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SKINK: a web server for string kernel based kink prediction in α-helices.

Tim Seifert¹, Andreas Lund¹, Benny Kneissl¹

¹Department of Software Engineering and Bioinformatics, Johannes Gutenberg University of Mainz, 55128 Mainz, Institute for Computer Science, Johann Wolfgang Goethe-University Frankfurt am Main, 60054 Frankfurt am Main, Data Science, Pharma Research and Early Development Informatics (pREDi), Roche Diagnostics GmbH, 82377 Penzberg, Department of Human Genetics, Saarland University Faculty of Medicine, 66421 Homburg and Lead Identification and Optimization Support, Boehringer-Ingelheim Pharma GmbH & Co. KG, 88397 Biberach, Germany.

Bioinformatics (Oxford, England)

|February 18, 2014

Summary

We developed SKINK, a web server predicting distortions in alpha-helical protein structures. SKINK identifies the most probable kink positions in alpha-helix sequences, aiding structural bioinformatics.

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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 bioinformatics
Protein structure analysis
Computational biology

Background:

Distortions in alpha-helical geometry are poorly understood but significantly impact protein structure.
Accurate prediction of these distortions is vital for structural bioinformatics.
Current methods for predicting helical distortions are limited.

Purpose of the Study:

To introduce SKINK, a novel web server for predicting kinks in alpha-helical sequences.
To extend previous work by annotating the most probable kink positions.
To provide a user-friendly tool for analyzing protein structural anomalies.

Main Methods:

Development of a string kernel-based prediction method.
Implementation of the SKINK web server.
Integration of SKINK into the BALL software package.

Main Results:

SKINK accurately predicts the presence of kinks in alpha-helical sequences.
The server provides annotations for the most probable kink locations.
SKINK offers a valuable tool for researchers in structural bioinformatics.

Conclusions:

SKINK represents a significant advancement in predicting alpha-helical distortions.
The web server facilitates a deeper understanding of protein structural changes.
SKINK is freely accessible, promoting wider research in the field.