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Atomic-Level Simulation and Modeling of Biomacromolecules

Vaidehi, Nagarajan and Goddard, William A., III (2001) Atomic-Level Simulation and Modeling of Biomacromolecules. In: Computational Modeling of Genetic and Biochemical Networks. MIT Press , Cambridge, MA, pp. 161-188. ISBN 0262024810. https://resolver.caltech.edu/CaltechAUTHORS:20190627-122009397

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Abstract

In principle, all the problems in biology could be solved by solving the time-dependent Schroedinger equation (quantum mechanics, QM). This would lead to a detailed under-standing of the role that molecular-level interactions play in determining the fundamental biochemistry at the heart of biology and pharmacology. The difficulty is the vast range of length and time scales, from a nitrous oxide molecule to an organ (heart, lung), which makes a QM solution both impractical and useless. It is impractical because there are too many degrees of freedom describing the motions of the electrons and atoms, whereas in the functioning of an organ it may be only the rate of transfer across some membrane. The solution to both problems is the hierarchical strategy outlined in figure 6.1. We average over the scale of electrons (from QM) to describe the forces on atoms (the force field, FF), then average over the dynamics of atoms (molecular dynamics, MD) to describe the motions of large biomolecules, then average over the molecular scale to obtain the properties of membranes, then average over the components in a cell, then average over the cells to describe a part of an organ. The strategy is to develop a methodology for going between these various levels so that first principle’s theory can be used to predict the properties of new systems.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://cognet.mit.edu/pdfviewer/book/9780262269056/chap6PublisherChapter
ORCID:
AuthorORCID
Goddard, William A., III0000-0003-0097-5716
Additional Information:© 2001 Massachusetts Institute of Technology. This research was funded by the National Science Foundation (grants CHE-95-22179, GCAG CHE 95-2217, and SGER DBI-9708929), U.S. Department of Energy (DOE)-BCTR (David Boron), and the National Institute of Child Health and Development (National Institutes of Health) grant HD3638502. The Materials Simulation Center is supported by grants from Army Research Office (DURIP), DOE-ASCI, British Petroleum Chemical, the Beckman Institute, Seiko-Epson, Exxon, Owens-Corning, Dow Chemical, Avery Dennison, Chevron Petroleum Technology, Chevron Chemical Co., Chevron Research Technology, and Asahi Chemical. Some calculations were carried out on the National Center for Supercomputing Applications (L. Smarr) at the University of Urbana.
Funders:
Funding AgencyGrant Number
NSFCHE-95-22179
NSFCHE 95-2217
NSFDBI-9708929
Department of Energy (DOE)UNSPECIFIED
NIHHD3638502
Army Research Office (DURIP)UNSPECIFIED
British Petroleum ChemicalUNSPECIFIED
Caltech Beckman InstituteUNSPECIFIED
Seiko-EpsonUNSPECIFIED
ExxonUNSPECIFIED
Owens-CorningUNSPECIFIED
Dow ChemicalUNSPECIFIED
Avery DennisonUNSPECIFIED
Chevron Petroleum TechnologyUNSPECIFIED
Chevron Chemical Co.UNSPECIFIED
Chevron Research TechnologyUNSPECIFIED
Asahi ChemicalUNSPECIFIED
Other Numbering System:
Other Numbering System NameOther Numbering System ID
WAG0482
Record Number:CaltechAUTHORS:20190627-122009397
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20190627-122009397
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:96788
Collection:CaltechAUTHORS
Deposited By: Donna Wrublewski
Deposited On:27 Jun 2019 20:05
Last Modified:03 Oct 2019 21:25

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