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Chemical Structure| 105832-38-0 Chemical Structure| 105832-38-0

Structure of TSTU
CAS No.: 105832-38-0

Chemical Structure| 105832-38-0

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Product Citations

Product Citations      Show More

Zhao, Spencer ; Loh, Kang Yong ; Tyson, Jonathan ; Kadur, Chandan ; Bertozzi, Carolyn ; Deisseroth, Karl , et al.

Abstract: Catalytic reactions of a broad range of abiotic molecules and macromolecules are beyond the native capabilities of mammals. Natural enzymes from prokaryotes or plant-based eukaryotes have limited substrate scopes. Therefore, broadening the range of catalytic bond-forming reactions that function in physiological conditions would enable the syntheses of a vast array of molecules directly within biological systems. This approach may provide an alternative way to modulate cellular behaviors if such molecules can be synthesized with spatiotemporal control on specific cell types in living systems; furthermore, restricting synthesis to well-defined cells or cell-types would enable a potentially transformative approach of treating cells as separable reaction vessels within living organisms. Herein, we use genetic targeting to incorporate an organic photocatalytic dye onto specific cell types to enable in-situ light-controlled and spatially defined chemical synthesis of non-natural molecules. We demonstrate, for the first time, a photo-patterned organic coupling reaction in the extracellular matrix of living cells under dilute, aqueous, aerobic physiological conditions. A 6-fold contrast in reaction yield can be achieved between two adjacent HEK293FT cells with and without light exposure. The above photocatalysis can be initiated using mild confocal laser stimulation as low as 16 μW/mm2 at multiple wavelengths. Furthermore, the cell-type specific photocatalyzed C-H functionalization coupling reactions taking place on cell surfaces are used to demonstrate anabolic construction of non-natural products. The above findings lay an important foundation for developing future abiotic cell-type specific chemical syntheses in living organisms.

Purchased from AmBeed: ; ; ;

Dana Qiang Murphy Soika ;

Abstract: Contrast agents (CAs) are small molecules used in magnetic resonance imaging (MRI) to help diagnose various forms of cancer. While MRI is advantageous over other clinical imaging techniques, limitations of today’s contrast agents containing gadolinium (Gd) hinder their safety, sensitivity, and specificity. The conventional CAs that MRI relies on are considered low-relaxivity and are not optimally effective at enhancing MR signal. Additionally, they lack cell-specificity and circulate throughout the body. Furthermore, unbound Gd3+ is nephrogenic which prevents its use in patients with impaired renal function. In the clinic, these limitations mean high dosages of these compounds must be administered to patients in order to produce an image that struggles to highlight the exact tumor location. Our aim was to improve conventional CAs by synthesizing a high-relaxivity (HR) targeted contrast agent (HR-TCA). The cell-specific nature of the HR-TCA will allow for its accumulation at tumor sites while the HR will produce a stronger MR signal per molecule of CA. Combined, this means a much lower and therefore safer dose of CA can be used to produce an image of the exact tumor location with superior contrast. Our modular approach allows us to easily combine this HR contrast agent (HR-CA) to any targeting peptide using a linker in a convergent, one-step synthesis. Our synthetic approach for the HR-CA module attaches a macrocyclic chelator, DO3A, to the side chain of an orthogonally protected alanine. This is a modification to the approach published by Boros in which t-butyl groups were utilized to protect DO3A. In our modular approach, Gd is chelated early to protect the acetic acid donor arms of DO3A from participating in unwanted side reactions for the remainder of the synthesis, eliminating any need to expose the final HR-TCA to the harsh acidic conditions of TFA that are necessary to remove t-butyl protecting groups. Upon removal of the N-and C-terminal protecting groups, the HR-CA module is coupled directly to our in-house synthesized targeting module which is comprised of the targeting agent (DCL) and linker (DSS) already attached to afford the final HR-TCA. T1 relaxation measurements of relevant intermediates and the final product were performed to compare their relaxivities with those of commercial CAs used in clinics, labs, and hospitals today. Although the HR-CA and final HR-TCA exhibited only a modest increase in T1 relaxivity compared to commercial CA Gd-DOTA, in a striking discovery it was observed that the presence of both a tryptophan spacer and an Fmoc protecting group boosted the T1 relaxivity significantly.

Purchased from AmBeed: ; ;

Alternative Products

Product Details of [ 105832-38-0 ]

CAS No. :105832-38-0
Formula : C9H16BF4N3O3
M.W : 301.05
SMILES Code : C[N+](C)=C(N(C)C)ON1C(CCC1=O)=O.F[B-](F)(F)F
MDL No. :MFCD00077875
InChI Key :YEBLHMRPZHNTEK-UHFFFAOYSA-N
Pubchem ID :9857522

Safety of [ 105832-38-0 ]

GHS Pictogram:
Signal Word:Danger
Hazard Statements:H302-H314
Precautionary Statements:P501-P260-P270-P264-P280-P303+P361+P353-P301+P330+P331-P363-P301+P312+P330-P304+P340+P310-P305+P351+P338+P310-P405
Class:8
UN#:1759
Packing Group:

Computational Chemistry of [ 105832-38-0 ] Show Less

Physicochemical Properties

Num. heavy atoms 20
Num. arom. heavy atoms 0
Fraction Csp3 0.67
Num. rotatable bonds 3
Num. H-bond acceptors 7.0
Num. H-bond donors 0.0
Molar Refractivity 67.22
TPSA ?

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

52.86 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

1.56
Log Po/w (WLOGP)?

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

1.86
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.

0.93
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

0.56

Water Solubility

Log S (ESOL):?

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

-2.49
Solubility 0.971 mg/ml ; 0.00323 mol/l
Class?

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

Soluble
Log S (Ali)?

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

-2.28
Solubility 1.58 mg/ml ; 0.00525 mol/l
Class?

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

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

-0.83
Solubility 44.2 mg/ml ; 0.147 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

No
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.

-7.03 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

0.0
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

5.0 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<0.0
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)

3.31
 

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