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Binding Sites

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Predicting lysine phosphoglycerylation with fuzzy SVM by incorporating k-spaced amino acid pairs into Chou׳s general PseAAC.

Journal of theoretical biology
As a new type of post-translational modification, lysine phosphoglycerylation plays a key role in regulating glycolytic process and metabolism in cells. Due to the traditional experimental methods are time-consuming and labor-intensive, it is importa...

Sequence-based prediction of protein-peptide binding sites using support vector machine.

Journal of computational chemistry
Protein-peptide interactions are essential for all cellular processes including DNA repair, replication, gene-expression, and metabolism. As most protein-peptide interactions are uncharacterized, it is cost effective to investigate them computational...

Predicting transcription factor site occupancy using DNA sequence intrinsic and cell-type specific chromatin features.

BMC bioinformatics
BACKGROUND: Understanding the mechanisms by which transcription factors (TF) are recruited to their physiological target sites is crucial for understanding gene regulation. DNA sequence intrinsic features such as predicted binding affinity are often ...

Antileishmanial activity of novel indolyl-coumarin hybrids: Design, synthesis, biological evaluation, molecular docking study and in silico ADME prediction.

Bioorganic & medicinal chemistry letters
In present work we have designed and synthesized total twelve novel 3-(3-(1H-indol-3-yl)-3-phenylpropanoyl)-4-hydroxy-2H-chromen-2-one derivatives 13(a-l) using Ho(3+) doped CoFe2O4 nanoparticles as catalyst and evaluated for their potential antileis...

A Sequence-Based Dynamic Ensemble Learning System for Protein Ligand-Binding Site Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
BACKGROUND: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands...

PRIdictor: Protein-RNA Interaction predictor.

Bio Systems
Several computational methods have been developed to predict RNA-binding sites in protein, but its inverse problem (i.e., predicting protein-binding sites in RNA) has received much less attention. Furthermore, most methods that predict RNA-binding si...

Prediction of Protein-Protein Interaction Sites with Machine-Learning-Based Data-Cleaning and Post-Filtering Procedures.

The Journal of membrane biology
Accurately predicting protein-protein interaction sites (PPIs) is currently a hot topic because it has been demonstrated to be very useful for understanding disease mechanisms and designing drugs. Machine-learning-based computational approaches have ...

Prediction the Substrate Specificities of Membrane Transport Proteins Based on Support Vector Machine and Hybrid Features.

IEEE/ACM transactions on computational biology and bioinformatics
Membrane transport proteins and their substrate specificities play crucial roles in a variety of cellular functions. Identifying the substrate specificities of membrane transport proteins is closely related to the protein-target interaction predictio...

Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification.

Immunogenetics
A key event in the generation of a cellular response against malicious organisms through the endocytic pathway is binding of peptidic antigens by major histocompatibility complex class II (MHC class II) molecules. The bound peptide is then presented ...

Characterization and machine learning prediction of allele-specific DNA methylation.

Genomics
A large collection of Single Nucleotide Polymorphisms (SNPs) has been identified in the human genome. Currently, the epigenetic influences of SNPs on their neighboring CpG sites remain elusive. A growing body of evidence suggests that locus-specific ...