The DOI matches its Crossref record; 72 of the 72 references it cites were found in a registry or an index.
Molecular Shape and Medicinal Chemistry: A Perspective
Open accessAbstract
The eight contributions here provide ample evidence that shape as a volume or as a surface is a vibrant and useful concept when applied to drug discovery. It provides a reliable scaffold for "decoration" with chemical intuition (or bias) for virtual screening and lead optimization but also has its unadorned uses, as in library design, ligand fitting, pose prediction, or active site description. Computing power has facilitated this evolution by allowing shape to be handled precisely without the need to reduce down to point descriptors or approximate metrics, and the diversity of resultant applications argues for this being an important step forward. Certainly, it is encouraging that as computation has enabled our intuition, molecular shape has consistently surprised us in its usefulness and adaptability. The first Aurelius question, "What is the essence of a thing?", seems well answered, however, the third, "What do molecules do?", only partly so. Are the topics covered here exhaustive, or is there more to come? To date, there has been little published on the use of the volumetric definition of shape described here as a QSAR variable, for instance, in the prediction or classification of activity, although other shape definitions have been successful applied, for instance, as embodied in the Compass program described above in "Shape from Surfaces". Crystal packing is a phenomenon much desired to be understood. Although powerful models have been applied to the problem, to what degree is this dominated purely by the shape of a molecule? The shape comparison described here is typically of a global nature, and yet some importance must surely be placed on partial shape matching, just as the substructure matching of chemical graphs has proved useful. The approach of using surfaces, as described here, offers some flavor of this, as does the use of metrics that penalize volume mismatch less than the Tanimoto, e.g., Tversky measures. As yet, there is little to go on as to how useful a paradigm this will be because there is less software and fewer concrete results.Finally, the distance between molecular shapes, or between any shapes defined as volumes or surfaces, is a metric property in the mathematical sense of the word. As yet, there has been little, if any, application of this observation. We cannot know what new application to the design and discovery of pharmaceuticals may yet arise from the simple concept of molecular shape, but it is fair to say that the progress so far is impressive.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Berman, H. M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.235 · Cited by 40,196
Coot : model-building tools for molecular graphics
Emsley, P., & Cowtan, K. (2004) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444904019158 · Cited by 30,571
Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2001) · Advanced Drug Delivery Reviews · doi:10.1016/s0169-409x(00)00129-0 · Cited by 18,139
Jones, T. A., Zou, J. Y., Cowan, S. W., & Kjeldgaard, M. (1991) · Acta Crystallographica Section A Foundations of Crystallography · doi:10.1107/s0108767390010224 · Cited by 12,648
Friesner, R. A., Murphy, R. B., Repasky, M. P., Frye, L. L., Greenwood, J. R., Halgren, T. A., Sanschagrin, P. C., & Mainz, D. T. (2006) · Journal of Medicinal Chemistry · doi:10.1021/jm051256o · Cited by 6,851
The Properties of Known Drugs. 1. Molecular Frameworks
Bemis, G. W., & Murcko, M. A. (1996) · Journal of Medicinal Chemistry · doi:10.1021/jm9602928 · Cited by 2,482
Reaching for high-hanging fruit in drug discovery at protein–protein interfaces
Wells, J. A., & McClendon, C. L. (2007) · Nature · doi:10.1038/nature06526 · Cited by 1,960
Eldridge, M. D., Murray, C. W., Auton, T. R., Paolini, G. V., & Mee, R. P. (1997) · Journal of Computer-Aided Molecular Design · doi:10.1023/a:1007996124545 · Cited by 1,686
Benchmarking sets for molecular docking.
