Type	Attachment
URL	http://www.nature.com/nbt/journal/v28/n9/pdf/nbt.1672.pdf
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Type	Journal Article
Author	Christopher S Henry
Author	Matthew DeJongh
Author	Aaron A Best
Author	Paul M Frybarger
Author	Ben Linsay
Author	Rick L Stevens
URL	http://dx.doi.org/10.1038/nbt.1672
Volume	28
Issue	9
Pages	977-982
Publication	Nat Biotech
ISSN	1087-0156
Date	2010
Journal Abbr	Nat Biotech
DOI	10.1038/nbt.1672
Accessed	2011-08-24 14:15:27
Library Catalog	Nature

Type	Attachment
URL	http://www.nature.com/msb/journal/v7/n1/pdf/msb201135.pdf
Accessed	2011-08-24 14:10:45
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Type	Journal Article
Author	Ori Folger
Author	Livnat Jerby
Author	Christian Frezza
Author	Eyal Gottlieb
Author	Eytan Ruppin
Author	Tomer Shlomi
URL	http://dx.doi.org/10.1038/msb.2011.35
Volume	7
Publication	Mol Syst Biol
Date	June 21, 2011
Journal Abbr	Mol Syst Biol
DOI	10.1038/msb.2011.35
Accessed	2011-08-24 14:10:44
Library Catalog	Nature

Type	Attachment
URL	http://www.nature.com/nrg/journal/v12/n9/full/nrg3033.html
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URL	http://www.nature.com/nrg/journal/v12/n9/pdf/nrg3033.pdf
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Type	Journal Article
Author	Balázs Papp
Author	Richard A. Notebaart
Author	Csaba Pál
URL	http://dx.doi.org/10.1038/nrg3033
Volume	12
Issue	9
Pages	591-602
Publication	Nat Rev Genet
ISSN	1471-0056
Date	2011
Journal Abbr	Nat Rev Genet
DOI	10.1038/nrg3033
Accessed	2011-08-23 13:43:26
Library Catalog	Nature

Type	Journal Article
Author	C Jarrold
Author	A D Baddeley
Author	A K Hewes
URL	http://www.ncbi.nlm.nih.gov/pubmed/10390025
Volume	37
Issue	6
Pages	637-651
Publication	Neuropsychologia
ISSN	0028-3932
Date	Jun 1999
Extra	PMID: 10390025
Journal Abbr	Neuropsychologia
Accessed	2011-07-20 18:44:56
Library Catalog	NCBI PubMed
Abstract	Wang and Bellugi [J clin exp Neuropsychol 1994;16:317 22] have suggested that Down's and Williams syndrome might be associated with specific and contrasting working memory deficits; with impaired verbal short-term memory in Down's syndrome, and a visuo-spatial short-term memory deficit in Williams syndrome. In two studies we examine whether these apparent deficits might simply be a consequence of the general pattern of learning difficulties associated with these disorders. Experiment 1 compared verbal and visuo-spatial short-term memory abilities in these groups, using analysis of covariance to control for mental age differences. In Experiment 2 individuals with Williams syndrome were matched to control groups for non-verbal mental age, and the short-term memory abilities of these matched groups were compared. The results of both experiments are broadly consistent with those reported by Wang and Bellugi, and support the view that working memory can be dissociated into separate subsystems.
Short Title	Genetically dissociated components of working memory

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URL	http://www.nature.com/nchembio/journal/v5/n5/pdf/nchembio.155.pdf
Accessed	2011-06-28 18:27:23
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Type	Journal Article
Author	Yu Chen
Author	Brian K Shoichet
URL	http://dx.doi.org/10.1038/nchembio.155
Volume	5
Issue	5
Pages	358-364
Publication	Nat Chem Biol
ISSN	1552-4450
Date	May 2009
Journal Abbr	Nat Chem Biol
DOI	10.1038/nchembio.155
Accessed	2011-06-28 18:27:22
Library Catalog	Nature

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URL	http://www.nature.com/nrd/journal/v7/n9/pdf/nrd2606.pdf
Accessed	2011-06-28 18:26:39
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Type	Journal Article
Author	Maurizio Pellecchia
Author	Ivano Bertini
Author	David Cowburn
Author	Claudio Dalvit
Author	Ernest Giralt
Author	Wolfgang Jahnke
Author	Thomas L. James
Author	Steve W. Homans
Author	Horst Kessler
Author	Claudio Luchinat
Author	Bernd Meyer
Author	Hartmut Oschkinat
Author	Jeff Peng
Author	Harald Schwalbe
Author	Gregg Siegal
URL	http://dx.doi.org/10.1038/nrd2606
Volume	7
Issue	9
Pages	738-745
Publication	Nat Rev Drug Discov
ISSN	1474-1776
Date	2008
Journal Abbr	Nat Rev Drug Discov
DOI	10.1038/nrd2606
Accessed	2011-06-28 18:26:38
Library Catalog	Nature
Short Title	Perspectives on NMR in drug discovery

