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Chemical Structure| 72607-53-5 Chemical Structure| 72607-53-5
Chemical Structure| 72607-53-5

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N-(3-Aminopropyl)methacrylamide hydrochloride

CAS No.: 72607-53-5

4.5 *For Research Use Only !

Cat. No.: A245395 Purity: 97%

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Product Citations      Show More

Erning, Kevin ; Wilson, Katrina L ; Smith, Cara S , et al.

Abstract: Ischemic stroke, a blockage in the vasculature of the brain that results in insufficient blood flow, is one of the world’s leading causes of disability. The cascade of inflammation and cell death that occurs immediately following stroke drives vascular and functional loss that does not fully recover over time, and no Food and Drug Administration (FDA)-approved therapies exist that stimulate regeneration post-stroke. A hyaluronic acid (HA)-based hydrogel was previously developed that delivered heparin nanoparticles alone, to reduce glial reactivity, and heparin nanoparticles with vascular endothelial growth factor (VEGF) bound to their surface, to promote angiogenesis. However, the inclusion of the naked heparin nanoparticles warranted concern over the development of bleeding complications. Here, it is explored how microporous annealed particle (MAP) scaffolds functionalized with VEGF coated heparin nanoparticles can both reduce glial reactivity and promote angiogenesis – without the inclusion of free heparin nanoparticles. It is showed that the updated design successfully promotes de novo tissue formation, including the development of mature vessels and neurite sprouting, and leads to functional improvement in a photothrombotic stroke model. In addition, increased astrocyte infiltration is found into the infarct site correlated with mature vessel formation. This work demonstrates how the biomaterial design can enhance endogenous regeneration post-stroke while eliminating the need for excess heparin.

Keywords: angiogenesis ; hydrogels ; MAP ; microgel/microparticles ; stroke ; VEGF ; vessel maturation

Purchased from AmBeed:

Erning, Kevin ; Wilson, Katrina L ; Smith, Cara S , et al.

Abstract: Ischemic stroke, a blockage in the vasculature of the brain that results in insufficient blood flow, is one of the world’s leading causes of disability. The cascade of inflammation and cell death that occurs immediately following stroke drives vascular and functional loss that does not fully recover over time, and no FDA-approved therapies exist that stimulate regeneration post-stroke. We have previously developed a hydrogel scaffold that delivered heparin nanoparticles with and without VEGF bound to their surface to promote angiogenesis and reduce inflammation, respectively. However, the inclusion of the naked heparin nanoparticles warranted concern over the development of bleeding complications. Here, we explore how microporous annealed particle (MAP) scaffolds functionalized with VEGF coated heparin nanoparticles can both reduce inflammation and promote angiogenesis - without the inclusion of free heparin nanoparticles. We show that our updated design not only successfully promotes de novo tissue formation, including the development of mature vessels and neurite sprouting, but it also leads to functional improvement in a photothrombotic stroke model. In addition, we find increased astrocyte infiltration into the infarct site correlated with mature vessel formation. This work demonstrates how our biomaterial design can enhance endogenous regeneration post-stroke while eliminating the need for excess heparin.

Keywords: MAP ; hydrogels ; microgel/microparticles ; angiogenesis ; vessel maturation ; VEGF ; stroke

Purchased from AmBeed:

Product Details of [ 72607-53-5 ]

CAS No. :72607-53-5
Formula : C7H15ClN2O
M.W : 178.66
SMILES Code : CC(C(NCCCN)=O)=C.[H]Cl
MDL No. :MFCD00078257
InChI Key :XHIRWEVPYCTARV-UHFFFAOYSA-N
Pubchem ID :10375005

Safety of [ 72607-53-5 ]

GHS Pictogram:
Signal Word:Warning
Hazard Statements:H302-H315-H319-H332-H335
Precautionary Statements:P261-P280-P305+P351+P338

Calculated chemistry of [ 72607-53-5 ] Show Less

Physicochemical Properties

Num. heavy atoms 11
Num. arom. heavy atoms 0
Fraction Csp3 0.57
Num. rotatable bonds 5
Num. H-bond acceptors 2.0
Num. H-bond donors 2.0
Molar Refractivity 47.96
TPSA ?

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

55.12 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

0.72
Log Po/w (WLOGP)?

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

0.83
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.

0.57
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

0.26
Consensus Log Po/w?

Consensus Log Po/w: Average of all five predictions

0.48

Water Solubility

Log S (ESOL):?

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

-1.07
Solubility 15.2 mg/ml ; 0.0849 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.

-1.46
Solubility 6.25 mg/ml ; 0.035 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

-1.54
Solubility 5.11 mg/ml ; 0.0286 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.

-6.88 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)

1.63
 

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