Structural and functional insights into CARDs of zebrafish (Danio rerio) NOD1 and NOD2, and their interaction with adaptor protein RIP2

Abstract

Nucleotide-binding and oligomerization domain-containing protein 1 (NOD1) and NOD2 are cytosolic pattern-recognition receptors (PRRs) composed of an N-terminal caspase activation and recruitment domain (CARD), a central NACHT domain and C-terminal leucine-rich repeats (LRRs). They play a vital role in innate immune signaling by activating the NF-κB pathway via recognition of peptidoglycans by LRRs, and ATP-dependent self-oligomerization of NACHT followed by downstream signaling. After oligomerization, CARD/s play a crucial role in activating downstream signaling via the adaptor molecule, RIP2. Due to the inadequacy of experimental 3D structures of CARD/s of NOD2 and RIP2, and results from differential experimental setups, the RIP2-mediated CARD-CARD interaction has remained as a contradictory statement. We employed a combinatorial approach involving protein modeling, docking, molecular dynamics simulation, and binding free energy calculation to illuminate the molecular mechanism that shows the possible involvement of either the acidic or basic patch of zebrafish NOD1/2-CARD/a and RIP2-CARD in CARD-CARD interaction. Herein, we have hypothesized 'type-I' mode of CARD-CARD interaction in NOD1 and NOD2, where NOD1/2-CARD/a involve their acidic surfaces to interact with RIP2. Asp37 and Glu51 (of NOD1) and Arg477, Arg521 and Arg529 (of RIP2) were identified to be crucial for NOD1-RIP2 interaction. However, in NOD2-RIP2, Asp32 (of NOD2) and Arg477 and Arg521 (of RIP2) were anticipated to be significant for downstream signaling. Furthermore, we found that strong electrostatic contacts and salt bridges are crucial for protein-protein interactions. Altogether, our study has provided novel insights into the RIP2-mediated CARD-CARD interaction in zebrafish NOD1 and NOD2, which will be helpful to understand the molecular basis of the NOD1/2 signaling mechanism.

NOD1CARD Might Be Using Multiple Interfaces for RIP2-Mediated CARD-CARD Interaction: Insights from Molecular Dynamics Simulation

“…NOD1 CARD showed an extensive negative surface and a small positively charged patch; however, RIP2 CARD portrayed several positive and negative patches over the surface (Fig 1B and 1C). Owing to the interest of this study, two potential type-I surface patches (both positive (α1 and α4; type-Ia) and negative (α2 and α3; type-Ib)) were identified on the basis of earlier reports on NOD1/NOD2-RIP2 and Ap1-C9 CARD-CARD interaction [15–20,23,24,33,34]. The binding patches including the critical/surface exposed residues (experimentally proved/predicted) were illustrated in Fig 1C–1E.…”

The role of microbiota in the development of colorectal cancer

“…Among them, nucleotide binding oligomerization domain containing (NOD)1 and NOD2 are active in intestinal cells and can recognize caspase recruitment domains (card‐card) . Under the stimulation of leucine‐rich repeats (LRRs), which are involved in bacterial‐sensing during pathogenesis, NOD1 and NOD2 interact with the receptor‐interacting protein 2 (RIP2), which stimulates tumor necrosis factor (TNF) receptor‐associated factor 6 (TRAF6) and recognizes transforming growth factor kinase 1(TAK1), triggering mitogen‐activated protein kinase (MAPK) and NF‐kappa B (NF‐κB) signaling . By contrast, there has been little research on CLRs.…”

POP1 might be recruiting its type‐Ia interface for NLRP3‐mediated PYD‐PYD interaction: Insights from MD simulation

“…The functional roles of NLRs depend significantly on their dynamic behavior and conformational states. In this context, MD simulation paves the way in understanding the dynamic aspects of protein structure and the governing biomolecular interactions (either with drug molecules, downstream proteins, or pathogenic ligands) in an important signaling pathway . Although the computational predictions are reliable in envisaging the functional aspects of biological macromolecules (the arbitrated biochemical interactions), the accuracy of prediction depends on selective algorithm, scoring function, and accessible hardware.…”