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Structure of 244193-56-4

Chemical Structure| 244193-56-4

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Product Citations

Product Citations

Karki, Nawaraj ; Wilson, Andrew J ;

Abstract: Control over reaction selectivity is among the leading challenges in a wide range of electrocatalytic reactions. Here, we report an approach to tune selectivity in electrocatalytic reactions involving neutrally charged analytes. Using electrocatalytic CO2 reduction in an aqueous medium as a model system, we show that after the interaction of the neutral analyte with an ionic species, the selectivity of CO production over competing H2 production is improved by targeting the mass transport enhancement of charged species using an external magnetic field. Nuclear magnetic resonance spectroscopy and infrared spectroscopy are used to confirm that CO2 can physisorb and chemisorb to imidazolium-based ionic liquids to form charged species. Chronoamperometry and measurements of products with gas chromatography provide evidence that the enhanced transport of charged CO2 complexes induced by an external magnetic field alters reaction selectivity. The reaction selectivity is tunable through the Lorentz force, dependent on the magnetic field strength and current density. Improving the mass transport of CO2 to electrocatalysts with ionic liquids and magnetic fields can improve the energy efficiency of CO2 reduction as well as alter concentration gradients, potentially allowing control over product branching beyond what is possible with electrocatalyst and electrolyte design. The general approach and insights provided in this study are also envisioned to be complementary to electrocatalyst and electrolyte developments for modulating selectivity in electrocatalytic reactions involving neutral species beyond CO2.

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Product Details of [ 244193-56-4 ]

CAS No. :244193-56-4
Formula : C14H27BF4N2
M.W : 310.18
SMILES Code : C[N+]1=CN(CCCCCCCCCC)C=C1.F[B-](F)(F)F
MDL No. :MFCD09038853
InChI Key :QGUMDWFYJYXDTH-UHFFFAOYSA-N
Pubchem ID :11461044

Safety of [ 244193-56-4 ]

GHS Pictogram:
Signal Word:Warning
Hazard Statements:H302-H315-H319
Precautionary Statements:P264-P270-P280-P301+P312+P330-P302+P352+P332+P313+P362+P364-P305+P351+P338+P337+P313-P501

Computational Chemistry of [ 244193-56-4 ] Show Less

Physicochemical Properties

Num. heavy atoms 21
Num. arom. heavy atoms 5
Fraction Csp3 0.79
Num. rotatable bonds 9
Num. H-bond acceptors 4.0
Num. H-bond donors 0.0
Molar Refractivity 82.73
TPSA ?

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

8.81 Ų

Lipophilicity

Log Po/w (iLOGP)?

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

0.0
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

6.8
Log Po/w (WLOGP)?

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

6.43
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.

3.24
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

3.16
Consensus Log Po/w?

Consensus Log Po/w: Average of all five predictions

3.93

Water Solubility

Log S (ESOL):?

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

-5.63
Solubility 0.000728 mg/ml ; 0.00000235 mol/l
Class?

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

Moderately soluble
Log S (Ali)?

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

-6.79
Solubility 0.00005 mg/ml ; 0.000000161 mol/l
Class?

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

Poorly 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

-4.01
Solubility 0.0301 mg/ml ; 0.0000971 mol/l
Class?

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

Moderately soluble

Pharmacokinetics

GI absorption?

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

Low
BBB permeant?

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

No
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.

-3.36 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

1.0
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

2.0 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<2.0
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)

2.37
 

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