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Chemical Structure| 351422-73-6 Chemical Structure| 351422-73-6
Chemical Structure| 351422-73-6

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CAS No.: 351422-73-6

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Mokhtarpour, Nazanin ; Sterling, Alyssa ; Garcia, Joshua J. , et al.

Abstract: Reactive oxygen species (ROS) are a heterogeneous group of highly reactive ions and mols. derived from mol. oxygen (O2) which can cause DNA damage and lead to skin cancer. NADPH oxidase 1 (Nox1) is a major producer of ROS in the skin upon exposure to UV light. Functionally, Nox1 forms a holoenzyme complex that generates two superoxide mols. and reduces NADPH. The signaling activation occurs when the organizer subunit Noxo1 translocates to the plasma membrane bringing a cytochrome P 450, through interaction with Cyba. We propose to design inhibitors that prevent Cyba-Noxo1 binding as a topical application to reduce UV-generated ROS in human skin cells. Design started from an apocynin backbone structure to generate a small mol. to serve as an anchor point. The initial compound was then modified by addition of a polyethylene glycol linked biotin. Both inhibitors were found to be non-toxic in human keratinocyte cells. Further in vitro experiments using isothermal calorimetric binding quantification showed the modified biotinylated compound bound Noxo1 peptide with a KD of 2 nM. Both using isothermal calorimetric binding and MALDI (TOF) MS showed that binding of a Cyba peptide to Noxo1 was blocked. In vivo experiments were performed using donated skin explants with topical application of the two inhibitors. Experiments show that UV light exposure of with the lead compound was able to reduce the amount of cyclobutene pyrimidine dimers in DNA, a mol. known to lead to carcinogenesis. Further synthesis showed that the polyethylene glycol but not the biotin was essential for inhibition.

Keywords: Reactive oxygen species ; Apocynin ; UV ; Noxo1 ; Cyba ; Cyclobutane pyrimidine dimer ; CPD ; UV protection

Purchased from AmBeed: ; ; ; ; ;

Senevirathne, Priyangika Prasadini ;

Abstract: Reactive oxygen species are a group of highly reactive oxygen-containing entities that are important at a cellular level for multiple biological processes. Low concentrations of ROS can be beneficial as powerful signaling molecules in those biological processes, although excessive concentrations can promote high levels of DNA damage and a variety of diseases such as skin cancer. A newly identified intracellular ROS production source in skin cells is NADPH oxidases. Out of the NOX enzyme family, the NOX1 holoenzyme is most abundantly expressed in the human keratinocyte cells. UV radiation can trigger the activation of NOX1 isoforms which stimulate the assembling of member CYBA and the cytoplasmic protein NOXO1. Inhibition of these enzymes represents a catalytic approach toward reducing ROS for the prevention of ROS inducible diseases. Key disease states include melanoma induced by UV exposure. The first half of the dissertation focuses on investigating new small molecule inhibitors of a key NOX1 holoenzyme to address these challenges. We designed a series of molecules by optimizing the structure of diapocynin and evaluated by in-silico docking methods to determine the binding affinity with NOXO1 cytoplasmic protein (1WLP crystal structure). And have synthesized the series of target molecules for the structure-activity relationship studies. In the first section of the project, we discovered that inhibitor NOX_inh_5 was not cytotoxic, but instead improved the viability of human primary cells from UV exposure, decreased the cellular stress in human skin through the p53 pathway, and reduced the UV-induced DNA damage as monitored by quantification of cyclobutane dimer formation after UV exposure. Then, we characterized the inhibition potential of NOX_inh_5 by using an Isothermal calorimetric (ITC) binding assay and heteronuclear single quantum coherence (HSQC) technique and revealed that the candidate iii molecule can prevent the complex formation of NOXO1 and CYBA membrane protein. In the second section of the project, we did a structure-activity relationship study for the NOX_inh_5 small molecule to optimize the biological characteristics. The last section of the dissertation discussed the development of ROS sensible prodrug to combat the opioid overdose crisis. Here we used oxidative stress conditions caused by opioid overdose to activate the prodrug. Even though opioid antagonist naloxone has a high affinity to bind with opioid receptors to block opioid-induced activation, it is metabolically unstable and has a short half-life of around 33 min. We developed a peroxide-induced prodrug to overcome this issue that can release a steady stream of naloxone. This allows the concentration of naloxone to remain high for longer periods.

Alternative Products

Product Details of [ 351422-73-6 ]

CAS No. :351422-73-6
Formula : C7H8BNO3
M.W : 164.95
SMILES Code : C1=C(C=CC=C1C(=O)N)B(O)O
MDL No. :MFCD03411948
InChI Key :WDGWHKRJEBENCE-UHFFFAOYSA-N
Pubchem ID :2737814

Safety of [ 351422-73-6 ]

GHS Pictogram:
Signal Word:Warning
Hazard Statements:H302-H315-H319-H335
Precautionary Statements:P261-P305+P351+P338

Calculated chemistry of [ 351422-73-6 ] Show Less

Physicochemical Properties

Num. heavy atoms 12
Num. arom. heavy atoms 6
Fraction Csp3 0.0
Num. rotatable bonds 2
Num. H-bond acceptors 3.0
Num. H-bond donors 3.0
Molar Refractivity 44.36
TPSA ?

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

83.55 ?2

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

-0.3
Log Po/w (WLOGP)?

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

-1.53
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.

-0.54
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

-1.58
Consensus Log Po/w?

Consensus Log Po/w: Average of all five predictions

-0.79

Water Solubility

Log S (ESOL):?

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

-0.91
Solubility 20.2 mg/ml ; 0.123 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.

-0.99
Solubility 16.7 mg/ml ; 0.101 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

-0.87
Solubility 22.3 mg/ml ; 0.135 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

 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

 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.

-7.52 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)

 1.47
 

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