Natural Product: NPC88484

Natural Product IDNPC88484
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
 Isosalipurposide
IUPAC Name (E)-1-[2,4-dihydroxy-6-[(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]oxyphenyl]-3-(4-hydroxyphenyl)prop-2-en-1-one
Synonyms
Synthetic Gene Cluster n.a.
ChEMBL Identifier CHEMBL2430461
PubChem CID 5318659
Chemical Classification
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000261] Phenylpropanoids and polyketides
      • [CHEMONTID:0000334] Flavonoids
        • [CHEMONTID:0001111] Flavonoid glycosides
          • [CHEMONTID:0001583] Flavonoid O-glycosides

The Chemical Classification was calculated by Classyfire, a software for chemical taxonomy calculation. Reference: DOI:10.1186/s13321-016-0174-y.

  Chemical Representations

Standard InCHIKey WQCWELFQKXIPCN-JSYAWONVSA-N
Standard InCHI InChI=1S/C21H22O10/c22-9-16-18(27)19(28)20(29)21(31-16)30-15-8-12(24)7-14(26)17(15)13(25)6-3-10-1-4-11(23)5-2-10/h1-8,16,18-24,26-29H,9H2/b6-3+/t16-,18-,19+,20-,21-/m1/s1
SMILES c1cc(ccc1/C=C/C(=O)c1c(cc(cc1O[C@H]1[C@@H]([C@H]([C@@H]([C@@H](CO)O1)O)O)O)O)O)O

  Calculated Properties

Physi-Chem Properties

Molecular Weight:   434.12 Volume:   412.913
?
Van der Waals volume.
Dense:   1.051 LogP:   0.788
?
The logarithm of the n-octanol/water distribution coefficients.
logD7.4:   1.206
?
The logarithm of the n-octanol/water distribution coefficient at pH=7.4.
 LogS:   -2.826
?
The logarithm of aqueous solubility value.
Rotatable Bonds:   6.0 Rigid Bonds:   20.0
TPSA:   177.14
?
Topological Polar Surface Area.
 H-Bond Acceptor:   10.0
H-Bond Donor:   7.0 Rings:   3.0
Heavy Atoms:   10.0

MedChem Properties

QED Drug-Likeness Score:   0.239 GASA:   0.0
?
GASA represents the probability of being difficult to synthesize, ranging from 0 to 1.
Synthetic Accessibility Score:   3.853 Fsp3:   0.286
MCE-18:   70.778
?
MCE-18 stands for medicinal chemistry evolution.MCE-18≥45 is considered a suitable value.
 Lipinski Rule-of-5:   Rejected
Pfizer Rule:   Rejected GSK Rule:   Accepted
Golden Triangle Rule:   Rejected BMS Rule:   0
Chelating Alert:   0 PAINS Alert:   0
Colloidal aggregators:   0.665 Fluc inhibitor:   0.62
?
The fluc inhibitor value is the probability of being fLuc inhibitors, within the range of 0 to 1.
Blue fluorescence:   0.343
?
The blue fluorescence value is the probability of being blue fluorescence, within the range of 0 to 1
 Green fluorescence:   0.77
?
The green fluorescence value is the probability of being green fluorescence, within the range of 0 to 1
Reactive compounds:   0.39 Promiscuous compounds:   0.492

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

Caco-2 Permeability:   -6.127 MDCK Permeability:   -5.183
Pgp-inhibitor:   0.0 Pgp-substrate:   0.037
PAMPA:   0.896
?
The experimental data for Peff was logarithmically transformed (logPeff). Molecules with log Peff values below 2.0 were classified as low-permeability (Category 0), while those with log Peff values exceeding 2.5 were classified as high-permeability (Category 1).
 Human Intestinal Absorption (HIA):   0.024
20% Bioavailability (F20%):   0.579 30% Bioavailability (F30%):   0.997
50% Bioavailability (F50%):   0.998

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):   0.0 MRP1:   0.007
Plasma Protein Binding (PPB):   88.4% Volume Distribution (VD):   -0.136
Fu: 9.759%
?
The fraction unbound in plasms.
 OATP1B1 inhibitor:   1.0
OATP1B3 inhibitor:   1.0 BCRP inhibitor:   0.272
BSEP inhibitor:   0.019

