@Misc{brunner04,
author = {Stephan Brunner and Charles F. F. Karney},
title = {Method and Computer Program Product for Drug Discovery
Using Weighted Grand Canonical {M}etropolis {M}onte
{C}arlo Sampling},
month = dec,
year = 2004,
day = 30,
note = {U.S. Patent Application No.
\HREF{http://appft1.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PG01&p=1&u=/netahtml/PTO/srchnum.html&r=1&f=G&l=50&s1=20040267456.PGNR.&OS=DN/20040267456&RS=DN/20040267456}{10/794,181},
filed Mar. 8, 2004; Publication No.
\HREF{http://www.freepatentsonline.com/20040267456.html}{2004/0267456}},
reprint = {US20040267456},
annote = {Earlier version: U.S. Patent Application No. 10/748,708,
filed Dec. 31, 2003; Publication No.
\HREF{http://www.freepatentsonline.com/20040267509.html}{2004/0267509},
Dec. 30, 2004},
abstract = {A method and computer program product for modeling a
system that includes a protein and a plurality of
different fragment types in order to identify drug
leads is presented. The basis of the method is a
weighted Metropolis Monte Carlo approach for sampling
the grand canonical ensemble. This method
distinguishes itself from an energy minimization
approach in that it provides fragment distributions
which are consistent with thermal fluctuations at
physiologically relevant temperatures. The weighted
Metropolis Monte Carlo scheme performs a quasi-uniform
sampling of all regions of interest on the protein,
and, in this way, enables to resolve the wide range in
densities of the thermodynamic distribution which
could not be achieved by a non-weighted Metropolis
scheme. Making use of the properties of the grand
canonical ensemble, the affinity of fragments for
different regions on the protein surface can be
efficiently computed, using a so-called
“simulated annealing of the chemical
potential” process. A protein binding site is
then identified as a region with high affinity for
multiple fragments with a diverse set of
physico-chemical properties. Within a binding site,
assembly of fragments into drug leads is finally
carried out based on binding affinity of the different
fragments, on geometric proximity, and a variety of
rules by which organic fragments may bond together.},
oabstract = {A method and computer program product for modeling a
system that includes a protein and a plurality of
fragments in order to identify drug leads is
presented. The basis of the method is a weighted
Metropolis Monte Carlo approach for sampling the Grand
Canonical ensemble. This method distinguishes itself
from an energy minimization approach in that it
provides fragment distributions which are consistent
with thermal fluctuations at physiologically relevant
temperatures. The weighted Metropolis Monte Carlo
scheme performs a quasi-uniform sampling of all
regions of interest on the protein, and, in this way,
enables to resolve the wide range in densities of the
thermodynamic distribution which could not be achieved
by a non-weighted Metropolis scheme. Making use of
the properties of the Grand Canonical ensemble, the
affinity of fragments for different regions on the
protein surface can be efficiently computed. A
protein binding site is then identified as a region
with high affinity for multiple fragments with a
diverse set of physico-chemical properties. Within a
binding site, assembly of fragments into drug leads is
finally carried out based on binding affinity of the
different fragments, on geometric proximity, and a
variety of rules by which organic fragments may bond
together.}
}