Home Cart Sign in  
Chemical Structure| 220728-62-1 Chemical Structure| 220728-62-1

Structure of 220728-62-1

Chemical Structure| 220728-62-1

*Storage: {[sel_prStorage]}

*Shipping: {[sel_prShipping]}

,{[proInfo.pro_purity]}

4.5 *For Research Use Only !

{[proInfo.pro_purity]}
Cat. No.: {[proInfo.prAm]} Purity: {[proInfo.pro_purity]}

Change View

Size Price VIP Price

US Stock

Global Stock

In Stock
{[ item.pr_size ]} Inquiry {[ getRatePrice(item.pr_usd,item.pr_rate,item.mem_rate,item.pr_is_large_size_no_price, item.vip_usd) ]}

US Stock: ship in 0-1 business day
Global Stock: ship in 5-7 days

  • {[ item.pr_size ]}

In Stock

- +

Please Login or Create an Account to: See VIP prices and availability

US Stock: ship in 0-1 business day
Global Stock: ship in 2 weeks

  • 1-2 Day Shipping
  • High Quality
  • Technical Support
Product Citations

Product Citations

Evan S. O& ; amp ; amp ; #39 ; Brien ; Vipin Ashok Rangari , et al.

Abstract: The µ-opioid receptor (µOR) is a well-established target for analgesia1, yet conventional agonists cause serious adverse efects, notably addiction and respiratory depression. These factors have contributed to the current opioid overdose epidemic driven by fentanyl2, a highly potent synthetic opioid. µOR negative allosteric modulators (NAMs) may serve as useful tools in preventing opioid overdose deaths, but promising chemical scafolds remain elusive. Here we screened a large DNA-encoded chemical library against inactive µOR, counter-screening with active, G-protein and agonist-bound receptor to ‘steer’ hits towards conformationally selective modulators. We discovered a NAM compound with high and selective enrichment to inactive µOR that enhances the afnity of the key opioid overdose reversal molecule, naloxone. The NAM works cooperatively with naloxone to potently block opioid agonist signalling. Using cryogenic electron microscopy, we demonstrate that the NAM accomplishes this efect by binding a site on the extracellular vestibule in direct contact with naloxone while stabilizing a distinct inactive conformation of the extracellular portions of the second and seventh transmembrane helices. The NAM alters orthosteric ligand kinetics in therapeutically desirable ways and works cooperatively with low doses of naloxone to efectively inhibit various morphine-induced and fentanyl-induced behavioural efects in vivo while minimizing withdrawal behaviours. Our results provide detailed structural insights into the mechanism of negative allosteric modulation of the µOR and demonstrate how this can be exploited in vivo.

Purchased from AmBeed: ; ;

Alternative Products

Product Details of [ 220728-62-1 ]

CAS No. :220728-62-1
Formula : C8H9IO
M.W : 248.06
SMILES Code : COC1=CC(I)=CC=C1C
MDL No. :MFCD06797971
InChI Key :JVKISKVALBFNFA-UHFFFAOYSA-N
Pubchem ID :10890246

Safety of [ 220728-62-1 ]

GHS Pictogram:
Signal Word:Warning
Hazard Statements:H315-H319-H335
Precautionary Statements:P261-P264-P271-P280-P302+P352-P304+P340+P312-P305+P351+P338-P332+P313-P337+P313-P362-P403+P233-P405-P501

Computational Chemistry of [ 220728-62-1 ] Show Less

Physicochemical Properties

Num. heavy atoms 10
Num. arom. heavy atoms 6
Fraction Csp3 0.25
Num. rotatable bonds 1
Num. H-bond acceptors 1.0
Num. H-bond donors 0.0
Molar Refractivity 50.62
TPSA ?

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

9.23 Ų

Lipophilicity

Log Po/w (iLOGP)?

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

2.48
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

2.91
Log Po/w (WLOGP)?

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

2.61
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.

3.03
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

3.25
Consensus Log Po/w?

Consensus Log Po/w: Average of all five predictions

2.86

Water Solubility

Log S (ESOL):?

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

-3.59
Solubility 0.0639 mg/ml ; 0.000257 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.

-2.76
Solubility 0.426 mg/ml ; 0.00172 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

-3.87
Solubility 0.0336 mg/ml ; 0.000136 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.

-5.75 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)

1.66
 

Historical Records

Technical Information

Categories