ADMET: Metabolism

CYP1A2-inhibitor:   0.066 CYP1A2-substrate:   0.0
CYP2C19-inhibitor:   0.0 CYP2C19-substrate:   0.402
CYP2C9-inhibitor:   0.018 CYP2C9-substrate:   0.006
CYP2D6-inhibitor:   0.046 CYP2D6-substrate:   0.824
CYP3A4-inhibitor:   0.0 CYP3A4-substrate:   1.0
CYP2B6-substrate:   0.0 CYP2C8-inhibitor:   1.0
HLM stability:   0.054
?
Human liver microsomal (HLM) stability. Category 0: stable+ (HLM > 30 min); Category 1: unstable- (HLM ≤ 30 min). The output value is the probability of human liver microsomal instability, where a value closer to 1 indicates a higher likelihood of instability.

ADMET: Excretion

Clearance (CL):  3.238 Half-life (T1/2):  2.867

ADMET: Toxicity

hERG Blockers:  0.053 hERG Blockers (10um):  0.156
Human Hepatotoxicity (H-HT):  0.747 Drug-induced Liver Injury (DILI):  0.767
AMES Toxicity:  0.836 Rat Oral Acute Toxicity:  0.015
Maximum Recommended Daily Dose:  0.127 Skin Sensitization:  0.998
Carcinogencity:  0.128 Eye Corrosion:  0.0
Eye Irritation:  0.772 Respiratory Toxicity:  0.034
Drug-induced Neurotoxicity:  0.03 Ototoxicity:  0.85
Hematotoxicity:  0.091 Drug-induced Nephrotoxicity:  0.378
Genotoxicity:  0.848 RPMI-8226 Immunitoxicity:  0.087
A549 Cytotoxicity:  0.486 Hek293 Cytotoxicity:  0.746
BCF:   0.583
?
Bioconcentration factors are used for considering secondary poisoning potential and assessing risks to human health via the food chain. The unit is -log10[(mg/L)/(1000*MW)].
 IGC50:   3.28
?
48 hour Tetrahymena pyriformis IGC50. The unit of IGC50 is -log10[(mg/L)/(1000*MW)].
LC50DM:   4.761
?
48 hour Daphnia magna LC50. The unit of LC50DM is -log10[(mg/L)/(1000*MW)].
 LC50FM:   4.104
?
96 hour fathead minnow LC50. The unit of LC50FM is -log10[(mg/L)/(1000*MW)].

  Species Source

Organism ID Organism Name Taxonomy Level Family SuperKingdom Isolation Part Collection Location Collection Time Reference
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Seeds Henan province, China DOI[10.1016/j.foodres.2020.109416]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Seeds Anhui province, China DOI[10.1016/j.foodres.2020.109416]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Seeds Gansu province, China DOI[10.1016/j.foodres.2020.109416]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Seeds Shandong province, China DOI[10.1016/j.foodres.2020.109416]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Seeds Shanxi province, China DOI[10.1016/j.foodres.2020.109416]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. DOI[10.2174/092986712800229032]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. n.a. n.a. PMID[19402674]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. PMID[19721258]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. PMID[19772486]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Roots n.a. n.a. PMID[20806783]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. PMID[21782011]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. PMID[22190295]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. seed n.a. PMID[23497864]
NPO12221 Acacia saligna Species Fabaceae Eukaryota n.a. n.a. n.a. PMID[25183120]
NPO30598 Corylopsis coreana Species Hamamelidaceae Eukaryota n.a. n.a. n.a. PMID[26028482]
NPO15254 Macropidia fuliginosa Species Haemodoraceae Eukaryota n.a. Australian n.a. PMID[26151487]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. PMID[26838074]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. PMID[27313650]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. PMID[27429639]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Roots n.a. n.a. PMID[29741372]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Seeds HeZe, ShanDong, China early autumn (from August to the beginning of September PMID[32545196]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Roots n.a. n.a. PMID[32951423]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Seeds Xinjiang,China PMID[33063333]
NPO15254 Macropidia fuliginosa Species Haemodoraceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO12221 Acacia saligna Species Fabaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. n.a. n.a. Database[TM-MC]
NPO894 Hypselodoris daniellae Species Chromodorididae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO15254 Macropidia fuliginosa Species Haemodoraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO8846 Carphochaete bigelovii Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO12221 Acacia saligna Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. n.a. n.a. Database[UNPD]

