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Effective patient prognosis necessitates identification of novel tumor promoting drivers of gastric cancer (GC) which contribute to worsened conditions by analysing TCGA-gastric adenocarcinoma dataset. Small leucine-rich proteoglycans, asporin (ASPN) and decorin (DCN), play overlapping roles in development and diseases; however, the mechanisms underlying their interplay remain elusive. Here, we investigated the complex interplay of asporin, decorin and their interaction with TGFβ in GC tumor and corresponding normal tissues. The mRNA levels, protein expressions and cellular localizations of ASPN and DCN were analyzed using real-time PCR, western blot and immunohistochemistry, respectively. The protein-protein interaction was predicted by in-silico interaction analysis and validated by co-immunoprecipitation assay. The correlations between ASPN and EMT proteins, VEGF and collagen were achieved using western blot analysis. A significant increase in expression of ASPN in tumor tissue vs. normal tissue was observed in both TCGA and our patient cohort. DCN, an effective inhibitor of the TGFβ pathway, was negatively correlated with stages of GC. Co-immunoprecipitation demonstrated that DCN binds with TGFβ, in normal gastric epithelium, whereas in GC, ASPN preferentially binds TGFβ. Possible activation of the canonical TGFβ pathway by phosphorylation of SMAD2 in tumor tissues suggests its role as an intracellular tumor promoter. Furthermore, tissues expressing ASPN showed unregulated EMT signalling. Our study uncovers ASPN as a GC-promoting gene and DCN as tumor suppressor, suggesting that ASPN can act as a prognostic marker in GC. For the first time, we describe the physical interaction of TGFβ with ASPN in GC and DCN with TGFβ in GC and normal gastric epithelium respectively. This study suggests that prevention of ASPN-TGFβ interaction or overexpression of DCN could serve as promising therapeutic strategies for GC patients.

According to the "jigsaw puzzle" model of protein folding, the isomorphism between sequence and structure is substantially determined by the specific geometry of sidechain interactions, within the protein interior. In this work, we have attempted to predict the hydrophobic core of cyclophilin (LdCyp) from Leishmania donovani, utilizing a surface complementarity function, which selects for high goodness of fit between hydrophobic side-chain surfaces, rather in the manner of assembling a three-dimensional jigsaw puzzle. The computational core prediction method implemented here has been tried on two distinct scenarios, on the LdCyp polypeptide chain with native non-core residues and all core residues initially set to alanine, on a poly-glycine polypeptide chain. Molecular dynamics simulations appeared to indicate partial destabilization of the two designed sequences. However, experimental characterization of the designed sequences by circular dichroism (CD) spectroscopy and denaturant (GdmCl) induced unfolding, demonstrated disordered proteins. Stepwise reconstruction of the designed cores by cumulative sequential mutations identified the specific mutation (M122L) as primarily responsible for fold collapse and all design objectives were achieved upon rectifying this mutation. In summary, the study demonstrates regions of the core to contain highly specific (jigsaw puzzle-like) interactions sensitive to any perturbations and a predictive algorithm to identify such regions. A mutation within the core has been identified which exercises an inordinate influence on the global fold, reminiscent of metamorphic proteins.In addition, the computational procedure could predict substantial regions of the core (given main-chain coordinates) without any reference to non-core residues.

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