@article{Naylor_2009,
  doi = {10.1038/nchembio.150},
  url = {http://dx.doi.org/10.1038/nchembio.150},
  year = {2009},
  month = {feb},
  publisher = {Nature Publishing Group},
  volume = {5},
  number = {4},
  pages = {220--226},
  author = {Edmund Naylor and Abdelilah Arredouani and Sridhar R Vasudevan and Alexander M Lewis and Raman Parkesh and Akiko Mizote and Daniel Rosen and Justyn M Thomas and Minoru Izumi and A Ganesan and Antony Galione and Grant C Churchill},
  title = {{Identification of a chemical probe for {NAADP} by virtual screening}},
  journal = {Nature Chemical Biology},
}


@article{Nicholls2010,
  author = {A. Nicholls and G. B. McGaughey and R. P. Sheridan and A. C. Good and G. Warren and M. Mathieu and S. W. Muchmore and S. P. Brown and J. A. Grant and J. A. Haigh},
  journal = {{J Med Chem} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/20158188}{20158188}] [PubMed Central:\href{http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2874267}{PMC2874267}] [doi:\href{http://dx.doi.org/10.1021/jm900818s}{10.1021/jm900818s}]}},
  number = {10},
  pages = {3862},
  publisher = {American Chemical Society},
  title = {{Molecular shape and medicinal chemistry: a perspective}},
  volume = {53},
  year = {2010},
}


@article{RushIII2005,
  author = {T. S. {Rush III} and J. A. Grant and L. Mosyak and A. Nicholls},
  journal = {{J Med Chem} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/15743191}{15743191}] [doi:\href{http://dx.doi.org/10.1021/jm040163o}{10.1021/jm040163o}]}},
  number = {5},
  pages = {1489--1495},
  publisher = {ACS Publications},
  title = {{A shape-based 3-D scaffold hopping method and its application to a bacterial protein-protein interaction}},
  volume = {48},
  year = {2005},
  issn = {0022-2623},
}


@article{McMasters2009,
  author = {D. R. McMasters and M. Garcia-Calvo and V. Maiorov and M. E. McCann and R. D. Meurer and H. G. Bull and J. M. Lisnock and K. L. Howell and R. J. DeVita},
  journal = {{Bioorganic \& medicinal chemistry letters} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/19410454}{19410454}] [doi:\href{http://dx.doi.org/10.1016/j.bmcl.2009.04.031}{10.1016/j.bmcl.2009.04.031}]}},
  number = {11},
  pages = {2965--2968},
  publisher = {Elsevier},
  title = {{Spiroimidazolidinone NPC1L1 inhibitors. 1: Discovery by 3D-similarity-based virtual screening}},
  volume = {19},
  year = {2009},
  issn = {0960-894X},
}


@article{Muchmore2006,
  author = {S. W. Muchmore and A. J. Souers and I. Akritopoulou-Zanze},
  journal = {{Chemical biology \& drug design} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/16492165}{16492165}] [doi:\href{http://dx.doi.org/10.1111/j.1747-0285.2006.00341.x}{10.1111/j.1747-0285.2006.00341.x}]}},
  number = {2},
  pages = {174--176},
  publisher = {Wiley Online Library},
  title = {{The Use of Three-Dimensional Shape and Electrostatic Similarity Searching in the Identification of a Melanin Concentrating Hormone Receptor 1 Antagonist}},
  volume = {67},
  year = {2006},
  issn = {1747-0285},
}


@article{Rees2004,
  author = {D. C. Rees and M. Congreve and C. W. Murray and R. Carr},
  journal = {{Nature Reviews Drug Discovery} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/15286733}{15286733}] [doi:\href{http://dx.doi.org/10.1038/nrd1467}{10.1038/nrd1467}]}},
  number = {8},
  pages = {660--672},
  publisher = {Nature Publishing Group},
  title = {{Fragment-based lead discovery}},
  volume = {3},
  year = {2004},
}


