Allowance for thermodynamic nonideality in the characterization of protein interactions by spectral techniques

2011 ◽  
Vol 158 (1) ◽  
pp. 21-25 ◽  
Author(s):  
Peter R. Wills ◽  
Donald J. Winzor
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Morten E. Pedersen ◽  
Ragna M. S. Haegebaert ◽  
Jesper Østergaard ◽  
Henrik Jensen

AbstractThe understanding and characterization of protein interactions is crucial for elucidation of complicated biomolecular processes as well as for the development of new biopharmaceutical therapies. Often, protein interactions involve multiple binding, avidity, oligomerization, and are dependent on the local environment. Current analytical methodologies are unable to provide a detailed mechanistic characterization considering all these parameters, since they often rely on surface immobilization, cannot measure under biorelevant conditions, or do not feature a structurally-related readout for indicating formation of multiple bound species. In this work, we report the use of flow induced dispersion analysis (FIDA) for in-solution characterization of complex protein interactions under in vivo like conditions. FIDA is an immobilization-free ligand binding methodology employing Taylor dispersion analysis for measuring the hydrodynamic radius (size) of biomolecular complexes. Here, the FIDA technology is utilized for a size-based characterization of the interaction between TNF-α and adalimumab. We report concentration-dependent complex sizes, binding affinities (Kd), kinetics, and higher order stoichiometries, thus providing essential information on the TNF-α–adalimumab binding mechanism. Furthermore, it is shown that the avidity stabilized complexes involving formation of multiple non-covalent bonds are formed on a longer timescale than the primary complexes formed in a simple 1 to 1 binding event.


Genetics ◽  
1998 ◽  
Vol 150 (1) ◽  
pp. 119-128
Author(s):  
M Rhys Dow ◽  
Paul E Mains

Abstract We have previously described the gene mei-1, which encodes an essential component of the Caenorhabditis elegans meiotic spindle. When ectopically expressed after the completion of meiosis, mei-1 protein disrupts the function of the mitotic cleavage spindles. In this article, we describe the cloning and the further genetic characterization of mel-26, a postmeiotic negative regulator of mei-1. mel-26 was originally identified by a gain-of-function mutation. We have reverted this mutation to a loss-of-function allele, which has recessive phenotypes identical to the dominant defects of its gain-of-function parent. Both the dominant and recessive mutations of mel-26 result in mei-1 protein ectopically localized in mitotic spindles and centrosomes, leading to small and misoriented cleavage spindles. The loss-of-function mutation was used to clone mel-26 by transformation rescue. As suggested by genetic results indicating that mel-26 is required only maternally, mel-26 mRNA was expressed predominantly in the female germline. The gene encodes a protein that includes the BTB motif, which is thought to play a role in protein-protein interactions.


2007 ◽  
Vol 42 (1-2) ◽  
pp. 141
Author(s):  
J. Fahrer ◽  
M. Altmeyer ◽  
R. Kranaster ◽  
S. Beneke ◽  
A. Marx ◽  
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Keyword(s):  

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Veenstra TD ◽  

Identifying all the molecular components within a living cell is the first step into understanding how it functions. To further understand how a cell functions requires identifying the interactions that occur between these components. This fact is especially relevant for proteins. No protein within a human cell functions on its own without interacting with another biomolecule - usually another protein. While Protein-Protein Interactions (PPI) have historically been determined by examining a single protein per study, novel technologies developed over the past couple of decades are enabling high-throughput methods that aim to describe entire protein networks within cells. In this review, some of the technologies that have led to these developments are described along with applications of these techniques. Ultimately the goal of these technologies is to map out the entire circuitry of PPI within human cells to be able to predict the global consequences of perturbations to the cell system. This predictive capability will have major impacts on the future of both disease diagnosis and treatment.


Author(s):  
Lok Man ◽  
William P. Klare ◽  
Ashleigh L. Dale ◽  
Joel A. Cain ◽  
Stuart J. Cordwell

Despite being considered the simplest form of life, bacteria remain enigmatic, particularly in light of pathogenesis and evolving antimicrobial resistance. After three decades of genomics, we remain some way from understanding these organisms, and a substantial proportion of genes remain functionally unknown. Methodological advances, principally mass spectrometry (MS), are paving the way for parallel analysis of the proteome, metabolome and lipidome. Each provides a global, complementary assay, in addition to genomics, and the ability to better comprehend how pathogens respond to changes in their internal (e.g. mutation) and external environments consistent with infection-like conditions. Such responses include accessing necessary nutrients for survival in a hostile environment where co-colonizing bacteria and normal flora are acclimated to the prevailing conditions. Multi-omics can be harnessed across temporal and spatial (sub-cellular) dimensions to understand adaptation at the molecular level. Gene deletion libraries, in conjunction with large-scale approaches and evolving bioinformatics integration, will greatly facilitate next-generation vaccines and antimicrobial interventions by highlighting novel targets and pathogen-specific pathways. MS is also central in phenotypic characterization of surface biomolecules such as lipid A, as well as aiding in the determination of protein interactions and complexes. There is increasing evidence that bacteria are capable of widespread post-translational modification, including phosphorylation, glycosylation and acetylation; with each contributing to virulence. This review focuses on the bacterial genotype to phenotype transition and surveys the recent literature showing how the genome can be validated at the proteome, metabolome and lipidome levels to provide an integrated view of organism response to host conditions.


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