Note for Reference:
In addition to directly collecting NP source organism data from primary literature (where reference will provided as NCBI PMID or DOI links), NPASS also integrated them from below databases:
☉ UNPD: Universal Natural Products Database [PMID: 23638153].
☉ StreptomeDB: a database of streptomycetes natural products [PMID: 33051671].
☉ TM-MC: a database of medicinal materials and chemical compounds in Northeast Asian traditional medicine [PMID: 26156871].
☉ TCM@Taiwan: a Traditional Chinese Medicine database [PMID: 21253603].
☉ TCMID: a Traditional Chinese Medicine database [PMID: 29106634].
☉ TCMSP: The traditional Chinese medicine systems pharmacology database and analysis platform [PMID: 24735618].
☉ HerDing: a herb recommendation system to treat diseases using genes and chemicals [PMID: 26980517].
☉ MetaboLights: a metabolomics database [PMID: 27010336].
☉ FooDB: a database of constituents, chemistry and biology of food species [www.foodb.ca].



  NP Quantity Composition/Concentration

Organism ID Organism Name Organism Material Preparation Organism Part NP Quantity (Standard) NP Quantity (Minimum) NP Quantity (Maximum) Quantity Unit Reference

Note for Reference:
In addition to directly collecting NP quantitative data from primary literature (where reference will provided as NCBI PMID or DOI links), NPASS also integrated NP quantitative records for specific NP domains (e.g., NPS from foods or herbs) from domain-specific databases. These databases include:
☉ DUKE: Dr. Duke's Phytochemical and Ethnobotanical Databases.
☉ PHENOL EXPLORER: is the first comprehensive database on polyphenol content in foods [PMID: 24103452], its homepage can be accessed at here.
☉ FooDB: a database of constituents, chemistry and biology of food species [www.foodb.ca].



 Biological Activity

Molecular-level activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference

In vitro activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference
NPT886 Cell line NIH3T3 Mus musculus IC50 > 200.0 ug.mL-1 DOI[10.1007/s00044-013-0773-3]
NPT396 Cell line T47D Homo sapiens IC50 > 200.0 ug.mL-1 DOI[10.1007/s00044-013-0773-3]
NPT492 Cell line Caco-2 Homo sapiens IC50 = 8.45 ug.mL-1 DOI[10.1007/s00044-013-0773-3]
NPT18 Organism Pseudomonas aeruginosa Pseudomonas aeruginosa IZ = 2.0 mm PMID[26151487]

In vivo activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference





 Experimental ADME

Experiment Model Experiment Tissue ADME Type ADME Relation ADME Value ADME Unit Reference





 Experimental Toxicity

Quantitative toxicity

Experiment Model Experiment Organism Toxicity Type Toxicity Relation Toxicity Value Toxicity Unit Reference

Common Abbreviations:
LC: Lethal Concentration; LD: Lethal Dose; LT:Lethal Time; NOAEL: No-observed-adverse-effect Level; BMDL: Benchmark Dose Lower Confidence Limit; BMD: Benchmark Dose; BMC:Benchmark Concentration; LOAEL: Lowest Observed Adverse Effect Level; RfD:Reference Dose; RfC:Reference Concentration; MRL: Minimal Risk Level; MEG: Maximum Exposure Guideline; PAC: Protective Action Criteria

Categorical toxicity labels

Hepatotoxicity Carcinogenicity Mutagenicity Cardiotoxicity Respiratory Toxicity Eye Irritation Endocrine Disruption
Hepatotoxicity Carcinogenicity Mutagenicity Cardiotoxicity Respiratory Toxicity Eye Irritation Endocrine Disruption

Note for Reference:
In addition to directly collecting NP quantitative data from primary literature (where reference will provided as NCBI PMID or DOI links), NPASS also integrated NP toxicity records from domain-specific databases. These databases include:
☉ ToxValDB: a curated database that compiles quantitative toxicity values for chemicals from diverse public sources to support toxicological research and risk assessment.
☉ TOXRIC: a comprehensive, free-to-access, online database providing toxicological/feature data. The toxicity labels are retrieved from this database. [PMID: 36400569]


  Chemically structural similarity

Similar Active Natural Products in NPASS

Top-200 similar NPs were calculated against the active-NP-set (includes approximately 50,000 NPs with experimentally-derived bioactivity available in NPASS)

Similarity is measured using the Tanimoto coefficient (Tc) , which compares the binary fingerprints of two molecules. Tc is calculated as the intersection divided by the union of '1' bits in the fingerprints, ranging from 0 to 1, with 1 indicating highest similarity.

