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3D Molecular Descriptors Important for Clinical Success
The pharmacokinetic and safety profiles of clinical drug candidates are greatly influenced by their requisite physicochemical properties. In particular, it has been shown that 2D molecular descriptors such as fraction of Sp3 carbon atoms (Fsp3) and number of stereo centers correlate with clinical su...
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| Published in: | Journal of chemical information and modeling 2013-02, Vol.53 (2), p.327-342 |
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| Main Authors: | , , , , , , , |
| Format: | Article |
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| cited_by | cdi_FETCH-LOGICAL-a373t-fb3cfbe7d0e7d82b01295c655ea2f969635601faf35ee416062526b91dd53e373 |
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| cites | cdi_FETCH-LOGICAL-a373t-fb3cfbe7d0e7d82b01295c655ea2f969635601faf35ee416062526b91dd53e373 |
| container_end_page | 342 |
| container_issue | 2 |
| container_start_page | 327 |
| container_title | Journal of chemical information and modeling |
| container_volume | 53 |
| creator | Kombo, David C Tallapragada, Kartik Jain, Rachit Chewning, Joseph Mazurov, Anatoly A Speake, Jason D Hauser, Terry A Toler, Steve |
| description | The pharmacokinetic and safety profiles of clinical drug candidates are greatly influenced by their requisite physicochemical properties. In particular, it has been shown that 2D molecular descriptors such as fraction of Sp3 carbon atoms (Fsp3) and number of stereo centers correlate with clinical success. Using the proteomic off-target hit rate of nicotinic ligands, we found that shape-based 3D descriptors such as the radius of gyration and shadow indices discriminate off-target promiscuity better than do Fsp3 and the number of stereo centers. We have deduced the relevant descriptor values required for a ligand to be nonpromiscuous. Investigating the MDL Drug Data Report (MDDR) database as compounds move from the preclinical stage toward the market, we have found that these shape-based 3D descriptors predict clinical success of compounds at preclinical and phase1 stages vs compounds withdrawn from the market better than do Fsp3 and LogD. Further, these computed 3D molecular descriptors correlate well with experimentally observed solubility, which is among well-known physicochemical properties that drive clinical success. We also found that about 84% of launched drugs satisfy either Shadow index or Fsp3 criteria, whereas withdrawn and discontinued compounds fail to meet the same criteria. Our studies suggest that spherical compounds (rather than their elongated counterparts) with a minimal number of aromatic rings may exhibit a high propensity to advance from clinical trials to market. |
| doi_str_mv | 10.1021/ci300445e |
| format | article |
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In particular, it has been shown that 2D molecular descriptors such as fraction of Sp3 carbon atoms (Fsp3) and number of stereo centers correlate with clinical success. Using the proteomic off-target hit rate of nicotinic ligands, we found that shape-based 3D descriptors such as the radius of gyration and shadow indices discriminate off-target promiscuity better than do Fsp3 and the number of stereo centers. We have deduced the relevant descriptor values required for a ligand to be nonpromiscuous. Investigating the MDL Drug Data Report (MDDR) database as compounds move from the preclinical stage toward the market, we have found that these shape-based 3D descriptors predict clinical success of compounds at preclinical and phase1 stages vs compounds withdrawn from the market better than do Fsp3 and LogD. Further, these computed 3D molecular descriptors correlate well with experimentally observed solubility, which is among well-known physicochemical properties that drive clinical success. We also found that about 84% of launched drugs satisfy either Shadow index or Fsp3 criteria, whereas withdrawn and discontinued compounds fail to meet the same criteria. Our studies suggest that spherical compounds (rather than their elongated counterparts) with a minimal number of aromatic rings may exhibit a high propensity to advance from clinical trials to market.