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Chemical Structure| 2243-61-0

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Product Citations

Zawadzka, Magdalena ; Nitschke, Pawel ; Musiol, Marta ; Siwy, Mariola ; Pluczyk-Malek, Sandra ; Honisz, Damian , et al.

Abstract: Electrochromism of organic compounds is a well-known phenomenon; however, nowadays, most research is focused on anodic coloring materials. Development of efficient, cathodic electrochromic materials is challenging due to the worse stability of electron accepting materials compared with electron donating ones. Nevertheless, designing stable cathodic coloring organic materials is highly desired-among other reasons-to increase the coloration performance. Hence, four phthalimide derivatives named 1,5-PhDI, 1,4-PhDI, 2,6-PhDI and 3,3-PhDI were synthesized and analyzed in depth. In all cases, two imide groups were connected via naphthalene (1,5-PhDI, 1,4-PhDI, 2,6-PhDI) or 3,3-dimethylnaphtidin (3,3-PhDI) bridge. To observe the effect of chem. structure on physicochem. properties, various positions of imide bond were considered, namely, 1,5- 1,4- and 2,6-. Addnl., a compound with the pyromellitic diimide unit capped with two 1-naphtalene substituents was obtained. All compounds were studied in terms of their thermal behavior, using differential calorimetry (DSC) and thermogravimetric anal. (TGA). Moreover, electrochem. (CV, DPV) and spectroelectrochem. (UV-Vis and EPR) analyses were performed to evaluate the obtained materials in terms of their application as cathodic electrochromic materials. All obtained materials undergo reversible electrochem. reduction which leads to changes in their optical properties. In the case of imide derivatives, absorption bands related to both reduced and neutral forms are located in the UV region. However, importantly, the introduction of the 3,3-dimethylnaphtidine bridge leads to a noticeable bathochromic shift of the reduced form absorption band of 3,3-PhDI. This indicates that optimization of the phthalimide structure allows us to obtain stable, cathodic electrochromic materials.

Keywords: electrochemistry ; spectroelectrochemistry ; electrochromism ; phthalimides

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Product Details of [ 2243-61-0 ]

CAS No. :2243-61-0
Formula : C10H10N2
M.W : 158.20
SMILES Code : NC1=C2C=CC=CC2=C(N)C=C1
MDL No. :MFCD01712813
InChI Key :OKBVMLGZPNDWJK-UHFFFAOYSA-N
Pubchem ID :16719

Safety of [ 2243-61-0 ]

GHS Pictogram:
Signal Word:Warning
Hazard Statements:H302-H319
Precautionary Statements:P305+P351+P338

Computational Chemistry of [ 2243-61-0 ] Show Less

Physicochemical Properties

Num. heavy atoms 12
Num. arom. heavy atoms 10
Fraction Csp3 0.0
Num. rotatable bonds 0
Num. H-bond acceptors 0.0
Num. H-bond donors 2.0
Molar Refractivity 52.76
TPSA ?

Topological Polar Surface Area: Calculated from
Ertl P. et al. 2000 J. Med. Chem.

52.04 Ų

Lipophilicity

Log Po/w (iLOGP)?

iLOGP: in-house physics-based method implemented from
Daina A et al. 2014 J. Chem. Inf. Model.

1.26
Log Po/w (XLOGP3)?

XLOGP3: Atomistic and knowledge-based method calculated by
XLOGP program, version 3.2.2, courtesy of CCBG, Shanghai Institute of Organic Chemistry

0.89
Log Po/w (WLOGP)?

WLOGP: Atomistic method implemented from
Wildman SA and Crippen GM. 1999 J. Chem. Inf. Model.

2.02
Log Po/w (MLOGP)?

MLOGP: Topological method implemented from
Moriguchi I. et al. 1992 Chem. Pharm. Bull.
Moriguchi I. et al. 1994 Chem. Pharm. Bull.
Lipinski PA. et al. 2001 Adv. Drug. Deliv. Rev.

1.88
Log Po/w (SILICOS-IT)?

SILICOS-IT: Hybrid fragmental/topological method calculated by
FILTER-IT program, version 1.0.2, courtesy of SILICOS-IT, http://www.silicos-it.com

1.53
Consensus Log Po/w?

Consensus Log Po/w: Average of all five predictions

1.52

Water Solubility

Log S (ESOL):?

ESOL: Topological method implemented from
Delaney JS. 2004 J. Chem. Inf. Model.

-2.0
Solubility 1.59 mg/ml ; 0.01 mol/l
Class?

Solubility class: Log S scale
Insoluble < -10 < Poorly < -6 < Moderately < -4 < Soluble < -2 Very < 0 < Highly

Very soluble
Log S (Ali)?

Ali: Topological method implemented from
Ali J. et al. 2012 J. Chem. Inf. Model.

-1.57
Solubility 4.28 mg/ml ; 0.0271 mol/l
Class?

Solubility class: Log S scale
Insoluble < -10 < Poorly < -6 < Moderately < -4 < Soluble < -2 Very < 0 < Highly

Very soluble
Log S (SILICOS-IT)?

