A novel Greedy approach for Sequence based Computational prediction of Binding-Sites in Protein-Protein Interaction

Author(s):  
Aishwarya Purohit ◽  
Shrinivas Acharya ◽  
James Green
2007 ◽  
Vol 21 (11) ◽  
pp. 2821-2831 ◽  
Author(s):  
Isabel Uyttendaele ◽  
Irma Lemmens ◽  
Annick Verhee ◽  
Anne-Sophie De Smet ◽  
Joël Vandekerckhove ◽  
...  

Abstract Binding of GH to its receptor induces rapid phosphorylation of conserved tyrosine motifs that function as recruitment sites for downstream signaling molecules. Using mammalian protein-protein interaction trap (MAPPIT), a mammalian two-hybrid method, we mapped the binding sites in the GH receptor for signal transducer and activator of transcription 5 (STAT5) a and b and for the negative regulators of cytokine signaling cytokine-inducible Src-homology 2 (SH2)-containing protein (CIS) and suppressor of cytokine signaling 2 (SOCS2). Y534, Y566, and Y627 are the major recruitment sites for STAT5. A non-overlapping recruitment pattern is observed for SOCS2 and CIS with positions Y487 and Y595 as major binding sites, ruling out SOCS-mediated inhibition of STAT5 activation by competition for shared binding sites. More detailed analysis revealed that CIS binding to the Y595, but not to the Y487 motif, depends on both its SH2 domain and the C-terminal part of its SOCS box, with a critical role for the CIS Y253 residue. This functional divergence of the two CIS/SOCS2 recruitment sites is also observed upon substitution of the Y+1 residue by leucine, turning the Y487, but not the Y595 motif into a functional STAT5 recruitment site.


2007 ◽  
Vol 8 (9) ◽  
pp. R192 ◽  
Author(s):  
Haidong Wang ◽  
Eran Segal ◽  
Asa Ben-Hur ◽  
Qian-Ru Li ◽  
Marc Vidal ◽  
...  

Author(s):  
Yiwei Li ◽  
Lucian Ilie

AbstractMotivationProteins usually perform their functions by interacting with other proteins, which is why accurately predicting protein-protein interaction (PPI) binding sites is a fundamental problem. Experimental methods are slow and expensive. Therefore, great efforts are being made towards increasing the performance of computational methods.ResultsWe propose DELPHI (DEep Learning Prediction of Highly probable protein Interaction sites), a new sequence-based deep learning suite for PPI binding sites prediction. DELPHI has an ensemble structure with data augmentation and it employs novel features in addition to existing ones. We comprehensively compare DELPHI to nine state-of-the-art programs on five datasets and show that it is more accurate.AvailabilityThe trained model, source code for training, predicting, and data processing are freely available at https://github.com/lucian-ilie/DELPHI. All datasets used in this study can be downloaded at http://www.csd.uwo.ca/~ilie/DELPHI/[email protected]


2004 ◽  
Vol 24 (23) ◽  
pp. 10151-10160 ◽  
Author(s):  
Tae-gyun Kim ◽  
Junqin Chen ◽  
Junich Sadoshima ◽  
Youngsook Lee

ABSTRACT Mice with a homozygous knockout of the jumonji (jmj) gene showed abnormal heart development and defective regulation of cardiac-specific genes, including the atrial natriuretic factor (ANF). ANF is one of the earliest markers of cardiac differentiation and a hallmark for cardiac hypertrophy. Here, we show that JMJ represses ANF gene expression by inhibiting transcriptional activities of Nkx2.5 and GATA4. JMJ represses the Nkx2.5- or GATA4-dependent activation of the reporter genes containing the ANF promoter-enhancer or containing the Nkx2.5 or GATA4-binding consensus sequence. JMJ physically associates with Nkx2.5 and GATA4 in vitro and in vivo as determined by glutathione S-transferase pull-down and immunoprecipitation assays. Using mutational analyses, we mapped the protein-protein interaction domains in JMJ, Nkx2.5, and GATA4. We identified two DNA-binding sites of JMJ in the ANF enhancer by gel mobility shift assays. However, these JMJ-binding sites do not seem to mediate ANF repression by JMJ. Mutational analysis of JMJ indicates that the protein-protein interaction domain of JMJ mediates the repression of ANF gene expression. Therefore, JMJ may play important roles in the down-regulation of ANF gene expression and in heart development.


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