@article{Congreve2008,
  author = {Miles Congreve and Gianni Chessari and Dominic Tisi and Andrew J. Woodhead},
  journal = {J Med Chem},
  month = {{May} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/18457385}{18457385}] [doi:\href{http://dx.doi.org/10.1021/jm8000373}{10.1021/jm8000373}]}},
  number = {13},
  pages = {3661--3680},
  publisher = {American Chemical Society},
  title = {{Recent Developments in Fragment-Based Drug Discovery}},
  volume = {51},
  year = {2008},
  issn = {0022-2623},
}


@article{Ebalunode2008,
  author = {Jerry Osagie Ebalunode and Zheng Ouyang and Jie Liang and Weifan Zheng},
  journal = {J. Chem. Inf. Model.},
  month = {{Apr} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/18396858}{18396858}] [doi:\href{http://dx.doi.org/10.1021/ci700368p}{10.1021/ci700368p}]}},
  number = {4},
  pages = {889--901},
  publisher = {American Chemical Society},
  title = {{Novel Approach to Structure-Based Pharmacophore Search Using Computational Geometry and Shape Matching Techniques}},
  volume = {48},
  year = {2008},
  abstract = {Computationally efficient structure-based virtual screening methods have recently been reported that seek to find effective means to utilize experimental structure information without employing detailed molecular docking calculations. These tools can be coupled with efficient experimental screening technologies to improve the probability of identifying hits and leads for drug discovery research. Commercial software ROCS (rapid overlay of chemical structures) from Open Eye Scientific is such an example, which is a shape-based virtual screening method using the 3D structure of a ligand, typically from a bound X-ray costructure, as the query. We report here the development of a new structure-based pharmacophore search method (called Shape4) for virtual screening. This method adopts a variant of the ROCS shape technology and expands its use to work with an empty crystal structure. It employs a rigorous computational geometry method and a deterministic geometric casting algorithm to derive the negative image (i.e., pseudoligand) of a target binding site. Once the negative image (or pseudoligand) is generated, an efficient shape comparison algorithm in the commercial OE SHAPE Toolkit is adopted to compare and match small organic molecules with the shape of the pseudoligand. We report the detailed computational protocol and its computational validation using known biologically active compounds extracted from the WOMBAT database. Models derived for five selected targets were used to perform the virtual screening experiments to obtain the enrichment data for various virtual screening methods. It was found that our approach afforded similar or better enrichment ratios than other related methods, often with better diversity among the top ranking computational hits.},
  issn = {1549-9596},
}


@article{Vainio2009,
  author = {M. J. Vainio and J. S. Puranen and M. S. Johnson},
  journal = {{Journal of chemical information and modeling} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/19434847}{19434847}] [doi:\href{http://dx.doi.org/10.1021/ci800315d}{10.1021/ci800315d}]}},
  number = {2},
  pages = {492--502},
  publisher = {ACS Publications},
  title = {{ShaEP: molecular overlay based on shape and electrostatic potential}},
  volume = {49},
  year = {2009},
  issn = {1549-9596},
}


@article{Cheeseright2006,
  author = {T. Cheeseright and M. Mackey and S. Rose and A. Vinter},
  journal = {{Journal of chemical information and modeling} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/16562997}{16562997}] [doi:\href{http://dx.doi.org/10.1021/ci050357s}{10.1021/ci050357s}]}},
  number = {2},
  pages = {665--676},
  publisher = {ACS Publications},
  title = {{Molecular field extrema as descriptors of biological activity: definition and validation}},
  volume = {46},
  year = {2006},
  issn = {1549-9596},
}


@article{Thorner1996,
  author = {D. A. Thorner and D. J. Wild and P. Willett and P. M. Wright},
  journal = {{J. Chem. Inf. Comput. Sci} note = {[doi:\href{http://dx.doi.org/10.1021/ci960002w}{10.1021/ci960002w}]}},
  number = {4},
  pages = {900--908},
  title = {{Similarity searching in files of three-dimensional chemical structures: flexible field-based searching of molecular electrostatic potentials}},
  volume = {36},
  year = {1996},
}