Type	Attachment
URL	http://www.nature.com/nrd/journal/v3/n8/pdf/nrd1467.pdf
Accessed	2011-06-28 18:26:19
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Type	Journal Article
Author	David C. Rees
Author	Congreve
Author	Christopher W. Murray
Author	Robin Carr
URL	http://dx.doi.org/10.1038/nrd1467
Volume	3
Issue	8
Pages	660-672
Publication	Nat Rev Drug Discov
ISSN	1474-1776
Date	2004
Journal Abbr	Nat Rev Drug Discov
DOI	10.1038/nrd1467
Accessed	2011-06-28 18:26:18
Library Catalog	Nature

Type	Attachment
URL	http://www.nature.com/nrd/journal/v6/n3/pdf/nrd2220.pdf
Accessed	2011-06-28 18:25:52
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Type	Journal Article
Author	Philip J. Hajduk
Author	Jonathan Greer
URL	http://dx.doi.org/10.1038/nrd2220
Volume	6
Issue	3
Pages	211-219
Publication	Nat Rev Drug Discov
ISSN	1474-1776
Date	March 2007
Journal Abbr	Nat Rev Drug Discov
DOI	10.1038/nrd2220
Accessed	2011-06-28 18:25:51
Library Catalog	Nature
Short Title	A decade of fragment-based drug design

Type	Attachment
URL	http://www.biomedcentral.com/content/pdf/1471-2164-9-102.pdf
Accessed	2011-06-24 14:57:51
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Type	Journal Article
Author	Yasushi Ishihama
Author	Thorsten Schmidt
Author	Juri Rappsilber
Author	Matthias Mann
Author	F Ulrich Hartl
Author	Michael Kerner
Author	Dmitrij Frishman
URL	http://www.biomedcentral.com/1471-2164/9/102
Volume	9
Issue	1
Pages	102
Publication	BMC Genomics
ISSN	1471-2164
Date	2008
DOI	10.1186/1471-2164-9-102
Accessed	2011-06-24 14:57:50
Library Catalog	BioMed Central and More
Abstract	BACKGROUND:Knowledge about the abundance of molecular components is an important prerequisite for building quantitative predictive models of cellular behavior. Proteins are central components of these models, since they carry out most of the fundamental processes in the cell. Thus far, protein concentrations have been difficult to measure on a large scale, but proteomic technologies have now advanced to a stage where this information becomes readily accessible.RESULTS:Here, we describe an experimental scheme to maximize the coverage of proteins identified by mass spectrometry of a complex biological sample. Using a combination of LC-MS/MS approaches with protein and peptide fractionation steps we identified 1103 proteins from the cytosolic fraction of the Escherichia coli strain MC4100. A measure of abundance is presented for each of the identified proteins, based on the recently developed emPAI approach which takes into account the number of sequenced peptides per protein. The values of abundance are within a broad range and accurately reflect independently measured copy numbers per cell.As expected, the most abundant proteins were those involved in protein synthesis, most notably ribosomal proteins. Proteins involved in energy metabolism as well as those with binding function were also found in high copy number while proteins annotated with the terms metabolism, transcription, transport, and cellular organization were rare. The barrel-sandwich fold was found to be the structural fold with the highest abundance. Highly abundant proteins are predicted to be less prone to aggregation based on their length, pI values, and occurrence patterns of hydrophobic stretches. We also find that abundant proteins tend to be predominantly essential. Additionally we observe a significant correlation between protein and mRNA abundance in E. coli cells.CONCLUSION:Abundance measurements for more than 1000 E. coli proteins presented in this work represent the most complete study of protein abundance in a bacterial cell so far. We show significant associations between the abundance of a protein and its properties and functions in the cell. In this way, we provide both data and novel insights into the role of protein concentration in this model organism.

