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Updated: Jul 5, 2026

The ITS2 Database

The ITS2 Database

Published on: March 12, 2012

An introduction to modeling structure from sequence.

Gregory A Petsko¹

¹Brandeis University, Waltham, Massachusetts, USA.

Current Protocols in Bioinformatics

|April 23, 2008

Summary

This summary is machine-generated.

Predicting protein structures from sequences is feasible because a limited number of protein folds exist. Recognizing protein folds from sequence data enables modeling structures for any given sequence.

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Area of Science:

Structural biology
Bioinformatics
Computational biology

Background:

The number of known protein sequences vastly exceeds the number of determined protein structures.
A fundamental principle in structural biology is that a limited repertoire of protein folds underlies a vast diversity of sequences.
This implies that many different protein sequences can adopt the same three-dimensional fold.

Purpose of the Study:

To introduce the concept of modeling protein structure directly from amino acid sequence information.
To survey existing methodologies for protein structure prediction based on sequence data.
To highlight the increasing importance of structure modeling due to the growing demand for structural information.

Main Methods:

The abstract introduces the concept of inferring protein fold from sequence.
It surveys methods for structure modeling, detailed in subsequent sections.
The core idea relies on the limited number of protein folds compared to sequences.

Main Results:

The premise suggests that recognizing protein folds from sequence alone is achievable.
A comprehensive database of protein folds could allow modeling of structures for novel sequences.
The demand for structural information necessitates advancements in modeling techniques.

Conclusions:

Protein structure modeling from sequence is a critical area in structural biology.
Understanding the relationship between sequence and fold is key to predicting protein structures.
The development and application of sequence-based modeling methods are essential for the field.