Abstract
Molecular dynamics simulations with coarse-grained or simplified Hamiltonians have proven to be an effective means of capturing the functionally important long-time and large-length scale motions of proteins and RNAs. Originally developed in the context of protein folding, structure-based models (SBMs) have since been extended to probe a diverse range of biomolecular processes, spanning from protein and RNA folding to functional transitions in molecular machines. The hallmark feature of a structure-based model is that part, or all, of the potential energy function is defined by a known structure. Within this general class of models, there exist many possible variations in resolution and energetic composition. SMOG 2 is a downloadable software package that reads user-designated structural information and user-defined energy definitions, in order to produce the files necessary to use SBMs with high performance molecular dynamics packages: GROMACS and NAMD. SMOG 2 is bundled with XML-formatted template files that define commonly used SBMs, and it can process template files that are altered according to the needs of each user. This computational infrastructure also allows for experimental or bioinformatics-derived restraints or novel structural features to be included, e.g. novel ligands, prosthetic groups and post-translational/transcriptional modifications. The code and user guide can be downloaded at http://smog-server.org/smog2.
Highlights
The study of biomolecular folding has produced theoretical concepts that are generalizable to many processes, such as conformational rearrangements in proteins and the functional dynamics of molecular assemblies
Since protein function is governed by the same energy landscape that determines folding dynamics [21], these models have been used to study the conformational dynamics involved in macromolecular function, e.g. adenylate kinase [22], kinesin [23, 24], and the ribosome [25]
SMOG 2 adopts this strategy for defining structure-based models (SBMs), which is consistent with the organization used for semi-empirical models, such as AMBER [38], CHARMM [39], and GROMOS [40]
Summary
The study of biomolecular folding has produced theoretical concepts that are generalizable to many processes, such as conformational rearrangements in proteins and the functional dynamics of molecular assemblies. Since protein function is governed by the same energy landscape that determines folding dynamics [21], these models have been used to study the conformational dynamics involved in macromolecular function, e.g. adenylate kinase [22], kinesin [23, 24], and the ribosome [25] These models have structural resolutions that vary from a single bead per residue [10], to all heavy atoms being explicitly represented [26], and their energetic complexity varies from “perfectly-funneled” landscapes, to Hamiltonians that include various flavors of non-native interactions [27,28,29]. See http://smog-server.org/smog for details and the user guide
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