7-(10,11-Dihydro-5H-dibenzo[a,d]cyclohepten-5-ylamino)-heptanoic acid

ID: ALA418995

Chembl Id: CHEMBL418995

Cas Number: 57574-09-1

PubChem CID: 34870

Product Number: A126068

Max Phase: Approved

Molecular Formula: C22H27NO2

Molecular Weight: 337.46

Molecule Type: Small molecule

Names and Identifiers

Synonyms: Amineptin | Dea no. 1219 | Amineptine|Amineptin|57574-09-1|Amineptine [INN]|Amineptino|Amineptinum|Amineptine (INN)|7-((10,11-Dihydro-5H-dibenzo(a,d)cyclohepten-5-yl)amino)heptanoic acid|7-(10,11-dihydro-5H-dibenzo[a,d]cyclohepten-5-ylamino)heptanoic acid|CHEMBL418995|DTXSID1048831|CHEBI:32499|27T1I13L6G|NCGC00183843-01|7-[(10,11-Dihydro-5H-dibenzo[a,d]cyclohepten-5-yl)amino]heptanoic Acid|Amineptinum [INN-Latin]|Amineptino [INN-Spanish]|Survector (TN)|S 1694|EINECS 260-818-0|EU 1694|BRN 2170218Show More⌵

Synonyms from Alternative Forms(1): Amineptine

Canonical SMILES:  O=C(O)CCCCCCNC1c2ccccc2CCc2ccccc21

Standard InChI:  InChI=1S/C22H27NO2/c24-21(25)13-3-1-2-8-16-23-22-19-11-6-4-9-17(19)14-15-18-10-5-7-12-20(18)22/h4-7,9-12,22-23H,1-3,8,13-16H2,(H,24,25)

Standard InChI Key:  ONNOFKFOZAJDHT-UHFFFAOYSA-N

Alternative Forms

1. Parent:

   

   ALA418995

   AMINEPTINE

2. Alternative Forms:

   

   ALA418995

   AMINEPTINE HYDROCHLORIDE

Molecule Features

Natural Product: No

Oral: No

Chemical Probe: No

Parenteral: No

Molecule Type: Small molecule

Topical: No

First In Class: No

Black Box: No

Chirality: Yes

Availability: No

Prodrug: No

Calculated Properties

Molecular Weight: 337.46

Molecular Weight (Monoisotopic): 337.2042

AlogP: 4.50

#Rotatable Bonds: 8

Polar Surface Area: 49.33

Molecular Species: ZWITTERION

HBA: 2

HBD: 2

#RO5 Violations: ┄

HBA (Lipinski): 3

HBD (Lipinski): 2

#RO5 Violations (Lipinski): ┄

CX Acidic pKa: 4.41

CX Basic pKa: 9.17

CX LogP: 2.74

CX LogD: 2.74

Aromatic Rings: 2

Heavy Atoms: 25

QED Weighted: 0.70

Np Likeness Score: 0.20

References

1. Quiñones-Torrelo C, Sagrado S, Villanueva-Camañas RM, Medina-Hernández MJ..  (1999)  Development of predictive retention-activity relationship models of tricyclic antidepressants by micellar liquid chromatography.,  42  (16): [PMID:10447960] [10.1021/jm9910369]

2. Protais P, Arbaoui J, Bakkali EH, Bermejo A, Cortes D..  (1995)  Effects of various isoquinoline alkaloids on in vitro 3H-dopamine uptake by rat striatal synaptosomes.,  58  (10): [PMID:8676127] [10.1021/np50124a001]

3. Santana L, González-Díaz H, Quezada E, Uriarte E, Yáñez M, Viña D, Orallo F..  (2008)  Quantitative structure-activity relationship and complex network approach to monoamine oxidase A and B inhibitors.,  51  (21): [PMID:18834112] [10.1021/jm800656v]

4. Prado-Prado FJ, García-Mera X, González-Díaz H..  (2010)  Multi-target spectral moment QSAR versus ANN for antiparasitic drugs against different parasite species.,  18  (6): [PMID:20185316] [10.1016/j.bmc.2010.01.068]

5. Pelletier DJ, Gehlhaar D, Tilloy-Ellul A, Johnson TO, Greene N..  (2007)  Evaluation of a published in silico model and construction of a novel Bayesian model for predicting phospholipidosis inducing potential.,  47  (1): [PMID:17428028] [10.1021/ci6004542]

6. Kolaczkowski M, Kolaczkowska A, Motohashi N, Michalak K..  (2009)  New high-throughput screening assay to reveal similarities and differences in inhibitory sensitivities of multidrug ATP-binding cassette transporters.,  53  (4): [PMID:19188399] [10.1128/aac.00956-08]

7. Lowe R, Glen RC, Mitchell JB..  (2010)  Predicting phospholipidosis using machine learning.,  7  (5): [PMID:20799726] [10.1021/mp100103e]

8. Fourches D, Barnes JC, Day NC, Bradley P, Reed JZ, Tropsha A..  (2010)  Cheminformatics analysis of assertions mined from literature that describe drug-induced liver injury in different species.,  23  (1): [PMID:20014752] [10.1021/tx900326k]