@article{Tervo2005,
  author = {A. J. Tervo and T. R\"onkk\"o and T. H. Nyr\"onen and A. Poso},
  journal = {{Journal of medicinal chemistry} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/15943481}{15943481}] [doi:\href{http://dx.doi.org/10.1021/jm049123a}{10.1021/jm049123a}]}},
  number = {12},
  pages = {4076--4086},
  publisher = {ACS Publications},
  title = {{BRUTUS: optimization of a grid-based similarity function for rigid-body molecular superposition. 1. Alignment and virtual screening applications}},
  volume = {48},
  year = {2005},
  issn = {0022-2623},
}


@article{Marin2008,
  author = {R. M. Mar\'i-n and N. F. Aguirre and E. E. Daza},
  journal = {{Journal of chemical information and modeling} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/18166018}{18166018}] [doi:\href{http://dx.doi.org/10.1021/ci7001878}{10.1021/ci7001878}]}},
  number = {1},
  pages = {109--118},
  publisher = {ACS Publications},
  title = {{Graph theoretical similarity approach to compare molecular electrostatic potentials}},
  volume = {48},
  year = {2008},
  issn = {1549-9596},
}


@article{Sastry2011,
  author = {M. Sastry and S. Dixon and W. Sherman},
  journal = {{J. Chem. Inf. Model.} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/21870862}{21870862}] [doi:\href{http://dx.doi.org/10.1021/ci2002704}{10.1021/ci2002704}]}},
  publisher = {ACS Publications},
  title = {{Rapid Shape-Based Ligand Alignment and Virtual Screening Method Based on Atom/Feature-Pair Similarities and Volume Overlap Scoring}},
  year = {2011},
  issn = {1549-9596},
}


@article{Good1993,
  author = {A. C. Good and W. G. Richards},
  journal = {J. Chem. Inf. Model.},
  number = {1},
  pages = {112--116},
  publisher = {American Chemical Society},
  title = {{Rapid evaluation of shape similarity using Gaussian functions}},
  volume = {33},
  year = {1993},
  abstract = {Uses gaussian function (approximating electron fields) to analytically calculate carbo index (amount of overlap) between two already aligned molecules. The analytical method is faster than a fine grained grid method.},
}


@article{Grant1996,
  author = {J. A. Grant and M. A. Gallardo and B. T. Pickup},
  journal = {Journal of Computational Chemistry},
  number = {14},
  pages = {1653--1666},
  publisher = {John Wiley \& Sons},
  title = {{A fast method of molecular shape comparison: A simple application of a Gaussian description of molecular shape}},
  volume = {17},
  year = {1996},
}


@article{Proschak2008,
  author = {Ewgenij Proschak and Matthias Rupp and Swetlana Derksen and Gisbert Schneider},
  journal = {{Journal of Computational Chemistry} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/17516427}{17516427}] [doi:\href{http://dx.doi.org/10.1002/jcc.20770}{10.1002/jcc.20770}]}},
  number = {1},
  pages = {108--114},
  publisher = {Wiley Subscription Services, Inc., A Wiley Company},
  title = {{Shapelets: Possibilities and limitations of shape-based virtual screening}},
  volume = {29},
  year = {2008},
  abstract = {Complementarity of molecular surfaces is crucial for molecular recognition. A method for representation of molecular shape is presented. We decompose the molecular surface into commensurate patches with defined shape by fitting hyperbolical paraboloids onto a triangulated isosurface of the Gaussian model of a molecule. As a result of this decomposition we obtain a 3D graph representation of the molecular shape, which can be used for complete and partial shape matching and isosteric group searching. To point out the possibilities and limitations of shape-only models, we challenged our method by three scenarios in a virtual screening contest: rigid body alignment, consensus shape filtering, and target-specific screening. {\^A}\textcopyright 2007 Wiley Periodicals, Inc. J Comput Chem, 2008},
  issn = {1096-987X},
}


@article{Fontaine2007,
  author = {F. Fontaine and E. Bolton and Y. Borodina and S. H. Bryant},
  journal = {{Chemistry Central Journal} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/17880744}{17880744}] [PubMed Central:\href{http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1994057}{PMC1994057}] [doi:\href{http://dx.doi.org/10.1186/1752-153X-1-12}{10.1186/1752-153X-1-12}]}},
  pages = {12},
  publisher = {BioMed Central},
  title = {{Fast 3D shape screening of large chemical databases through alignment-recycling}},
  volume = {1},
  year = {2007},
}


