Many (if not most) biological processes require structural, configurational, or compositional flexibility. DNA binding proteins, for example, are often highly flexible yet demonstrate only a few configurations that are functionally significant. Other systems frequently contain components that exist in multiple oligomeric states or assemblies, each with distinctly different behavior. Once such way of analyzing the averaged data obtained from such heterogeneous conditions is with a minimal ensemble, a collection of components that together are able to recapitulate the available experimental data.
MESMER (Minimal Ensemble Solutions to Multiple Experimental Restraints) seeks to assist researchers in analyzing the experimentally averaged data obtained from any number of experimental techniques. SAXS, NMR pseudocontact shifts, residual dipolar coupling, FRET, and DEER data, for example, can all be simultaneously fit by MESMER in order to provide the both the range of potential structures or to identify particularly prominent states of a given system. MESMER is easy to use, open source, highly customizable, and comes with an array of tools to fit, analyze, and interpret the data and results from your system.
Molecular dynamics are essential for life, and nuclear magnetic resonance (NMR) spectroscopy has been used extensively to characterize these phenomena since the 1950s. For the past 15 years, the Carr-Purcell Meiboom-Gill relaxation dispersion (CPMG RD) NMR experiment has afforded advanced NMR labs access to kinetic, thermodynamic, and structural details of protein and RNA dynamics in the crucial μs-ms time window. However, analysis of RD data is challenging because datasets are often large and require many non-linear fitting parameters, thereby confounding assessment of accuracy. Moreover, novice CPMG experimentalists face an additional barrier because current software options lack an intuitive user interface and extensive documentation.
We present the open-source software package GUARDD (Graphical User-friendly Analysis of Relaxation Dispersion Data), which is designed to organize, automate, and enhance the analytical procedures which operate on CPMG RD data (guardd-master.zip). This MATLAB-based program includes a graphical user interface, permits global fitting to multi-field, multi-temperature, multi-coherence data, and implements χ 2-mapping procedures, via grid-search and Monte Carlo methods, to enhance and assess fitting accuracy. The presentation features allow users to seamlessly traverse the large amount of results, and the RD Simulator feature can help design future experiments as well as serve as a teaching tool for those unfamiliar with RD phenomena. Based on these innovative features, we expect that GUARDD will fill a well-defined gap in service of the RD NMR community.