Fast clustering of long Molecular Dynamics
BitClust´s latest documentation is available here
BitClust is a Python command-line interface (CLI) conceived for fast
clustering of relatively long Molecular Dynamics trajectories following
Daura’s algorithm [1]. Retrieved clusters are roughly equivalent to those
reported by VMD’s internal command measure cluster but they are computed in a much faster way (see benchmark section for more details).
Nowadays very long simulations are carried on routinely. Enhanced sampling
methods like metadynamics, REMD, and accelerated dynamics allow escaping from
potential energy minima, returning trajectories that are conformationally sparsed
and where every cluster can be potentially important to detect and analyze. Improvements
on software designed to address this task is an important field of research.
BitClust offer is a classical tradeoff; RAM for speed. It can
calculate all pairwise distances between frames to run a clustering job and
then store them in memory instead of recalculating them whenever a cluster is found.
It is worth noting that used memory has been deeply optimized by encoding similarity distances
as bits (0 if the distance is less equal than a specified threshold, 1 otherwise).
This encoding result in a storage reduction as high as 32X/64X compared to similar algorithms
that saves the same information as single-precision/double-precision float values.
BitClust is built on the shoulders of two giants:
MDTraj software that allows a very fast
calculation of RMSD pairwise distances between all frames of trajectories in
a parallelized fashion and
bitarray third-party python library
which offers a memory-efficient data structure of bit-vectors (bit arrays)
and a set of bitwise operations that are the very heart of our clustering
implementation.
If you make use of BitClust in your scientific work, BitCool and cite it ;)
BitClust is licensed under GNU General Public License v3.0.
[1] Daura, X.; van Gunsteren, W. F.; Jaun, B.; Mark, A. E.; Gademann, K.; Seebach, D. Peptide Folding: When Simulation Meets Experiment. Angew. Chemie Int. Ed. 1999, 38 (1/2), 236–240.