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Residue-centric modeling and design of saccharide and glycoconjugate structures.

ABSTRACT: The RosettaCarbohydrate framework is a new tool for modeling a wide variety of saccharide and glycoconjugate structures. This report describes the development of the framework and highlights its applications. The framework integrates with established protocols within the Rosetta modeling and design suite, and it handles the vast complexity and variety of carbohydrate molecules, including branching and sugar modifications. To address challenges of sampling and scoring, RosettaCarbohydrate can sample glycosidic bonds, side-chain conformations, and ring forms, and it utilizes a glycan-specific term within its scoring function. Rosetta can work with standard PDB, GLYCAM, and GlycoWorkbench (.gws) file formats. Saccharide residue-specific chemical information is stored internally, permitting glycoengineering and design. Carbohydrate-specific applications described herein include virtual glycosylation, loop-modeling of carbohydrates, and docking of glyco-ligands to antibodies. Benchmarking data are presented and compared to other studies, demonstrating Rosetta's ability to predict glyco-ligand binding. The framework expands the tools available to glycoscientists and engineers. © 2016 Wiley Periodicals, Inc.

SUBMITTER: Labonte JW

PROVIDER: S-EPMC5182120 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Residue-centric modeling and design of saccharide and glycoconjugate structures.

Labonte Jason W JW Adolf-Bryfogle Jared J Schief William R WR Gray Jeffrey J JJ

Journal of computational chemistry 20161130 5

The RosettaCarbohydrate framework is a new tool for modeling a wide variety of saccharide and glycoconjugate structures. This report describes the development of the framework and highlights its applications. The framework integrates with established protocols within the Rosetta modeling and design suite, and it handles the vast complexity and variety of carbohydrate molecules, including branching and sugar modifications. To address challenges of sampling and scoring, RosettaCarbohydrate can sam ...[more]

PMID: 27900782

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Project description:BACKGROUND: A significant proportion of myocardial infarction (MI) patients undergo complex, coordinated perturbations at the molecular level that may eventually drive the occurrence of ventricular dysfunction and heart failure. Despite advances in the elucidation of key processes implicated in this condition, traditional methods relying on gene expression data and the identification of individual biomarkers in isolation pose major limitations not only for improving prediction power, but also for model interpretability. Mechanisms underlying clinical responses after MI remain elusive and there is no biomarker with the capacity to accurately predict ventricular dysfunction after MI. This calls for the exploration of system-level modeling of ventricular dysfunction in post-MI patients. Within this discovery framework key perturbations and predictive patterns are characterized by the integrated biological activity levels observed in pathways, rather than in individual genes. METHODOLOGY/PRINCIPAL FINDINGS: Here we report an integrative approach to identifying pathways related with ventricular dysfunction post MI with potential prognostic and therapeutic value. We found that a diversity of pathway-level perturbations can be profiled in samples of patients with ventricular dysfunction post MI, most of which represent major reductions of gene expression. Highly perturbed pathways included those implicated in antigen-dependent B-cell activation and the synthesis of leucine. By analyzing patient-specific samples encoded with information derived from highly-perturbed pathways, it is possible to visualize differential prognostic patterns and to perform computational classification of patients with areas under the receiver operating characteristic curve above 0.75. We also demonstrate how the integration of the outcomes generated by different pathway-based analysis models may improve ventricular dysfunction prediction performance. SIGNIFICANCE: This research offers an alternative, comprehensive view of key relationships and perturbations that may trigger the emergence or prevention of ventricular dysfunction post-MI.

Dataset Information

Residue-centric modeling and design of saccharide and glycoconjugate structures.

Publications

Residue-centric modeling and design of saccharide and glycoconjugate structures.

Similar Datasets

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