The conservation of phosphate-binding residues among PHT1 transporters suggests that distinct transport affinities are unlikely to result from differences in the phosphate-binding site

2016 ◽  
Vol 44 (5) ◽  
pp. 1541-1548 ◽  
Author(s):  
S. Antony Ceasar ◽  
Alison Baker ◽  
Stephen P. Muench ◽  
S. Ignacimuthu ◽  
Stephen A. Baldwin

The plant PHosphate Transporter 1 (PHT1) family of membrane proteins belongs to the major facilitator super family and plays a major role in the acquisition of inorganic phosphate (Pi) from the soil and its transport within the plant. These transporters have been well characterized for expression patterns, localization, and in some cases affinity. Furthermore, the crystal structure of a high-affinity eukaryotic phosphate transporter from the fungus Piriformospora indica (PiPT) has revealed important information on the residues involved in Pi transport. Using multiple-sequence alignments and homology modelling, the phosphate-binding site residues were shown to be well conserved between all the plant PHT1 proteins, Saccharomyces cerevisiae PHO84 and PiPT. For example, Asp 324 in PiPT is conserved in the equivalent position in all plant PHT1 and yeast transporters analyzed, and this residue in ScPHO84 was shown by mutagenesis to be important for both the binding and transport of Pi. Moreover, Asp 45 and Asp 149, which are predicted to be involved in proton import, and Lys 459, which is putatively involved in Pi-binding, are all fully conserved in PHT1 and ScPHO84 transporters. The conserved nature of the residues that play a key role in Pi-binding and transport across the PHT1 family suggests that the differing Pi affinities of these transporters do not reside in differences in the Pi-binding site. Recent studies suggest that phosphate transporters could possess dual affinity and that post-translational modifications may be important in regulating affinity for phosphate.

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Elena N. Judd ◽  
Alison R. Gilchrist ◽  
Nicholas R. Meyerson ◽  
Sara L. Sawyer

Abstract Background The Type I interferon response is an important first-line defense against viruses. In turn, viruses antagonize (i.e., degrade, mis-localize, etc.) many proteins in interferon pathways. Thus, hosts and viruses are locked in an evolutionary arms race for dominance of the Type I interferon pathway. As a result, many genes in interferon pathways have experienced positive natural selection in favor of new allelic forms that can better recognize viruses or escape viral antagonists. Here, we performed a holistic analysis of selective pressures acting on genes in the Type I interferon family. We initially hypothesized that the genes responsible for inducing the production of interferon would be antagonized more heavily by viruses than genes that are turned on as a result of interferon. Our logic was that viruses would have greater effect if they worked upstream of the production of interferon molecules because, once interferon is produced, hundreds of interferon-stimulated proteins would activate and the virus would need to counteract them one-by-one. Results We curated multiple sequence alignments of primate orthologs for 131 genes active in interferon production and signaling (herein, “induction” genes), 100 interferon-stimulated genes, and 100 randomly chosen genes. We analyzed each multiple sequence alignment for the signatures of recurrent positive selection. Counter to our hypothesis, we found the interferon-stimulated genes, and not interferon induction genes, are evolving significantly more rapidly than a random set of genes. Interferon induction genes evolve in a way that is indistinguishable from a matched set of random genes (22% and 18% of genes bear signatures of positive selection, respectively). In contrast, interferon-stimulated genes evolve differently, with 33% of genes evolving under positive selection and containing a significantly higher fraction of codons that have experienced selection for recurrent replacement of the encoded amino acid. Conclusion Viruses may antagonize individual products of the interferon response more often than trying to neutralize the system altogether.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Farhan Quadir ◽  
Raj S. Roy ◽  
Randal Halfmann ◽  
Jianlin Cheng

AbstractDeep learning methods that achieved great success in predicting intrachain residue-residue contacts have been applied to predict interchain contacts between proteins. However, these methods require multiple sequence alignments (MSAs) of a pair of interacting proteins (dimers) as input, which are often difficult to obtain because there are not many known protein complexes available to generate MSAs of sufficient depth for a pair of proteins. In recognizing that multiple sequence alignments of a monomer that forms homomultimers contain the co-evolutionary signals of both intrachain and interchain residue pairs in contact, we applied DNCON2 (a deep learning-based protein intrachain residue-residue contact predictor) to predict both intrachain and interchain contacts for homomultimers using multiple sequence alignment (MSA) and other co-evolutionary features of a single monomer followed by discrimination of interchain and intrachain contacts according to the tertiary structure of the monomer. We name this tool DNCON2_Inter. Allowing true-positive predictions within two residue shifts, the best average precision was obtained for the Top-L/10 predictions of 22.9% for homodimers and 17.0% for higher-order homomultimers. In some instances, especially where interchain contact densities are high, DNCON2_Inter predicted interchain contacts with 100% precision. We also developed Con_Complex, a complex structure reconstruction tool that uses predicted contacts to produce the structure of the complex. Using Con_Complex, we show that the predicted contacts can be used to accurately construct the structure of some complexes. Our experiment demonstrates that monomeric multiple sequence alignments can be used with deep learning to predict interchain contacts of homomeric proteins.


2016 ◽  
pp. btw474 ◽  
Author(s):  
Guy Yachdav ◽  
Sebastian Wilzbach ◽  
Benedikt Rauscher ◽  
Robert Sheridan ◽  
Ian Sillitoe ◽  
...  

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