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Recent advances in the UltraScan SOlution MOdeller (US-SOMO) hydrodynamic and small-angle scattering data analysis and simulation suite

  • Emre Brookes
  • Mattia Rocco
Original Article

Abstract

The UltraScan SOlution MOdeller (US-SOMO) is a comprehensive, public domain, open-source suite of computer programs centred on hydrodynamic modelling and small-angle scattering (SAS) data analysis and simulation. We describe here the advances that have been implemented since its last official release (#3087, 2017), which are available from release #3141 for Windows, Linux and Mac operating systems. A major effort has been the transition from the legacy Qt3 cross platform software development and user interface library to the modern Qt5 release. Apart from improved graphical support, this has allowed the direct implementation of the newest, almost two-orders of magnitude faster version of the ZENO hydrodynamic computation algorithm for all operating systems. Coupled with the SoMo-generated bead models with overlaps, ZENO provides the most accurate translational friction computations from atomic-level structures available (Rocco and Byron Eur Biophys J 44:417–431, 2015a), with computational times comparable with or faster than those of other methods. In addition, it has allowed us to introduce the direct representation of each atom in a structure as a (hydrated) bead, opening interesting new modelling possibilities. In the small-angle scattering (SAS) part of the suite, an indirect Fourier transform Bayesian algorithm has been implemented for the computation of the pairwise distance distribution function from SAS data. Finally, the SAS HPLC module, recently upgraded with improved baseline correction and Gaussian decomposition of not baseline-resolved peaks and with advanced statistical evaluation tools (Brookes et al. J Appl Cryst 49:1827–1841, 2016), now allows automatic top-peak frame selection and averaging.

Keywords

Hydrodynamics Hydration ZENO SAXS/SANS Pairwise distance distribution function Multi-resolution modelling 

Notes

Acknowledgements

This work was supported by a National Science Foundation (USA) Grant, CHE-1265817, to E. Brookes. Part of this work was presented at the 23rd International AUC Workshop and Symposium, Glasgow, Scotland, 23–28 July 2017. We thank Dr. P. Vachette (I2BC, CEA, CNRS, Université Paris-Sud, Orsay, France) for providing GNOM-generated P(r) vs. r data. We are indebted to D. Juba, W. Keyrouz and J. Douglas (NIST, Gaithersburg, MD, USA) for developments in the ZENO code; in addition, discussions with D. Audus (NIST) contributed to the development of the “vdW with overlaps” method.

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Copyright information

© European Biophysical Societies' Association 2018

Authors and Affiliations

  1. 1.Department of BiochemistryUniversity of Texas at San Antonio Health CenterSan AntonioUSA
  2. 2.Biopolimeri e Proteomica, Ospedale Policlinico San MartinoGenovaItaly

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