Structural signatures: a web server for exploring a database of and generating protein structural features from human...

Area of Science:

• Proteomics and Bioinformatics
• Structural Biology
• Genomics

Background:

• Protein structural features offer insights into biological function and similarity.
• Previous studies utilized structural features for tissue type prediction and drug relationship characterization.
• Gene sets from transcriptomic and proteomic data often contain valuable protein feature information.

Purpose of the Study:

• To develop a web server, "Structural Signatures," for annotating and analyzing protein features from gene sets.
• To create a database of structural features from normal and diseased human tissue samples.
• To demonstrate the utility of structural signatures in analyzing single-cell RNA sequencing data from lung cancer.

Main Methods:

• Development of the "Structural Signatures" web server.
• Creation of a structural feature database using normal and disease human tissue samples.
• Application of the server and database to analyze single-cell RNA sequencing data from lung cancer.

Main Results:

• The "Structural Signatures" server enables annotation and analysis of protein features.
• The structural feature database provides insights into tissue-specific and disease-related protein structures.
• Analysis revealed relationships within lung cancer single-cell RNA sequencing data using structural signatures.

Conclusions:

• Structural signatures provide a valuable tool for analyzing protein features in biological data.
• The platform facilitates understanding of tissue states and disease relationships.
• The freely available tool supports further research in structural biology and cancer genomics.