Type	Attachment
URL	http://www.nature.com/msb/journal/v3/n1/pdf/msb4100155.pdf
Accessed	2011-05-31 18:24:45
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Type	Journal Article
Author	Adam M Feist
Author	Christopher S Henry
Author	Jennifer L Reed
Author	Markus Krummenacker
Author	Andrew R Joyce
Author	Peter D Karp
Author	Linda J Broadbelt
Author	Vassily Hatzimanikatis
Author	Bernhard O Palsson
URL	http://dx.doi.org/10.1038/msb4100155
Volume	3
Publication	Mol Syst Biol
Date	June 26, 2007
Journal Abbr	Mol Syst Biol
DOI	10.1038/msb4100155
Accessed	2011-05-31 18:24:44
Library Catalog	Nature

Type	Attachment
URL	http://pubs.acs.org/doi/abs/10.1021/ci6003652
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URL	http://pubs.acs.org/doi/pdf/10.1021/ci6003652
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Type	Journal Article
Author	Harald Mauser
Author	Martin Stahl
URL	http://dx.doi.org/10.1021/ci6003652
Volume	47
Issue	2
Pages	318-324
Publication	Journal of Chemical Information and Modeling
Date	March 01, 2007
DOI	10.1021/ci6003652
Accessed	2011-05-19 21:21:44
Library Catalog	ACS Publications
Abstract	Chemical fragment spaces are combinations of molecular fragments and connection rules. They offer the possibility to encode an enormously large number of chemical structures in a very compact format. Fragment spaces are useful both in similarity-based (2D) and structure-based (3D) de novo design applications. We present disconnection and filtering rules leading to several thousand unique, medium size fragments when applied to databases of druglike molecules. We evaluate alternative strategies to select subsets of these fragments, with the aim of maximizing the coverage of known druglike chemical space with a strongly reduced set of fragments. For these evaluations, we use the Ftrees fragment space method. We assess a diversity-oriented selection method based on maximum common substructures and a method biased toward high frequency of occurrence of fragments and find that they are complementary to each other.

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URL	http://pubs.acs.org/doi/abs/10.1021/ci100232h
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URL	http://pubs.acs.org/doi/pdf/10.1021/ci100232h
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Type	Journal Article
Author	Ammar Abdo
Author	Naomie Salim
URL	http://dx.doi.org/10.1021/ci100232h
Volume	51
Issue	1
Pages	25-32
Publication	Journal of Chemical Information and Modeling
Date	January 24, 2011
DOI	10.1021/ci100232h
Accessed	2011-05-19 21:21:26
Library Catalog	ACS Publications
Abstract	Many of the conventional similarity methods assume that molecular fragments that do not relate to biological activity carry the same weight as the important ones. One possible approach to this problem is to use the Bayesian inference network (BIN), which models molecules and reference structures as probabilistic inference networks. The relationships between molecules and reference structures in the Bayesian network are encoded using a set of conditional probability distributions, which can be estimated by the fragment weighting function, a function of the frequencies of the fragments in the molecule or the reference structure as well as throughout the collection. The weighting function combines one or more fragment weighting schemes. In this paper, we have investigated five different weighting functions and present a new fragment weighting scheme. Later on, these functions were modified to combine the new weighting scheme. Simulated virtual screening experiments with the MDL Drug Data Report(23) and maximum unbiased validation data sets show that the use of new weighting scheme can provide significantly more effective screening when compared with the use of current weighting schemes.

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URL	http://pubs.acs.org/doi/abs/10.1021/ci960090k
Accessed	2011-05-19 21:21:06
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URL	http://pubs.acs.org/doi/pdf/10.1021/ci960090k
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Type	Journal Article
Author	John M. Barnard
Author	Geoff M. Downs
URL	http://dx.doi.org/10.1021/ci960090k
Volume	37
Issue	1
Pages	141-142
Publication	Journal of Chemical Information and Computer Sciences
Date	January 01, 1997
DOI	10.1021/ci960090k
Accessed	2011-05-19 21:21:01
Library Catalog	ACS Publications
Abstract	Barnard Chemical Information Ltd.'s software products for generation of fragment-dictionary-based chemical structure fingerprints and for hierarchical and nonhierarchical clustering of large files of structures are described.

