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Chemical Structure| 162011-90-7 Chemical Structure| 162011-90-7

Structure of Rofecoxib
CAS No.: 162011-90-7

Chemical Structure| 162011-90-7

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Synonyms: MK 966; MK-0966; Ceoxx

4.5 *For Research Use Only !

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Product Citations

Product Citations

Wegner, Scott A ; Kim, Hahn ; Avalos, José L ;

Abstract: Lactate transport plays a crucial role in the metabolism, microenvironment, and survival of cancer cells. However, current drugs targeting either MCT1 or MCT4, which traditionally mediate lactate import or efflux respectively, show limited efficacy beyond in vitro models. This limitation partly arises from the existence of both isoforms in certain tumors, however existing high-affinity MCT1/4 inhibitors are years away from human testing. Therefore, we conducted an optogenetic drug screen in Saccharomyces cerevisiae on a subset of the FDA-approved drug library to identify existing scaffolds that could be repurposed as monocarboxylate transporter (MCT) inhibitors. Our findings show that several existing drug classes inhibit MCT1 activity, including non-steroidal estrogens, non-steroidal anti-inflammatory drugs (NSAIDs), and natural products (in total representing approximately 1% of the total library, 78 out of 6400), with a moderate affinity (IC50 1.8–21 μM). Given the well-tolerated nature of NSAIDs, and their known anticancer properties associated with COX inhibition, we chose to further investigate their MCT1 inhibition profile. The majority of NSAIDs in our screen cluster into a single large structural grouping. Moreover, this group is predominantly comprised of FDA-approved NSAIDs, with seven exhibiting moderate MCT1 inhibition. Since these molecules form a distinct structural cluster with known NSAID MCT4 inhibitors, such as diclofenac, ketoprofen, and indomethacin, we hypothesize that these newly identified inhibitors may also inhibit both transporters. Consequently, NSAIDs as a class, and piroxicam specifically (IC50 4.4 μM), demonstrate MCT1 inhibition at theoretically relevant human dosages, suggesting immediate potential for standalone MCT inhibition or combined anticancer therapy.

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Product Details of [ 162011-90-7 ]

CAS No. :162011-90-7
Formula : C17H14O4S
M.W : 314.36
SMILES Code : O=C1OCC(C2=CC=C(S(=O)(C)=O)C=C2)=C1C3=CC=CC=C3
Synonyms :
MK 966; MK-0966; Ceoxx
MDL No. :MFCD00935806
InChI Key :RZJQGNCSTQAWON-UHFFFAOYSA-N
Pubchem ID :5090

Safety of [ 162011-90-7 ]

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

Computational Chemistry of [ 162011-90-7 ] Show Less

Physicochemical Properties

Num. heavy atoms 22
Num. arom. heavy atoms 12
Fraction Csp3 0.12
Num. rotatable bonds 3
Num. H-bond acceptors 4.0
Num. H-bond donors 0.0
Molar Refractivity 83.69
TPSA ?

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

68.82 Ų

Lipophilicity

Log Po/w (iLOGP)?

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

2.17
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

2.27
Log Po/w (WLOGP)?

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

3.64
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.

2.62
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

3.27
Consensus Log Po/w?

Consensus Log Po/w: Average of all five predictions

2.79

Water Solubility

Log S (ESOL):?

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

-3.42
Solubility 0.118 mg/ml ; 0.000376 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.

-3.35
Solubility 0.14 mg/ml ; 0.000445 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

-5.92
Solubility 0.000381 mg/ml ; 0.00000121 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

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

Yes
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

Yes
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.

-6.61 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

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<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)

2.82
 

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