@article{Haigh2005,
  author = {J. A. Haigh and B. T. Pickup and J. A. Grant and A. Nicholls},
  journal = {{J. Chem. Inf. Model} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/15921457}{15921457}] [doi:\href{http://dx.doi.org/10.1021/ci049651v}{10.1021/ci049651v}]}},
  number = {3},
  pages = {673--684},
  publisher = {ACS Publications},
  title = {{Small molecule shape-fingerprints}},
  volume = {45},
  year = {2005},
}


@article{Putta2002,
  author = {S. Putta and C. Lemmen and P. Beroza and J. Greene},
  journal = {{J. Chem. Inf. Comput. Sci} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/12377013}{12377013}]}},
  number = {5},
  pages = {1230--1240},
  title = {{A novel shape-feature based approach to virtual library screening}},
  volume = {42},
  year = {2002},
}


@article{Ballester2007,
  author = {P. J. Ballester and W. G. Richards},
  journal = {{J. Comp. Chem.} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/17342716}{17342716}] [doi:\href{http://dx.doi.org/10.1002/jcc.20681}{10.1002/jcc.20681}]}},
  number = {10},
  pages = {1711},
  publisher = {John Wiley \& Sons, Ltd},
  title = {{Ultrafast shape recognition to search compound databases for similar molecular shapes}},
  volume = {28},
  year = {2007},
}


@article{Zauhar2003,
  author = {R. J. Zauhar and G. Moyna and L. F. Tian and Z. J. Li and W. J. Welsh},
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  number = {26},
  pages = {5674--5690},
  title = {{Shape signatures: a new approach to computer-aided ligand-and receptor-based drug design}},
  volume = {46},
  year = {2003},
}


@article{Schneider2005,
  author = {Gisbert Schneider and Uli Fechner},
  journal = {Nat Rev Drug Discov},
  month = {{Aug} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/16056391}{16056391}] [doi:\href{http://dx.doi.org/10.1038/nrd1799}{10.1038/nrd1799}]}},
  number = {8},
  pages = {649--663},
  title = {{Computer-based de novo design of drug-like molecules}},
  volume = {4},
  year = {2005},
  issn = {1474-1776},
  url = {http://dx.doi.org/10.1038/nrd1799},
}


@article{Kick1997,
  author = {E. K. Kick and D. C. Roe and A. {Geoffrey Skillman} and G. Liu and T. J. A. Ewing and Y. Sun and I. D. Kuntz and J. A. Ellman},
  journal = {{Chemistry \& Biology} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/9195867}{9195867}]}},
  number = {4},
  pages = {297--307},
  publisher = {Elsevier},
  title = {{Structure-based design and combinatorial chemistry yield low nanomolar inhibitors of cathepsin D}},
  volume = {4},
  year = {1997},
}


@article{Murray1997,
  author = {C. W. Murray and D. E. Clark and T. R. Auton and M. A. Firth and J. Li and R. A. Sykes and B. Waszkowycz and D. R. Westhead and S. C. Young},
  journal = {{J Comput Aided Mol Des} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/9089436}{9089436}]}},
  number = {2},
  pages = {193--207},
  publisher = {Springer},
  title = {{PRO\_SELECT: combining structure-based drug design and combinatorial chemistry for rapid lead discovery. 1. Technology}},
  volume = {11},
  year = {1997},
}


@article{Li1998,
  author = {J. Li and C. W. Murray and B. Waszkowycz and S. C. Young},
  journal = {Drug discovery today},
  number = {3},
  pages = {105--112},
  publisher = {Elsevier},
  title = {{Targeted molecular diversity in drug discovery: integration of structure-based design and combinatorial chemistry}},
  volume = {3},
  year = {1998},
  issn = {1359-6446},
}


