arrow
Return

Programmable Potentials: Approximate N-body potentials from coarse-level logic

delete2016-09-27
delete0
delete
OA
AI
G
Gunjan Thakur *
R
Ryan Mohr
I
Igor Mezić
DOI:10.1038/srep33415delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
This paper gives a systematic method for constructing an N-body potential, approximating the true potential, that accurately captures meso-scale behavior of the chemical or biological system using pairwise potentials coming from experimental data or ab initio methods. The meso-scale behavior is translated into logic rules for the dynamics. Each pairwise potential has an associated logic function that is constructed using the logic rules, a class of elementary logic functions, and AND, OR, and NOT gates. The effect of each logic function is to turn its associated potential on and off. The N-body potential is constructed as linear combination of the pairwise potentials, where the coefficients of the potentials are smoothed versions of the associated logic functions. These potentials allow a potentially low-dimensional description of complex processes while still accurately capturing the relevant physics at the meso-scale. We present the proposed formalism to construct coarse-grained potential models for three examples: an inhibitor molecular system, bond breaking in chemical reactions, and DNA transcription from biology. The method can potentially be used in reverse for design of molecular processes by specifying properties of molecules that can carry them out.
Keywords:
RNA-POLYMERASE-II
MECHANISM
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Scientific Reports cover
Scientific Reports
IF:
3.9
Papers:
27.8W
Citations:
83.5W

Organization

H
Harvard University
Scholars:
26.5W
Papers: 22.0W
Citations: 28.7W
University of California System cover
University of California System
Scholars:
37.5W
Papers: 33.7W
Citations: 6.6K