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Chemical Structure| 30361-28-5

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Kim, Jiho ;

Abstract: Polyunsaturated aldehydes (PUAs) are secondary oxylipins produced by some diatoms. PUAs are produced at a greater rate when diatom cells are damaged, suggesting that they may act as chemical grazing deterrents. Past studies showed the deleterious effects of particulate PUAs on diatom consumers like copepods and marine invertebrates. However, to date, very few studies have explored the potential for diatom-derived PUAs to affect marine vertebrates, such as forage fishes. Forage fishes are a foundational functional group in marine ecosystems whose early life history stages are often sympatric with diatoms due to their nearshore spawning behavior and planktivorous diet. In this study, I addressed the question of whether PUAs detrimentally affect a common Salish Sea forage fish, the surf smelt (Hypomesus pretiosus; Girard 1854). The project focused on determining whether PUAs affect the development and physiology of surf smelt embryos and larvae. This was done by measuring survival and hatch success rates, embryonic heart rates, usage of endogenous energy reserves, and morphological features at hatch. Higher concentrations of PUAs resulted in higher mortality and lower hatch success rates of embryonic surf smelt. Embryonic heart rates were equivalent among treatments when embryos were exposed to PUAs soon after fertilization, suggesting that surf smelt embryos can acclimate to PUAs if exposed during early development. However, higher concentrations of PUAs significantly lowered the heart rates of embryos that were exposed to PUAs days after fertilization. Exposure to PUAs diminished the consumption rate of endogenous energy reserves, and the overall size of surf smelt at hatch was reduced. Our results indicate that exposure to dissolved PUAs could impair the fitness of ecologically foundational forage fish early life history stages. Negative effects that manifest into low adult population sizes will have cascading effects on marine ecosystems.

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Jeremy Johnson ;

Abstract: In coastal, nutrient-rich waters like the Salish Sea, diatoms dominate the phytoplankton community during seasonal upwelling events. Diatoms were once believed to be an ideal food source for primary consumers like copepods, but their role in food web dynamics changed upon discovery that diatoms can produce organic compounds upon cell death known as polyunsaturated aldehydes (PUAs). These compounds directly affect the reproductive success of diatom consumers by reducing egg production and viability, deforming embryos, and delaying embryonic development. PUA production dynamics have been assessed under varying nutrient concentrations and culture age, but no study has tested the effect of elevated dissolved CO2 (pCO2) on the production of these organic molecules. In addition, most surveys of PUA-producing diatoms have only assessed pelagic production. In this study, I isolated benthic diatom species from the Salish Sea and tested them for PUA production. I also conducted a microcosm upwelling experiment using a benthic and pelagic diatom under varying pCO2 levels to assess whether PUA production is affected by inorganic carbon level. I found that all Salish Sea benthic diatom species tested produced PUA molecules, and elevated pCO2 did not significantly affect the production of PUA molecules. Experimental results indicate that upwelling events alone are likely not causing an increase in PUA production. The survey results indicate that benthic diatoms should be included in future PUA producer surveys to assess PUA production in the water column. Future research should assess the synergy between elevated pCO2 and nutrient limitation on PUA production, as these conditions are expected with worsening climate change. In addition, future studies on the impact of PUAs on grazer fecundity should be expanded to include benthic diatom consumers, including mollusks and other benthic invertebrates.

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Product Details of [ 30361-28-5 ]

CAS No. :30361-28-5
Formula : C8H12O
M.W : 124.18
SMILES Code : CCC/C=C/C=C/C=O
MDL No. :MFCD00014676
InChI Key :DVVATNQISMINCX-YTXTXJHMSA-N
Pubchem ID :5283329

Safety of [ 30361-28-5 ]

GHS Pictogram:
Signal Word:Warning
Hazard Statements:H227-H315
Precautionary Statements:P280

Computational Chemistry of [ 30361-28-5 ] Show Less

Physicochemical Properties

Num. heavy atoms 9
Num. arom. heavy atoms 0
Fraction Csp3 0.38
Num. rotatable bonds 4
Num. H-bond acceptors 1.0
Num. H-bond donors 0.0
Molar Refractivity 39.82
TPSA ?

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

17.07 Ų

Lipophilicity

Log Po/w (iLOGP)?

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

2.11
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

2.17
Log Po/w (WLOGP)?

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

2.1
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.

1.87
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

2.09
Consensus Log Po/w?

Consensus Log Po/w: Average of all five predictions

2.07

Water Solubility

Log S (ESOL):?

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

-1.71
Solubility 2.4 mg/ml ; 0.0194 mol/l
Class?

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

Very soluble
Log S (Ali)?

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

-2.16
Solubility 0.856 mg/ml ; 0.00689 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

-1.16
Solubility 8.57 mg/ml ; 0.069 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.

-5.52 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

2.0
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

3.0 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)

2.91
 

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