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Vina-Carb: Improving Glycosidic Angles during Carbohydrate Docking.

Anita K Nivedha1, David F Thieker1, Spandana Makeneni1

  • 1Complex Carbohydrate Research Center, University of Georgia , Athens, Georgia 30602, United States.

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Vina-Carb (VC) improves protein-carbohydrate complex prediction by incorporating carbohydrate intrinsic (CHI) energy functions into molecular docking. This enhanced approach accurately models flexible glycosidic linkages, boosting structural prediction success rates.

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Area of Science:

  • Computational chemistry
  • Structural biology
  • Biochemistry

Background:

  • Molecular docking typically struggles with flexible carbohydrate molecules due to limitations in scoring functions.
  • Oligosaccharide flexibility, particularly at glycosidic linkages, presents a significant challenge for accurate docking.
  • Carbohydrate Intrinsic (CHI) energy functions quantify glycosidic torsion angle preferences.

Purpose of the Study:

  • To enhance molecular docking performance for protein-carbohydrate complexes.
  • To integrate CHI energy functions into the AutoDock Vina (ADV) scoring function, creating Vina-Carb (VC).
  • To evaluate the efficacy of VC in predicting the structures of protein-carbohydrate complexes.

Main Methods:

  • Incorporated CHI energy functions into the AutoDock Vina scoring function.
  • Introduced user-adjustable parameters: chi_coeff (CHI-energy weight) and chi_cutoff (CHI-energy cutoff).
  • Tested VC on a dataset of 101 protein-carbohydrate complexes and 29 apoprotein structures.

Main Results:

  • Vina-Carb (VC) achieved acceptable structures within the top five poses in 74% of tested systems.
  • AutoDock Vina (ADV) alone had a success rate of 55% for the same dataset.
  • VC demonstrated improved accuracy by accounting for intramolecular energies of glycosidic linkages.

Conclusions:

  • VC represents a significant advancement in accurately predicting protein-carbohydrate complex structures.
  • The approach effectively models the flexibility of carbohydrate ligands during docking.
  • The methodology is adaptable for other ligand classes with defined conformational states.