Extending the Martini coarse-grained forcefield to N-glycans

Extending the Martini coarse-grained forcefield to N-glycans
Title:
Extending the Martini coarse-grained forcefield to N-glycans
Other Titles:
bioRxiv
Publication Date:
10 May 2020
Citation:
bioRxiv 2020.05.08.085399;
Abstract:
Glycans play a vital role in a large number of cellular processes. Their complex and flexible nature hampers structure-function studies using experimental techniques. Molecular dynamics (MD) simulations can help in understanding dynamic aspects of glycans if the forcefield (FF) parameters used can reproduce key experimentally observed properties. Here, we present optimized coarse-grained (CG) Martini FF parameters for N-glycans, calibrated against experimentally derived binding affinities for lectins. The CG bonded parameters were obtained from atomistic (ATM) simulations for different glycan topologies including high mannose and complex glycans with various branching patterns. In the CG model, additional elastic networks are shown to improve maintenance of the overall conformational distribution. Solvation free energies and octanol-water partition coefficients were also calculated for various n-glycan disaccharide combinations. When using standard Martini non-bonded parameters, we observed that glycans spontaneously aggregated in the solution and required down-scaling of their interactions for reproduction of ATM model radial distribution functions. We also optimised the non-bonded interactions for glycans interacting with seven lectin candidates and show that scaling down the glycan-protein interactions can reproduce free energies obtained from experimental studies. These parameters should be of use in studying the role of glycans in various glycoproteins, carbohydrate binding proteins (CBPs) as well as their complexes, while benefiting from the efficiency of CG sampling.
License type:
http://creativecommons.org/licenses/by-nc-nd/4.0/
Funding Info:
This work was supported in part by funding from the Ministry of Education, AcRF grant R-154-100-580-112 to ATS, MOE2012-T3-1-008 to CSV, PJB and PM, and the National Research Foundation grant NRF2017NRF-CRP001-027 to PJB and JKM.
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