Trichloromethane

ID: ALA44618

Chembl Id: CHEMBL44618

Cas Number: 67-66-3

PubChem CID: 6212

Product Number: C112202

Max Phase: Approved

Molecular Formula: CHCl3

Molecular Weight: 119.38

Molecule Type: Small molecule

Names and Identifiers

Synonyms: Chloroform bp | Chloroformum | Hcc 20 | R 20 (refrigerant) | NSC-77361 | CHLOROFORM|Trichloromethane|67-66-3|Trichlormethan|Formyl trichloride|Trichloroform|Methane, trichloro-|Methenyl trichloride|Chloroforme|Methyl trichloride|Methane trichloride|CHCl3|R 20 (Refrigerant)|Triclorometano|Cloroformio|Trichloormethaan|Freon 20|1,1,1-Trichloromethane|Methenyl chloride|RCRA waste number U044|NCI-C02686|Chloroformum|Caswell No. 192|Chloroform bp|Methylidyne trichloride|HSDB 56|Refrigerant R20|CCRIS 1Show More⌵

Canonical SMILES:  ClC(Cl)Cl

Standard InChI:  InChI=1S/CHCl3/c2-1(3)4/h1H

Standard InChI Key:  HEDRZPFGACZZDS-UHFFFAOYSA-N

Alternative Forms

1. Parent:

   

   ALA44618

   CHLOROFORM

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: 119.38

Molecular Weight (Monoisotopic): 117.9144

AlogP: 1.99

#Rotatable Bonds: ┄

Polar Surface Area: 0.00

Molecular Species: ┄

HBA: ┄

HBD: ┄

#RO5 Violations: ┄

HBA (Lipinski): ┄

HBD (Lipinski): ┄

#RO5 Violations (Lipinski): ┄

CX Acidic pKa: ┄

CX Basic pKa: ┄

CX LogP: 1.83

CX LogD: 1.83

Aromatic Rings: ┄

Heavy Atoms: 4

QED Weighted: 0.43

Np Likeness Score: -0.05

References

1. Wilson LY, Famini GR..  (1991)  Using theoretical descriptors in quantitative structure-activity relationships: some toxicological indices.,  34  (5): [PMID:2033592] [10.1021/jm00109a021]

2. Ghose AK, Crippen GM..  (1985)  Use of physicochemical parameters in distance geometry and related three-dimensional quantitative structure-activity relationships: a demonstration using Escherichia coli dihydrofolate reductase inhibitors.,  28  (3): [PMID:3882967] [10.1021/jm00381a013]

3. Benigni R, Cotta-Ramusino M, Giorgi F, Gallo G..  (1995)  Molecular similarity matrices and quantitative structure-activity relationships: a case study with methodological implications.,  38  (4): [PMID:7861411] [10.1021/jm00004a009]

4. Yokono S, Shieh DD, Goto H, Arakawa K..  (1982)  Hydrogen bonding and anesthetic potency.,  25  (7): [PMID:7108906] [10.1021/jm00349a023]

5. Caron G, Ermondi G..  (2005)  Calculating virtual log P in the alkane/water system (log P(N)(alk)) and its derived parameters deltalog P(N)(oct-alk) and log D(pH)(alk).,  48  (9): [PMID:15857133] [10.1021/jm048980b]

6. Pérez-Garrido A, Morales Helguera A, Abellán Guillén A, Cordeiro MN, Garrido Escudero A..  (2009)  Convenient QSAR model for predicting the complexation of structurally diverse compounds with beta-cyclodextrins.,  17  (2): [PMID:19056282] [10.1016/j.bmc.2008.11.040]

7. Massarelli I, Imbriani M, Coi A, Saraceno M, Carli N, Bianucci AM..  (2009)  Development of QSAR models for predicting hepatocarcinogenic toxicity of chemicals.,  44  (9): [PMID:19272677] [10.1016/j.ejmech.2009.02.014]

8. Guerra A, Campillo NE, Páez JA..  (2010)  Neural computational prediction of oral drug absorption based on CODES 2D descriptors.,  45  (3): [PMID:20022146] [10.1016/j.ejmech.2009.11.034]

9. PubChem BioAssay data set, 

10. 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]

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

12. Greene N, Fisk L, Naven RT, Note RR, Patel ML, Pelletier DJ..  (2010)  Developing structure-activity relationships for the prediction of hepatotoxicity.,  23  (7): [PMID:20553011] [10.1021/tx1000865]

13. Ekins S, Williams AJ, Xu JJ..  (2010)  A predictive ligand-based Bayesian model for human drug-induced liver injury.,  38  (12): [PMID:20843939] [10.1124/dmd.110.035113]

14. Abraham MH, Ibrahim A, Acree WE..  (2008)  Air to lung partition coefficients for volatile organic compounds and blood to lung partition coefficients for volatile organic compounds and drugs.,  43  (3): [PMID:17544548] [10.1016/j.ejmech.2007.04.002]

15. Scott S. Auerbach, DrugMatrix¨ and ToxFX¨ Coordinator National Toxicology Program. DrugMatrix in vitro pharmacology data, 

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

17. Teulon DA, Davidson MM, Hedderley DI, James DE, Fletcher CD, Larsen L, Green VC, Perry NB..  (2007)  4-pyridyl carbonyl and related compounds as thrips lures: effectiveness for onion thrips and new zealand flower thrips in field experiments.,  55  (15): [PMID:17602496] [10.1021/jf070389a]

18. PubChem BioAssay data set, 

19. Hopfinger AJ, Battershell RD..  (1976)  Application of SCAP to drug design. 1. Prediction of octanol-water partition coefficients using solvent-dependent conformational analyses.,  19  (5): [PMID:1271397] [10.1021/jm00227a001]

20. Unpublished dataset, 

21. WHO Anatomical Therapeutic Chemical Classification, 

22. DrugMatrix,  [10.6019/CHEMBL3885881]

Source

Source(6):

• Scientific Literature
• PubChem BioAssays
• USP Dictionary of USAN and International Drug Names
• DrugMatrix
• Withdrawn Drugs
• WHO Anatomical Therapeutic Chemical Classification