Zebra
Web-server For Bioinformatic Analysis Of Protein Families
To Identify Amino Acid Residues Responsible For Functional Diversity

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Have a protein family? ...

... to identify variable amino acid residues
responsible for functional diversity
and to select hotspots for directed evolution
or rational design experiments


OR

Access your results by JobID

JobID:

Example: use ID dc631f45f13b4b to access an example output page



Build large alignments of protein families automatically
with the Mustguseal server

You can use the Mustguseal server to automatically construct large multiple alignments of protein families from all available information about their structures and sequences in public databases. Multiple alignments of thousands of protein sequences and structures can be constructed using this public web-server.


Zebra Support

Dmitry Suplatov

Publications
Zebra algorithm, its principles, mathematics, and advantages
Suplatov D., Shalaeva D., Kirilin E., Arzhanik V., Švedas V. (2014). Bioinformatic analysis of protein families for identification of variable amino acid residues responsible for functional diversity. J.Biomol.Struct.Dyn. 32(1):75-87. DOI:10.1080/07391102.2012.750249 PMID:23384165
Download Supplementary materials.

Practical guidelines to implement the bioinformatic analysis
Suplatov D., Kirilin E., Takhaveev V., Švedas V. (2014). Zebra: web-server for bioinformatic analysis of diverse protein families, J.Biomol.Struct.Dyn., 32(11), 1752-1758. DOI:10.1080/07391102.2013.834514 PMID:24028489

Zebra bioinformatic analysis in the wet-laboratory practice
Suplatov D, Panin N, Kirilin E, Shcherbakova T, Kudryavtsev P, Švedas V. (2014) Computational Design of a pH Stable Enzyme: Understanding Molecular Mechanism of Penicillin Acylase's Adaptation to Alkaline Conditions. PLoS ONE 9(6): e100643. DOI:10.1371/journal.pone.0100643 PMID:24959852

Suplatov, D. A., Besenmatter, W., Švedas, V. K., Svendsen, A. (2012). Bioinformatic analysis of alpha/beta-hydrolase fold enzymes reveals subfamily-specific positions responsible for discrimination of amidase and lipase activities. Protein Eng.Des.Sel., 25(11), 689-697. DOI:10.1093/protein/gzs068 PMID:23043134


Navigation:

New! Do you have a protein family and what to identify and rank binding sites in proteins by functional significance and select particular positions in the structure that are important for selective binding of substrates/inhibitors/effectors? See our latest algorithm pocketZebra.


Questions other people ask about Zebra:
Q: HTTPS version?
Q: What is Zebra?
Q: What makes Zebra different?
Q: Why are the subfamily-specific positions (SSPs) important?
Q: Why to identify the SSPs?
Q: Can SSPs have practical application?
Q: What makes the bioinformatic analysis driven protein design different from other methods?
Q: How to implement Zebra in experimental research?
Q: What do I need to run Zebra?
Q: What is a JobID?
Q: What do I get from Zebra?
Q: How can I cite Zebra?
Contacts
Update history

Q: Does Zebra server support HTTPS connection?
A: Yes, since February 7th 2017 this site supports HTTPS. Switch to https now to encrypt your connection.

Q: What is Zebra?
A: Zebra is a bioinformatic algorithm to systematically study diverse protein superfamilies and identify the subfamily-specific positions (SSPs) – conserved only within protein subfamilies, but different between subfamilies – that seem to be responsible for functional diversity (different substrate specificity, catalytic activity, stability, etc.).

Q: What makes Zebra different?
A: A new scoring function is implemented that takes into account structural information as well as physicochemical conservation of functional subfamilies. Zebra is the first application that provides specificity determinants at different levels of functional classification, therefore addressing complex functional diversity of large superfamilies. Statistical analysis is implemented to automatically select a set of highly significant subfamily-specific positions for further evaluation.

Q: Why are the subfamily-specific positions (SSPs) important?
A: Proteins within a single family share a common function but differ in more specific properties and can be divided into subfamilies with different specificity, enantioselectivity, stability, etc. Completely conserved positions can define general properties of the entire family (for example, have direct roles in enzyme catalytic machinery) but do not explain functional diversity. On the opposite the subfamily-specific positions (SSPs) – conserved only within protein subfamilies, but different between subfamilies – seem to be responsible for functional diversity.

Q: Why to identify the SSPs?
A: SSPs can contribute to a better understanding of enzyme evolution and structure-function relationship. Why do similar active sites in homologous enzymes perform different chemical transformations? How can we study the structure-function relationship and predict structural changes that lead to functional diversity? These are the fundamental questions to anwser by using the subfamily-specific positions.

