IM-UFF: extending the Universal Force Field for interactive molecular modeling

Léonard Jaillet 1 Svetlana Artemova 1 Stephane Redon 1
1 NANO-D - Algorithms for Modeling and Simulation of Nanosystems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : The universal force field (UFF) is a broadly applicable classical force field that contains parameters for almost every atom type of the periodic table. This force field is non-reactive, i.e. the topology of the system under study is considered as fixed and no creation or breaking of covalent bonds is possible. This paper introduces interactive modeling-UFF (IM-UFF), an extension of UFF that combines the possibility to significantly modify molecular structures (as with reactive force fields) with a broad diversity of supported systems thanks to the universality of UFF. Such an extension lets the user easily build and edit molecular systems interactively while being guided by physics based inter-atomic forces. This approach introduces weighted atom types and weighted bonds, used to update topologies and atom parameterizations at every time step of a simulation. IM-UFF has been evaluated on a large set of benchmarks and is proposed as a self-contained implementation integrated in a new module for the SAMSON software platform for computational nanoscience available at http://www.samson-connect.net.
Document type :
Journal articles
Complete list of metadatas

Cited literature [40 references]  Display  Hide  Download

https://hal.inria.fr/hal-01676519
Contributor : Nano-D Equipe <>
Submitted on : Thursday, January 18, 2018 - 4:49:12 PM
Last modification on : Wednesday, April 11, 2018 - 1:59:15 AM
Long-term archiving on : Thursday, May 24, 2018 - 1:24:13 AM

File

IM-Uff_Unmarked.pdf
Files produced by the author(s)

Identifiers

Citation

Léonard Jaillet, Svetlana Artemova, Stephane Redon. IM-UFF: extending the Universal Force Field for interactive molecular modeling. Journal of Molecular Graphics and Modelling, Elsevier, 2017, 77, pp.350 - 362. ⟨10.1016/j.jmgm.2017.08.023⟩. ⟨hal-01676519⟩

Share

Metrics

Record views

463

Files downloads

326