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A Protocol for Computer-Based Protein Structure and Function Prediction

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Published on: November 3, 2011

Bridging the Gap between Sequence and Structure Classifications of Proteins with AlphaFold Models.

Jimin Pei¹, Antonina Andreeva², Sara Chuguransky²

¹Eugene McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, USA; Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.

Journal of Molecular Biology

|August 28, 2024

Summary

This study classifies protein domains using AlphaFold predictions and the DPAM tool, linking sequence-based Pfam families to the structure-based ECOD classification. It reveals novel domain families and evolutionary relationships, enhancing our understanding of the protein universe.

Keywords:

AlphaFold structural modeling DPAM ECOD Pfam Protein classification

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Area of Science:

Structural bioinformatics
Computational biology
Protein domain classification

Background:

Protein domain classification is crucial for understanding protein function.
AlphaFold has significantly advanced protein structure prediction, increasing data availability.
Pfam and ECOD are established databases for protein domain classification.

Purpose of the Study:

To classify approximately 9000 Pfam families into the Evolutionary Classification of Domains (ECOD) hierarchy using AlphaFold-predicted structures.
To investigate homologous relationships and domain boundaries by integrating sequence-based (Pfam) and structure-based (ECOD) classifications.
To identify potentially novel protein domain families and superfamilies through analysis of unassigned domains.

Main Methods:

Utilized predicted protein structures from AlphaFold.
Employed the Domain Parser for AlphaFold Models (DPAM) tool for domain parsing and classification.
Compared and integrated Pfam domain families with the ECOD hierarchy.
Analyzed sequence and structural features of assigned and unassigned domains.

Main Results:

Over half of the analyzed Pfam families were confidently assigned to ECOD using DPAM and AlphaFold models.
Assigned domains predominantly belong to well-known folds like Immunoglobulin-like (IgL), Armadillo (ARM), helix-turn-helix (HTH), and Src homology 3 (SH3).
A significant fraction of DPAM domains remained unassigned to ECOD, exhibiting distinct characteristics such as shorter length and more transmembrane segments, suggesting novel families or superfamilies.

Conclusions:

The integration of AlphaFold structure predictions with DPAM facilitates robust protein domain classification, bridging Pfam and ECOD.
Unassigned domains represent a rich source for discovering novel protein folds and evolutionary relationships.
This work enhances the comprehensive understanding of the protein universe by providing structural and functional insights into previously uncharacterized proteins.