Vina-Carb: Improving Glycosidic Angles during Carbohydrate Docking
By A. Nivedha, David F. Thieker, Spandana Makeneni, Huimin Hu, R. Woods. 2016
112 citations recorded by the source corpus.
Molecular docking programs are primarily designed to align rigid, drug-like fragments into the binding sites of macromolecules and frequently display poor performance when applied to flexible carbohydrate molecules. A critical source of flexibility within an oligosaccharide is the glycosidic linkages. Recently, Carbohydrate Intrinsic (CHI) energy functions were reported that attempt to quantify the glycosidic torsion angle preferences. In the present work, the CHI-energy functions have been incorporated into the AutoDock Vina (ADV) scoring function, subsequently termed Vina-Carb (VC). Two user-adjustable parameters have been introduced, namely, a CHI- energy weight term (chi_coeff) that affects the magnitude of the CHI-energy penalty and a CHI-cutoff term (chi_cutoff) that negates CHI-energy penalties below a specified value. A data set consisting of 101 protein–carbohydrate complexes and 29 apoprotein structures was used in the development and testing of VC, including antibodies, lectins, and carbohydrate binding modules. Accounting for the intramolecular energies of the glycosidic linkages in the oligosaccharides during docking led VC to produce acceptable structures within the top five ranked poses in 74% of the systems tested, compared to a success rate of 55% for ADV. An enzyme system was employed in order to illustrate the potential application of VC to proteins that may distort glycosidic linkages of carbohydrate ligands upon binding. VC represents a significant step toward accurately predicting the structures of protein–carbohydrate complexes. Furthermore, the described approach is conceptually applicable to any class of ligands that populate well-defined conformational states.
Subfields: Molecular Biology, Organic Chemistry
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- David Baker
- Jeffrey J. Gray
- Tanja Kortemme
- Rhiju Das
- Frank DiMaio
- Hahnbeom Park
- Brian Kuhlman
- Jens Meiler
In Organic Chemistry
- Tanja Kortemme
- Maxim V. Shapovalov
- Brian Kuhlman
- Andrew Leaver-Fay
- David Baker
- Rhiju Das
- Frances H. Arnold
- Amelie Stein
Citations in the corpus
- The Rosetta all-atom energy function for macromolecular modeling and design (2017, background): “66 Labonte et al 68 implemented Woods’ CarboHydrate-Intrinsic (CHI) function 109,110 which evaluates glycan geometries given the axial-equatorial character of the bonds.”
- Growing Glycans in Rosetta: Accurate de novo glycan modeling, density fitting, and rational sequon design (2021, background): “Glycans can also improve stability [9] and solubility [10], reduce aggregation [11], and even improve biological drug-targeting and vaccine design through glycan masking of off-target regions [12].”