Type	Attachment
URL	http://pubs.acs.org/doi/abs/10.1021/ci900123v
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URL	http://pubs.acs.org/doi/pdf/10.1021/ci900123v
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Type	Journal Article
Author	Naoki Tanaka
Author	Kazuki Ohno
Author	Tatsuya Niimi
Author	Ayako Moritomo
Author	Kenichi Mori
Author	Masaya Orita
URL	http://dx.doi.org/10.1021/ci900123v
Volume	49
Issue	12
Pages	2677-2686
Publication	Journal of Chemical Information and Modeling
Date	December 28, 2009
DOI	10.1021/ci900123v
Accessed	2011-05-19 21:20:14
Library Catalog	ACS Publications
Abstract	A wide variety of networks in various fields have been characterized as small-world networks. In scale-free networks, a representative class of small-world networks, numbers of contacts (degree distributions) of nodes follow power laws. Although several examples of power-law distributions have been found in the field of chemoinformatics, the network structures of chemical libraries have not been analyzed. Here, we show that small-world phenomena are observed not only in existing chemical libraries but also in virtual libraries generated from structurally diverse fragments when represented as networks. On the basis of this observation, we propose that an efficient compound-prioritization method of fragment-based drug discovery (FBDD) would be to select those fragments as a starting point such that the linked compounds become hubs in the library and therefore allow identification of many similar compounds when all-to-all fragment linkings are performed. Moreover, our analyses indicated that the variety of linkers had a marked influence on the network structure and thus on the diversity of the compounds synthesized by linking fragment hits.
Short Title	Small-World Phenomena in Chemical Library Networks

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URL	http://pubs.acs.org/doi/abs/10.1021/ci9501610
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URL	http://pubs.acs.org/doi/pdf/10.1021/ci9501610
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Type	Journal Article
Author	P. G. Mezey
Author	Z. Zimpel
Author	P. Warburton
Author	P. D. Walker
Author	D. G. Irvine
Author	D. G. Dixon
Author	B. Greenberg
URL	http://dx.doi.org/10.1021/ci9501610
Volume	36
Issue	3
Pages	602-611
Publication	Journal of Chemical Information and Computer Sciences
Date	January 01, 1996
DOI	10.1021/ci9501610
Accessed	2011-05-19 21:20:00
Library Catalog	ACS Publications
Abstract	A new, high-resolution shape-fragment database has been developed for computing ab initio quality molecular electron densities for polyaromatic hydrocarbons (PAHs) which play a significant role as toxicants in the environment. Using the new PAH electron density fragment database and the Molecular Electron Density Lego Assembler (MEDLA) method, one can generate detailed and reliable electron densities for virtually any of the PAH molecules. Accurate electron density shape representations for these molecules is essential in the study of detailed shape-toxicity correlations. One of our goals is to investigate the potential of detailed molecular shape analysis as a predictive tool in toxicological risk assessment. In this study we report the results of the first phase of the study:  the construction and testing of a high quality shape-fragment database for PAHs.

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URL	http://www.nature.com/msb/journal/v7/n1/pdf/msb201121.pdf
Accessed	2011-05-11 13:36:55
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Type	Journal Article
Author	Mary J Dunlop
Author	Zain Y Dossani
Author	Heather L Szmidt
Author	Hou Cheng Chu
Author	Taek Soon Lee
Author	Jay D Keasling
Author	Masood Z Hadi
Author	Aindrila Mukhopadhyay
URL	http://dx.doi.org/10.1038/msb.2011.21
Volume	7
Publication	Mol Syst Biol
Date	May 10, 2011
Journal Abbr	Mol Syst Biol
DOI	10.1038/msb.2011.21
Accessed	2011-05-11 13:36:53
Library Catalog	Nature

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Type	Journal Article
Author	Dallas R. Donohoe
Author	Nikhil Garge
Author	Xinxin Zhang
Author	Wei Sun
Author	Thomas M. O'Connell
Author	Maureen K. Bunger
Author	Scott J. Bultman
URL	http://www.cell.com/cell-metabolism/abstract/S1550-4131(11)00143-4
Volume	13
Issue	5
Pages	517-526
Publication	Cell Metabolism
ISSN	15504131
Date	5/2011
Journal Abbr	Cell Metabolism
DOI	10.1016/j.cmet.2011.02.018
Accessed	2011-05-10 17:12:15
Library Catalog	CrossRef

