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Protein sequence analysis using the MPI Bioinformatics Toolkit

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Gabler,  F
Department Protein Evolution, Max Planck Institute for Developmental Biology, Max Planck Society;
Protein Bioinformatics Group, Department Protein Evolution, Max Planck Institute for Developmental Biology, Max Planck Society;

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Nam,  S-Z
Department Protein Evolution, Max Planck Institute for Developmental Biology, Max Planck Society;
Protein Bioinformatics Group, Department Protein Evolution, Max Planck Institute for Developmental Biology, Max Planck Society;

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Till,  S
Department Protein Evolution, Max Planck Institute for Developmental Biology, Max Planck Society;
Protein Bioinformatics Group, Department Protein Evolution, Max Planck Institute for Developmental Biology, Max Planck Society;

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Lupas,  AN
Department Protein Evolution, Max Planck Institute for Developmental Biology, Max Planck Society;

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Alva,  V
Department Protein Evolution, Max Planck Institute for Developmental Biology, Max Planck Society;
Protein Bioinformatics Group, Department Protein Evolution, Max Planck Institute for Developmental Biology, Max Planck Society;

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Citation

Gabler, F., Nam, S.-Z., Till, S., Mirdita, M., Steinegger, M., Söding, J., et al. (2020). Protein sequence analysis using the MPI Bioinformatics Toolkit. Current Protocols in Bioinformatics, 72(1): e108. doi:10.1002/cpbi.108.


Cite as: https://hdl.handle.net/21.11116/0000-000A-538B-C
Abstract
The MPI Bioinformatics Toolkit (https://toolkit.tuebingen.mpg.de) provides interactive access to a wide range of the best‐performing bioinformatics tools and databases, including the state‐of‐the‐art protein sequence comparison methods HHblits and HHpred. The Toolkit currently includes 35 external and in‐house tools, covering functionalities such as sequence similarity searching, prediction of sequence features, and sequence classification. Due to this breadth of functionality, the tight interconnection of its constituent tools, and its ease of use, the Toolkit has become an important resource for biomedical research and for teaching protein sequence analysis to students in the life sciences. In this article, we provide detailed information on utilizing the three most widely accessed tools within the Toolkit: HHpred for the detection of homologs, HHpred in conjunction with MODELLER for structure prediction and homology modeling, and CLANS for the visualization of relationships in large sequence datasets.

Basic Protocol 1: Sequence similarity searching using HHpred

Alternate Protocol: Pairwise sequence comparison using HHpred

Support Protocol: Building a custom multiple sequence alignment using PSI‐BLAST and forwarding it as input to HHpred

Basic Protocol 2: Calculation of homology models using HHpred and MODELLER

Basic Protocol 3: Cluster analysis using CLANS