Evaluation of Selected Classical Force Fields for Alchemical Binding Free Energy Calculations of Protein-Carbohydrate Complexes
| Authors | |
|---|---|
| Year of publication | 2015 |
| Type | Article in Periodical |
| Magazine / Source | Journal of Chemical Theory and Computation |
| MU Faculty or unit | |
| Citation | |
| web | http://pubs.acs.org/doi/full/10.1021/acs.jctc.5b00159 |
| Doi | http://dx.doi.org/10.1021/acs.jctc.5b00159 |
| Field | Physical chemistry and theoretical chemistry |
| Keywords | MOLECULAR-DYNAMICS SIMULATIONS; THERMODYNAMIC INTEGRATION; DRUG DESIGN; RALSTONIA-SOLANACEARUM; EFFICIENT GENERATION; CONCANAVALIN-A; AM1-BCC MODEL; SUGAR BINDING; LECTIN; AFFINITIES |
| Description | Protein carbohydrate recognition is crucial in many vital biological processes including host-pathogen recognition, cell-signaling, and catalysis. Accordingly, computational prediction of protein-carbohydrate binding free energies is of enormous interest for drug design. However, the accuracy of current force fields (FFs) for predicting binding free energies of protein-carbohydrate complexes is not well understood owing to technical challenges such as the highly polar nature of the complexes, anomerization, and conformational flexibility of carbohydrates. The present study evaluated the performance of alchemical predictions of binding free energies with the GAFF1.7/AM1-BCC and GLYCAMO6j force fields for modeling protein carbohydrate complexes. Mean unsigned errors of 1.1 +/- 0.06 (GLYCAMO6j) and 2.6 +/- 0.08 (GAFF1.7/AM1-BCC) kcal.mol(-1) are achieved for a large data set of monosaccharide ligands for Ralstonia solanacearum lectin (RSL). The level of accuracy provided by GLYCAMO6j is sufficient to discriminate potent, moderate, and weak binders, a goal that has been difficult to achieve through other scoring approaches. Accordingly, the protocols presented here could find useful applications in carbohydrate-based drug and vaccine developments. |
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