Structure

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Physi-Chem Properties

Molecular Weight:  380.16
Volume:  394.998
LogP:  5.773
LogD:  3.427
LogS:  -3.688
# Rotatable Bonds:  2
TPSA:  90.9
# H-Bond Aceptor:  5
# H-Bond Donor:  3
# Rings:  4
# Heavy Atoms:  5

MedChem Properties

QED Drug-Likeness Score:  0.422
Synthetic Accessibility Score:  3.875
Fsp3:  0.348
Lipinski Rule-of-5:  Accepted
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:  -4.836
MDCK Permeability:  1.5203277143882588e-05
Pgp-inhibitor:  0.204
Pgp-substrate:  0.984
Human Intestinal Absorption (HIA):  0.027
20% Bioavailability (F20%):  0.119
30% Bioavailability (F30%):  0.088

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.009
Plasma Protein Binding (PPB):  96.10962677001953%
Volume Distribution (VD):  0.642
Pgp-substrate:  7.409558296203613%

ADMET: Metabolism

CYP1A2-inhibitor:  0.643
CYP1A2-substrate:  0.721
CYP2C19-inhibitor:  0.635
CYP2C19-substrate:  0.134
CYP2C9-inhibitor:  0.836
CYP2C9-substrate:  0.965
CYP2D6-inhibitor:  0.544
CYP2D6-substrate:  0.376
CYP3A4-inhibitor:  0.186
CYP3A4-substrate:  0.162

ADMET: Excretion

Clearance (CL):  4.069
Half-life (T1/2):  0.146

ADMET: Toxicity

hERG Blockers:  0.011
Human Hepatotoxicity (H-HT):  0.565
Drug-inuced Liver Injury (DILI):  0.962
AMES Toxicity:  0.627
Rat Oral Acute Toxicity:  0.894
Maximum Recommended Daily Dose:  0.992
Skin Sensitization:  0.81
Carcinogencity:  0.713
Eye Corrosion:  0.005
Eye Irritation:  0.878
Respiratory Toxicity:  0.957

Download Data

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

  Natural Product: NPC319200

Natural Product ID:  NPC319200
Common Name*:   1,3,5-Trihydroxy-2-(2',2'-Dimethyl-4'-Isopropenyl)Cyclopentanylxanthone
IUPAC Name:   2-[(1S,4S)-2,2-dimethyl-4-prop-1-en-2-ylcyclopentyl]-1,3,5-trihydroxyxanthen-9-one
Synonyms:   6-deoxy-5-O-demethylpaxanthonin
Standard InCHIKey:  AUUIZUXRGRVPCU-GXTWGEPZSA-N
Standard InCHI:  InChI=1S/C23H24O5/c1-11(2)12-8-14(23(3,4)10-12)18-16(25)9-17-19(21(18)27)20(26)13-6-5-7-15(24)22(13)28-17/h5-7,9,12,14,24-25,27H,1,8,10H2,2-4H3/t12-,14+/m0/s1
SMILES:  CC(=C)[C@H]1C[C@@H](C(C1)(C)C)c1c(O)cc2c(c1O)c(=O)c1c(o2)c(O)ccc1
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   CHEMBL447199
PubChem CID:   11245970
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000002] Organoheterocyclic compounds
      • [CHEMONTID:0000123] Benzopyrans
        • [CHEMONTID:0003410] 1-benzopyrans
          • [CHEMONTID:0002817] Dibenzopyrans
            • [CHEMONTID:0000200] Xanthenes
              • [CHEMONTID:0000204] Xanthones

*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

☑ 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

☑ 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

☑ 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 NPC319200 and all remaining natural products in the NPASS database.
●  The right table: Most similar natural products (Tc>=0.56 or Top200).

  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 NPC319200 and all drugs/candidates.
●  The right table: Most similar clinical/approved drugs (Tc>=0.56 or Top200).

  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