The DOI matches its Crossref record; 75 of the 75 references it cites were found in a registry or an index.
Going further than Lipinski's rule in drug design
Abstract
INTRODUCTION: Lipinski's 1997 publication of the 'Rule of 5' (Ro5) was one of the most influential recent medicinal chemistry publications. In the almost 15 years since the publication of the original Ro5 paper, multiple groups have refined and expanded on the Ro5 and proposed additional heuristics to guide medicinal chemistry programs. While many variations on the Ro5 have been proposed, the majority of these remain close to the original guidelines proposed by Lipinski et al. AREAS COVERED: This review provides an overview of heuristic methods for the design of drug-like molecules. The article also provides the reader with suggestions on future directions for the field. EXPERT OPINION: While Lipinski's publication of the Ro5 and subsequent work by other authors has made medicinal chemists more aware of the relationships between physical properties and ADMET, it has hardly been a panacea. Pharmaceutical productivity continues to lag, and the industry is exploring new models to improve its output. If we are to progress, we need to move beyond simple models based on lipophilicity and gain a deeper understanding of molecular interactions.
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Cites
Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (1997) · Advanced Drug Delivery Reviews · doi:10.1016/s0169-409x(96)00423-1 · Cited by 11,385
Molecular properties that influence the oral bioavailability of drug candidates
Veber, D. F., Johnson, S. R., Cheng, H.-Y., Smith, B. R., Ward, K. W., & Kopple, K. D. (2002) · Journal of Medicinal Chemistry · doi:10.1021/jm020017n · Cited by 8,420
Lead- and drug-like compounds: the rule-of-five revolution
Lipinski, C. A. (2004) · Drug Discovery Today: Technologies · doi:10.1016/j.ddtec.2004.11.007 · Cited by 6,199
Angewandte Chemie International Edition
(2006) · Angewandte Chemie International Edition · doi:10.1002/(issn)1521-3773 · Cited by 5,242
Escape from Flatland: Increasing Saturation as an Approach to Improving Clinical Success
Lovering, F., Bikker, J., & Humblet, C. (2009) · Journal of Medicinal Chemistry · doi:10.1021/jm901241e · Cited by 4,495
Baell, J. B., & Holloway, G. A. (2010) · Journal of Medicinal Chemistry · doi:10.1021/jm901137j · Cited by 3,944
Ghose, A. K., Viswanadhan, V. N., & Wendoloski, J. J. (1999) · Journal of Combinatorial Chemistry · doi:10.1021/cc9800071 · Cited by 3,068
The Medicinal Chemist’s Toolbox: An Analysis of Reactions Used in the Pursuit of Drug Candidates
Roughley, S. D., & Jordan, A. M. (2011) · Journal of Medicinal Chemistry · doi:10.1021/jm200187y · Cited by 2,725
The influence of drug-like concepts on decision-making in medicinal chemistry
Leeson, P. D., & Springthorpe, B. (2007) · Nature Reviews Drug Discovery · doi:10.1038/nrd2445 · Cited by 2,403
Prediction of Drug Absorption Using Multivariate Statistics
Egan, W. J., Merz, & Baldwin, J. J. (2000) · Journal of Medicinal Chemistry · doi:10.1021/jm000292e · Cited by 1,970
Cited by
Oral Druggable Space beyond the Rule of 5: Insights from Drugs and Clinical Candidates
Doak, B. C., Over, B., Giordanetto, F., & Kihlberg, J. (2014) · Chemistry & Biology · doi:10.1016/j.chembiol.2014.08.013 · Cited by 835
The application of in silico drug-likeness predictions in pharmaceutical research
Tian, S., Wang, J., Li, Y., Li, D., Xu, L., & Hou, T. (2015) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2015.01.009 · Cited by 498
Protac-Induced Protein Degradation in Drug Discovery: Breaking the Rules or Just Making New Ones?
Churcher, I. (2018) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.7b01272 · Cited by 491
Chemical predictive modelling to improve compound quality
Cumming, J. G., Davis, A. M., Muresan, S., Haeberlein, M., & Chen, H. (2013) · Nature Reviews Drug Discovery · doi:10.1038/nrd4128 · Cited by 311
Recent Developments in PROTAC‐Mediated Protein Degradation: From Bench to Clinic
Hu, Z., & Crews, C. M. (2022) · ChemBioChem · doi:10.1002/cbic.202100270 · Cited by 231
Metadata
- Authors
- Walters, W. P.
- Venue
- Expert Opinion on Drug Discovery
- Publisher
- Informa UK Limited
- Published
- 2012-01-13
- Volume
- 7
- Issue
- 2
- Pages
- 99-107
- ISSN
- 1746-0441 (ISSN-L)
- 1746-045X
- OpenAlex
- W2100947872
- Cited by
- 306
- References
- 75
- FWCI
- 11.20
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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