9. Chen M, Vijay V, Shi Q, Liu Z, Fang H, Tong W..  (2011)  FDA-approved drug labeling for the study of drug-induced liver injury.,  16  (15-16): [PMID:21624500] [10.1016/j.drudis.2011.05.007]

10. Liu Z, Shi Q, Ding D, Kelly R, Fang H, Tong W..  (2011)  Translating clinical findings into knowledge in drug safety evaluation--drug induced liver injury prediction system (DILIps).,  7  (12): [PMID:22194678] [10.1371/journal.pcbi.1002310]

11. USP Dictionary of USAN and International Names (2010 edition) and USAN registrations 2007-date, 

12. Biour M, Ben Salem C, Chazouillères O, Grangé JD, Serfaty L, Poupon R..  (2004)  [Drug-induced liver injury; fourteenth updated edition of the bibliographic database of liver injuries and related drugs].,  28  (8-9): [PMID:15646539] [10.1016/s0399-8320(04)95062-2]

13. PubChem BioAssay data set, 

14. Unpublished dataset, 

15. WHO Anatomical Therapeutic Chemical Classification, 

16. Chen M, Suzuki A, Thakkar S, Yu K, Hu C, Tong W..  (2016)  DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans.,  21  (4): [PMID:26948801] [10.1016/j.drudis.2016.02.015]

17. Bernhard Ellinger, Denisa Bojkova, Andrea Zaliani, Jindrich Cinatl, Carsten Claussen, Sandra Westhaus, Jeanette Reinshagen, Maria Kuzikov, Markus Wolf, Gerd Geisslinger, Philip Gribbon, Sandra Ciesek.  (2020)  Identification of inhibitors of SARS-CoV-2 in-vitro cellular toxicity in human (Caco-2) cells using a large scale drug repurposing collection,  [10.21203/rs.3.rs-23951/v1]

18. Rana P, Will Y, Nadanaciva S, Jones LH..  (2016)  Development of a cell viability assay to assess drug metabolite structure-toxicity relationships.,  26  (16): [PMID:27397500] [10.1016/j.bmcl.2016.06.088]

19. Maria Kuzikov, Elisa Costanzi, Jeanette Reinshagen, Francesca Esposito, Laura Vangeel, Markus Wolf, Bernhard Ellinger, Carsten Claussen, Gerd Geisslinger, Angela Corona, Daniela Iaconis, Carmine Talarico, Candida Manelfi, Rolando Cannalire, Giulia Rossetti, Jonas Gossen, Simone Albani, Francesco Musiani, Katja Herzog, Yang Ye, Barbara Giabbai, Nicola Demitri, Dirk Jochmans, Steven De Jonghe, Jasper Rymenants, Vincenzo Summa, Enzo Tramontano, Andrea R. Beccari, Pieter Leyssen, Paola Storici, Johan Neyts, Philip Gribbon, and Andrea Zaliani.  (2020)  Identification of inhibitors of SARS-Cov2 M-Pro enzymatic activity using a small molecule repurposing screen,  [10.6019/CHEMBL4495564]

20. Andrea Zaliani, Laura Vangeel, Jeanette Reinshagen, Daniela Iaconis, Maria Kuzikov, Oliver Keminer, Markus Wolf, Bernhard Ellinger, Francesca Esposito, Angela Corona, Enzo Tramontano, Candida Manelfi, Katja Herzog, Dirk Jochmans, Steven De Jonghe, Winston Chiu, Thibault Francken, Joost Schepers, Caroline Collard, Kayvan Abbasi, Carsten Claussen , Vincenzo Summa, Andrea R. Beccari, Johan Neyts, Philip Gribbon and Pieter Leyssen.  (2020)  Cytopathic SARS-Cov2 screening on VERO-E6 cells in a large repurposing effort,  [10.6019/CHEMBL4495565]

21. Bernhard Ellinger, Justus Dick, Vanessa Lage-Rupprecht, Bruce Schultz, Andrea Zaliani, Marcin Namysl, Stephan Gebel, Ole Pless, Jeanette Reinshagen, Christian Ebeling, Alexander Esser, Marc Jacobs, Carsten Claussen, and Martin Hofmann-Apitius.  (2021)  HDAC6 screening dataset using tau-based substrate in an enzymatic assay yields selective inhibitors and activators,  [10.6019/CHEMBL4808148]

22. Sutherland JJ, Yonchev D, Fekete A, Urban L..  (2023)  A preclinical secondary pharmacology resource illuminates target-adverse drug reaction associations of marketed drugs.,  14  (1): [PMID:37468498] [10.1038/s41467-023-40064-9]

Source

Source(7):

• Scientific Literature
• PubChem BioAssays
• USP Dictionary of USAN and International Drug Names
• Withdrawn Drugs
• WHO Anatomical Therapeutic Chemical Classification
• SARS-CoV-2 Screening Data 2020-21
• Fraunhofer HDAC6