This document contains an agenda for bioinformatics lessons covering various topics like biological databases, sequence similarity, sequence alignments, database searching, phylogenetics, protein structure, gene prediction, and bioinformatics applications in drug discovery. It also discusses ongoing bioinformatics research projects and ambitions to publish peer-reviewed work. Finally, it provides background on protein structure, levels of protein structure from primary to tertiary, and experimental methods like X-ray crystallography used to determine protein structures.

2. FBW 1-12-2011 Wim Van Criekinge

8. Rationale for understanding protein structure and function Protein sequence -large numbers of sequences, including whole genomes Protein function - rational drug design and treatment of disease - protein and genetic engineering - build networks to model cellular pathways - study organismal function and evolution ? structure determination structure prediction homology rational mutagenesis biochemical analysis model studies Protein structure - three dimensional - complicated - mediates function

10. MIS-SENSE MUTATION e.g. Sickle Cell Anaemia Cause : defective haemoglobin due to mutation in β-globin gene Symptoms : severe anaemia and death in homozygote

24. Backbone Torsion Angles

25. Backbone Torsion Angles

27. Ramachandran / Phi-Psi Plot

28. The alpha-helix

30. Beta-sheets

31. Topologies of Beta-sheets

32. Secondary structure prediction ?

36. Preference parameters Secondary structure prediction:CHOU-FASMAN Residue P(a) P(b) P(t) f(i) f(i+1) f(i+2) f(i+3) Ala 1.45 0.97 0.57 0.049 0.049 0.034 0.029 Arg 0.79 0.90 1.00 0.051 0.127 0.025 0.101 Asn 0.73 0.65 1.68 0.101 0.086 0.216 0.065 Asp 0.98 0.80 1.26 0.137 0.088 0.069 0.059 Cys 0.77 1.30 1.17 0.089 0.022 0.111 0.089 Gln 1.17 1.23 0.56 0.050 0.089 0.030 0.089 Glu 1.53 0.26 0.44 0.011 0.032 0.053 0.021 Gly 0.53 0.81 1.68 0.104 0.090 0.158 0.113 His 1.24 0.71 0.69 0.083 0.050 0.033 0.033 Ile 1.00 1.60 0.58 0.068 0.034 0.017 0.051 Leu 1.34 1.22 0.53 0.038 0.019 0.032 0.051 Lys 1.07 0.74 1.01 0.060 0.080 0.067 0.073 Met 1.20 1.67 0.67 0.070 0.070 0.036 0.070 Phe 1.12 1.28 0.71 0.031 0.047 0.063 0.063 Pro 0.59 0.62 1.54 0.074 0.272 0.012 0.062 Ser 0.79 0.72 1.56 0.100 0.095 0.095 0.104 Thr 0.82 1.20 1.00 0.062 0.093 0.056 0.068 Trp 1.14 1.19 1.11 0.045 0.000 0.045 0.205 Tyr 0.61 1.29 1.25 0.136 0.025 0.110 0.102 Val 1.14 1.65 0.30 0.023 0.029 0.011 0.029

44. Domains

45. Protein Architecture

48. Protein Architecture

49. Levels of protein structure: Topology

50. Hydrophobicity Plot P53_HUMAN (P04637) human cellular tumor antigen p53 Kyte-Doolittle hydrophilicty, window=19

52. The ‘positive inside’ rule (EMBO J. 5:3021; EJB 174:671,205:1207; FEBS lett. 282:41) Bacterial IM In: 16% KR out: 4% KR Eukaryotic PM In: 17% KR out: 7% KR Thylakoid membrane In: 13% KR out: 5% KR Mitochondrial IM In: 10% KR out: 3% KR

55. GPCR Topology

57. GPCR Topology Eg. Plot conserverd residues (or multiple alignement: MSA to SSA)

63. PDB

64. PDB

65. PDB

66. PDB

67. Visualizing Structures Cn3D versie 4.0 (NCBI)

68. Ball: Van der Waals radius Stick: length joins center N, blue/O, red/S, yellow/C, gray (green) Visualizing Structures

69. From N to C Visualizing Structures

72. Modeling

79. **T112/dhso – 4.9 Å (348 residues; 24%) **T92/yeco – 5.6 Å (104 residues; 12%) **T128/sodm – 1.0 Å (198 residues; 50%) **T125/sp18 – 4.4 Å (137 residues; 24%) **T111/eno – 1.7 Å (430 residues; 51%) **T122/trpa – 2.9 Å (241 residues; 33%) Comparative modelling at CASP CASP4: overall model accuracy ranging from 1 Å to 6 Å for 50-10% sequence identity CASP2 fair ~ 75% ~ 1.0 Å ~ 3.0 Å CASP3 fair ~75% ~ 1.0 Å ~ 2.5 Å CASP4 fair ~75% ~ 1.0 Å ~ 2.0 Å CASP1 poor ~ 50% ~ 3.0 Å > 5.0 Å BC excellent ~ 80% 1.0 Å 2.0 Å alignment side chain short loops longer loops

81. Protein Engineering / Protein Design