1-{[1-[5-(4-Chloro-phenyl)-furan-2-yl]-meth-(E)-ylidene]-amino}-3-[3-(4-methyl-piperazin-1-yl)-propyl]-imidazolidine-2,4-dione

ID: ALA123558

Chembl Id: CHEMBL123558

Max Phase: Phase

Molecular Formula: C23H28ClN5O3

Molecular Weight: 457.96

Molecule Type: Small molecule

Names and Identifiers

Synonyms: Azimilide

Synonyms from Alternative Forms(3): Azimilide dihydrochloride | Azimilide hydrochloride | NE-10064

Canonical SMILES:  CN1CCN(CCCCN2C(=O)CN(/N=C/c3ccc(-c4ccc(Cl)cc4)o3)C2=O)CC1

Standard InChI:  InChI=1S/C23H28ClN5O3/c1-26-12-14-27(15-13-26)10-2-3-11-28-22(30)17-29(23(28)31)25-16-20-8-9-21(32-20)18-4-6-19(24)7-5-18/h4-9,16H,2-3,10-15,17H2,1H3/b25-16+

Standard InChI Key:  MREBEPTUUMTTIA-PCLIKHOPSA-N

Alternative Forms

1. Parent:

   

   ALA123558

   AZIMILIDE

2. Alternative Forms:

   

   ALA123558

   AZIMILIDE DIHYDROCHLORIDE
3. 

   ALA123558

   Azimilide 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: 457.96

Molecular Weight (Monoisotopic): 457.1881

AlogP: 3.23

#Rotatable Bonds: 8

Polar Surface Area: 72.60

Molecular Species: NEUTRAL

HBA: 6

HBD: ┄

#RO5 Violations: ┄

HBA (Lipinski): 8

HBD (Lipinski): ┄

#RO5 Violations (Lipinski): ┄

CX Acidic pKa: 11.95

CX Basic pKa: 8.30

CX LogP: 2.59

CX LogD: 1.64

Aromatic Rings: 2

Heavy Atoms: 32

QED Weighted: 0.35

Np Likeness Score: -1.38

References

1. Bruno-Blanch L, Gálvez J, García-Domenech R..  (2003)  Topological virtual screening: a way to find new anticonvulsant drugs from chemical diversity.,  13  (16): [PMID:12873507] [10.1016/s0960-894x(03)00535-3]

2. Keserü GM..  (2003)  Prediction of hERG potassium channel affinity by traditional and hologram qSAR methods.,  13  (16): [PMID:12873512] [10.1016/s0960-894x(03)00492-x]

3. Cavalli A, Poluzzi E, De Ponti F, Recanatini M..  (2002)  Toward a pharmacophore for drugs inducing the long QT syndrome: insights from a CoMFA study of HERG K(+) channel blockers.,  45  (18): [PMID:12190308] [10.1021/jm0208875]

4. Du LP, Tsai KC, Li MY, You QD, Xia L..  (2004)  The pharmacophore hypotheses of I(Kr) potassium channel blockers: novel class III antiarrhythmic agents.,  14  (18): [PMID:15324906] [10.1016/j.bmcl.2004.06.070]

5. Tobita M, Nishikawa T, Nagashima R..  (2005)  A discriminant model constructed by the support vector machine method for HERG potassium channel inhibitors.,  15  (11): [PMID:15911273] [10.1016/j.bmcl.2005.03.080]

6. Jia L, Sun H..  (2008)  Support vector machines classification of hERG liabilities based on atom types.,  16  (11): [PMID:18448342] [10.1016/j.bmc.2008.04.028]

7. Du L, Li M, Yang Q, Tang Y, You Q, Xia L..  (2009)  Molecular hybridization, synthesis, and biological evaluation of novel chroman I(Kr) and I(Ks) dual blockers.,  19  (5): [PMID:19185489] [10.1016/j.bmcl.2009.01.022]

8. Ermondi G, Visentin S, Caron G..  (2009)  GRIND-based 3D-QSAR and CoMFA to investigate topics dominated by hydrophobic interactions: the case of hERG K+ channel blockers.,  44  (5): [PMID:19110341] [10.1016/j.ejmech.2008.11.009]

9. Obach RS, Lombardo F, Waters NJ..  (2008)  Trend analysis of a database of intravenous pharmacokinetic parameters in humans for 670 drug compounds.,  36  (7): [PMID:18426954] [10.1124/dmd.108.020479]

10. Sinha N, Sen S..  (2011)  Predicting hERG activities of compounds from their 3D structures: development and evaluation of a global descriptors based QSAR model.,  46  (2): [PMID:21185626] [10.1016/j.ejmech.2010.11.042]

11. HESI Myocyte Subteam: Blinova K., Brock M., Dang Q., Entcheva E., Feaster T.K., Gintant G., Guo, L., Herron T., Kanda Y., Kettenhofen R., Kraushaar U., Lu H.R., Lu J., Millard D., Objero-Paz C., Osada T., Pang L., Pierson J., Sawada K., Sekino Y., Shi H., Smith G., Snodgrass R., Stockbridge N., Strauss D.G., Traebert M., Wakatsuki T., Wu J., Zeng H., Zhang X..  (2019)  Evaluation of the utility of stem-cell derived cardiomyocytes for drug proarrhythmic potential,  [10.6019/CHEMBL4295262]

12. Unpublished dataset, 

13. Ellen Van Damme.  (2021)  Screening of ~5500 FDA-approved drugs and clinical candidates for anti-SARS-CoV-2 activity,  [10.6019/CHEMBL4651402]

14. 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]

Source

Source(5):

• Scientific Literature
• Clinical Candidates
• HESi
• IMI-CARE SARS-CoV-2 Data
• Fraunhofer HDAC6