Parsing Compound-Protein Bioactivity Tables.
Sign Up to like & getrecommendations! Published in 2018 at "Methods in molecular biology"
DOI: 10.1007/978-1-4939-8639-2_4
Abstract: With the availability of a multitude of databases that contain information on the bioactivity between compounds and proteins, several fundamental tasks arise. These include parsing of the original data in order to filter out unusable… read more here.
Keywords: compound protein; bioactivity; parsing compound; biology ... See more keywords
MONN: A Multi-objective Neural Network for Predicting Compound-Protein Interactions and Affinities
Sign Up to like & getrecommendations! Published in 2020 at "Cell systems"
DOI: 10.1016/j.cels.2020.03.002
Abstract: Summary Computational approaches for understanding compound-protein interactions (CPIs) can greatly facilitate drug development. Recently, a number of deep-learning-based methods have been proposed to predict binding affinities and attempt to capture local interaction sites in compounds… read more here.
Keywords: neural network; compound protein; protein interactions;
Yuel: Improving the Generalizability of Structure-Free Compound-Protein Interaction Prediction
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.1c01531
Abstract: Predicting binding affinities between small molecules and the protein target is at the core of computational drug screening and drug target identification. Deep learning-based approaches have recently been adapted to predict binding affinities and they… read more here.
Keywords: compound protein; prediction; protein interaction; protein ... See more keywords
DeepCDA: deep cross-domain compound-protein affinity prediction through LSTM and convolutional neural networks
Sign Up to like & getrecommendations! Published in 2020 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btaa544
Abstract: MOTIVATION An essential part of drug discovery is the accurate prediction of the binding affinity of new compound-protein pairs. Most of the standard computational methods assume that compounds or proteins of the test data are… read more here.
Keywords: protein; compound protein; affinity; compound ... See more keywords
CPRiL: compound-protein relationships in literature
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DOI: 10.1093/bioinformatics/btac539
Abstract: AVAILABILITY Newly discovered functional relationships of (bio-)molecules are a key component in molecular biology and life science research. Especially in the drug discovery field, knowledge of how small molecules associate with proteins plays a fundamental… read more here.
Keywords: compound protein; protein relationships; cpril compound; relationships literature ... See more keywords
Perceiver CPI: a nested cross-attention network for compound–protein interaction prediction
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DOI: 10.1093/bioinformatics/btac731
Abstract: Abstract Motivation Compound–protein interaction (CPI) plays an essential role in drug discovery and is performed via expensive molecular docking simulations. Many artificial intelligence-based approaches have been proposed in this regard. Recently, two types of models… read more here.
Keywords: information; interaction; compound protein; protein interaction ... See more keywords
Extracting Explicable Rules for the Identification of Compound–Protein Interactions
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DOI: 10.1109/access.2020.2984824
Abstract: Compound–protein interaction (CPI) is one of the essential interaction patterns in living organisms. However, its underlying mechanism has not been fully revealed because of its complicated processes. Determining CPIs with traditional experiments can reveal solid… read more here.
Keywords: explicable rules; cpis; extracting explicable; compound ... See more keywords
Effectively Identifying Compound-Protein Interactions by Learning from Positive and Unlabeled Examples.
Sign Up to like & getrecommendations! Published in 2018 at "IEEE/ACM transactions on computational biology and bioinformatics"
DOI: 10.1109/tcbb.2016.2570211
Abstract: Prediction of compound-protein interactions (CPIs) is to find new compound-protein pairs where a protein is targeted by at least a compound, which is a crucial step in new drug design. Currently, a number of machine… read more here.
Keywords: protein; compound protein; cpis; unlabeled examples ... See more keywords
CPInformer for Efficient and Robust Compound-Protein Interaction Prediction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE/ACM Transactions on Computational Biology and Bioinformatics"
DOI: 10.1109/tcbb.2022.3144008
Abstract: Recently, deep learning has become the mainstream methodology for Compound-Protein Interaction (CPI) prediction. However, the existing compound-protein feature extraction methods have some issues that limit their performance. First, graph networks are widely used for structural… read more here.
Keywords: compound protein; compound; protein interaction; cpinformer ... See more keywords