scholarly journals Plucking the high hanging fruit: A systematic approach for targeting protein–protein interactions

2013 ◽  
Vol 21 (14) ◽  
pp. 4051-4057 ◽  
Author(s):  
Monika Raj ◽  
Brooke N. Bullock ◽  
Paramjit S. Arora
2021 ◽  
Author(s):  
Rebeca Queiroz Figueiredo ◽  
Tamara Raschka ◽  
Alpha Tom Kodamullil ◽  
Martin Hofmann-Apitius ◽  
Sarah Mubeen ◽  
...  

AbstractIn this work, we attempt to address a key question in the joint analysis of transcriptomic data: can we correlate the patterns we observe in transcriptomic datasets to known molecular interactions and pathway knowledge to broaden our understanding of disease pathophysiology? We present a systematic approach that sheds light on the patterns observed in hundreds of transcriptomic datasets from over sixty indications by using pathways and molecular interactions as a template. Our analysis employs transcriptomic datasets to construct dozens of disease specific co-expression networks, alongside a human interactome network of protein-protein interactions described in the literature. Leveraging the interoperability between these two network templates, we explore patterns both common and particular to these diseases on three different levels. Firstly, at the node-level, we identify the most and least common proteins in these diseases and evaluate their consistency against the interactome as a proxy for their prevalence in the scientific literature. Secondly, we overlay both network templates to analyze common correlations and interactions across diseases at the edge-level. Thirdly, we explore the similarity between patterns observed at the disease level and pathway knowledge to identify pathway signatures associated with specific diseases and indication areas. Finally, we present a case scenario in the context of schizophrenia, where we show how our approach can be used to investigate disease pathophysiology.


2011 ◽  
Vol 49 (08) ◽  
Author(s):  
LC König ◽  
M Meinhard ◽  
C Sandig ◽  
MH Bender ◽  
A Lovas ◽  
...  

1974 ◽  
Vol 31 (03) ◽  
pp. 403-414 ◽  
Author(s):  
Terence Cartwright

SummaryA method is described for the extraction with buffers of near physiological pH of a plasminogen activator from porcine salivary glands. Substantial purification of the activator was achieved although this was to some extent complicated by concomitant extraction of nucleic acid from the glands. Preliminary characterization experiments using specific inhibitors suggested that the activator functioned by a similar mechanism to that proposed for urokinase, but with some important kinetic differences in two-stage assay systems. The lack of reactivity of the pig gland enzyme in these systems might be related to the tendency to protein-protein interactions observed with this material.


2020 ◽  
Author(s):  
Salvador Guardiola ◽  
Monica Varese ◽  
Xavier Roig ◽  
Jesús Garcia ◽  
Ernest Giralt

<p>NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-<i>i</i>3 and PD-<i>i</i>6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>


2020 ◽  
Author(s):  
Salvador Guardiola ◽  
Monica Varese ◽  
Xavier Roig ◽  
Jesús Garcia ◽  
Ernest Giralt

<p>NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-<i>i</i>3 and PD-<i>i</i>6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>


2020 ◽  
Author(s):  
James Frederich ◽  
Ananya Sengupta ◽  
Josue Liriano ◽  
Ewa A. Bienkiewicz ◽  
Brian G. Miller

Fusicoccin A (FC) is a fungal phytotoxin that stabilizes protein–protein interactions (PPIs) between 14-3-3 adapter proteins and their phosphoprotein interaction partners. In recent years, FC has emerged as an important chemical probe of human 14-3-3 PPIs implicated in cancer and neurological diseases. These previous studies have established the structural requirements for FC-induced stabilization of 14-3-3·client phosphoprotein complexes; however, the effect of different 14-3-3 isoforms on FC activity has not been systematically explored. This is a relevant question for the continued development of FC variants because there are seven distinct isoforms of 14-3-3 in humans. Despite their remarkable sequence and structural similarities, a growing body of experimental evidence supports both tissue-specific expression of 14-3-3 isoforms and isoform-specific functions <i>in vivo</i>. Herein, we report the isoform-specificity profile of FC <i>in vitro</i>using recombinant human 14-3-3 isoforms and a focused library of fluorescein-labeled hexaphosphopeptides mimicking the C-terminal 14-3-3 recognition domains of client phosphoproteins targeted by FC in cell culture. Our results reveal modest isoform preferences for individual client phospholigands and demonstrate that FC differentially stabilizes PPIs involving 14-3-3s. Together, these data provide strong motivation for the development of non-natural FC variants with enhanced selectivity for individual 14-3-3 isoforms.


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