@article{Liebeschuetz2002,
  author = {J. W. Liebeschuetz and S. D. Jones and P. J. Morgan and C. W. Murray and A. D. Rimmer and J. M. E. Roscoe and B. Waszkowycz and P. M. Welsh and W. A. Wylie and S. C. Young},
  journal = {{Journal of medicinal chemistry} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/11881991}{11881991}]}},
  number = {6},
  pages = {1221--1232},
  publisher = {ACS Publications},
  title = {{PRO\_SELECT: combining structure-based drug design and array-based chemistry for rapid lead discovery. 2. The development of a series of highly potent and selective factor Xa inhibitors}},
  volume = {45},
  year = {2002},
  issn = {0022-2623},
}


@article{Brenke2009,
  author = {R. Brenke and D. Kozakov and G. Y. Chuang and D. Beglov and D. Hall and M. R. Landon and C. Mattos and S. Vajda},
  journal = {{Bioinformatics} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/19176554}{19176554}] [PubMed Central:\href{http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2647826}{PMC2647826}] [doi:\href{http://dx.doi.org/10.1093/bioinformatics/btp036}{10.1093/bioinformatics/btp036}]}},
  number = {5},
  pages = {621},
  publisher = {Oxford Univ Press},
  title = {{Fragment-based identification of druggable hot spots of proteins using Fourier domain correlation techniques}},
  volume = {25},
  year = {2009},
  issn = {1367-4803},
}


@article{Bronstein2009,
  author = {A. M. Bronstein and M. M. Bronstein and A. M. Bruckstein and R. Kimmel},
  journal = {International Journal of Computer Vision},
  number = {2},
  pages = {163--183},
  publisher = {Springer},
  title = {{Partial similarity of objects, or how to compare a centaur to a horse}},
  volume = {84},
  year = {2009},
  issn = {0920-5691},
}


@article{Zhang2009,
  author = {J. Zhang and S. Smith},
  journal = {Journal of Computing and Information Science in Engineering},
  pages = {034503},
  title = {{Shape Similarity Matching With Octree Representations}},
  volume = {9},
  year = {2009},
}


@inproceedings{keim1999,
  address = {New York, NY, USA},
  author = {Daniel A. Keim},
  booktitle = {{Proc. of the Intl. Conf. on Management of Data}},
  pages = {419--430},
  publisher = {ACM},
  title = {{Efficient geometry-based similarity search of 3D spatial databases}},
  year = {1999},
  doi = {10.1145/304182.304219},
  isbn = {1-58113-084-8},
  url = {http://doi.acm.org/10.1145/304182.304219},
}


@article{Rohrer2009,
  author = {S. G. Rohrer and K. Baumann},
  journal = {{J Chem Inf Model} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/19434821}{19434821}] [doi:\href{http://dx.doi.org/10.1021/ci8002649}{10.1021/ci8002649}]}},
  number = {2},
  pages = {169--84},
  title = {{Maximum unbiased validation (MUV) data sets for virtual screening based on PubChem bioactivity data}},
  volume = {49},
  year = {2009},
  abstract = {Refined nearest neighbor analysis was recently introduced for the analysis of virtual screening benchmark data sets. It constitutes a technique from the field of spatial statistics and provides a mathematical framework for the nonparametric analysis of mapped point patterns. Here, refined nearest neighbor analysis is used to design benchmark data sets for virtual screening based on PubChem bioactivity data. A workflow is devised that purges data sets of compounds active against pharmaceutically relevant targets from unselective hits. Topological optimization using experimental design strategies monitored by refined nearest neighbor analysis functions is applied to generate corresponding data sets of actives and decoys that are unbiased with regard to analogue bias and artificial enrichment. These data sets provide a tool for Maximum Unbiased Validation (MUV) of virtual screening methods. The data sets and a software package implementing the MUV design workflow are freely available at http://www.pharmchem.tu-bs.de/lehre/baumann/MUV.html.},
}


@article{Good2008,
  author = {A. C. Good and T. I. Oprea},
  journal = {Journal of computer-aided molecular design},
  number = {3},
  pages = {169--178},
  publisher = {Springer},
  title = {{Optimization of CAMD techniques 3. Virtual screening enrichment studies: a help or hindrance in tool selection?}},
  volume = {22},
  year = {2008},
  issn = {0920-654X},
}