Huang, N., Shoichet, B. K., & Irwin, J. J. (2006) · Journal of Medicinal Chemistry · doi:10.1021/jm0608356 · Cited by 1,318
Comparison of Shape-Matching and Docking as Virtual Screening Tools
Hawkins, P. C. D., Skillman, A. G., & Nicholls, A. (2007) · Journal of Medicinal Chemistry · doi:10.1021/jm0603365 · Cited by 993
Self-citationMolecular Complexity and Its Impact on the Probability of Finding Leads for Drug Discovery
Hann, M. M., Leach, A. R., & Harper, G. (2001) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci000403i · Cited by 877
Evaluating Virtual Screening Methods: Good and Bad Metrics for the “Early Recognition” Problem
Truchon, J.-F., & Bayly, C. I. (2007) · Journal of Chemical Information and Modeling · doi:10.1021/ci600426e · Cited by 874
The Design of Leadlike Combinatorial Libraries
Teague, S. J., Davis, A. M., Leeson, P. D., & Oprea, T. (1999) · Angewandte Chemie International Edition · doi:10.1002/(sici)1521-3773(19991216)38:24<3743::aid-anie3743>3.0.co;2-u · Cited by 870
Is There a Difference between Leads and Drugs? A Historical Perspective
Oprea, T. I., Davis, A. M., Teague, S. J., & Leeson, P. D. (2001) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci010366a · Cited by 769
Refinement of severely incomplete structures with maximum likelihood in BUSTER–TNT
Blanc, E., Roversi, P., Vonrhein, C., Flensburg, C., Lea, S. M., & Bricogne, G. (2004) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444904016427 · Cited by 717
Lewell, X. Q., Judd, D. B., Watson, S. P., & Hann, M. M. (1998) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci970429i · Cited by 691
Rush, T. S., Grant, J. A., Mosyak, L., & Nicholls, A. (2005) · Journal of Medicinal Chemistry · doi:10.1021/jm040163o · Cited by 600
Self-citationMcGann, M. R., Almond, H. R., Nicholls, A., Grant, J. A., & Brown, F. K. (2003) · Biopolymers · doi:10.1002/bip.10207 · Cited by 491
Self-citationPerola, E., & Charifson, P. S. (2004) · Journal of Medicinal Chemistry · doi:10.1021/jm030563w · Cited by 447
A third blind test of crystal structure prediction
Day, G. M., Motherwell, W. D. S., Ammon, H. L., Boerrigter, S. X. M., Della Valle, R. G., Venuti, E., Dzyabchenko, A., Dunitz, J. D., Schweizer, B., van Eijck, B. P., et al. (2005) · Acta Crystallographica Section B Structural Science · doi:10.1107/s0108768105016563 · Cited by 430
Maximum common subgraph isomorphism algorithms for the matching of chemical structures
Raymond, J. W., & Willett, P. (2002) · Journal of Computer-Aided Molecular Design · doi:10.1023/a:1021271615909 · Cited by 424
Comparison of Topological, Shape, and Docking Methods in Virtual Screening
McGaughey, G. B., Sheridan, R. P., Bayly, C. I., Culberson, J. C., Kreatsoulas, C., Lindsley, S., Maiorov, V., Truchon, J.-F., & Cornell, W. D. (2007) · Journal of Chemical Information and Modeling · doi:10.1021/ci700052x · Cited by 417
Self-citationRecommendations for evaluation of computational methods
Jain, A. N., & Nicholls, A. (2008) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-008-9196-5 · Cited by 350
Self-citationUltrafast shape recognition to search compound databases for similar molecular shapes
Ballester, P. J., & Richards, W. G. (2007) · Journal of Computational Chemistry · doi:10.1002/jcc.20681 · Cited by 327
