Enhancing the population of the encounter complex affects protein complex formation efficiency.

Optimal charge distribution is considered to be important for efficient formation of protein complexes. Electrostatic interactions guide encounter complex formation that precedes the formation of an active protein complex. However, disturbing the optimized distribution by introduction of extra charged patches on cytochrome c peroxidase does not lead to a reduction in productive encounters with its partner cytochrome c. To test whether a complex with a high population of encounter complex is more easily affected by suboptimal charge distribution, the interactions of cytochrome c mutant R13A with wild-type cytochrome c peroxidase and a variant with an additional negative patch were studied. The complex of the peroxidase and cytochrome c R13A was reported to have an encounter state population of 80%, compared to 30% for the wild-type cytochrome c. NMR analysis confirms the dynamic nature of the interaction and demonstrates that the mutant cytochrome c samples the introduced negative patch. Kinetic experiments show that productive complex formation is fivefold to sevenfold slower at moderate and high ionic strength values for cytochrome c R13A but the association rate is not affected by the additional negative patch on cytochrome c peroxidase, showing that the total charge on the protein surface can compensate for less optimal charge distribution. At low ionic strength (44 mm), the association with the mutant cytochrome c reaches the same high rates as found for wild-type cytochrome c, approaching the diffusion limit.

A Fast and Economical Sample Preparation Protocol for Interaction Proteomics Analysis.

A simple and fast immunoprecipitation (IP) protocol is designed with the sample preparation incorporated, applicable to both low and high throughput. This new protocol combines two procedures based on magnetic beads in 96-well plate format. Protein complexes are captured by antibodies and magnetic beads conjugated with protein A. Proteins are washed and on-bead digested by using Single-Pot solid-phase sample preparation (SP3). The whole IP-SP3 approach can be completed in one day, which is considerably faster compared to the classical approach. No major quantitative differences are found between SP3 and FASP (filter-aided sample preparation) or a longer incubation protocol. Taken together, the IP-SP3 protocol is a fast and economical approach easily applicable for large-scale protein interactome analysis.

In silico Structural characterization of podocin and assessment of nephrotic syndrome-associated podocin mutants.

Nephrotic syndrome (NS) is manifested by hyperproteinuria, hypoalbuminemia, and edema. NPHS2 that encodes podocin was found to have most mutations among the genes that are involved in the pathophysiology of NS. Podocin, an integral membrane protein belonging to stomatin family, is expressed exclusively in podocytes and is localized to slit-diaphragm (SD). Mutations in podocin are known to be associated with steroid-resistant NS and rapid progression to end-stage renal disease, thus signifying its role in maintaining SD integrity and podocyte function. The structural insights of podocin are not known, and the precise mechanism by which podocin contributes to the architecture of SD is yet to be elucidated. In this study, we deduced a model for human podocin, discussed the details of transmembrane localization and intrinsically unstructured regions, and provide an understanding of how podocin interacts with other SD components. Intraprotein interactions were assessed in wild-type podocin and in some of its mutants that are associated with idiopathic NS. Mutations in podocin alter the innate intraprotein interactions affecting the native structure of podocin and its ability to form critical complex with subpodocyte proteins. © 2016 IUBMB Life, 68(7):578-588, 2016.

Structural and functional assessment of APOBEC3G macromolecular complexes.

There are eleven members in the human APOBEC family of proteins that are evolutionarily related through their zinc-dependent cytidine deaminase domains. The human APOBEC gene clusters arose on chromosome 6 and 22 through gene duplication and divergence to where current day APOBEC proteins are functionally diverse and broadly expressed in tissues. APOBEC serve enzymatic and non enzymatic functions in cells. In both cases, formation of higher-order structures driven by APOBEC protein-protein interactions and binding to RNA and/or single stranded DNA are integral to their function. In some circumstances, these interactions are regulatory and modulate APOBEC activities. We are just beginning to understand how macromolecular interactions drive processes such as APOBEC subcellular compartmentalization, formation of holoenzyme complexes, gene targeting, foreign DNA restriction, anti-retroviral activity, formation of ribonucleoprotein particles and APOBEC degradation. Protein-protein and protein-nucleic acid cross-linking methods coupled with mass spectrometry, electrophoretic mobility shift assays, glycerol gradient sedimentation, fluorescence anisotropy and APOBEC deaminase assays are enabling mapping of interacting surfaces that are essential for these functions. The goal of this methods review is through example of our research on APOBEC3G, describe the application of cross-linking methods to characterize and quantify macromolecular interactions and their functional implications. Given the homology in structure and function, it is proposed that these methods will be generally applicable to the discovery process for other APOBEC and RNA and DNA editing and modifying proteins.