</description><identifier>ISSN: 1549-9596</identifier><identifier>EISSN: 1549-960X</identifier><identifier>DOI: 10.1021/ci300445e</identifier><identifier>PMID: 23244494</identifier><language>eng</language><publisher>Washington, DC: American Chemical Society</publisher><subject>Analytical, structural and metabolic biochemistry ; Animals ; Biological and medical sciences ; Chemical compounds ; Chemistry ; Clinical trials ; Clinical Trials as Topic ; Databases, Pharmaceutical ; Drug Discovery - methods ; Exact sciences and technology ; Fundamental and applied biological sciences. Psychology ; General and physical chemistry ; General aspects, investigation methods ; General pharmacology ; General. Nomenclature, chemical documentation, computer chemistry ; Humans ; Ligands ; Medical sciences ; Molecular chemistry ; Molecules ; Pharmaceutical Preparations - chemistry ; Pharmaceutical Preparations - metabolism ; Pharmaceutical technology. Pharmaceutical industry ; Pharmacokinetics. Pharmacogenetics. Drug-receptor interactions ; Pharmacology ; Pharmacology. Drug treatments ; Proteins ; Proteins - metabolism ; Solubility ; Structure-Activity Relationship ; Theory of reactions, general kinetics. Catalysis. Nomenclature, chemical documentation, computer chemistry</subject><ispartof>Journal of chemical information and modeling, 2013-02, Vol.53 (2), p.327-342</ispartof><rights>Copyright © 2012 American Chemical Society</rights><rights>2014 INIST-CNRS</rights><rights>Copyright American Chemical Society Feb 25, 2013</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a373t-fb3cfbe7d0e7d82b01295c655ea2f969635601faf35ee416062526b91dd53e373</citedby><cites>FETCH-LOGICAL-a373t-fb3cfbe7d0e7d82b01295c655ea2f969635601faf35ee416062526b91dd53e373</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,786,790,27957,27958</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27110166$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23244494$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kombo, David C</creatorcontrib><creatorcontrib>Tallapragada, Kartik</creatorcontrib><creatorcontrib>Jain, Rachit</creatorcontrib><creatorcontrib>Chewning, Joseph</creatorcontrib><creatorcontrib>Mazurov, Anatoly A</creatorcontrib><creatorcontrib>Speake, Jason D</creatorcontrib><creatorcontrib>Hauser, Terry A</creatorcontrib><creatorcontrib>Toler, Steve</creatorcontrib><title>3D Molecular Descriptors Important for Clinical Success</title><title>Journal of chemical information and modeling</title><addtitle>J. Chem. Inf. Model</addtitle><description>The pharmacokinetic and safety profiles of clinical drug candidates are greatly influenced by their requisite physicochemical properties. In particular, it has been shown that 2D molecular descriptors such as fraction of Sp3 carbon atoms (Fsp3) and number of stereo centers correlate with clinical success. Using the proteomic off-target hit rate of nicotinic ligands, we found that shape-based 3D descriptors such as the radius of gyration and shadow indices discriminate off-target promiscuity better than do Fsp3 and the number of stereo centers. We have deduced the relevant descriptor values required for a ligand to be nonpromiscuous. Investigating the MDL Drug Data Report (MDDR) database as compounds move from the preclinical stage toward the market, we have found that these shape-based 3D descriptors predict clinical success of compounds at preclinical and phase1 stages vs compounds withdrawn from the market better than do Fsp3 and LogD. Further, these computed 3D molecular descriptors correlate well with experimentally observed solubility, which is among well-known physicochemical properties that drive clinical success. We also found that about 84% of launched drugs satisfy either Shadow index or Fsp3 criteria, whereas withdrawn and discontinued compounds fail to meet the same criteria. Our studies suggest that spherical compounds (rather than their elongated counterparts) with a minimal number of aromatic rings may exhibit a high propensity to advance from clinical trials to market.</description><subject>Analytical, structural and metabolic biochemistry</subject><subject>Animals</subject><subject>Biological and medical sciences</subject><subject>Chemical compounds</subject><subject>Chemistry</subject><subject>Clinical trials</subject><subject>Clinical Trials as Topic</subject><subject>Databases, Pharmaceutical</subject><subject>Drug Discovery - methods</subject><subject>Exact sciences and technology</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General and physical chemistry</subject><subject>General aspects, investigation methods</subject><subject>General pharmacology</subject><subject>General. Nomenclature, chemical documentation, computer chemistry</subject><subject>Humans</subject><subject>Ligands</subject><subject>Medical sciences</subject><subject>Molecular chemistry</subject><subject>Molecules</subject><subject>Pharmaceutical Preparations - chemistry</subject><subject>Pharmaceutical Preparations - metabolism</subject><subject>Pharmaceutical technology. Pharmaceutical industry</subject><subject>Pharmacokinetics. Pharmacogenetics. Drug-receptor interactions</subject><subject>Pharmacology</subject><subject>Pharmacology. Drug treatments</subject><subject>Proteins</subject><subject>Proteins - metabolism</subject><subject>Solubility</subject><subject>Structure-Activity Relationship</subject><subject>Theory of reactions, general kinetics. Catalysis. 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Chem. Inf. Model</addtitle><date>2013-02-25</date><risdate>2013</risdate><volume>53</volume><issue>2</issue><spage>327</spage><epage>342</epage><pages>327-342</pages><issn>1549-9596</issn><eissn>1549-960X</eissn><notes>ObjectType-Article-1</notes><notes>SourceType-Scholarly Journals-1</notes><notes>ObjectType-Feature-2</notes><notes>content type line 23</notes><abstract>The pharmacokinetic and safety profiles of clinical drug candidates are greatly influenced by their requisite physicochemical properties. In particular, it has been shown that 2D molecular descriptors such as fraction of Sp3 carbon atoms (Fsp3) and number of stereo centers correlate with clinical success. Using the proteomic off-target hit rate of nicotinic ligands, we found that shape-based 3D descriptors such as the radius of gyration and shadow indices discriminate off-target promiscuity better than do Fsp3 and the number of stereo centers. We have deduced the relevant descriptor values required for a ligand to be nonpromiscuous. Investigating the MDL Drug Data Report (MDDR) database as compounds move from the preclinical stage toward the market, we have found that these shape-based 3D descriptors predict clinical success of compounds at preclinical and phase1 stages vs compounds withdrawn from the market better than do Fsp3 and LogD. Further, these computed 3D molecular descriptors correlate well with experimentally observed solubility, which is among well-known physicochemical properties that drive clinical success. We also found that about 84% of launched drugs satisfy either Shadow index or Fsp3 criteria, whereas withdrawn and discontinued compounds fail to meet the same criteria. Our studies suggest that spherical compounds (rather than their elongated counterparts) with a minimal number of aromatic rings may exhibit a high propensity to advance from clinical trials to market.</abstract><cop>Washington, DC</cop><pub>American Chemical Society</pub><pmid>23244494</pmid><doi>10.1021/ci300445e</doi><tpages>16</tpages></addata></record> |
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| ispartof | Journal of chemical information and modeling, 2013-02, Vol.53 (2), p.327-342 |
| issn | 1549-9596 1549-960X |
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| source | American Chemical Society:Jisc Collections:American Chemical Society Read & Publish Agreement 2022-2024 (Reading list) |
| subjects | Analytical, structural and metabolic biochemistry Animals Biological and medical sciences Chemical compounds Chemistry Clinical trials Clinical Trials as Topic Databases, Pharmaceutical Drug Discovery - methods Exact sciences and technology Fundamental and applied biological sciences. Psychology General and physical chemistry General aspects, investigation methods General pharmacology General. Nomenclature, chemical documentation, computer chemistry Humans Ligands Medical sciences Molecular chemistry Molecules Pharmaceutical Preparations - chemistry Pharmaceutical Preparations - metabolism Pharmaceutical technology. Pharmaceutical industry Pharmacokinetics. Pharmacogenetics. Drug-receptor interactions Pharmacology Pharmacology. Drug treatments Proteins Proteins - metabolism Solubility Structure-Activity Relationship Theory of reactions, general kinetics. Catalysis. Nomenclature, chemical documentation, computer chemistry |
| title | 3D Molecular Descriptors Important for Clinical Success |
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