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Biology subjects

Gamarra, M. D.

Publications and source records attributed to Gamarra, M. D..

2 recordsLinked to original sources

A cryptic pocket allosterically modulates oligosaccharide binding to DC-SIGN

DC-SIGN is a C-type lectin receptor expressed on antigen-presenting cells, crucial for pathogen recognition and immune modulation. Here, we identify and characterize a previously unrecognized cryptic allosteric pocket in DC-SIGN using molecular dynamics simulations, NMR spectroscopy, cryogenic electron microscopy and biochemical assays. Rotation of the gatekeeper residue M270 exposes the pocket whose occupancy modulates glycan binding. Mutations M270F and T314A mimic the occupied and unoccupied states of this pocket, respectively, shifting the conformational equilibrium of -helix 2 and altering oligosaccharide affinity via the extended carbohydrate binding site. While Ca{superscript 2} coordination at the canonical binding site remains unaffected, our data reveal a complex interplay between the Ca{superscript 2} binding sites and the canonical and extended glycan binding surfaces. These findings uncover a hierarchical allosteric mechanism that enables selective tuning of glycan affinity and suggest the cryptic pocket as a novel target for drug discovery in C-type lectins.

biochemistry↗

Molecular Dynamics and Water site bias docking method allows the identification of key amino acids in the Carbohydrate Recognition Domain of a viral protein

Carbohydrate-binding modules (CBMs) are protein domains that typically reside near catalytic domains, increasing substrate-protein proximity by constraining the conformational space of carbohydrates. Due to the flexibility and variability of glycans, the molecular details of how these protein regions recognize their target molecules are not always fully understood. Computational methods, including molecular docking and molecular dynamics simulations, have been employed to investigate lectin-carbohydrate interactions. In this study, we introduce a novel approach that integrates multiple computational techniques to identify the critical amino acids involved in the interaction between a CBM located at the tip of bacteriophage J-1s tail and its carbohydrate counterparts. Our results highlight three amino acids that play a significant role in binding, which we confirmed through in vitro experiments. By presenting this approach, we offer an intriguing alternative for pinpointing amino acids that contribute to protein-sugar interactions, leading to a more thorough comprehension of the molecular determinants of lectin-carbohydrate interactions.

bioinformatics↗