Molecule-pharmacophore superpositioning and pattern matching in computational drug design
Wolber, G., Seidel, T., Bendix, F., & Langer, T. (2008) · Drug Discovery Today · doi:10.1016/j.drudis.2007.09.007 · Cited by 315
Assessing the performance of OMEGA with respect to retrieving bioactive conformations
Boström, J., Greenwood, J. R., & Gottfries, J. (2003) · Journal of Molecular Graphics and Modelling · doi:10.1016/s1093-3263(02)00204-8 · Cited by 312
Structural Diversity of Organic Chemistry. A Scaffold Analysis of the CAS Registry
Lipkus, A. H., Yuan, Q., Lucas, K. A., Funk, S. A., Bartelt, W. F., Schenck, R. J., & Trippe, A. J. (2008) · The Journal of Organic Chemistry · doi:10.1021/jo8001276 · Cited by 302
Non-peptide fibrinogen receptor antagonists. 1. Discovery and design of exosite inhibitors
Hartman, G. D., Egbertson, M. S., Halczenko, W., Laswell, W. L., Duggan, M. E., Smith, R. L., Naylor, A. M., Manno, P. D., & Lynch, R. J. (1992) · Journal of Medicinal Chemistry · doi:10.1021/jm00102a020 · Cited by 301
Miller, M. D., Kearsley, S. K., Underwood, D. J., & Sheridan, R. P. (1994) · Journal of Computer-Aided Molecular Design · doi:10.1007/bf00119865 · Cited by 281
Self-citationCAVEAT: A program to facilitate the design of organic molecules
Lauri, G., & Bartlett, P. A. (1994) · Journal of Computer-Aided Molecular Design · doi:10.1007/bf00124349 · Cited by 266
Fragment-Based Drug Design: How Big Is Too Big?
Hajduk, P. J. (2006) · Journal of Medicinal Chemistry · doi:10.1021/jm060511h · Cited by 265
Protein–protein interactions as targets for small molecule drug discovery
Fry, D. C. (2006) · Peptide Science · doi:10.1002/bip.20608 · Cited by 206
Pierce, A. C., Rao, G., & Bemis, G. W. (2004) · Journal of Medicinal Chemistry · doi:10.1021/jm030543u · Cited by 185
Zhang, Q., & Muegge, I. (2006) · Journal of Medicinal Chemistry · doi:10.1021/jm050468i · Cited by 182
Ligand-Based Structural Hypotheses for Virtual Screening
Jain, A. N. (2004) · Journal of Medicinal Chemistry · doi:10.1021/jm030520f · Cited by 181
Self-citationBoström, J. (2001) · Journal of Computer-Aided Molecular Design · doi:10.1023/a:1015930826903 · Cited by 178
Jain, A. N., Koile, K., & Chapman, D. (1994) · Journal of Medicinal Chemistry · doi:10.1021/jm00041a010 · Cited by 177
Self-citationFragment-based screening using X-ray crystallography and NMR spectroscopy
Jhoti, H., Cleasby, A., Verdonk, M., & Williams, G. (2007) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2007.07.010 · Cited by 166
What has virtual screening ever done for drug discovery?
Clark, D. E. (2008) · Expert Opinion on Drug Discovery · doi:10.1517/17460441.3.8.841 · Cited by 148
Baxter, E. W., Conway, K. A., Kennis, L. E. J., Bischoff, F., Mercken, M. H., Winter, H. L. D., Reynolds, C. H., Tounge, B. A., Luo, C., Scott, M. K., et al. (2007) · Journal of Medicinal Chemistry · doi:10.1021/jm0705408 · Cited by 146
Murray, C. W., Auton, T. R., & Eldridge, M. (1998) · Journal of Computer-Aided Molecular Design · doi:10.1023/a:1008040323669 · Cited by 144
Maaß, P. C., Schulz‐Gasch, T., Ståhl, M., & Rarey, M. (2007) · Journal of Chemical Information and Modeling · doi:10.1021/ci060094h · Cited by 141
Lessons in Molecular Recognition. 2. Assessing and Improving Cross-Docking Accuracy