●  The left chart: Distribution of similarity level between NPC88484 and all remaining natural products in the NPASS database.
●  The right table: Most similar natural products (Tc>=0.5 or Top200).

Similarity Score Similarity Level Natural Product ID
0.7206 Intermediate Similarity NPC57587
0.6957 Remote Similarity NPC259767
0.6667 Remote Similarity NPC259182
0.6667 Remote Similarity NPC106025
0.6471 Remote Similarity NPC199335
0.6471 Remote Similarity NPC477240
0.6377 Remote Similarity NPC190217
0.6364 Remote Similarity NPC23817
0.6267 Remote Similarity NPC257963
0.6164 Remote Similarity NPC606353
0.6032 Remote Similarity NPC129132
0.5658 Remote Similarity NPC88043
0.5634 Remote Similarity NPC85799
0.5634 Remote Similarity NPC303422
0.557 Remote Similarity NPC145319
0.557 Remote Similarity NPC166180
0.5513 Remote Similarity NPC26195
0.5513 Remote Similarity NPC488085
0.5488 Remote Similarity NPC259834
0.5455 Remote Similarity NPC169248
0.5455 Remote Similarity NPC72649
0.5429 Remote Similarity NPC214910
0.5395 Remote Similarity NPC99233
0.5393 Remote Similarity NPC168789
0.5325 Remote Similarity NPC601828
0.5316 Remote Similarity NPC39351
0.527 Remote Similarity NPC242028
0.527 Remote Similarity NPC203230
0.527 Remote Similarity NPC252169
0.5256 Remote Similarity NPC160156
0.5256 Remote Similarity NPC92565
0.525 Remote Similarity NPC149244
0.525 Remote Similarity NPC106625
0.5224 Remote Similarity NPC200092
0.5211 Remote Similarity NPC26080
0.5211 Remote Similarity NPC165686
0.5205 Remote Similarity NPC97326
0.5195 Remote Similarity NPC177742
0.519 Remote Similarity NPC308265
0.5185 Remote Similarity NPC181014
0.5181 Remote Similarity NPC606922
0.5156 Remote Similarity NPC142319
0.5132 Remote Similarity NPC260681
0.5132 Remote Similarity NPC121001
0.5125 Remote Similarity NPC471457
0.5125 Remote Similarity NPC127782
0.5122 Remote Similarity NPC472320
0.5075 Remote Similarity NPC87231
0.5075 Remote Similarity NPC56031
0.507 Remote Similarity NPC23084
0.5067 Remote Similarity NPC65530
0.5067 Remote Similarity NPC611586
0.5062 Remote Similarity NPC310064

Similar Clinical/Approved Drugs

Similarity level is defined by Tanimoto coefficient (Tc) between two molecules.

●  The left chart: Distribution of similarity level between NPC88484 and all drugs/candidates.
●  The right table: Most similar clinical/approved drugs (Tc>=0.5 or Top200).

Similarity Score Similarity Level Drug ID Developmental Stage
NPD

Bioactivity similarity

  Bioactivity similarity

Similar Natural Products in NPASS

Similarity level is defined by Bioactivity similarity was calculated based on bioactivity descriptors of compounds. The bioactivity descriptors were calculated by a recently developed AI algorithm Chemical Checker (CC) [Nature Biotechnology, 38:1087–1096, 2020; Nature Communications, 12:3932, 2021], which evaluated bioactivity similarities at five levels:
☉ A: chemistry similarity;
☉ B: biological targets similarity;
☉ C: networks similarity;
☉ D: cell-based bioactivity similarity;
☉ E: similarity based on clinical data.
Those 5 categories of CC bioactivity descriptors were calculated and then subjected to manifold projection using UMAP algorithm, to project all NPs on a 2-Dimensional space. The current NP was highlighted with a small circle in the 2-D map. Below figures: left-to-right, A-to-E.

A: chemistry similarity
B: biological targets similarity
C: networks similarity
D: cell-based bioactivity similarity
E: similarity based on clinical data