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Designing therapeutic peptides and proteins using Open source Software

Designing therapeutic peptides and proteins using Open source Software. Dr G P S Raghava, Head Bioinformatics Centre. Institute of Microbial Technology, Chandigarh, India. Email: raghava@imtech.res.in http://crdd.osdd.net/ http://ww.imtech.res.in/raghava/.

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Designing therapeutic peptides and proteins using Open source Software

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  1. Designing therapeutic peptides and proteins using Open source Software Dr G P S Raghava, Head Bioinformatics Centre Institute of Microbial Technology, Chandigarh, India Email: raghava@imtech.res.inhttp://crdd.osdd.net/ http://ww.imtech.res.in/raghava/

  2. Drug/inhibitor/vaccine/ Disease Diagnostics Peptide-Protein Interaction Peptide Structure, docked structure Adaptive Immunity: B-cell, T-cell Epitope Innate Immunity: Toll-like receptors Anti-(bacterial , microbial, cancer, viral) peptides Mimotopes for diseases diagnostics Structure determination: Natural, non-natural , modified bonds Structure prediction: Natural, non-natural , modified bonds Peptide/ Proteins Synthesis: Phase display, SPSS, Codon Suffeling Natural bioactive peptides from metagenomics Mimotopes for B/T epitopes Mimicking of Drug Molecules Size Optimization for function/Str. ADMET: Proteolytic enzymes, Half-life Oral Delivery : Trans. & Adjuvant

  3. Peptide Bioinformatics Therapeutic Application of Peptides Limitation of Peptides & Challenge for Bioinformaticians Peptide Web Servers Peptide Databases Application of peptides in treating cancer

  4. Therapeutic Application of Biomolecules • Peptide based Drugs (Small Molecule, Peptide, Protein) • Anticancer peptides • Antibacterial peptides • Peptide for delivering drug • Cell-penetrating peptides • Tumor-homing peptides • Peptide as disease diagnostics • Disease specific Mimotopes • Epitope/Peptide based Vaccines • T-cell epitopes • B-cell epitopes

  5. Limitation of Peptides & Challenges for Bioinformaticians • Peptide Degradation (short half-life) • Large peptide degrading enzymes • Hepatic/renal Clearance (liver/kidenys) • Low Oral Bioavailability (injection) • High conformational flexibility • Environment dependent tertiary structure • Low selectivity • Immunogenicity and antigenicity • High cost of production & Storage • Modification/glycosylation of peptides

  6. Important Resources/Databases MHCBN: MHC binding and non-binding peptides CPPsite: Cell penetrating peptides BCIpep: B-cell epitope datbase HMRbase: A database of hormones and their receptors TumorHope: Tumor hoping peptides TumorHPD: Designing of Tumor Homing Peptides CellPPD: Designing of cell penetrating peptides Pepstr: Prediction of Peptide structure AntiCP: Prediction and designing of anticancer peptides

  7. Adaptive Immunity Protective Antigens Vaccine Informatics Bioinformatics Centre Disease Causing Agents Innate Immunity IMTECH, Chandigarh Vaccine Delivery Pathogens/Invaders

  8. Adaptive Immunity Protective Antigens Vaccine Informatics Bioinformatics Centre Innate Immunity IMTECH, Chandigarh Vaccine Delivery Purified Antigen WHOLE ORGANISM Epitopes (Subunit Vaccine) T cell epitope Attenuated

  9. Adaptive Immunity Protective Antigens Vaccine Informatics Bioinformatics Centre Innate Immunity IMTECH, Chandigarh Vaccine Delivery Endogenous Antigen Processing ER TAP Prediction of CTL Epitopes (Cell-mediated immunity)

  10. Adaptive Immunity Protective Antigens Vaccine Informatics Bioinformatics Centre Innate Immunity IMTECH, Chandigarh Vaccine Delivery Prediction of B-Cell Epitopes • BCEpred: Prediction of Continuous B-cell epitopes • Benchmarking of existing methods • Poor performance slightly better than random • Combine all properties and achieve accuracy around 58% • Saha and Raghava (2004) ICARIS 197-204. • ABCpred: ANN based method for B-cell epitope prediction • Extract all epitopes from BCIPEP (around 2400) • 700 non-redundant epitopes used for testing and training • Recurrent neural network • Accuracy 66% achieved • Saha and Raghava (2006) Proteins,65:40-48 • ALGpred: Mapping and Prediction of Allergenic Epitopes • Allergenic proteins • IgE epitope and mapping • Saha and Raghava (2006) Nucleic Acids Research 34:W202-W209 • CBTOPE: Prediction of conformational epitopes

  11. Modelling of Immune System for Designing Epitope-based Vaccines Adaptive Immunity (Cellular Response) : Thelper Epitopes Propred: for promiscuous MHC II binders MMBpred:for high affinity mutated binders MHC2pred: SVM based method MHCBN: A database of MHC/TAP binders and non-binders Pcleavage: for proteome cleavage sites TAPpred: for predicting TAP binders Propred1: for promiscuous MHC I binders CTLpred: Prediction of CTL epitopes Adaptive Immunity (Cellular Response) : CTL Epitopes BCIpep: A database of B-cell eptioes; ABCpred: for predicting B-cell epitopes ALGpred: for allergens and IgE eptopes HaptenDB: A datbase of haptens Adaptive Immunity (Humoral Response) :B-cell Epitopes Innate Immunity : Pathogen Recognizing Receptors and ligands PRRDB: A database of PRRs & ligands Antibp: for anti-bacterial peptides Signal transduction in Immune System Cytopred: for classification of Cytokines

  12. Peptide structure prediction • 3D structures of 77 biologically active peptides (9-20 residues)

  13. Peptide structure prediction Averaged backbone root mean deviation before and after energy minimization and dynamics simulations.

  14. Peptide Web Servers

  15. Peptide Web Servers

  16. Designing of antibacterial stable peptides Scanning of peptides in a protein Submition of multiple peptides

  17. Peptide Resources/Databases

  18. Peptide Web Servers

  19. Designing of therapeutic peptides against cancer Anticancer peptides Designing of effective anticancer peptides Peptide inhibitors Identification of inhibitors against cancer targets Cell Penetrating Peptides CPPsite: Database CellPred: Design ? Tumor Homing Peptides TumorHoPe: Database TumorHPD: Design Peptides Half-life HLP: prediction in intestine Depend on environment Toxicity of Peptides Immuno-, cyto-toxicity Off targets

  20. Peptide Resources/Databases

  21. Peptide Resources/Databases Work in Progress 1. Prediction of CPP 2. Designing CPP 3. Scanning in proteins

  22. Thankyou

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