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Binding Sites

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RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach.

BMC bioinformatics
BACKGROUND: RNAs play key roles in cells through the interactions with proteins known as the RNA-binding proteins (RBP) and their binding motifs enable crucial understanding of the post-transcriptional regulation of RNAs. How the RBPs correctly recog...

Imputation for transcription factor binding predictions based on deep learning.

PLoS computational biology
Understanding the cell-specific binding patterns of transcription factors (TFs) is fundamental to studying gene regulatory networks in biological systems, for which ChIP-seq not only provides valuable data but is also considered as the gold standard....

A machine learning approach for ranking clusters of docked protein-protein complexes by pairwise cluster comparison.

Proteins
Reliable identification of near-native poses of docked protein-protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein-protein interactions is challenging for traditional biophysical or knowledge based potentials and th...

Synthesis and antimicrobial studies of novel derivatives of 4-(4-formyl-3-phenyl-1H-pyrazol-1-yl)benzoic acid as potent anti-Acinetobacter baumannii agents.

Bioorganic & medicinal chemistry letters
Microbial resistance to antibiotics is a global concern. The World Health Organization (WHO) has identified antimicrobial resistance as one the three greatest threats for human beings in the 21st century. Without urgent and coordinated action, the wo...

An ensemble micro neural network approach for elucidating interactions between zinc finger proteins and their target DNA.

BMC genomics
BACKGROUND: The ability to engineer zinc finger proteins binding to a DNA sequence of choice is essential for targeted genome editing to be possible. Experimental techniques and molecular docking have been successful in predicting protein-DNA interac...

Predicting protein conformational changes for unbound and homology docking: learning from intrinsic and induced flexibility.

Proteins
Predicting protein conformational changes from unbound structures or even homology models to bound structures remains a critical challenge for protein docking. Here we present a study directly addressing the challenge by reducing the dimensionality a...

A high-order representation and classification method for transcription factor binding sites recognition in Escherichia coli.

Artificial intelligence in medicine
BACKGROUND: Identifying transcription factors binding sites (TFBSs) plays an important role in understanding gene regulatory processes. The underlying mechanism of the specific binding for transcription factors (TFs) is still poorly understood. Previ...

A Graph Approach to Mining Biological Patterns in the Binding Interfaces.

Journal of computational biology : a journal of computational molecular cell biology
Protein-RNA interactions play important roles in the biological systems. Searching for regular patterns in the Protein-RNA binding interfaces is important for understanding how protein and RNA recognize each other and bind to form a complex. Herein, ...

Development of a sugar-binding residue prediction system from protein sequences using support vector machine.

Computational biology and chemistry
Several methods have been proposed for protein-sugar binding site prediction using machine learning algorithms. However, they are not effective to learn various properties of binding site residues caused by various interactions between proteins and s...