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Conserved Binding Sites

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...

Conserved Binding Sites

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...

Conservation of Protein Domains Over Different Proteins

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain. Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...

Conservation of Protein Domains

Conservation of Protein Domains

Protein domains are small structurally independent units that are part of a single amino acid chain. Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...

Protein Kinases and Phosphatases

Protein Kinases and Phosphatases

Proteins undergo chemical modifications that trigger changes in the charge, structure, and conformation of the proteins. Phosphorylation, acetylation, glycosylation, nitrosylation, ubiquitination, lipidation, methylation, and proteolysis are various protein modifications that regulate protein activity. Such modifications are usually enzyme-driven.
Protein kinases
Many proteins in the cell are regulated by phosphorylation, the addition of a phosphate group. A family of enzymes called kinases...

Protein Kinases and Phosphatases

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Proteins undergo chemical modifications that trigger changes in the charge, structure, and conformation of the proteins. Phosphorylation, acetylation, glycosylation, nitrosylation, ubiquitination, lipidation, methylation, and proteolysis are various protein modifications that regulate protein activity. Such modifications are usually enzyme-driven.
Protein kinases
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Related Experiment Video

Updated: May 25, 2026

Identification of Kinase-substrate Pairs Using High Throughput Screening

Identification of Kinase-substrate Pairs Using High Throughput Screening

Published on: August 29, 2015

Predicting kinase substrates using conservation of local motif density.

Andy C W Lai¹, Alex N Nguyen Ba, Alan M Moses

¹Department of Cell and Systems Biology, University of Toronto, Toronto, Canada M5S 3G5.

Bioinformatics (Oxford, England)

|February 4, 2012

Summary

This study introduces ConDens, a new computational method to predict protein kinase substrates using evolutionary information. ConDens improves accuracy and does not require training data, advancing cell signaling research.

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Last Updated: May 25, 2026

Identification of Kinase-substrate Pairs Using High Throughput Screening

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Area of Science:

Computational Biology
Molecular Biology
Bioinformatics

Background:

Protein kinases are crucial in cell signaling pathways.
Identifying kinase substrates is a significant challenge in computational biology.

Purpose of the Study:

To develop a novel computational method for predicting kinase substrates.
To overcome limitations of existing methods, particularly regarding degenerate motif positioning and the need for training data.

Main Methods:

Introduced ConDens, a method utilizing evolutionary information from multiple sequence alignments.
ConDens is tolerant to degenerate motif positioning and compares observed match density to a null evolutionary model.
The method does not require labeled training data.

Main Results:

ConDens demonstrated improved performance over several existing methods.
The method is generalizable and can predict substrates for eukaryotic kinases lacking training data.
Validated improved performance and generalizability of the ConDens method.

Conclusions:

ConDens offers a robust and data-efficient approach for kinase substrate prediction.
The method advances the systematic identification of kinase substrates in cell signaling.
Enables substrate prediction for kinases where training data is unavailable.