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Updated: Jun 8, 2026

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Protein loop modeling by using fragment assembly and analytical loop closure.

Julian Lee¹, Dongseon Lee, Hahnbeom Park

¹Department of Bioinformatics and Life Science, Soongsil University, Seoul 156-743, Korea. jul@ssu.ac.kr

|September 28, 2010

Summary

This summary is machine-generated.

This study introduces a new protein loop modeling method using fragment assembly and analytical loop closure. This approach efficiently generates accurate protein loop conformations, outperforming existing techniques.

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A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Area of Science:

Structural biology
Computational biology
Biophysics

Background:

Protein loops are crucial for biological functions like molecular recognition and enzymatic activity.
Understanding protein loop structures is key to deciphering molecular mechanisms of protein function.

Purpose of the Study:

To develop a novel and efficient method for protein loop modeling.
To improve the accuracy and speed of predicting three-dimensional loop conformations.

Main Methods:

Fragment assembly to reduce conformational search space.
Analytical loop closure for efficient and geometrically consistent conformation generation.
Derivation of an analytic gradient formula for optimizing loop models with experimental or database restraints.

Main Results:

The developed method significantly reduces the conformational space of protein loops.
Achieved efficient generation of geometrically consistent loop conformations.
Demonstrated superior performance compared to existing methods on loop targets of lengths 4-12.

Conclusions:

The novel protein loop modeling method offers enhanced efficiency and accuracy.
The derived analytic gradient facilitates optimization using diverse restraints.
This technique advances the field of computational protein structure prediction.