AIMC Journal:
Journal of chemical information and modeling

Showing 461 to 470 of 940 articles

Computational Predictions of Nonclinical Pharmacokinetics at the Drug Design Stage.

Journal of chemical information and modeling Jan 3, 2023
Although computational predictions of pharmacokinetics (PK) are desirable at the drug design stage, existing approaches are often limited by prediction accuracy and human interpretability. Using a discovery data set of mouse and rat PK studies at Roc...
Biological Availability Pharmacokinetics Models, Biological Administration, Intravenous Drug Design Pharmaceutical Preparations Rats Humans Animals Neural Networks, Computer
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ElectroPredictor: An Application to Predict Mayr's Electrophilicity through Implementation of an Ensemble Model Based on Machine Learning Algorithms.

Journal of chemical information and modeling Jan 3, 2023
Electrophilicity () is one of the most important parameters to understand the reactivity of an organic molecule. Although the theoretical electrophilicity index (ω) has been associated with in a small homologous series, the use of to predict in a ...
Algorithms Databases, Factual Machine Learning
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Personal Precise Force Field for Intrinsically Disordered and Ordered Proteins Based on Deep Learning.

Journal of chemical information and modeling Dec 19, 2022
Intrinsically disordered proteins (IDPs) are proteins without a fixed three-dimensional (3D) structure under physiological conditions and are associated with Parkinson's disease, Alzheimer's disease, cancer, cardiovascular disease, amyloidosis, diabe...
Protein Conformation Protein Folding Intrinsically Disordered Proteins Humans Molecular Dynamics Simulation Deep Learning Alzheimer Disease
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TIRESIA: An eXplainable Artificial Intelligence Platform for Predicting Developmental Toxicity.

Journal of chemical information and modeling Dec 15, 2022
Herein, a robust and reproducible eXplainable Artificial Intelligence (XAI) approach is presented, which allows prediction of developmental toxicity, a challenging human-health endpoint in toxicology. The application of XAI as an alternative method i...
Humans Quantitative Structure-Activity Relationship Algorithms Artificial Intelligence Animals
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Structural Analysis and Prediction of Hematotoxicity Using Deep Learning Approaches.

Journal of chemical information and modeling Dec 6, 2022
Hematotoxicity has been becoming a serious but overlooked toxicity in drug discovery. However, only a few models have been reported for the prediction of hematotoxicity. In this study, we constructed a high-quality dataset comprising 759 hematotoxic...
Computer Simulation Algorithms Deep Learning Machine Learning Drug Discovery
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Graph-Convolutional Neural Net Model of the Statistical Torsion Profiles for Small Organic Molecules.

Journal of chemical information and modeling Dec 1, 2022
We present a graph-convolutional neural network (GCNN)-based method for learning and prediction of statistical torsional profiles (STP) in small organic molecules based on the experimental X-ray structure data. A specialized GCNN torsion profile mode...
Databases, Factual Crystallography Neural Networks, Computer
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Exposing the Limitations of Molecular Machine Learning with Activity Cliffs.

Journal of chemical information and modeling Dec 1, 2022
Machine learning has become a crucial tool in drug discovery and chemistry at large, , to predict molecular properties, such as bioactivity, with high accuracy. However, activity cliffs─pairs of molecules that are highly similar in their structure bu...
Models, Molecular Structure-Activity Relationship Machine Learning Drug Discovery Algorithms
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Exploration of Chemical Space Guided by PixelCNN for Fragment-Based De Novo Drug Discovery.

Journal of chemical information and modeling Dec 1, 2022
We report a novel framework for achieving fragment-based molecular design using pixel convolutional neural network (PixelCNN) combined with the simplified molecular input line entry system (SMILES) as molecular representation. While a widely used rec...
Neural Networks, Computer Drug Discovery Molecular Structure Drug Design
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Machine Learning Modeling and Insights into the Structural Characteristics of Drug-Induced Neurotoxicity.

Journal of chemical information and modeling Nov 30, 2022
Neurotoxicity can be resulted from many diverse clinical drugs, which has been a cause of concern to human populations across the world. The detection of drug-induced neurotoxicity (DINeurot) potential with biological experimental methods always requ...
Machine Learning Humans Computer Simulation
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DeepCV: A Deep Learning Framework for Blind Search of Collective Variables in Expanded Configurational Space.

Journal of chemical information and modeling Nov 29, 2022
We present (DeepCV), a computer code that provides an efficient and customizable implementation of the deep autoencoder neural network (DAENN) algorithm that has been developed in our group for computing collective variables (CVs) and can be used wi...
Molecular Dynamics Simulation Neural Networks, Computer Algorithms Deep Learning Software
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