Computational research of superoxide dismutase 1 and its modulators by CADD approaches to reveal potential drug candidates for amyotrophic lateral sclerosis treatment
Rafael Dolezal, Michaela Melikova, Jan Trejbal, Ondrej Krejcar
Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disease that leads to destruction of motoric neurons and finally to profound muscular paralysis. According to recent reports, this sporadic illness is linked with mutations of superoxide dismutase 1 (SOD1) enzyme that exhibits, besides its normal catalytic functions, also considerable side toxic effects. Experiments with SOD1 knock-out mice have shown no ALS symptoms, while transgenic mice with incorporated malfunctioning human gene G93A of SOD1 have developed the symptoms . The latest findings have also proved abundant proteinaceous aggregates of SOD1 in post-mortem brains of ALS patients. Although extensive biochemical experiments have confirmed a clear connection between malfunctioning SOD1 and ALS, especially the familial type, no drug has been discovered so far to treat ALS by modulation of SOD1. In the project implementing advanced computer-aided drug design (CADD) methods, we will investigate the structure of available SOD1 3D X-ray models by bioinformatics tools to reveal the extent of the mutations, further the structure of SOD1 will be deeply analyzed to find potential binding sites, then structure-based virtual screening (SBVS) by high-throughput flexible molecular docking will be performed to reveal potential drug candidates for modulation of SOD1. Finally, the interaction stability of top-scoring candidates in SOD1 will be evaluated by molecular dynamics. All these innovative computational approaches represent extremely demanding tasks, which need parallelized computer performance to be accomplished in reasonable time span. In particular, the most exhaustive calculations within SBVS will be carried out by self-developed applications utilizing “pleasing” parallelization principles and message passing interface (MPI) based techniques. Remaining tasks such as molecular dynamics will be performed with the use of CPU/GPU hybridized computational protocols.