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Binding Sites

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ScanNet: A Web Server for Structure-based Prediction of Protein Binding Sites with Geometric Deep Learning.

Journal of molecular biology
Predicting the various binding sites of a protein from its structure sheds light on its function and paves the way towards design of interaction inhibitors. Here, we report ScanNet, a freely available web server for prediction of protein-protein, pro...

Scaffolding protein functional sites using deep learning.

Science (New York, N.Y.)
The binding and catalytic functions of proteins are generally mediated by a small number of functional residues held in place by the overall protein structure. Here, we describe deep learning approaches for scaffolding such functional sites without n...

Deep learning for de-convolution of Smad2 versus Smad3 binding sites.

BMC genomics
BACKGROUND: The transforming growth factor beta-1 (TGF β-1) cytokine exerts both pro-tumor and anti-tumor effects in carcinogenesis. An increasing body of literature suggests that TGF β-1 signaling outcome is partially dependent on the regulatory tar...

Structural Bioinformatics and Deep Learning of Metalloproteins: Recent Advances and Applications.

International journal of molecular sciences
All living organisms require metal ions for their energy production and metabolic and biosynthetic processes. Within cells, the metal ions involved in the formation of adducts interact with metabolites and macromolecules (proteins and nucleic acids)....

A web server for identifying circRNA-RBP variable-length binding sites based on stacked generalization ensemble deep learning network.

Methods (San Diego, Calif.)
Circular RNA (circRNA) can exert biological functions by interacting with RNA-binding protein (RBP), and some deep learning-based methods have been developed to predict RBP binding sites on circRNA. However, most of these methods identify circRNA-RBP...

ProB-Site: Protein Binding Site Prediction Using Local Features.

Cells
Protein-protein interactions (PPIs) are responsible for various essential biological processes. This information can help develop a new drug against diseases. Various experimental methods have been employed for this purpose; however, their applicatio...

AI-based prediction of new binding site and virtual screening for the discovery of novel P2X3 receptor antagonists.

European journal of medicinal chemistry
Artificial intelligence (AI) has been recognized as a powerful technique that can accelerate drug discovery during the hit compound identification step. However, most simple deep learning models have been used for naive pre-filtering as the predictio...

DeepPN: a deep parallel neural network based on convolutional neural network and graph convolutional network for predicting RNA-protein binding sites.

BMC bioinformatics
BACKGROUND: Addressing the laborious nature of traditional biological experiments by using an efficient computational approach to analyze RNA-binding proteins (RBPs) binding sites has always been a challenging task. RBPs play a vital role in post-tra...

Explainable deep drug-target representations for binding affinity prediction.

BMC bioinformatics
BACKGROUND: Several computational advances have been achieved in the drug discovery field, promoting the identification of novel drug-target interactions and new leads. However, most of these methodologies have been overlooking the importance of prov...

Machine Learning Guided Batched Design of a Bacterial Ribosome Binding Site.

ACS synthetic biology
Optimization of gene expression levels is an essential part of the organism design process. Fine control of this process can be achieved by engineering transcription and translation control elements, including the ribosome binding site (RBS). Unfortu...