AI Medical Compendium Journal:
Journal of computer-aided molecular design

Showing 31 to 40 of 67 articles

Comparing classification models-a practical tutorial.

Journal of computer-aided molecular design Sep 22, 2021
While machine learning models have become a mainstay in Cheminformatics, the field has yet to agree on standards for model evaluation and comparison. In many cases, authors compare methods by performing multiple folds of cross-validation and reportin...
Machine Learning ROC Curve
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Multitask machine learning models for predicting lipophilicity (logP) in the SAMPL7 challenge.

Journal of computer-aided molecular design Jul 17, 2021
Accurate prediction of lipophilicity-logP-based on molecular structures is a well-established field. Predictions of logP are often used to drive forward drug discovery projects. Driven by the SAMPL7 challenge, in this manuscript we describe the steps...
Models, Chemical Quantum Theory Drug Discovery Models, Statistical Thermodynamics Solubility Solvents Neural Networks, Computer Machine Learning
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Binding affinity prediction for binary drug-target interactions using semi-supervised transfer learning.

Journal of computer-aided molecular design Jun 30, 2021
In the field of drug-target interactions prediction, the majority of approaches formulated the problem as a simple binary classification task. These methods used binary drug-target interaction datasets to train their models. The prediction of drug-ta...
Drug Interactions Supervised Machine Learning Algorithms Pharmaceutical Preparations Humans
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Fine-tuning of a generative neural network for designing multi-target compounds.

Journal of computer-aided molecular design May 28, 2021
Exploring the origin of multi-target activity of small molecules and designing new multi-target compounds are highly topical issues in pharmaceutical research. We have investigated the ability of a generative neural network to create multi-target com...
Neural Networks, Computer Drug Design
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Prediction of activity cliffs on the basis of images using convolutional neural networks.

Journal of computer-aided molecular design Mar 19, 2021
An activity cliff (AC) is formed by a pair of structurally similar compounds with a large difference in potency. Accordingly, ACs reveal structure-activity relationship (SAR) discontinuity and provide SAR information for compound optimization. Herein...
Drug Design Structure-Activity Relationship Neural Networks, Computer
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Machine learning-accelerated quantum mechanics-based atomistic simulations for industrial applications.

Journal of computer-aided molecular design Oct 9, 2020
Atomistic simulations have become an invaluable tool for industrial applications ranging from the optimization of protein-ligand interactions for drug discovery to the design of new materials for energy applications. Here we review recent advances in...
Pharmaceutical Preparations Quantum Theory Drug Discovery Models, Molecular Ligands Machine Learning Drug Design
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ProIn-Fuse: improved and robust prediction of proinflammatory peptides by fusing of multiple feature representations.

Journal of computer-aided molecular design Sep 23, 2020
A proinflammatory peptide (PIP) is a type of signaling molecules that are secreted from immune cells, which contributes to the first line of defense against invading pathogens. Numerous experiments have shown that PIPs play an important role in human...
Peptide Fragments Inflammation Mediators Computer Simulation Computational Biology Machine Learning Algorithms Humans
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Meta-iPVP: a sequence-based meta-predictor for improving the prediction of phage virion proteins using effective feature representation.

Journal of computer-aided molecular design Jun 16, 2020
Phage virion protein (PVP) perforate the host cell membrane and eventually culminates in cell rupture thereby releasing replicated phages. The accurate identification of PVP is thus a crucial step towards improving our understanding of the biological...
Humans Machine Learning Bacteriophages Viral Proteins Sequence Analysis, Protein Virion Computational Biology Support Vector Machine Software Algorithms
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Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions.

Journal of computer-aided molecular design May 2, 2020
Difficulties in interpreting machine learning (ML) models and their predictions limit the practical applicability of and confidence in ML in pharmaceutical research. There is a need for agnostic approaches aiding in the interpretation of ML models re...
Pharmaceutical Preparations Therapeutic Equivalency Structure-Activity Relationship Models, Molecular Machine Learning Drug Discovery Humans Neural Networks, Computer
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Revealing cytotoxic substructures in molecules using deep learning.

Journal of computer-aided molecular design Apr 16, 2020
In drug development, late stage toxicity issues of a compound are the main cause of failure in clinical trials. In silico methods are therefore of high importance to guide the early design process to reduce time, costs and animal testing. Technical a...
Cytotoxins HEK293 Cells Cell Survival Models, Biological Drug Design Toxicology Software Drug Discovery Small Molecule Libraries Computer-Aided Design Deep Learning Humans Hep G2 Cells Neural Networks, Computer
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