A survey of computational methods for protein complex prediction from protein interaction networks.

Complexes of physically interacting proteins are one of the fundamental functional units responsible for driving key biological mechanisms within the cell. Their identification is therefore necessary to understand not only complex formation but also the higher level organization of the cell. With the advent of "high-throughput" techniques in molecular biology, significant amount of physical interaction data has been cataloged from organisms such as yeast, which has in turn fueled computational approaches to systematically mine complexes from the network of physical interactions among proteins (PPI network). In this survey, we review, classify and evaluate some of the key computational methods developed till date for the identification of protein complexes from PPI networks. We present two insightful taxonomies that reflect how these methods have evolved over the years toward improving automated complex prediction. We also discuss some open challenges facing accurate reconstruction of complexes, the crucial ones being the presence of high proportion of errors and noise in current high-throughput datasets and some key aspects overlooked by current complex detection methods. We hope this review will not only help to condense the history of computational complex detection for easy reference but also provide valuable insights to drive further research in this area.

Functional assessment of TSC2 variants identified in individuals with tuberous sclerosis complex.

Tuberous sclerosis complex (TSC) is an autosomal dominant disorder caused by mutations in the TSC1 or TSC2 genes. The TSC1 and TSC2 gene products, TSC1 and TSC2, form a complex that inhibits the mammalian target of rapamycin (mTOR) complex 1 (TORC1). Here, we investigate the effects of 78 TSC2 variants identified in individuals suspected of TSC, on the function of the TSC1-TSC2 complex. According to our functional assessment, 40 variants disrupted the TSC1-TSC2-dependent inhibition of TORC1. We classified 34 of these as pathogenic, three as probably pathogenic and three as possibly pathogenic. In one case, a likely effect on splicing as well as an effect on function was noted. In 15 cases, our functional assessment did not agree with the predictions of the SIFT amino acid substitution analysis software. Our data support the notion that different, nonterminating TSC2 mutations can have distinct effects on TSC1-TSC2 function, and therefore, on TSC pathology.

Comparative evolutionary analysis of protein complexes in E. coli and yeast.

BACKGROUND: Proteins do not act in isolation; they frequently act together in protein complexes to carry out concerted cellular functions. The evolution of complexes is poorly understood, especially in organisms other than yeast, where little experimental data has been available. RESULTS: We generated accurate, high coverage datasets of protein complexes for E. coli and yeast in order to study differences in the evolution of complexes between these two species. We show that substantial differences exist in how complexes have evolved between these organisms. A previously proposed model of complex evolution identified complexes with cores of interacting homologues. We support findings of the relative importance of this mode of evolution in yeast, but find that it is much less common in E. coli. Additionally it is shown that those homologues which do cluster in complexes are involved in eukaryote-specific functions. Furthermore we identify correlated pairs of non-homologous domains which occur in multiple protein complexes. These were identified in both yeast and E. coli and we present evidence that these too may represent complex cores in yeast but not those of E. coli. CONCLUSIONS: Our results suggest that there are differences in the way protein complexes have evolved in E. coli and yeast. Whereas some yeast complexes have evolved by recruiting paralogues, this is not apparent in E. coli. Furthermore, such complexes are involved in eukaryotic-specific functions. This implies that the increase in gene family sizes seen in eukaryotes in part reflects multiple family members being used within complexes. However, in general, in both E. coli and yeast, homologous domains are used in different complexes.