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Structure of 595-91-5

Chemical Structure| 595-91-5

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Vlahakis, Niko William ;

Abstract: Microcrystal electron diffraction (MicroED) has emerged as a powerful method for atomic structure determination without need for large, pristine crystals, a prerequisite for successful structure determination by single-crystal X-ray diffraction. However, the accuracy of MicroED structures appears to trail behind that of structures determined by X-ray crystallography, especially for crystals of beam-sensitive small molecules or proteins. This dissertation details work toward methodological improvement of MicroED for use in interrogating biomolecular structure by characterizing sources of error, developing new data acquisition strategies, and testing the limits of the technique for extracting elusive structural information from nanocrystals. Critical to the effort are the reduction of electron dose delivered to these radiation-sensitive crystals, and accounting for nanocrystal imperfections common in molecular crystals. The former of these obstacles compelled us to leverage fast counting direct electron detectors for rapid diffraction data acquisition on small molecules, where we demonstrate that in certain cases the total beam fluence on a crystal can be limited to under 1 e-2 while still delivering accurate atomic resolution structures. In doing so, we also assess the impact of coincidence loss on MicroED data collected using this strategy. In developing these methods, we identified and characterized an electron beam-induced warping effect we occurring near-ubiquitously during electron diffraction of molecular nanocrystals. This manifests as non-monotonic fluctuations in Bragg reflection intensities in response to electron beam irradiation of a crystal, occurs concurrently with the anticipated radiolytic decay of diffraction signal, and can be modeled as bends propagating through the crystal lattice. These investigations inform a study applying MicroED to capture structures of the model enzyme papain soaked with libraries of biosynthetic potential inhibitors; in cases where the identity of a ligand detected in a cocktail-soaked enzyme crystal structure remains ambiguous, we demonstrate that native mass spectrometry paired with MicroED precisely identifies the bound compound. Lastly, we detail advances in developing sample preparation and data acquisition methods for acquiring diffraction data at room temperature on hydrated nanocrystals, opening the door for MicroED to deliver novel insights on temperature-dependent conformational dynamics. These developments expand the utility of MicroED in determining atomic structures of macromolecules, biologically active small molecules, and protein-ligand complexes.

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Product Details of [ 595-91-5 ]

CAS No. :595-91-5
Formula : C20H16O2
M.W : 288.34
SMILES Code : OC(=O)C(C1=CC=CC=C1)(C1=CC=CC=C1)C1=CC=CC=C1
MDL No. :MFCD00004185
InChI Key :DCYGAPKNVCQNOE-UHFFFAOYSA-N
Pubchem ID :68992

Safety of [ 595-91-5 ]

GHS Pictogram:
Signal Word:Warning
Hazard Statements:H302-H315-H319-H335-H413
Precautionary Statements:P261-P305+P351+P338

Computational Chemistry of [ 595-91-5 ] Show Less

Physicochemical Properties

Num. heavy atoms 22
Num. arom. heavy atoms 18
Fraction Csp3 0.05
Num. rotatable bonds 4
Num. H-bond acceptors 2.0
Num. H-bond donors 1.0
Molar Refractivity 86.84
TPSA ?

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

37.3 Ų

Lipophilicity

Log Po/w (iLOGP)?

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

2.47
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

4.32
Log Po/w (WLOGP)?

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

4.11
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.

4.36
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

4.3
Consensus Log Po/w?

Consensus Log Po/w: Average of all five predictions

3.91

Water Solubility

Log S (ESOL):?

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

-4.69
Solubility 0.00588 mg/ml ; 0.0000204 mol/l
Class?

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

Moderately soluble
Log S (Ali)?

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

-4.82
Solubility 0.00439 mg/ml ; 0.0000152 mol/l
Class?

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

Moderately 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

-6.85
Solubility 0.000041 mg/ml ; 0.000000142 mol/l
Class?

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

Poorly 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

Yes
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.

-4.99 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

1.0
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.

0.56

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

0.0 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)

2.36

Application In Synthesis of [ 595-91-5 ]

* All experimental methods are cited from the reference, please refer to the original source for details. We do not guarantee the accuracy of the content in the reference.

  • Downstream synthetic route of [ 595-91-5 ]
 

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