Dataset Information

Energetic determinants of protein binding specificity: insights into protein interaction networks.

ABSTRACT: One of the challenges of the postgenomic era is to provide a more realistic representation of cellular processes by combining a systems biology description of functional networks with information on their interacting components. Here we carried out a systematic large-scale computational study on a structural protein-protein interaction network dataset in order to dissect thermodynamic characteristics of binding determining the interplay between protein affinity and specificity. As expected, interactions involving specific binding sites display higher affinities than those of promiscuous binding sites. Next, in order to investigate a possible role of modular distribution of hot spots in binding specificity, we divided binding sites into modules previously shown to be energetically independent. In general, hot spots that interact with different partners are located in different modules. We further observed that common hot spots tend to interact with partners exhibiting common binding motifs, whereas different hot spots tend to interact with partners with different motifs. Thus, energetic properties of binding sites provide insights into the way proteins modulate interactions with different partners. Knowledge of those factors playing a role in protein specificity is important for understanding how proteins acquire additional partners during evolution. It should also be useful in drug design.

SUBMITTER: Carbonell P

PROVIDER: S-EPMC7299235 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Energetic determinants of protein binding specificity: insights into protein interaction networks.

Carbonell Pablo P Nussinov Ruth R del Sol Antonio A

Proteomics 20090401 7

One of the challenges of the postgenomic era is to provide a more realistic representation of cellular processes by combining a systems biology description of functional networks with information on their interacting components. Here we carried out a systematic large-scale computational study on a structural protein-protein interaction network dataset in order to dissect thermodynamic characteristics of binding determining the interplay between protein affinity and specificity. As expected, inte ...[more]

PMID: 19253304

Similar Datasets

Project description:BACKGROUND: Improving our understanding of processes at the core of cellular lifestyles can be aided by combining information from genetic analyses, high-throughput experiments and computational predictions. RESULTS: We combined data and predictions derived from phenotypic, physiological, genetic and computational analyses to dissect the metabolic and energetic networks of the facultative photosynthetic bacterium Rhodobacter sphaeroides. We focused our analysis on pathways crucial to the production and recycling of pyridine nucleotides during aerobic respiratory and anaerobic photosynthetic growth in the presence of an organic electron donor. In particular, we assessed the requirement for NADH/NADPH transhydrogenase enzyme, PntAB during respiratory and photosynthetic growth. Using high-throughput phenotype microarrays (PMs), we found that PntAB is essential for photosynthetic growth in the presence of many organic electron donors, particularly those predicted to require its activity to produce NADPH. Utilizing the genome-scale metabolic model iRsp1095, we predicted alternative routes of NADPH synthesis and used gene expression analyses to show that transcripts from a subset of the corresponding genes were conditionally increased in a ?pntAB mutant. We then used a combination of metabolic flux predictions and mutational analysis to identify flux redistribution patterns utilized in the ?pntAB mutant to compensate for the loss of this enzyme. Data generated from metabolic and phenotypic analyses of wild type and mutant cells were used to develop iRsp1140, an expanded genome-scale metabolic reconstruction for R. sphaeroides with improved ability to analyze and predict pathways associated with photosynthesis and other metabolic processes. CONCLUSIONS: These analyses increased our understanding of key aspects of the photosynthetic lifestyle, highlighting the added importance of NADPH production under these conditions. It also led to a significant improvement in the predictive capabilities of a metabolic model for the different energetic lifestyles of a facultative organism.

Dataset Information

Energetic determinants of protein binding specificity: insights into protein interaction networks.

Publications

Energetic determinants of protein binding specificity: insights into protein interaction networks.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure