The DOI matches its Crossref record; 131 of the 131 references it cites were found in a registry or an index.
Computational analysis of calculated physicochemical and ADMET properties of protein-protein interaction inhibitors
Open accessAbstract
The modulation of PPIs by low molecular weight chemical compounds, particularly by orally bioavailable molecules, would be very valuable in numerous disease indications. However, it is known that PPI inhibitors (iPPIs) tend to have properties that are linked to poor Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) and in some cases to poor clinical outcomes. Previously reported in silico analyses of iPPIs have essentially focused on physicochemical properties but several other ADMET parameters would be important to assess. In order to gain new insights into the ADMET properties of iPPIs, computations were carried out on eight datasets collected from several databases. These datasets involve compounds targeting enzymes, GPCRs, ion channels, nuclear receptors, allosteric modulators, oral marketed drugs, oral natural product-derived marketed drugs and iPPIs. Several trends are reported that should assist the design and optimization of future PPI inhibitors, either for drug discovery endeavors or for chemical biology projects.
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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
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
Pires, D. E. V., Blundell, T. L., & Ascher, D. B. (2015) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.5b00104 · Cited by 5,716
Amidon, G. L., Lennernäs, H., Shah, V. P., & Crison, J. R. (1995) · Pharmaceutical Research · doi:10.1023/a:1016212804288 · Cited by 5,430
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
ChEMBL: a large-scale bioactivity database for drug discovery
Gaulton, A., Bellis, L. J., Bento, A. P., Chambers, J., Davies, M., Hersey, A., Light, Y., McGlinchey, S., Michalovich, D., Al-Lazikani, B., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr777 · Cited by 4,382
Zanger, U. M., & Schwab, M. (2013) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2012.12.007 · Cited by 4,169
Baell, J. B., & Holloway, G. A. (2010) · Journal of Medicinal Chemistry · doi:10.1021/jm901137j · Cited by 3,944
Ertl, P., Rohde, B., & Selzer, P. (2000) · Journal of Medicinal Chemistry · doi:10.1021/jm000942e · Cited by 3,084
The re-emergence of natural products for drug discovery in the genomics era
Harvey, A. L., Edrada-Ebel, R., & Quinn, R. J. (2015) · Nature Reviews Drug Discovery · doi:10.1038/nrd4510 · Cited by 2,572
Cited by
Verma, S., Goand, U. K., Husain, A., Katekar, R. A., Garg, R., & Gayen, J. R. (2021) · Drug Development Research · doi:10.1002/ddr.21832 · Cited by 151
Metadata
- Authors
- Lagorce, D., Douguet, D., Miteva, M. A., & Villoutreix, B. O.
- Venue
- Scientific Reports
- Published
- 2017-04-11
- Volume
- 7
- Issue
- 1
- Pages
- 46277-46277
- ISSN
- 2045-2322 (ISSN-L)
- OpenAlex
- W2607333556
- Cited by
- 266
- References
- 131
- FWCI
- 8.77
- Type
- journal article
- Language
- en
- Open access
- gold
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