Evaluation of Selected Classical Force Fields for Alchemical Binding Free Energy Calculations of Protein-Carbohydrate Complexes

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Authors

MISHRA Sushil Kumar CALABRO Gaetano LOEFFLER Hannes H. MICHEL Julien KOČA Jaroslav

Year of publication 2015
Type Article in Periodical
Magazine / Source Journal of Chemical Theory and Computation
MU Faculty or unit

Central European Institute of Technology

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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