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Manuscript Title: SLDMOL: A tool for the structural characterization of thermally disordered membrane proteins.
Authors: Joseph E. Curtis, Hailiang Zhang, Hirsh Nanda
Program title: SLDMOL
Catalogue identifier: AETX_v1_0
Distribution format: tar.gz
Journal reference: Comput. Phys. Commun. 185(2014)3010
Programming language: Python.
Computer: PC/Mac.
Operating system: 32- and 64-bit Linux (Ubuntu 10.04, Centos 5.6) and Mac OS X (10.7 - 10.9).
RAM: 1 GB
Keywords: Neutron reflectivity, X-ray reflectivity, Membrane proteins, Disordered proteins, Computer modeling.
Classification: 3.

External routines: Python 2.6.5, numpy 1.4.0, scipy 0.8.0, Tcl 8.5, Tk 8.5, Mac installation requires Xcode 3 development tools.

Subprograms used:
Cat Id Title Reference
AEKL_v1_0 SASSIE CPC 183(2012)382

Nature of problem:
Reflectivity is a powerful technique to study the conformation of biological molecules at surface and interfaces. Open source software that facilitates computational modeling and interpretation of experimental results in terms of detailed molecular structure is currently lacking.

Solution method:
SLDMOL takes one or an ensemble of atomistic configurations of proteins and compares them to 1-D scattering length density (SLD) profiles determined from reflectivity experiments. Protein structures can be generated independently (e.g. molecular dynamics simulations) or through the SASSIE software package. SLDMOL performs an optimization to determine which structure best fits the SLD profile. Structures can also be averaged either directly or through a Monte-Carlo weighting algorithm. Finally SLDMOL allows the modeling of reflectivity experiments through the in-silico selective deuteration of amino acids and the calculation of SLD profiles in a number of different aqueous solvent contrasts.

Running time:
Varies depending on application. Typically 10 minutes to 24 hours depending on the number of structures to be evaluated.