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.
Docking algorithms that aim to be applicable to a broad range of ligands suffer reduced accuracy because they are unable to incorporate ligand-specific conformational energies. Here, we develop internal energy functions, Carbohydrate Intrinsic (CHI), to account for the rotational preferences of the glycosidic torsion angles in carbohydrates. The relative energies predicted by the CHI energy functions mirror the conformational distributions of glycosidic linkages determined from a survey of oligosaccharide-protein complexes in the Protein Data Bank. Addition of CHI energies to the standard docking scores in Autodock 3, 4.2, and Vina consistently improves pose ranking of oligosaccharides docked to a set of anti-carbohydrate antibodies. The CHI energy functions are also independent of docking algorithm, and with minor modifications, may be incorporated into both theoretical modeling methods, and experimental NMR or X-ray structure refinement programs.
In this work, we developed a computational protocol that employs multiple molecular docking experiments, followed by pose clustering, molecular dynamic simulations (10 ns), and energy rescoring to produce reliable 3D models of antibody–carbohydrate complexes. The protocol was applied to 10 antibody–carbohydrate co-complexes and three unliganded (apo) antibodies. Pose clustering significantly reduced the number of potential poses. For each system, 15 or fewer clusters out of 100 initial poses were generated and chosen for further analysis. Molecular dynamics (MD) simulations allowed the docked poses to either converge or disperse, and rescoring increased the likelihood that the best-ranked pose was an acceptable pose. This approach is amenable to automation and can be a valuable aid in determining the structure of antibody–carbohydrate complexes provided there is no major side chain rearrangement or backbone conformational change in the H3 loop of the CDR regions. Further, the basic protocol of docking a small ligand to a known binding site, clustering the results, and performing MD with a suitable force field is applicable to any protein ligand system.
We report a new classification method for pyranose ring conformations called Best-fit, Four-Membered Plane (BFMP), which describes pyranose ring conformations based on reference planes defined by four atoms. The method is able to characterize all asymmetrical and symmetrical shapes of a pyran ring, is readily automated, easy to interpret, and maps trivially to IUPAC definitions. It also provides a qualitative measurement of the distortion of the ring. Example applications include the analysis of data from crystal structures and molecular dynamics simulations.
Recognition of furanosides (five-membered ring sugars) by proteins plays important roles in host–pathogen interactions. In comparison to their six-membered ring counterparts (pyranosides), detailed studies of the molecular motifs involved in the recognition of furanosides by proteins are scarce. Here the first in-depth molecular characterization of a furanoside–protein interaction system, between an antibody (CS-35) and cell wall polysaccharides of mycobacteria, including the organism responsible for tuberculosis is reported. The approach was centered on the generation of the single chain variable fragment of CS-35 and a rational library of its mutants. Investigating the interaction from various aspects revealed the structural motifs that govern the interaction, as well as the relative contribution of molecular forces involved in the recognition. The specificity of the recognition was shown to originate mainly from multiple CH–π interactions and, to a lesser degree, hydrogen bonds formed in critical distances and geometries.
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