-Aware Multimodal Deep Learning for Drug-Protein Interaction Prediction.

Journal of chemical information and modeling Feb 24, 2022
Identifying drug-protein interactions (DPIs) is crucial in drug discovery, and a number of machine learning methods have been developed to predict DPIs. Existing methods usually use unrealistic data sets with hidden bias, which will limit the accurac...
Neural Networks, Computer Machine Learning Deep Learning Proteins Amino Acid Sequence
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Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder.

Journal of chemical information and modeling Feb 17, 2022
Some of the most common applications of machine learning (ML) algorithms dealing with small molecules usually fall within two distinct domains, namely, the prediction of molecular properties and the design of novel molecules with some desirable prope...
Machine Learning Algorithms Physical Phenomena
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