U.S. Department of EnergyOffice of Scientific and Technical Information
Collision-free poisson motion planning in ultra high-dimensional molecular conformation spaces
Abstract
The function of protein, RNA, and DNA is modulated by fast, dynamic exchanges between three-dimensional conformations. Conformational sampling of biomolecules with exact and nullspace inverse kinematics, using rotatable bonds as revolute joints and noncovalent interactions as holonomic constraints, can accurately characterize these native ensembles. However, sampling biomolecules remains challenging owing to their ultra-high dimensional configuration spaces, and the requirement to avoid (self-) collisions, which results in low acceptance rates. In this paper, we present two novel mechanisms to overcome these limitations. First, we introduce temporary constraints between near-colliding links. The resulting constraint varieties instantaneously redirect the search for collision-free conformations, and couple motions between distant parts of the linkage. Second, we adapt a randomized Poisson-disk motion planner, which prevents local oversampling and widens the search, to ultra-high dimensions. Tests on several model systems show that the sampling acceptance rate can increase from 16% to 70%, and that the conformational coverage in loop modeling measured as average closeness to existing loop conformations doubled. Finally, correlated protein motions identified with our algorithm agree with those from MD simulations.
- Authors:
-
[1];
[2];
[3]
- Stanford Univ., CA (United States). Molecular and Cellular Physiology; SLAC National Accelerator Lab., Menlo Park, CA (United States). Bioscience Division
- Univ. of Erlangen-Nuremberg, Erlangen (Germany). Chair of Applied Dynamics
- SLAC National Accelerator Lab., Menlo Park, CA (United States). Bioscience Division
- Publication Date:
- Research Org.:
- SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Stanford Univ., CA (United States); Univ. of Erlangen-Nuremberg, Erlangen (Germany)
- Sponsoring Org.:
- USDOE; Deutsche Telekom Stiftung (Germany); Novo Nordisk Foundation (Denmark)
- OSTI Identifier:
- 1471534
- Grant/Contract Number:
- AC02-76SF00515; NNF15OC0015268
- Resource Type:
- Journal Article: Accepted Manuscript
- Journal Name:
- Journal of Computational Chemistry
- Additional Journal Information:
- Journal Volume: 39; Journal Issue: 12; Journal ID: ISSN 0192-8651
- Publisher:
- Wiley
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; 97 MATHEMATICS AND COMPUTING; high dimensional motion and path planning; collision-avoidance; poisson sampling; computational biology; inverse kinematics; molecular rigidity
Citation Formats
Fonseca, Rasmus, Budday, Dominik, and van den Bedem, Henry. Collision-free poisson motion planning in ultra high-dimensional molecular conformation spaces. United States: N. p., 2018.
Web. doi:10.1002/jcc.25138.
Fonseca, Rasmus, Budday, Dominik, & van den Bedem, Henry. Collision-free poisson motion planning in ultra high-dimensional molecular conformation spaces. United States. https://doi.org/10.1002/jcc.25138
Fonseca, Rasmus, Budday, Dominik, and van den Bedem, Henry. 2018.
"Collision-free poisson motion planning in ultra high-dimensional molecular conformation spaces". United States. https://doi.org/10.1002/jcc.25138. https://www.osti.gov/servlets/purl/1471534.
@article{osti_1471534,
title = {Collision-free poisson motion planning in ultra high-dimensional molecular conformation spaces},
author = {Fonseca, Rasmus and Budday, Dominik and van den Bedem, Henry},
abstractNote = {The function of protein, RNA, and DNA is modulated by fast, dynamic exchanges between three-dimensional conformations. Conformational sampling of biomolecules with exact and nullspace inverse kinematics, using rotatable bonds as revolute joints and noncovalent interactions as holonomic constraints, can accurately characterize these native ensembles. However, sampling biomolecules remains challenging owing to their ultra-high dimensional configuration spaces, and the requirement to avoid (self-) collisions, which results in low acceptance rates. In this paper, we present two novel mechanisms to overcome these limitations. First, we introduce temporary constraints between near-colliding links. The resulting constraint varieties instantaneously redirect the search for collision-free conformations, and couple motions between distant parts of the linkage. Second, we adapt a randomized Poisson-disk motion planner, which prevents local oversampling and widens the search, to ultra-high dimensions. Tests on several model systems show that the sampling acceptance rate can increase from 16% to 70%, and that the conformational coverage in loop modeling measured as average closeness to existing loop conformations doubled. Finally, correlated protein motions identified with our algorithm agree with those from MD simulations.},
doi = {10.1002/jcc.25138},
url = {https://www.osti.gov/biblio/1471534},
journal = {Journal of Computational Chemistry},
issn = {0192-8651},
number = 12,
volume = 39,
place = {United States},
year = {Fri Jan 05 00:00:00 EST 2018},
month = {Fri Jan 05 00:00:00 EST 2018}
}
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Figure 1: Kinematic representation of molecules and constraints. a) A molecular graph with double bonds and partial double bonds highlighted. After edge-contractions these atoms become a single rigid body vertex. The remaining bonds can rotate around the bond axis and are described by dihedral angles. b) Small section of amore »
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