Theoretical exploration of fundamental biological processes involving the forced 
unraveling of multimeric proteins, the sliding motion in protein fibers and the 
mechanical deformation of biomolecular assemblies under physiological force 
loads is challenging even for distributed computing systems. Using a C(α)-based 
coarse-grained self organized polymer (SOP) model, we implemented the Langevin 
simulations of proteins on graphics processing units (SOP-GPU program). We 
assessed the computational performance of an end-to-end application of the 
program, where all the steps of the algorithm are running on a GPU, by profiling 
the simulation time and memory usage for a number of test systems. The ∼90-fold 
computational speedup on a GPU, compared with an optimized central processing 
unit program, enabled us to follow the dynamics in the centisecond timescale, 
and to obtain the force-extension profiles using experimental pulling speeds 
(v(f) = 1-10 μm/s) employed in atomic force microscopy and in optical 
tweezers-based dynamic force spectroscopy. We found that the mechanical 
molecular response critically depends on the conditions of force application and 
that the kinetics and pathways for unfolding change drastically even upon a 
modest 10-fold increase in v(f). This implies that, to resolve accurately the 
free energy landscape and to relate the results of single-molecule experiments 
in vitro and in silico, molecular simulations should be carried out under the 
experimentally relevant force loads. This can be accomplished in reasonable 
wall-clock time for biomolecules of size as large as 10(5) residues using the 
SOP-GPU package.