Journal
JOURNAL OF CHEMICAL INFORMATION AND MODELING
Volume 57, Issue 4, Pages 650-656Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.jcim.7b00096
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Funding
- EPSRC via the ICSS DTC [EP/G03690X/1]
- Biotechnology and Biological Sciences Research Council [BB/H000658/1] Funding Source: researchfish
- Engineering and Physical Sciences Research Council [EP/M022609/1] Funding Source: researchfish
- BBSRC [BB/H000658/1] Funding Source: UKRI
- EPSRC [EP/M022609/1] Funding Source: UKRI
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Development of coarse-grained (CG) molecular dynamics models is often a laborious process which commonly relies upon approximations, to similar models, rather than systematic parametrization. PyCGTOOL automates much of the construction of CG models via calculation of both equilibrium values and force constants of internal coordinates directly from atomistic molecular dynamics simulation trajectories. The derivation of bespoke parameters from atomistic simulations improves the quality of the CG model compared to the use of generic parameters derived from other molecules, while automation greatly reduces the time required. The ease of configuration of PyCGTOOL enables the rapid investigation of multiple atom-to-bead mappings and topologies. Although we present PyCGTOOL used in combination with the GROMACS Molecular dynamics engine its use of standard trajectory input libraries means that it is in principle compatible with other software.
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