Structure

Physi-Chem Properties

Molecular Weight:  496.16
Volume:  449.962
LogP:  -0.405
LogD:  0.588
LogS:  -2.277
# Rotatable Bonds:  7
TPSA:  184.6
# H-Bond Aceptor:  12
# H-Bond Donor:  6
# Rings:  8
# Heavy Atoms:  12

MedChem Properties

QED Drug-Likeness Score:  0.247
Synthetic Accessibility Score:  6.241
Fsp3:  0.696
Lipinski Rule-of-5:  Rejected
Pfizer Rule:  Accepted
GSK Rule:  Rejected
BMS Rule:  0
Golden Triangle Rule:  Accepted
Chelating Alert:  0
PAINS Alert:  0

ADMET Properties (ADMETlab2.0)

ADMET: Absorption

Caco-2 Permeability:  -6.262
MDCK Permeability:  7.699562411289662e-05
Pgp-inhibitor:  0.001
Pgp-substrate:  0.946
Human Intestinal Absorption (HIA):  0.924
20% Bioavailability (F20%):  0.984
30% Bioavailability (F30%):  0.977

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.218
Plasma Protein Binding (PPB):  24.05568504333496%
Volume Distribution (VD):  0.428
Pgp-substrate:  57.59691619873047%

ADMET: Metabolism

CYP1A2-inhibitor:  0.002
CYP1A2-substrate:  0.986
CYP2C19-inhibitor:  0.014
CYP2C19-substrate:  0.564
CYP2C9-inhibitor:  0.002
CYP2C9-substrate:  0.127
CYP2D6-inhibitor:  0.002
CYP2D6-substrate:  0.122
CYP3A4-inhibitor:  0.045
CYP3A4-substrate:  0.054

ADMET: Excretion

Clearance (CL):  1.438
Half-life (T1/2):  0.275

ADMET: Toxicity

hERG Blockers:  0.009
Human Hepatotoxicity (H-HT):  0.052
Drug-inuced Liver Injury (DILI):  0.282
AMES Toxicity:  0.703
Rat Oral Acute Toxicity:  0.715
Maximum Recommended Daily Dose:  0.013
Skin Sensitization:  0.12
Carcinogencity:  0.842
Eye Corrosion:  0.003
Eye Irritation:  0.009
Respiratory Toxicity:  0.418

Download Data

Data Type Select
General Info & Identifiers & Properties  
Structure MOL file  
Source Organisms  
Biological Activities  
Similar NPs/Drugs  

  Natural Product: NPC160785

Natural Product ID:  NPC160785
Common Name*:   FCHVXNVDFYXLIL-UHFFFAOYSA-N
IUPAC Name:   n.a.
Synonyms:  
Standard InCHIKey:  FCHVXNVDFYXLIL-UHFFFAOYSA-N
Standard InCHI:  InChI=1S/C23H28O12/c1-20-8-22(30)13-6-23(20,33-18-16(28)15(27)14(26)12(7-24)32-18)21(13,19(34-20)35-22)9-31-17(29)10-2-4-11(25)5-3-10/h2-5,12-16,18-19,24-28,30H,6-9H2,1H3
SMILES:  CC12CC3(C4CC1(C4(COC(=O)c1ccc(cc1)O)C(O2)O3)OC1C(C(C(C(CO)O1)O)O)O)O
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   429559
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000012] Lipids and lipid-like molecules
      • [CHEMONTID:0000259] Prenol lipids
        • [CHEMONTID:0002049] Terpene glycosides

*Note: the InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
**Note: the Chemical Classification was calculated by NPClassifier Version 1.5. Reference: PMID:34662515.

  Species Source

Organism ID Organism Name Taxonomy Level Family SuperKingdom Isolation Part Collection Location Collection Time Reference
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 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 Henan province, China DOI[10.1016/j.foodres.2020.109416]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. DOI[10.2174/092986712800229032]
NPO22550 Paeonia suffruticosa Species Paeoniaceae Eukaryota n.a. n.a. n.a. PMID[11339628]
NPO22550 Paeonia suffruticosa Species Paeoniaceae Eukaryota n.a. bark n.a. PMID[17260795]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. n.a. n.a. PMID[19402674]
NPO22550 Paeonia suffruticosa Species Paeoniaceae Eukaryota n.a. Daejeon, Korea 2007-Jan PMID[19670875]
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]
NPO22550 Paeonia suffruticosa Species Paeoniaceae Eukaryota n.a. seed n.a. PMID[20822014]
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]
NPO22550 Paeonia suffruticosa Species Paeoniaceae Eukaryota n.a. root n.a. PMID[22547314]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. seed n.a. PMID[23497864]
NPO22550 Paeonia suffruticosa Species Paeoniaceae Eukaryota root bark Bozhou, Anhui Province, China 2010-AUG PMID[24377852]
NPO22550 Paeonia suffruticosa Species Paeoniaceae Eukaryota n.a. flower n.a. PMID[24504864]
NPO22550 Paeonia suffruticosa Species Paeoniaceae Eukaryota Flowers LuoYang, HeNan, China n.a. PMID[24621197]
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]
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]
NPO22550 Paeonia suffruticosa 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]
NPO22550 Paeonia suffruticosa 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]
NPO22550 Paeonia suffruticosa Species Paeoniaceae Eukaryota n.a. n.a. n.a. Database[TM-MC]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO22550 Paeonia suffruticosa 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 NP ID 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

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

☑ Note for Activity Records:
☉ The quantitative biological activities were primarily integrated from ChEMBL (Version-30) database and were also directly collected from PubMed literature. PubMed PMID was provided as the reference link for each activity record.

  Chemically structural similarity: I. Similar Active Natural Products in NPASS

Top-200 similar NPs were calculated against the active-NP-set (includes 4,3285 NPs with experimentally-derived bioactivity available in NPASS)

Similarity level is defined by Tanimoto coefficient (Tc) between two molecules. Tc lies between [0, 1] where '1' indicates the highest similarity. What is Tanimoto coefficient

●  The left chart: Distribution of similarity level between NPC160785 and all remaining natural products in the NPASS database.
●  The right table: Most similar natural products (Tc>=0.56 or Top200).

Similarity Score Similarity Level Natural Product ID

  Chemically structural similarity: II. Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC160785 and all drugs/candidates.
●  The right table: Most similar clinical/approved drugs (Tc>=0.56 or Top200).

Similarity Score Similarity Level Drug ID Developmental Stage

  Bioactivity similarity: Similar Natural Products in NPASS

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