Sutherland, J. J., Nandigam, R. K., Erickson, J. A., & Vieth, M. (2007) · Journal of Chemical Information and Modeling · doi:10.1021/ci700253h · Cited by 127
Pharmacophore Discovery - Lessons Learned
Drie, J. H. V. (2003) · Current Pharmaceutical Design · doi:10.2174/1381612033454568 · Cited by 120
Jain, A. N. (2000) · Journal of Computer-Aided Molecular Design · doi:10.1023/a:1008100132405 · Cited by 116
Self-citationSmall Molecule Shape-Fingerprints
Haigh, J. A., Pickup, B. T., Grant, J., et al. (2005) · Journal of Chemical Information and Modeling · doi:10.1021/ci049651v · Cited by 116
Self-citation[23] Bayesian statistical viewpoint on structure determination: Basic concepts and examples
Bricogne, G. (1997) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/s0076-6879(97)76069-5 · Cited by 114
Barillari, C., Marcou, G., & Rognan, D. (2008) · Journal of Chemical Information and Modeling · doi:10.1021/ci800064z · Cited by 111
SQ: A Program for Rapidly Producing Pharmacophorically Relevent Molecular Superpositions
Miller, M. D., Sheridan, R. P., & Kearsley, S. K. (1999) · Journal of Medicinal Chemistry · doi:10.1021/jm9806143 · Cited by 107
Self-citationCompass: A shape-based machine learning tool for drug design
Jain, A. N., Dietterich, T. G., Lathrop, R. H., Chapman, D., Critchlow, R. E., Bauer, B. E., Webster, T. A., & Lozano‐Pérez, T. (1994) · Journal of Computer-Aided Molecular Design · doi:10.1007/bf00124012 · Cited by 100
Self-citationBricogne, G. (1993) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444992010400 · Cited by 97
The SeeDs Approach: Integrating Fragments into Drug Discovery
Hubbard, R. E., Davis, B. J., Chen, I., & Drysdale, M. (2007) · Current Topics in Medicinal Chemistry · doi:10.2174/156802607782341109 · Cited by 86
Ultrafast shape recognition: Evaluating a new ligand-based virtual screening technology
Ballester, P. J., Finn, P. W., & Richards, W. G. (2009) · Journal of Molecular Graphics and Modelling · doi:10.1016/j.jmgm.2009.01.001 · Cited by 83
Automated ligand placement and refinement with a combined force field and shape potential
Wlodek, S. T., Skillman, A. G., & Nicholls, A. O. (2006) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444906016076 · Cited by 82
Self-citationRecent developments in de novo design and scaffold hopping.
Mauser, H., & Guba, W. (2008) · PubMed · Cited by 76
Cleves, A. E., & Jain, A. N. (2007) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-007-9150-y · Cited by 73
Self-citationMuchmore, S. W., Souers, A. J., & Akritopoulou‐Zanze, I. (2006) · Chemical Biology & Drug Design · doi:10.1111/j.1747-0285.2006.00341.x · Cited by 70
Self-citationProgress toward a practical BACE-1 inhibitor.
Hills, I. D., & Vacca, J. P. (2007) · PubMed · Cited by 68
Conformationally biased P3 amide replacements of β-secretase inhibitors
Stachel, S. J., Coburn, C. A., Steele, T. G., Crouthamel, M.-C., Pietrak, B., Lai, M., Holloway, M. K., Munshi, S. K., Graham, S. L., & Vacca, J. P. (2005) · Bioorganic & Medicinal Chemistry Letters · doi:10.1016/j.bmcl.2005.10.032 · Cited by 67
Flux (2): Comparison of Molecular Mutation and Crossover Operators for Ligand-Based de Novo Design
Fechner, U., & Schneider, G. (2007) · Journal of Chemical Information and Modeling · doi:10.1021/ci6005307 · Cited by 66
Progress toward the discovery and development of efficacious BACE inhibitors.