SILICOS-IT: Fragmental method calculated by
FILTER-IT program, version 1.0.2, courtesy of SILICOS-IT, http://www.silicos-it.com

-3.34
Solubility 0.072 mg/ml ; 0.000455 mol/l
Class?

Solubility class: Log S scale
Insoluble < -10 < Poorly < -6 < Moderately < -4 < Soluble < -2 Very < 0 < Highly

Soluble

Pharmacokinetics

GI absorption?

Gatrointestinal absorption: according to the white of the BOILED-Egg

High
BBB permeant?

BBB permeation: according to the yolk of the BOILED-Egg

Yes
P-gp substrate?

P-glycoprotein substrate: SVM model built on 1033 molecules (training set)
and tested on 415 molecules (test set)
10-fold CV: ACC=0.72 / AUC=0.77
External: ACC=0.88 / AUC=0.94

No
CYP1A2 inhibitor?

Cytochrome P450 1A2 inhibitor: SVM model built on 9145 molecules (training set)
and tested on 3000 molecules (test set)
10-fold CV: ACC=0.83 / AUC=0.90
External: ACC=0.84 / AUC=0.91

Yes
CYP2C19 inhibitor?

Cytochrome P450 2C19 inhibitor: SVM model built on 9272 molecules (training set)
and tested on 3000 molecules (test set)
10-fold CV: ACC=0.80 / AUC=0.86
External: ACC=0.80 / AUC=0.87

No
CYP2C9 inhibitor?

Cytochrome P450 2C9 inhibitor: SVM model built on 5940 molecules (training set)
and tested on 2075 molecules (test set)
10-fold CV: ACC=0.78 / AUC=0.85
External: ACC=0.71 / AUC=0.81

No
CYP2D6 inhibitor?

Cytochrome P450 2D6 inhibitor: SVM model built on 3664 molecules (training set)
and tested on 1068 molecules (test set)
10-fold CV: ACC=0.79 / AUC=0.85
External: ACC=0.81 / AUC=0.87

No
CYP3A4 inhibitor?

Cytochrome P450 3A4 inhibitor: SVM model built on 7518 molecules (training set)
and tested on 2579 molecules (test set)
10-fold CV: ACC=0.77 / AUC=0.85
External: ACC=0.78 / AUC=0.86

No
Log Kp (skin permeation)?

Skin permeation: QSPR model implemented from
Potts RO and Guy RH. 1992 Pharm. Res.

-6.63 cm/s

Druglikeness

Lipinski?

Lipinski (Pfizer) filter: implemented from
Lipinski CA. et al. 2001 Adv. Drug Deliv. Rev.
MW ≤ 500
MLOGP ≤ 4.15
N or O ≤ 10
NH or OH ≤ 5

0.0
Ghose?

Ghose filter: implemented from
Ghose AK. et al. 1999 J. Comb. Chem.
160 ≤ MW ≤ 480
-0.4 ≤ WLOGP ≤ 5.6
40 ≤ MR ≤ 130
20 ≤ atoms ≤ 70

None
Veber?

Veber (GSK) filter: implemented from
Veber DF. et al. 2002 J. Med. Chem.
Rotatable bonds ≤ 10
TPSA ≤ 140

0.0
Egan?

Egan (Pharmacia) filter: implemented from
Egan WJ. et al. 2000 J. Med. Chem.
WLOGP ≤ 5.88
TPSA ≤ 131.6

0.0
Muegge?

Muegge (Bayer) filter: implemented from
Muegge I. et al. 2001 J. Med. Chem.
200 ≤ MW ≤ 600
-2 ≤ XLOGP ≤ 5
TPSA ≤ 150
Num. rings ≤ 7
Num. carbon > 4
Num. heteroatoms > 1
Num. rotatable bonds ≤ 15
H-bond acc. ≤ 10
H-bond don. ≤ 5

1.0
Bioavailability Score?

Abbott Bioavailability Score: Probability of F > 10% in rat
implemented from
Martin YC. 2005 J. Med. Chem.

0.55

Medicinal Chemistry

PAINS?

Pan Assay Interference Structures: implemented from
Baell JB. & Holloway GA. 2010 J. Med. Chem.

0.0 alert
Brenk?

Structural Alert: implemented from
Brenk R. et al. 2008 ChemMedChem

1.0 alert: heavy_metal
Leadlikeness?

Leadlikeness: implemented from
Teague SJ. 1999 Angew. Chem. Int. Ed.
250 ≤ MW ≤ 350
XLOGP ≤ 3.5
Num. rotatable bonds ≤ 7

No; 1 violation:MW<1.0
Synthetic accessibility?

Synthetic accessibility score: from 1 (very easy) to 10 (very difficult)
based on 1024 fragmental contributions (FP2) modulated by size and complexity penaties,
trained on 12'782'590 molecules and tested on 40 external molecules (r2 = 0.94)

1.0
 

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