@article{Verdonk2004,
  author = {M. L. Verdonk and V. Berdini and M. J. Hartshorn and W. T. Mooij and C. W. Murray and R. D. Taylor and P. Watson},
  journal = {{Journal of chemical information and computer sciences} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/15154744}{15154744}] [doi:\href{http://dx.doi.org/10.1021/ci034289q}{10.1021/ci034289q}]}},
  number = {3},
  pages = {793},
  title = {{Virtual screening using protein-ligand docking: avoiding artificial enrichment.}},
  volume = {44},
  year = {2004},
}


@article{Anstead1997,
  author = {G. M. Anstead and K. E. Carlson and J. A. Katzenellenbogen},
  journal = {{Steroids} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/9071738}{9071738}]}},
  number = {3},
  pages = {268--303},
  publisher = {Elsevier},
  title = {{The estradiol pharmacophore: ligand structure-estrogen receptor binding affinity relationships and a model for the receptor binding site}},
  volume = {62},
  year = {1997},
  issn = {0039-128X},
}


@article{Tiikkainen2009,
  author = {Pekka Tiikkainen and Patrick Markt and Gerhard Wolber and Johannes Kirchmair and Simona Distinto and Antti Poso and Olli Kallioniemi},
  journal = {Journal of Chemical Information and Modeling},
  month = {{Oct} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/19799417}{19799417}] [doi:\href{http://dx.doi.org/10.1021/ci900249b}{10.1021/ci900249b}]}},
  number = {10},
  pages = {2168--2178},
  publisher = {American Chemical Society},
  title = {{Critical Comparison of Virtual Screening Methods against the MUV Data Set}},
  volume = {49},
  year = {2009},
  abstract = {In the current work, we measure the performance of seven ligand-based virtual screening tools - five similarity search methods and two pharmacophore elucidators - against the MUV data set. For the similarity search tools, single active molecules as well as active compound sets clustered in terms of their chemical diversity were used as templates. Their score was calculated against all inactive and active compounds in their target class. Subsequently the scores were used to calculate different performance metrics including enrichment factors and AUC values. We also studied the effect of data fusion on the results. To measure the performance of the pharmacophore tools, a set of active molecules was picked either random- or chemical diversity-based from each target class to build a pharmacophore model which was then used to screen the remaining compounds in the set. Our results indicate that template sets selected by their chemical diversity are the best choice for similarity search tools, whereas the optimal training sets for pharmacophore elucidators are based on random selection underscoring that pharmacophore modeling cannot be easily automated. We also suggest a number of improvements for future benchmark sets and discuss activity cliffs as a potential problem in ligand-based virtual screening.},
  issn = {1549-9596},
}


@misc{sproxel,
  howpublished = {\url{http://code.google.com/p/sproxel/}},
  title = {{sproxel, r173}},
}


@article{Stierand2007,
  author = {K. Stierand and M. Rarey},
  journal = {{ChemMedChem} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/17436259}{17436259}] [doi:\href{http://dx.doi.org/10.1002/cmdc.200700010}{10.1002/cmdc.200700010}]}},
  number = {6},
  pages = {853--860},
  publisher = {Wiley Online Library},
  title = {{From Modeling to Medicinal Chemistry: Automatic Generation of Two{\^a}Dimensional Complex Diagrams}},
  volume = {2},
  year = {2007},
  issn = {1860-7187},
}


@article{Hu2005,
  author = {L. Hu and M. L. Benson and R. D. Smith and M. G. Lerner and H. A. Carlson},
  journal = {{Proteins: Struct Funct Bioinf} note = {[PubMed:\href{http://www.ncbi.nlm.nih.gov/pubmed/15971202}{15971202}] [doi:\href{http://dx.doi.org/10.1002/prot.20512}{10.1002/prot.20512}]}},
  number = {3},
  pages = {333--340},
  publisher = {Wiley Online Library},
  title = {{Binding MOAD (mother of all databases)}},
  volume = {60},
  year = {2005},
  issn = {1097-0134},
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