Journal of Chemical Theory and Computation · 2024 · 34 citations · 86 references
Natural SciencesBiochemistryBiophysicsProtein FoldingStructural BiologyStructural BiophysicsCoarse-grained ModelingComputational Structural BiologyForce FieldsMolecular DynamicsProtein DynamicsProtein StructureCoarse-grained Force FieldsGo-like ModelsHydrogen BondingMartini Force FieldProtein Coarse-grainingProtein ComplexesProtein StabilityQuaternary Structure Stability
Coarse-grained molecular dynamics simulations enable the modeling of increasingly complex systems at millisecond timescales. The transferable coarse-grained force field Martini 3 has shown great promise in modeling a wide range of biochemical processes, yet folded proteins in Martini 3 are not stable without the application of external bias potentials, such as elastic networks or Go̅-like models. We herein develop an algorithm, called OLIVES, which identifies native contacts with hydrogen bond capabilities in coarse-grained proteins and use it to implement a novel Go̅-like model for Martini 3. We show that the protein structure instability originates in part from the lack of hydrogen bond energy in the coarse-grained force field representation. By using realistic hydrogen bond energies obtained from literature ab initio calculations, it is demonstrated that protein stability can be recovered by the reintroduction of a coarse-grained hydrogen bond network and that OLIVES removes the need for secondary structure restraints. OLIVES is validated against known protein complexes and at the same time addresses the open question of whether there is a need for protein quaternary structure bias in Martini 3 simulations. It is shown that OLIVES can reduce the number of bias terms, hereby speeding up Martini 3 simulations of proteins by up to ≈30% on a GPU architecture compared to the established Go̅MARTINI Go̅-like model.
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Helen M. Berman · Nucleic Acids Research · 2000 · 39.8K citations
Canonical sampling through velocity rescaling
Giovanni Bussi, Davide Donadio, Michele Parrinello · The Journal of Chemical Physics · 2007 · 18.4K citations · Full text
Natural Sciences, Chemistry, Physics +17