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Sanjay Rajnikant Patel ;

Abstract: The current view for fluorescence collisional quenching (FCQ) experiments is that no quantitative information can be retrieved from macromolecules containing more than a single dye-quencher pair attached at two specific positions on a macromolecule. This holds true for pyrene excimer formation (PEF), a well-established FCQ phenomenon, where an excimer is produced through the encounter between an excited and a ground-state pyrenyl labels attached onto a macromolecule. In contrast, recent studies suggest that the analysis of fluorescence decays acquired with macromolecules containing many pyrenyl labels with the model free analysis (MFA) and florescence blob model (FBM) yields quantitative information about the internal dynamics and local density of macromolecules in solution. The underlying physical principle enabling the MFA and FBM to probe macromolecules in this manner is based on the direct relationship existing between the average rate constant () for PEF and the local concentration ([Py]loc) of pyrenyl labels on the macromolecule. Yet, and despite its importance, no study has conclusively validated this relationship. This is due, in part, to the difficulty in determining [Py]loc for pyrene-labeled macromolecules (PyLM) and benchmarking this methodology against other experimental techniques. In the present thesis, this fundamental relationship was demonstrated with a series of polyamidoamine (PAMAM) dendrimers of generations GY (=0, 1, or 2) that had been labeled with pyrene derivatives having different numbers X (= 4, 8, or 12) of carbon atoms in the pyrenyl linker to yield the PyCX-PAMAM-GY samples. The fluorescence decays were acquired in N,Ndimethylformamide (DMF) and dimethylsulfoxide (DMSO) and analyzed with the MFA to retrieve , which was compared to [Py]loc obtained by assuming that the internal segments of the PyCX-PAMAM-GY samples linking the pyrenyl labels obeyed Gaussian statistics. The direct relationship found between and [Py]loc for the PyCX-PAMAM-GY samples provided a vi validation for this assumption and demonstrated that PEF can be employed to probe the conformation of macromolecules in solution. Subsequently, PEF was applied to probe the conformational changes induced by protonating the internal tertiary amines of the PyCX-PAMAM-GY samples, showcasing PEF's ability to study these conformational changes intramolecularly, a feat difficult to achieve by traditional methods used for characterizing macromolecular conformations in solution. Expanding beyond dendrimers, PEF was applied to study the conformation of larger macromolecules like poly(glutamic acid) (PGA) and polynorbornene (PNb) on different length scales by using 1-pyrenealkylamines with varied alkyl side chains. The fluorescence blob model (FBM) was applied to determine the number (Nblob exp) of structural units within a blob, the volume probed by an excited pyrenyl label, taken as a measure of the local macromolecular density. Comparison of Nblob exp with Nblob MMO obtained through molecular mechanic optimizations (MMOs) validated PEF's ability to probe macromolecular conformations over different length scales. The conformation of the Py-PGA constructs was found to remain unchanged when probed with 1-pyrenealkylamines having different linker lengths reflecting a homogeneous conformation over different length scales. In contrast, the Py-PNb samples appeared helical and randomly coiled for the 1-pyrenealkylamines with a shorter and longer linker, respectively, highlighting the potential of PEF at probing complex macromolecules with heterogeneous conformation across various length scales. In conclusion, this thesis further supports the applicability of PEF as a robust experimental technique for probing the conformations and internal dynamics of macromolecules in solution.

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Patel, Sanjay ; Duhamel, Jean ;

Abstract: A series of pyrene-labeled PAMAM dendrimers (PyCX-PAMAM-GY, where X (=4, 8, or 12) and Y (=0, 1, or 2) represent the number of atoms in the pyrenyl linker and the dendrimer generation, resp.) were studied by acquiring their time-resolved fluorescence decays in N,N-dimethylformamide (DMF) and DMSO. The fluorescence decays were fitted globally according to the model-free anal. (MFA), which yielded the average rate constant 〈k〉 for pyrene excimer formation (PEF). 〈k〉 was compared with the local pyrene concentration [Py]loc inside the dendrimers, which was calculated by assuming that the segments constituting the dendrimer interior obey Gaussian statistics. 〈k〉 was found to increase linearly with [Py]loc in both solvents, but the straight lines had different slopes due to differences in solvent viscosity and polarity. These differences were accounted for by dividing 〈k〉 by kdiff, which is the bimol. rate constant for PEF generated by n-hexyl-1-pyrenebutyramide used as a model compound The 〈k〉/kdiff ratios obtained for all the PyCX-PAMAM-GY samples in DMF and DMSO collapsed onto a single master line where 〈k〉/kdiff increased linearly with [Py]loc. The strong correlation found between 〈k〉 and [Py]loc suggested that the oligomeric segments constituting the interior of the low-generation (Y = 0, 1, and 2) PAMAM dendrimers obeyed Gaussian statistics. This fact was further supported by using the Gaussian approximation to calculate the radius of gyration (Rg) of PAMAM dendrimers and compare them to the Rg values obtained by mol. dynamics simulations. The excellent agreement obtained between the two sets of Rg values validated the assumption. Furthermore, the direct relationship between 〈k〉 and [Py]loc established in this study demonstrates that 〈k〉 provides a quant. measure of the internal d. of the dendrimers, an observation with considerable implications for the quant. conformational characterization of macromols. with a complex architecture in solution

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Product Details of [ 3903-40-0 ]

CAS No. :3903-40-0
Formula : C13H24O4
M.W : 244.33
SMILES Code : O=C(OC)CCCCCCCCCCC(O)=O
MDL No. :MFCD00053323
InChI Key :REGGDLIBDASKGE-UHFFFAOYSA-N
Pubchem ID :231998

Safety of [ 3903-40-0 ]

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

Computational Chemistry of [ 3903-40-0 ] Show Less

Physicochemical Properties

Num. heavy atoms 17
Num. arom. heavy atoms 0
Fraction Csp3 0.85
Num. rotatable bonds 12
Num. H-bond acceptors 4.0
Num. H-bond donors 1.0
Molar Refractivity 67.66
TPSA ?

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

63.6 Ų

Lipophilicity

Log Po/w (iLOGP)?

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

2.84
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

3.73
Log Po/w (WLOGP)?

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

3.15
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.

2.4
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

3.14
Consensus Log Po/w?

Consensus Log Po/w: Average of all five predictions

3.05

Water Solubility

Log S (ESOL):?

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

-2.91
Solubility 0.299 mg/ml ; 0.00122 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.

-4.76
Solubility 0.00427 mg/ml ; 0.0000175 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

-3.38
Solubility 0.101 mg/ml ; 0.000413 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.

-5.14 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

1.0
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<3.0
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)

2.09
 

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