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URL	http://pubs.acs.org/doi/abs/10.1021/ci100476q
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URL	http://pubs.acs.org/doi/pdf/10.1021/ci100476q
Accessed	2011-05-05 18:46:57
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Type	Journal Article
Author	Yoshihiro Yamanishi
Author	Edouard Pauwels
Author	Hiroto Saigo
Author	Véronique Stoven
URL	http://dx.doi.org/10.1021/ci100476q
Publication	Journal of Chemical Information and Modeling
DOI	10.1021/ci100476q
Accessed	2011-05-05 18:46:55
Library Catalog	ACS Publications
Abstract	The identification of rules governing molecular recognition between drug chemical substructures and protein functional sites is a challenging issue at many stages of the drug development process. In this paper we develop a novel method to extract sets of drug chemical substructures and protein domains that govern drug-target interactions on a genome-wide scale. This is made possible using sparse canonical correspondence analysis (SCCA) for analyzing drug substructure profiles and protein domain profiles simultaneously. The method does not depend on the availability of protein 3D structures. From a data set of known drug-target interactions including enzymes, ion channels, G protein-coupled receptors, and nuclear receptors, we extract a set of chemical substructures shared by drugs able to bind to a set of protein domains. These two sets of extracted chemical substructures and protein domains form components that can be further exploited in a drug discovery process. This approach successfully clusters protein domains that may be evolutionary unrelated but that bind a common set of chemical substructures. As shown in several examples, it can also be very helpful for predicting new protein–ligand interactions and addressing the problem of ligand specificity. The proposed method constitutes a contribution to the recent field of chemogenomics that aims to connect the chemical space with the biological space.

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URL	http://www.biomedcentral.com/content/pdf/1471-2105-11-S1-S31.pdf
Accessed	2011-05-03 13:17:26
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Type	Journal Article
Author	Hiroto Saigo
Author	Masahiro Hattori
Author	Hisashi Kashima
Author	Koji Tsuda
URL	http://www.biomedcentral.com/1471-2105/11/S1/S31
Volume	11
Issue	Suppl 1
Pages	S31
Publication	BMC Bioinformatics
ISSN	1471-2105
Date	2010
DOI	10.1186/1471-2105-11-S1-S31
Accessed	2011-05-03 13:17:25
Library Catalog	BioMed Central and More
Abstract	BACKGROUND:Understanding of secondary metabolic pathway in plant is essential for finding druggable candidate enzymes. However, there are many enzymes whose functions are not yet discovered in organism-specific metabolic pathways. Towards identifying the functions of those enzymes, assignment of EC numbers to the enzymatic reactions they catalyze plays a key role, since EC numbers represent the categorization of enzymes on one hand, and the categorization of enzymatic reactions on the other hand.RESULTS:We propose reaction graph kernels for automatically assigning EC numbers to unknown enzymatic reactions in a metabolic network. Reaction graph kernels compute similarity between two chemical reactions considering the similarity of chemical compounds in reaction and their relationships. In computational experiments based on the KEGG/REACTION database, our method successfully predicted the first three digits of the EC number with 83% accuracy. We also exhaustively predicted missing EC numbers in plant's secondary metabolism pathway. The prediction results of reaction graph kernels on 36 unknown enzymatic reactions are compared with an expert's knowledge. Using the same data for evaluation, we compared our method with E-zyme, and showed its ability to assign more number of accurate EC numbers.CONCLUSION:Reaction graph kernels are a new metric for comparing enzymatic reactions.

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URL	http://www.ploscompbiol.org/article/fetchObjectAttachment.action?uri=info%3Adoi%2F10.1371%2Fjournal.pcbi.1002037&representation=PDF
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Type	Journal Article
Author	Li Xie
Author	Thomas Evangelidis
Author	Lei Xie
Author	Philip E. Bourne
URL	http://dx.doi.org/10.1371/journal.pcbi.1002037
Volume	7
Issue	4
Pages	e1002037
Publication	PLoS Comput Biol
Date	April 28, 2011
Journal Abbr	PLoS Comput Biol
DOI	10.1371/journal.pcbi.1002037
Accessed	2011-05-02 23:47:27
Library Catalog	PLoS Comput Biol
Abstract	The traditional approach to drug discovery of “one drug – one target – one disease” is insufficient, especially for complex diseases, like cancer. This inadequacy is partially addressed by accepting the notion of polypharmacology – one drug is likely to bind to multiple targets with varying affinity. However, to identify multiple targets for a drug is a complex and challenging task. We have developed a structural proteome-wide off-target determination pipeline by integrating computational methods for high-throughput ligand binding site comparison and binding free energy calculations to predict potential off-targets for known drugs. Here this method is applied to identify human off-targets for Nelfinavir, an antiretroviral drug with anti-cancer behavior. We propose inhibition by Nelfinavir of multiple protein kinase targets. We suggest that broad-spectrum low affinity binding by a drug or drugs to multiple targets may lead to a collective effect important in treating complex diseases such as cancer. The challenge is to understand enough about such processes so as to control them.
Short Title	Drug Discovery Using Chemical Systems Biology