PPI_SVM: Prediction of protein-protein interactions using machine learning, domain-domain affinities and frequency tables
Protein-protein interactions (PPI) control most of the biological processes in a living cell. In
order to fully understand protein functions, a knowledge of protein-protein interactions is …
order to fully understand protein functions, a knowledge of protein-protein interactions is …
E3bind: An end-to-end equivariant network for protein-ligand docking
In silico prediction of the ligand binding pose to a given protein target is a crucial but
challenging task in drug discovery. This work focuses on blind flexible selfdocking, where …
challenging task in drug discovery. This work focuses on blind flexible selfdocking, where …
Learning protein-ligand binding affinity with atomic environment vectors
Scoring functions for the prediction of protein-ligand binding affinity have seen renewed
interest in recent years when novel machine learning and deep learning methods started to …
interest in recent years when novel machine learning and deep learning methods started to …
DeepHomo2. 0: improved protein–protein contact prediction of homodimers by transformer-enhanced deep learning
Protein–protein interactions play an important role in many biological processes. However,
although structure prediction for monomer proteins has achieved great progress with the …
although structure prediction for monomer proteins has achieved great progress with the …
Protein–protein interaction site prediction through combining local and global features with deep neural networks
Abstract Motivation Protein–protein interactions (PPIs) play important roles in many
biological processes. Conventional biological experiments for identifying PPI sites are costly …
biological processes. Conventional biological experiments for identifying PPI sites are costly …
A machine learning approach to predicting protein–ligand binding affinity with applications to molecular docking
PJ Ballester, JBO Mitchell - Bioinformatics, 2010 - academic.oup.com
Motivation: Accurately predicting the binding affinities of large sets of diverse protein–ligand
complexes is an extremely challenging task. The scoring functions that attempt such …
complexes is an extremely challenging task. The scoring functions that attempt such …
A deep dilated convolutional residual network for predicting interchain contacts of protein homodimers
Motivation Deep learning has revolutionized protein tertiary structure prediction recently.
The cutting-edge deep learning methods such as AlphaFold can predict high-accuracy …
The cutting-edge deep learning methods such as AlphaFold can predict high-accuracy …
DeeplyTough: learning structural comparison of protein binding sites
M Simonovsky, J Meyers - Journal of chemical information and …, 2020 - ACS Publications
Protein pocket matching, or binding site comparison, is of importance in drug discovery.
Identification of similar binding pockets can help guide efforts for hit-finding, understanding …
Identification of similar binding pockets can help guide efforts for hit-finding, understanding …
AlphaFold2-aware protein–DNA binding site prediction using graph transformer
Protein–DNA interactions play crucial roles in the biological systems, and identifying protein–
DNA binding sites is the first step for mechanistic understanding of various biological …
DNA binding sites is the first step for mechanistic understanding of various biological …