1. Structural Immunoinformatics – two case studies M. Atanasova, I. Dimitrov, A. Patronov, I. Doytchinova Medical University of SofiaFaculty of Pharmacy Regional Conference in Supercomputing Applications in Science and Industry, 20-21 Sept. 2011, Sunny Beach, Bulgaria

2. Medical University of SofiaFaculty of Pharmacy Immunoinformastic Approaches: Sequence - based Structure - based peptide pIC50exp ILDPFPVTV8.654 ALDPFPPTV8.170 VLDPFPITV8.139....................... FLDPFPATV8.270 Affinity = f (Chemical Structure) Motif-based, QMs, ANN, SVM Affinity = f (Interaction energy) Molecular docking Molecular dynamics Immunoinformatics (Computational Immunology, Theoretical Immunology)

3. Medical University of SofiaFaculty of Pharmacy Case study 1: T-cell epitope prediction of proteins from Boophilus microplus Boophilus microplus tick. Ticks are hematophagous parasites that feed on variety of domestic animals. B. microplus tick: a hard tick; transmits lethal pathogens; causes disease and death. Collaborator: University of Pretoria, SA Aim: to predict peptides originating from B. microplus and binding with high affinity to murine MHC class II proteins IAd and IEd.

4. Medical University of SofiaFaculty of Pharmacy Case study 1: T-cell epitope prediction of proteins from Boophilus microplus Approaches used Sequence - based Structure - based MHCPred and RANKPEP servers for MHC class II binding prediction Molecular docking calculations

5. Medical University of SofiaFaculty of Pharmacy Case study 1: T-cell epitope prediction of proteins from Boophilus microplus Selection of high immunogenic B. microplus proteins by VaxiJen server. Presentation of the selected proteins as sets of overlapping peptides. 1. 2. B. Microplus number Protein peptides Contig282859 Contig742093 CK18162461 Selection of input X-ray structures of complexes of murine MHC II protein with a peptide. Ova/IAd (pdb code: 2iad) HB/IEk (pdb code:1iea) Homology modeling of IEk to IEd structure 3. Optimization of complexes of each peptide with each MHC II protein. Docking calculations biding site - 6Å; Chemscore – scoring function; fixed protein and peptide backbone; ranking – by score; GOLD v.5.0.2. Workflow:

6. Medical University of SofiaFaculty of Pharmacy Case study 1: T-cell epitope prediction of proteins from Boophilus microplus Binding affinity prediction to IAd by MHCPred and RANKPEP MHCPred: Predicted binders with IC50 < 50 nM are highlighted in green. RANKPEP: Predicted binders with binding threshold: 7.10 are highlighted in purple.

7. Medical University of SofiaFaculty of Pharmacy Case study 1: T-cell epitope prediction of proteins from Boophilus microplus Binding affinity prediction to IAd and IEd by Molecular docking IAdIEd The top 2 best clusters of binders are highlighted in magenta.

8. Medical University of SofiaFaculty of Pharmacy Case study 1: T-cell epitope prediction of proteins from Boophilus microplus Peptides selected for further experimental studies

9. Medical University of SofiaFaculty of Pharmacy Case study 2: Prediction of peptide binding to Swine Leukocyte Antigen (SLA-1) Aim: to generate quatitative matrices (QMs) for prediction of peptides binding to SLA-1 Intestinal Diarrhea Respiratory Coughing Sore Throat Physchological Lethargy Lack of appetite Swine influenza symptoms Nasopharynx Sneezing Mucous: nose/eyes Systemic Fever Weight loss Poor growth Swine Influenza in pigs: - An acute respiratory disease; - High morbidity depending on the immune status; - Can results in important economic losses. CReSA Centre de Recerca en Sanitat Animal

10. Modeled proteins: SLA-1*0101 SLA-1*0401 SLA-1*0501 SLA-1*1101 7 anchor positions X 19 aa = 133 + 1 original ligand = 134 peptides biding site - 6Å; Chemscore – scoring function; fixed protein and ligand apart from the residues from the tested peptide position; ranking – by lowest RMS; GOLD v.5.0.2. normalization of the binding energies and compilation into QMs. P1 P2 P3 P5 P6 P7 P9 Medical University of SofiaFaculty of Pharmacy Workflow: 1.Homology modeling of SLA-1 from HLA*0201 (pdb:3pwj). 2. Construction of combinatorial library of peptides. 3. Molecular docking of peptides to SLA proteins. 4. Forming of docking score-based QMs (DS-QMs). Case study 2: Prediction of peptide binding to Swine Leukocyte Antigen (SLA-1)

11. Medical University of SofiaFaculty of Pharmacy Workflow: 1.Homology modeling of SLA-1 from HLA*0201 (pdb:3pwj). 2. Construction of combinatorial library of peptides. 3. Molecular docking of peptides to SLA proteins. 4. Forming of docking score-based QMs (DS-QMs). Case study 2: Prediction of peptide binding to Swine Leukocyte Antigen (SLA-1) Combinatorial library peptide avr score normalized PKYVKQNTLKLAT - 71.47 + 0.456 PKXVKQNTLKLAT - 63.72 - 0.123 PKYXKQNTLKLAT … … PKYVKXNTLKLAT … … PKYVKQNXLKLAT … … PKYVKQNTXKLAT … … PKYVKQNTLKXAT … … PKYVKQNTLKLXT … … aa\pocket 1 2 3 5 6 7 9 A … … … … … … … C … … … … … … … D … … … … … … … E … … … … … … … … … … … … … … … QM

12. 0101 – Asn 0101 - Leu 0501 - Trp Medical University of SofiaFaculty of Pharmacy Case study 2: Prediction of peptide binding to Swine Leukocyte Antigen (SLA-1) SLA allelePocket 2 profileP2 accepts 0101 Tyr 9, Ala 24, Val 34, Met 45, Glu 63, Lys 66, Gln 67 Leu, Met, Asn 0501 Ser 9, Ala 24, Val 34, Met 45, Glu 63, Lys 66, Gln 67 Trp, Leu, Phe 0401 Tyr 9, Ala 24, Val 34, Met 45, Glu 63, Asn 66, Val 67 Leu, Met, Thr 1101 Ser 9, Glu 24, Val 34, Met 45, Glu 63, Arg 66, Val 67 Leu, Met, Ile

13. 0401 - Met 1101 - Met Medical University of SofiaFaculty of Pharmacy Case study 2: Prediction of peptide binding to Swine Leukocyte Antigen (SLA-1) SLA allelePocket 2 profileP2 accepts 0101 Tyr 9, Ala 24, Val 34, Met 45, Glu 63, Lys 66, Gln 67 Leu, Met, Asn 0501 Ser 9, Ala 24, Val 34, Met 45, Glu 63, Lys 66, Gln 67 Trp, Leu, Phe 0401 Tyr 9, Ala 24, Val 34, Met 45, Glu 63, Asn 66, Val 67 Leu, Met, Thr 1101 Ser 9, Glu 24, Val 34, Met 45, Glu 63, Arg 66, Val 67 Leu, Met, Ile

14. Medical University of SofiaFaculty of Pharmacy Case study 2: Prediction of peptide binding to Swine Leukocyte Antigen (SLA-1) SIV proteins screened to predict SLA binders: - hemagglutinin (HA) - nucleocapsid protein (NP) - matrix protein 1 (M1) - polymerase PB1 (PB1)

15. Thank you for your attention!