Snake Venom PLA2: Bioinformatics Approach

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Snake Venom PLA2Bioinformatics Approach
Md. Asif Khan
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Outline

• Overview
• Challenges
• Database
• Pharmacological properties
• Structure-Function classification
• Hydropathy profiles
• Conclusion

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Snakes

• Why snake toxins?
• 100 million years
• 1300 living species of snakes
• Glands ? Toxins ? Key role in various biological
  processes
• Natural library 200,000 different toxins
• Known gt 1
• Attractive candidates for
• drugs,
• therapeutics, and
• diagnostic agents.

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Snake Venom PLA2

• Why snake venom PLA2?
• Major snake toxin superfamilies
• Phospholipase A2 (svPLA2),
• Three finger neurotoxins
• Metalloproteinases.
• PLA2s pharmacologically versatile
• Neurotoxicity,
• Myotoxicity and
• Anticoagulant effects

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svPLA2s

• Dual functions
• prey digestion
• potent toxins.
• Structurally similar but display differences in
  toxicity.
• Important tool in
• physiological,
• biochemical and
• pharmacological studies

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Challenges

• Exponential growth of sequences
• Toxicity test?
• Data scattered across
• multiple sources
• A need to
• compile,
• organise and
• classify these data

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Aims

• i) svPLA2s database
• ii) structure-function classification.
• iii) analysis

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Database

• Facilitate information retrieval and data
  analysis
• http//sdmc.lit.org.sg/Templar/DB/snaketoxin_PLA2/
  index.html
• Special features
• i) 3-D structure viewer feature and
• ii) functional annotation of entries.

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Data retrieval

• Keyword and sequence search
• 45 unique entries and 55 redundant.
• November 2002- 289 unique entries in database

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Pharmacological properties

• Enriched entries
• 150 svPLA2s - pharmacologically uncharacterised
• 139-reasonably characterised
• Multiple effect

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Structure-Function Classification

• Correlating functional properties to structural
  information
• Structure-function comparison ? putative
  functional sites and motifs
• Prediction modules
• Structure-function correlation investigated
• Pharmacological properties,
• Disulfide bridge patterns and
• Evolutionary relationship.

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Classification Tree

• Structural and functional information
• Tree layers
• Orphan group

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Classification Tree

• Disulfide bridge patterns evolutionary
  relationship ? not included
• 249 toxin sequences (excluding fragment
  sequences)
• Detailed structure-function classification

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Hydropathy Profiles

• Residues between
• 80-110 of neurotoxic svPLA2s ? binding to
  presynaptic membrane
• 61 neurotoxic and 228 non-neurotoxic in the
  database larger sample size
• Only monomeric toxins

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Conclusion

• Foundation for a more detailed and more
  systematic study of structure-function
  relationship of svPLA2s.
• Prediction modules.
• Exponential growth of data
• Bioinformatics analyses in the study of svPLA2s.

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Pharmacological properties

• Multiple effects group- 23 entries
• Different multiple effects? separate groups
• Sequence Comparison

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Disulfide patterns

• CysAlign tool
• Seven unique disulfide patterns from 140 entries
• Classification?

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Disulfide patterns
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Phylogenetic analysis

• Low bootstrap values
• Evolutionary relationship of svPLA2s
• Classification?