Structure of 674799-96-3
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The BI-3802 was designed by Boehringer Ingelheim and could be obtained free of charge through the Boehringer Ingelheim open innovation portal opnMe.com, associated with its negative control.
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A Versatile Silica Functionalization Strategy for Nanomaterials
Keisuke Nagao ; Katherine Lei ; Peyton Worthington ; Noah Kent ; Michika Onoda ; Elian Malkin , et al.
Abstract: Chemical interactions between nanoparticles and their surroundings are governed by their surface chemistry, and thus a versatile strategy for surface functionalization compatible with a variety of particle compositions would empower nanotechnology research. Although silica coating offers a promising approach, common protocols are often impeded by inconsistent reproducibility, non-uniform thicknesses, difficulty in producing thin coatings, and particle aggregation during functionalization. Here, we demonstrate that these challenges can be overcome by adding additional surface ligands to stabilize the particle cores during the silica growth process. The inclusion of excess ligands alters the nanoparticles’ surface chemistry such that particle aggregation is suppressed, even for thin silica coatings (<1 nm) and coatings on a wide range of nanoparticle compositions, sizes, and shapes. The versatility and reproducibility of this approach is illustrated through its application to isotropic magnetite nanoparticles with diameters between 20-28 nm, anisotropic magnetite nanodiscs >200 nm in diameter, and CdS/ZnS quantum dots. These silica-coated nanomaterials retain their functional properties, and the silica shell can be further modified with application-specific organic moieties. Being agnostic to the nanomaterials shape and composition, this approach is enabling to nanomaterials applications demanding precise control over their surface chemistry independent of their functional properties.
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Keywords: silica shell coating ; reverse microemulsion method ; magnetic nanoparticles ; nanodiscs ; quantum dots
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CAS No. : | 674799-96-3 |
Formula : | C13H14N6O |
M.W : | 270.29 |
SMILES Code : | NCC1=CC=C(COC2=NC(N)=NC3=C2NC=N3)C=C1 |
MDL No. : | MFCD22577247 |
InChI Key : | UINSGVKWAFJDPI-UHFFFAOYSA-N |
Pubchem ID : | 25149605 |
GHS Pictogram: |
![]() |
Signal Word: | Warning |
Hazard Statements: | H302-H315-H319-H332-H335 |
Precautionary Statements: | P280-P305+P351+P338-P310 |
Num. heavy atoms | 20 |
Num. arom. heavy atoms | 15 |
Fraction Csp3 | 0.15 |
Num. rotatable bonds | 4 |
Num. H-bond acceptors | 5.0 |
Num. H-bond donors | 3.0 |
Molar Refractivity | 74.74 |
TPSA ? Topological Polar Surface Area: Calculated from |
115.73 Ų |
Log Po/w (iLOGP)? iLOGP: in-house physics-based method implemented from |
1.38 |
Log Po/w (XLOGP3)? XLOGP3: Atomistic and knowledge-based method calculated by |
0.41 |
Log Po/w (WLOGP)? WLOGP: Atomistic method implemented from |
0.68 |
Log Po/w (MLOGP)? MLOGP: Topological method implemented from |
0.53 |
Log Po/w (SILICOS-IT)? SILICOS-IT: Hybrid fragmental/topological method calculated by |
1.23 |
Consensus Log Po/w? Consensus Log Po/w: Average of all five predictions |
0.84 |
Log S (ESOL):? ESOL: Topological method implemented from |
-2.07 |
Solubility | 2.33 mg/ml ; 0.00861 mol/l |
Class? Solubility class: Log S scale |
Soluble |
Log S (Ali)? Ali: Topological method implemented from |
-2.41 |
Solubility | 1.06 mg/ml ; 0.00392 mol/l |
Class? Solubility class: Log S scale |
Soluble |
Log S (SILICOS-IT)? SILICOS-IT: Fragmental method calculated by |
-4.52 |
Solubility | 0.00824 mg/ml ; 0.0000305 mol/l |
Class? Solubility class: Log S scale |
Moderately soluble |
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 |
No |
P-gp substrate? P-glycoprotein substrate: SVM model built on 1033 molecules (training set) |
Yes |
CYP1A2 inhibitor? Cytochrome P450 1A2 inhibitor: SVM model built on 9145 molecules (training set) |
Yes |
CYP2C19 inhibitor? Cytochrome P450 2C19 inhibitor: SVM model built on 9272 molecules (training set) |
No |
CYP2C9 inhibitor? Cytochrome P450 2C9 inhibitor: SVM model built on 5940 molecules (training set) |
No |
CYP2D6 inhibitor? Cytochrome P450 2D6 inhibitor: SVM model built on 3664 molecules (training set) |
No |
CYP3A4 inhibitor? Cytochrome P450 3A4 inhibitor: SVM model built on 7518 molecules (training set) |
No |
Log Kp (skin permeation)? Skin permeation: QSPR model implemented from |
-7.66 cm/s |
Lipinski? Lipinski (Pfizer) filter: implemented from |
0.0 |
Ghose? Ghose filter: implemented from |
None |
Veber? Veber (GSK) filter: implemented from |
0.0 |
Egan? Egan (Pharmacia) filter: implemented from |
0.0 |
Muegge? Muegge (Bayer) filter: implemented from |
0.0 |
Bioavailability Score? Abbott Bioavailability Score: Probability of F > 10% in rat |
0.55 |
PAINS? Pan Assay Interference Structures: implemented from |
0.0 alert |
Brenk? Structural Alert: implemented from |
0.0 alert: heavy_metal |
Leadlikeness? Leadlikeness: implemented from |
No; 1 violation:MW<0.0 |
Synthetic accessibility? Synthetic accessibility score: from 1 (very easy) to 10 (very difficult) |
2.66 |
* 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.
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