Proteins are the """"""""working horse"""""""" of the cell. Their roles span functions as diverse as being molecular machines and signaling. They carry out catalytic reactions, transport, form the viral capsids, traverse the membranes and form regulated channels, transmit the information from the DNA to RNA, making possible the synthesis of new proteins, and they are responsible for the degradation of the unnecessary proteins and nucleic acids. They are the vehicles of the immune response and are responsible for viral entry into the cell. Given their importance, considerable effort has been centered on the prediction of protein function. A prime way to predict protein function is through identification of binding partners. If the function of at least one of the components with which the protein interacts is known, that should facilitate assigning its function(s) and the pathway(s) in which it plays a role. This holds since the vast majority of their chores in the living cell involve protein-protein interactions. Proteins never function in isolation. Hence, through the intricate network of protein-protein interactions we can map cellular pathways, their interconnectivities and their dynamic regulation. Identification of protein-protein interactions is at the heart of functional genomics. Prediction of protein-protein interactions is crucial for drug discovery. Knowledge of the pathway, its topology, length, and dynamics may provide useful information for forecasting side effects. Yet, the goal of predicting protein-protein interaction is daunting. Some associations are obligatory, whereas others are continuously forming and dissociating. In principle, from the physical standpoint, any two proteins can interact. The question is under what conditions and at which strength. The principles of protein-protein interactions are general: The non-covalent interactions of two proteins are largely the outcome of the hydrophobic effect. The hydrophobic effect drives protein-protein interactions. In addition, hydrogen bonds and electrostatic interactions play important roles. Thus, many of the interactions observed in vitro are the outcome of experimental over-expression. This complicates the functional prediction. Energetic hot spots account for a significant portion of the total binding free energy and correlate with structurally conserved interface residues. We map experimentally determined hot spots and structurally conserved residues to investigate their geometrical organization. 'Unfilled pockets' are pockets that remain unfilled after protein-protein complexation, while 'complemented pockets' are pockets that disappear upon binding, representing tightly fit regions. We find that structurally conserved residues and energetic hot spots are strongly favored to be located in complemented pockets, and disfavored in unfilled pockets. For the three available protein-protein complexes with complemented pockets where both complex-members were alanine-scanned, 62% of all hot spots (DeltaDeltaG greater than 2 kcal/mol) are within these pockets, and 60% of the residues in the complemented pockets are hot spots. 93% of all """"""""redhot"""""""" residues (DeltaDeltaG greater than 4 kcal/mol) either protrude into or are located in complemented pockets. The occurrence of hot spots and conserved residues in complemented pockets highlights the role of local tight packing in protein associations, and rationalizes their energy contribution and conservation. Complemented pockets and their corresponding protruding residues emerge among the most important geometric features in protein-protein interactions. By screening the solvent, this organization shields backbone hydrogen bonds and charge-charge interactions. Complemented pockets often pre-exist binding. For 19 protein-protein complexes with complemented pockets whose unbound structures are also available, in 16 the pockets pre-exist in the unbound structures.

Agency
National Institute of Health (NIH)
Institute
Division of Basic Sciences - NCI (NCI)
Type
Intramural Research (Z01)
Project #
1Z01BC010441-04
Application #
7291812
Study Section
(CCRN)
Project Start
Project End
Budget Start
Budget End
Support Year
4
Fiscal Year
2005
Total Cost
Indirect Cost
Name
Basic Sciences
Department
Type
DUNS #
City
State
Country
United States
Zip Code
Nussinov, Ruth (2013) The spatial structure of cell signaling systems. Phys Biol 10:045004
Zanuy, David; Ballano, Gema; Jimenez, Ana I et al. (2009) Protein segments with conformationally restricted amino acids can control supramolecular organization at the nanoscale. J Chem Inf Model 49:1623-9
Pan, Yongping; Nussinov, Ruth (2008) p53-Induced DNA bending: the interplay between p53-DNA and p53-p53 interactions. J Phys Chem B 112:6716-24
Keskin, Ozlem; Nussinov, Ruth; Gursoy, Attila (2008) PRISM: protein-protein interaction prediction by structural matching. Methods Mol Biol 484:505-21
Liu, Jin; Pan, Yongping; Ma, Buyong et al. (2006) ""Similarity trap"" in protein-protein interactions could be carcinogenic: simulations of p53 core domain complexed with 53BP1 and BRCA1 BRCT domains. Structure 14:1811-21
Aleman, Carlos; Zanuy, David; Jimenez, Ana I et al. (2006) Concepts and schemes for the re-engineering of physical protein modules: generating nanodevices via targeted replacements with constrained amino acids. Phys Biol 3:S54-62
Zanuy, David; Nussinov, Ruth; Aleman, Carlos (2006) From peptide-based material science to protein fibrils: discipline convergence in nanobiology. Phys Biol 3:S80-90
Haspel, Nurit; Zanuy, David; Aleman, Carlos et al. (2006) De novo tubular nanostructure design based on self-assembly of beta-helical protein motifs. Structure 14:1137-48
Tsai, Hui-Hsu Gavin; Gunasekaran, Kannan; Nussinov, Ruth (2006) Sequence and structure analysis of parallel beta helices: implication for constructing amyloid structural models. Structure 14:1059-72
Tsai, Chung-Jung; Zheng, Jie; Nussinov, Ruth (2006) Designing a nanotube using naturally occurring protein building blocks. PLoS Comput Biol 2:e42

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