Q: Can SSPs have practical application?
A: From the practical point of view, we would like to know how to enhance functional properties of existing enzymes. SSPs can be used as hotspots for directed evolution or rational design experiments to change protein function and create novel biocatalysts.

Q: What makes the bioinformatic analysis driven protein design different from other methods?
A: The Stochastic techniques, such as Directed evolution, remain resource demanding and inefficient because of high frequency of deleterious mutations and low frequency of functionally beneficial phenotypes. On the other hand, empirical rational design strategies rely on visual expert inspection of sequence or structural information and greatly depend on a qualification of a particular researcher. In both cases the problem is that the hotspot selection is very subjective and the whole process is hardly reproducible. Contrary, Zebra bioinformatic analysis provides reproducible and experimentally testable hypotheses for further evaluation. It is a systematic and reproducible approach to study structure-function relationship in enzymes and to design their functional properties.

Q: How to implement Zebra in the experimental research?
A:

  • Bioinformatic analysis was used to study how lipase and amidase catalytic activities are implemented into the same structural framework. Candida antarctica lipase B mutants have been produced with significant increase of experimentally measured amidase activity.

    Suplatov D.A., Besenmatter W., Švedas, V.K., Svendsen, A. (2012). Bioinformatic analysis of alpha/beta-hydrolase fold enzymes reveals subfamily-specific positions responsible for discrimination of amidase and lipase activities. Protein Eng.Des.Sel., 25(11), 689-697. DOI:10.1093/protein/gzs068 PMID:23043134

  • Zebra has been applied to study the molecular mechanisms of alkaline adaptation of the Ntn-hydrolase superfamily enzymes. The proposed penicillin acylase mutant has been produced experimentally and showed significant increase in stability under alkaline conditions without sacrificing the catalytic functions.

    Suplatov D, Panin N, Kirilin E, Shcherbakova T, Kudryavtsev P, Švedas V. (2014) Computational Design of a pH Stable Enzyme: Understanding Molecular Mechanism of Penicillin Acylase's Adaptation to Alkaline Conditions. PLoS ONE 9(6): e100643. DOI:10.1371/journal.pone.0100643 PMID:24959852

Q: What do I need to run Zebra?
A: A multiple sequence alignment and, optionally, structural information about the protein superfamily. Zebra does not mandatorily require information about the three-dimensional protein structure but can largely benefit when it is available. Algorithm does not require predefined subfamily classification and can propose it automatically.

Q: What is a JobID?
A: Zebra algorithm will be applied to your input data and your results will be placed in a public directory protected by a unique 14-symbol access code (JobID). JobID can be shared with a colleague and used to access your results at any time. You can always delete your results from the public directory by pressing the "Delete Zebra Results" button at the top of the results page or by sending us an e-mail request containing the JobID.

Q: What do I get from Zebra?
A: Zebra generates a list of statistically significant subfamily-specific positions that are supposed to be responsible for functional diversity at different levels of functional classification. These positions can be used as hotspots for directed evolution or rational design experiments and analyzed studying the structure-function relationship. In other words, Zebra bioinformatic analysis provides reproducible and experimentally testable hypotheses for further evaluation.

Q: How can I cite Zebra?
A: Please cite

(1) Suplatov D., Shalaeva D., Kirilin E., Arzhanik V., Švedas V. (2014). Bioinformatic analysis of protein families for identification of variable amino acid residues responsible for functional diversity. J.Biomol.Struct.Dyn. 32(1):75-87.

(2) Suplatov D., Kirilin E., Takhaveev V., Švedas V. (2014). Zebra: web-server for bioinformatic analysis of diverse protein families, J.Biomol.Struct.Dyn., 32(11):1752-1758

Q: Still have a question?
A: Don`t hesitate to contact us.
Contact:

Dmitry Suplatov




Update history
2014/Jan/15: Implemented validation of input data to help you meet the prerequisites. Minor bugs fixed.
2013/June/27: Delete button has been implemented to safely remove your results from the server for submissions starting from today.
2013/June/13: Minor bugs in data preprocessing fixed.
2013/May/01:Automatic preprocessing of structural data has been implemented. Submit a multiple sequence alignment and a PDB file representing one of the sequences (at least 95% pairwise identity) in QuickZebra+3D or Manual mode. The alignment and the PDB file will be superimposed automatically.

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