TY  - JOUR
AU  - Fernandez-Ballester, G.
AU  - Beltrao, P.
AU  - Gonzalez, J. M.
AU  - Song, Y.-H.
AU  - Wilmanns, M.
AU  - Valencia, A.
AU  - Serrano, L.
AU  - DESY
TI  - Structure-based prediction of the Saccharomyces cerevisiae SH3-ligand interactions
JO  - Journal of molecular biology
VL  - 388
SN  - 0022-2836
CY  - Amsterdam [u.a.]
PB  - Elsevier
M1  - PHPPUBDB-12664
SP  - 902-916
PY  - 2009
N1  - © Elsevier Ltd.; Post referee fulltext in progress 2; Embargo 12 months from publication
AB  - A great challenge in the proteomics and structural genomics era is to discover protein structure and function, including the identification of biological partners. Experimental investigation is costly and time-consuming, making computational methods very attractive for predicting protein function. In this work, we used the existing structural information in the SH3 family to first extract all SH3 structural features important for binding and then used this information to select the right templates to homology model most of the Saccharomyces cerevisiae SH3 domains. Second, we classified, based on ligand orientation with respect to the SH3 domain, all SH3 peptide ligands into 29 conformations, of which 18 correspond to variants of canonical type I and type II conformations and 11 correspond to non-canonical conformations. Available SH3 templates were expanded by chimera construction to cover some sequence variability and loop conformations. Using the 29 ligand conformations and the homology models, we modelled all possible complexes. Using these complexes and in silico mutagenesis scanning, we constructed position-specific ligand binding matrices. Using these matrices, we determined which sequences will be favorable for every SH3 domain and then validated them with available experimental data. Our work also allowed us to identify key residues that determine loop conformation in SH3 domains, which could be used to model human SH3 domains and do target prediction. The success of this methodology opens the way for sequence-based, genome-wide prediction of protein-protein interactions given enough structural coverage.
KW  - Algorithms
KW  - Amino Acid Sequence
KW  - Computer Simulation
KW  - Humans
KW  - Ligands
KW  - Models, Molecular
KW  - Molecular Sequence Data
KW  - Peptides: chemistry
KW  - Peptides: metabolism
KW  - Protein Binding
KW  - Protein Conformation
KW  - Reproducibility of Results
KW  - Saccharomyces cerevisiae: chemistry
KW  - Saccharomyces cerevisiae: metabolism
KW  - Saccharomyces cerevisiae Proteins: chemistry
KW  - Saccharomyces cerevisiae Proteins: genetics
KW  - Saccharomyces cerevisiae Proteins: metabolism
KW  - Sequence Alignment
KW  - src Homology Domains
KW  - Ligands (NLM Chemicals)
KW  - Peptides (NLM Chemicals)
KW  - Saccharomyces cerevisiae Proteins (NLM Chemicals)
LB  - PUB:(DE-HGF)16
C6  - pmid:19324052
UR  - <Go to ISI:>//WOS:000266302500018
DO  - DOI:10.1016/j.jmb.2009.03.038
UR  - https://bib-pubdb1.desy.de/record/93926
ER  -