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1. FRETting about the affinity of bimolecular protein–protein interactions

   https://doi.org/10.1002/pro.3482  

   Lin, Tao ; Scott, Brandon L. ; Hoppe, Adam D. ; Chakravarty, Suvobrata ( October 2018 , Protein Science)

   Fluorescenceresonanceenergytransfer (FRET) is a powerful tool to study macromolecular interactions such as protein–protein interactions (PPIs). Fluorescent protein (FP) fusions enable FRET‐based PPI analysis of signaling pathways and molecular structure in living cells. Despite FRET's importance in PPI studies, FRET has seen limited use in quantifying the affinities of PPIs in living cells. Here, we have explored the relationship between FRET efficiency and PPI affinity over a wide range when expressed from a single plasmid system inEscherichia coli.Using live‐cell microscopy and a set of 20 pairs of small interacting proteins, belonging to different structural folds and interaction affinities, we demonstrate that FRET efficiency can reliably measure the dissociation constant (K_D) over a range of mMto nM. A 10‐fold increase in the interaction affinity results in 0.05 unit increase in FRET efficiency, providing sufficient resolution to quantify large affinity differences (> 10‐fold) using live‐cell FRET. This approach provides a rapid and simple strategy for assessment of PPI affinities over a wide range and will have utility for high‐throughput analysis of protein interactions.

    

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2. Single‐molecule tracking reveals that the nucleoid‐associated protein HU plays a dual role in maintaining proper nucleoid volume through differential interactions with chromosomal DNA

   https://doi.org/10.1111/mmi.14572  

   Bettridge, Kelsey ; Verma, Subhash ; Weng, Xiaoli ; Adhya, Sankar ; Xiao, Jie ( August 2020 , Molecular Microbiology)

   HU (Histone‐like protein fromEscherichia colistrain U93) is the most conserved nucleoid‐associated protein in eubacteria, but how it impacts global chromosome organization is poorly understood. Using single‐molecule tracking, we demonstrate that HU exhibits nonspecific, weak, and transitory interactions with the chromosomal DNA. These interactions are largely mediated by three conserved, surface‐exposed lysine residues (triK), which were previously shown to be responsible for nonspecific binding to DNA. The loss of these weak, transitory interactions in a HUα(triKA) mutant results in an over‐condensed and mis‐segregated nucleoid. Mutating a conserved proline residue (P63A) in the HUα subunit, deleting the HUβ subunit, or deleting nucleoid‐associated naRNAs, each previously implicated in HU’s high‐affinity binding to kinked or cruciform DNA, leads to less dramatically altered interacting dynamics of HU compared to the HUα(triKA) mutant, but highly expanded nucleoids. Our results suggest HU plays a dual role in maintaining proper nucleoid volume through its differential interactions with chromosomal DNA. On the one hand, HU compacts the nucleoid through specific DNA structure‐binding interactions. On the other hand, it decondenses the nucleoid through many nonspecific, weak, and transitory interactions with the bulk chromosome. Such dynamic interactions may contribute to the viscoelastic properties and fluidity of the bacterial nucleoid to facilitate proper chromosome functions.

    

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3. Large-scale discovery of protein interactions at residue resolution using co-evolution calculated from genomic sequences

   https://doi.org/10.1038/s41467-021-21636-z  

   Green, Anna G. ; Elhabashy, Hadeer ; Brock, Kelly P. ; Maddamsetti, Rohan ; Kohlbacher, Oliver ; Marks, Debora S. ( March 2021 , Nature Communications)

   Increasing numbers of protein interactions have been identified in high-throughput experiments, but only a small proportion have solved structures. Recently, sequence coevolution-based approaches have led to a breakthrough in predicting monomer protein structures and protein interaction interfaces. Here, we address the challenges of large-scale interaction prediction at residue resolution with a fast alignment concatenation method and a probabilistic score for the interaction of residues. Importantly, this method (EVcomplex2) is able to assess the likelihood of a protein interaction, as we show here applied to large-scale experimental datasets where the pairwise interactions are unknown. We predict 504 interactions de novo in theE. colimembrane proteome, including 243 that are newly discovered. While EVcomplex2 does not require available structures, coevolving residue pairs can be used to produce structural models of protein interactions, as done here for membrane complexes including the Flagellar Hook-Filament Junction and the Tol/Pal complex.

    

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4. Computational identification of protein-protein interactions in model plant proteomes

   https://doi.org/10.1038/s41598-019-45072-8  

   Ding, Ziyun ; Kihara, Daisuke ( June 2019 , Scientific Reports)

   Protein-protein interactions (PPIs) play essential roles in many biological processes. A PPI network provides crucial information on how biological pathways are structured and coordinated from individual protein functions. In the past two decades, large-scale PPI networks of a handful of organisms were determined by experimental techniques. However, these experimental methods are time-consuming, expensive, and are not easy to perform on new target organisms. Large-scale PPI data is particularly sparse in plant organisms. Here, we developed a computational approach for detecting PPIs trained and tested on known PPIs ofArabidopsis thalianaand applied to three plants,Arabidopsis thaliana,Glycine max(soybean), andZea mays(maize) to discover new PPIs on a genome-scale. Our method considers a variety of features including protein sequences, gene co-expression, functional association, and phylogenetic profiles. This is the first work where a PPI prediction method was developed for is the first PPI prediction method applied on benchmark datasets ofArabidopsis. The method showed a high prediction accuracy of over 90% and very high precision of close to 1.0. We predicted 50,220 PPIs inArabidopsis thaliana, 13,175,414 PPIs in corn, and 13,527,834 PPIs in soybean. Newly predicted PPIs were classified into three confidence levels according to the availability of existing supporting evidence and discussed. Predicted PPIs in the three plant genomes are made available for future reference.

    

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5. Electron‐deficient p‐benzoyl‐ l ‐phenylalanine derivatives increase covalent chemical capture yields for protein–protein interactions

   https://doi.org/10.1002/pro.3621  

   Joiner, Cassandra M. ; Breen, Meghan E. ; Mapp, Anna K. ( April 2019 , Protein Science)

   The photoactivatable amino acid p‐benzoyl‐l‐phenylalanine (pBpa) has been used for the covalent capture of protein–protein interactions (PPIs)in vitroand in living cells. However, this technique often suffers from poor photocrosslinking yields due to the low reactivity of the active species. Here we demonstrate that the incorporation of halogenated pBpa analogs into proteins leads to increased crosslinking yields for protein–protein interactions. The analogs can be incorporated into live yeast and upon irradiation capture endogenous PPIs. Halogenated pBpas will extend the scope of PPIs that can be captured and expand the toolbox for mapping PPIs in their native environment.

    

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