Parallel GPGPU Evaluation of Small Angle X-Ray Scattering Profiles in a Markov Chain Monte Carlo Framework - Biomedical Engineering Systems and Technologies - page 200

Parallel GPGPU Evaluation of Small Angle X-Ray
Scattering Profiles in a Markov Chain Monte Carlo
Framework

Lubomir D. Antonov , Christian Andreetta , and Thomas Hamelryck

The Bioinformatics Section, Department of Biology, University of Copenhagen, Denmark
[e-mail]

Abstract. Inference of protein structure from experimental data is of crucial in-
terest in science, medicine and biotechnology. Low-resolution methods, such as
small angle X-ray scattering (SAXS), play a major role in investigating important
biological questions regarding the structure of proteins in solution.
To infer protein structure from SAXS data, it is necessary to calculate the
expected experimental observations given a protein structure, by making use of
a so-called forward model. This calculation needs to be performed many times
during a conformational search. Therefore, computational efficiency directly de-
termines the complexity of the systems that can be explored.
We present an efficient implementation of the forward model for SAXS with
full hardware utilization of Graphics Processor Units (GPUs). The proposed al-
gorithm is orders of magnitude faster than an efficient CPU implementation, and
implements a caching procedure employed in the partial forward model evalua-
tions within a Markov chain Monte Carlo framework.

Keywords: SAXS, GPU, GPGPU, MCMC, Protein Structure Determination,
OpenCL.

1 Introduction

Proteins play a crucial role in science, medicine and biotechnology: without them, cel-
lular activities such as catalysis, signaling and regulation would be next to impossible.
Protein function is determined by protein structure, which has been proven to be deter-
mined by the amino acid sequence [1].
Despite encouraging improvements, determining the ensemble of possible confor-
mations in solution is far from an accomplished goal. High resolution experimental
methods, notably X-ray crystallography and Nuclear Magnetic Resonance (NMR), can
only partially provide information on such ensembles, and encounter several limitations
in fully describing the flexibility of large systems in physiological conditions [2].
Low resolution methods, on the other hand, can more easily provide information
on such ensembles. In particular, Small Angle X-ray Scattering (SAXS) provides in-
formation on the excess electron density of the sample versus the surrounding envi-
ronment. Recently, with the advent of automated high-throughput SAXS analysis of

These authors contributed equally to this work.