Durham, T. B., & Shepherd, T. A. (2006) · PubMed · Cited by 64
Sheridan, R. P., McGaughey, G. B., & Cornell, W. D. (2008) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-008-9168-9 · Cited by 62
Self-citationModelling prior distributions of atoms for macromolecular refinement and completion
Roversi, P., Blanc, E., Vonrhein, C., Evans, G., & Bricogne, G. (2000) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444900008490 · Cited by 62
Barrow, J. C., Stauffer, S. R., Rittle, K. E., Ngo, P. L., Yang, Z.-Q., Selnick, H. G., Graham, S. L., Munshi, S. K., McGaughey, G. B., Holloway, M. K., et al. (2008) · Journal of Medicinal Chemistry · doi:10.1021/jm800914n · Cited by 61
Self-citationYang, L., Guo, L., Pasternak, A., Mosley, R., Rohrer, S. P., Birzin, E. T., Foor, F., Cheng, K., Schaeffer, J. M., & Patchett, A. A. (1998) · Journal of Medicinal Chemistry · doi:10.1021/jm980194h · Cited by 54
A Robust Clustering Method for Chemical Structures
Ståhl, M., Mauser, H., Tsui, M., & Taylor, N. R. (2005) · Journal of Medicinal Chemistry · doi:10.1021/jm040213p · Cited by 52
Jain, A. N., Harris, N. L., & Park, J. Y. (1995) · Journal of Medicinal Chemistry · doi:10.1021/jm00008a008 · Cited by 50
Self-citationFeuston, B. P., Miller, M. D., Culberson, J. C., Nachbar, R. B., & Kearsley, S. K. (2001) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci000464g · Cited by 50
Chemical similarity searches: when is complexity justified?
Sheridan, R. P. (2007) · Expert Opinion on Drug Discovery · doi:10.1517/17460441.2.4.423 · Cited by 49
Self-citationGraph-Based Molecular Alignment (GMA)
Marialke, J., Körner, R., Tietze, S., & Apostolakis, J. (2007) · Journal of Chemical Information and Modeling · doi:10.1021/ci600387r · Cited by 47
X-LIGAND: an application for the automated addition of flexible ligands into electron density
Oldfield, T. (2001) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444901003894 · Cited by 44
CORES: An Automated Method for Generating Three-Dimensional Models of Protein/Ligand Complexes
Hare, B. J., Walters, W. P., Caron, P. R., et al. (2004) · Journal of Medicinal Chemistry · doi:10.1021/jm0499054 · Cited by 39
Cited by
Molecular graph convolutions: moving beyond fingerprints
Kearnes, S., McCloskey, K., Berndl, M., Pande, V., & Riley, P. (2016) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-016-9938-8 · Cited by 1,631
Enumeration of 166 Billion Organic Small Molecules in the Chemical Universe Database GDB-17
Ruddigkeit, L., van Deursen, R., Blum, L. C., & Reymond, J.-L. (2012) · Journal of Chemical Information and Modeling · doi:10.1021/ci300415d · Cited by 1,505
Pharmit: interactive exploration of chemical space
Sunseri, J., & Koes, D. R. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw287 · Cited by 420
The future of molecular dynamics simulations in drug discovery
Borhani, D. W., & Shaw, D. E. (2012) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-011-9517-y · Cited by 313
“Our computational chemistry tools, impressive and helpful as they are (e.g., shape-based methods [82]), do not yet provide comprehensive drug design solutions.”
MethodDamm-Ganamet, K. L., Smith, R. D., Dunbar, J. B., Stuckey, J. A., & Carlson, H. A. (2013) · Journal of Chemical Information and Modeling · doi:10.1021/ci400025f · Cited by 133
Metadata
- Authors
- Nicholls, A., McGaughey, G. B., Sheridan, R. P., Good, A. C., Warren, G., Mathieu, M., Muchmore, S. W., Brown, S. P., Grant, J. A., Haigh, J. A., Nevins, N., Jain, A. N., & Kelley, B.
- Venue
- Journal of Medicinal Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-05-27
- Volume
- 53
- Issue
- 10
- Pages
- 3862-3886
- ISSN
- 0022-2623 (ISSN-L)
- 1520-4804
- OpenAlex
- W2060153789
- Cited by
- 310
- References
- 72
- FWCI
- 31.73
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.