Gürol M. Süel, Steve W. Lockless, Mark A. Wall, and Rama Ra

Transcription

1 Gürol M. Süel, Steve W. Lockless, Mark A. Wall, and Rama Ranganathan, Evolutionarily conserved networks of residues mediate allosteric communication in proteins, Nature Structural Biology, vol. 10, no. 1, pp , BBSI 2008 Journal Club Presentation Department of Computational Biology, University of Pittsburgh July 17, 2008

2 Outline Communication Networks in Proteins Statistical Identification of Communication Networks Perturbation of Multiple Sequence Alignment (MSA) Clustering analysis of MSA Perturbations Analysis of GPCR Family MSA Perturbations Analysis of Chymotrypsin-like Serine Protease Family MSA Perturbations Analysis of Hemoglobin Family MSA Perturbations

3 Communication Networks in Proteins Transmission of signals initiated at one functional site to a distinct surface mediating downstream signaling Conformational changes in protein upon ligand binding in GPCRs

4 Statistical Identification of Communication Networks in a family of protein Multiple Sequence Alignment large enough to represent statistical properties of protein family If residues at particular site l is functionally not important then aminoacid frequencies is unconstrained and approaches to their mean in all proteins If residues at i and j are functionally coupled, the distributions of aminoacids at these indices should co-vary Perturbing one of these residues affects distribution of these residues Computational perturbation of residues in MSA For any aminoacid x, i.e., x Ala, Cys,..., Tyr: Gj x = kt log(pj x /PMSA) x ( Statistical Energy ) G x j i = Gj x G x j i ( Coupling Energy )

5 Computational perturbation of residues in GPCR Family MSA : Perturbation of Rhodopsin at Tyr296 a b c d e f Frequency Pos19 Pos125 Pos305 A CD E F GH I K LM NP QR S T VWY Amino acid g G stat (kt*) 5 Tyr Position

6 Clustering analysis of MSA Perturbations 1. Apply the statistical perturbation on N pert different sites j in MSA which is N msa long (N pert N msa ) 2. Determine Gj stat = Gj Ala, G Cys j,, G Tyr j 3. Plot Gj stat on columns, i.e., have 4. Cluster columns Arrange the perturbations which have similar perturbation profile together 5. Cluster rows Arrange the MSA sites which have similar perturbation values together 6. Iterative Focusing on high Gj stat for covariation of residues

7 Clustering analysis of MSA Perturbations Cluster Gj stat vs. Site index for each perturbation of MSA Determine the clusters of MSA sites which have most similar perturbation profile and perturbation values 1 2 N pert 1 2 N pert N pert 1 CLUSTER (rows and columns) N MSA N MSA N MSA N MSA N MSA N MSA N MSA

8 Clustering analysis of G-Protein Coupled Receptor(GPCR) Family MSA Perturbations Membrane proteins responsible for high variety of cellular signaling MSA containing 940 sequences in class A GPCR family Perturbations at 107 different sites

9 Clustering analysis of GPCR Family MSA Perturbations a b c N C 317F 123A 219M 157I 92P 268F 296Y 254L 144Y 78S

10 Clustering analysis of GPCR Family MSA Perturbations a b W265 K296 F Y268 F212 I213 6 b c c F91 2 T92 3 A164 4 E I259 M257 N302 6 V N78 I123 F261 I E122 P170 V129 L125 d 8 d M317 7 M253 6 C222 V254 Y136, 8 T I75 V S144

11 Clustering analysis of Chymotrypsin-like serine protease Family MSA Perturbations Serine proteases: Enzymes that cut peptide bonds in proteins The interaction on a deep pocket, named S1, with P1 residue on substrate is vital MSA containing 616 sequences in chymotrypsin family Perturbations at 69 different sites

12 Clustering analysis of Chymotrypsin-like serine protease Family MSA Perturbations a b c N A A d 17V 40H 30Q 51W 180M 31V 152P 187G 209L 189D 215W 228Y 226G A C 124P 47I 118V 229T 212I 46L 26S 67L 92P 203G 136C 81Q 201C 201

13 Clustering analysis of Chymotrypsin-like serine protease Family MSA Perturbations a b A221A C191 D189 Y172 W215 M180 G188A b T229 Q210 C157 C136 C22 C201 P124 S195 H57 D102 c L46 c D71 Q81 W51 L105 M104

14 Clustering analysis of Hemoglobin Family MSA Perturbations Hemoglobin: High oxygen binding capability Tetramer of two α and β subunits Two stable conformations 1. Low oxygen affinity (T-state) 2. High oxygen affinity (R-state) Binding of an oxygen to any subunit in T-state causes conformational change in other subunits into R-state MSA containing 880 sequences in Hemoglobin Family Perturbations at 32 different sites

15 Clustering analysis of Hemoglobin Family MSA Perturbations a b c N A B C E F 84S 94D 136L 95P 101L 74D 97N 91L 28A 110A 51G 93V 98F 55V 100L 132V 118T 86L 61K 119P 7K 123A G H C

16 Clustering analysis of Hemoglobin Family MSA Perturbations a b c β1 B E D C F C E α2 B b β1 K66 F E D V54 L91 L96 V98 C C L91 V93 F S49 E L86 B K61 α2 A α1 H G H F G β2 A c F103 β1 L106 E B N102 F V98 P100 D99 C P95 D94 F98 C N97 G F L136 E B A H112 α2

17 Identification of networks of functional residues in proteins Functional networks or networks of structural cores?

18 Thanks for listening! Questions?