Tag: Protein Structure Alignment

DeepAlign 1.35 – Pairwise Protein Structure Alignment

DeepAlign 1.35

:: DESCRIPTION

Different from many other tools, DeepAlign aligns two protein structures using evolutionary information and beta strand orientation in addition to geometric similarity. Therefore, DeepAlign favors the alignment of evolutionarily-related residues and also aligns beta sheets more correctly than the others. The DeepAlign alignments are also much more consistent with manual alignments than the others.

::DEVELOPER

Xu group , Sheng Wang

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 DeepAlign

:: MORE INFORMATION

Citation:

Sci Rep. 2013;3:1448. doi: 10.1038/srep01448.
Protein structure alignment beyond spatial proximity.
Wang S, Ma J, Peng J, Xu J.

TopMatch – Protein Structure Alignment

TopMatch

:: DESCRIPTION

TopMatch is an effective tool for protein structure alignment and visualization of structural similarities. Given a pair of protein structures, TopMatch calculates a list of alignments ordered by structural similarity.

::DEVELOPER

C.A.M.E. – the Center of Applied Molecular Engineering.

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux/Windows

:: DOWNLOAD

 TopMatch

:: MORE INFORMATION

Citation

Sippl & Wiederstein (2008)
A note on difficult structure alignment problems.
Bioinformatics 24, 426-427.

Sippl (2008)
On distance and similarity in fold space.
Bioinformatics 24, 872-873.

LOCK 2.0 – Vector-based Protein Structure Alignment

LOCK 2.0

:: DESCRIPTION

LOCK is a vector based protein structure superposition algorithm capable of recognizing distant structural similarities. Statistical significance values for alignments are provided.

::DEVELOPER

 The Brutlag Bioinformatics Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C Complier

:: DOWNLOAD

 LOCK

:: MORE INFORMATION

Citation:

Amit P. Singh ,Douglas L. Brutlag
Hierarchical Protein Structure Superposition using both Secondary Structure and Atomic Representations
Proceedings of the 5th International Conference on Intelligent Systems for Molecular Biology

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