Structure

Physi-Chem Properties

Molecular Weight:  566.23
Volume:  601.675
LogP:  5.235
LogD:  3.743
LogS:  -3.588
# Rotatable Bonds:  12
TPSA:  127.45
# H-Bond Aceptor:  7
# H-Bond Donor:  5
# Rings:  4
# Heavy Atoms:  7

MedChem Properties

QED Drug-Likeness Score:  0.075
Synthetic Accessibility Score:  3.74
Fsp3:  0.171
Lipinski Rule-of-5:  Rejected
Pfizer Rule:  Accepted
GSK Rule:  Rejected
BMS Rule:  0
Golden Triangle Rule:  Rejected
Chelating Alert:  0
PAINS Alert:  0

ADMET Properties (ADMETlab2.0)

ADMET: Absorption

Caco-2 Permeability:  -5.642
MDCK Permeability:  8.93389278644463e-06
Pgp-inhibitor:  0.167
Pgp-substrate:  0.056
Human Intestinal Absorption (HIA):  0.365
20% Bioavailability (F20%):  0.999
30% Bioavailability (F30%):  0.998

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.005
Plasma Protein Binding (PPB):  101.74798583984375%
Volume Distribution (VD):  0.23
Pgp-substrate:  0.40727487206459045%

ADMET: Metabolism

CYP1A2-inhibitor:  0.574
CYP1A2-substrate:  0.866
CYP2C19-inhibitor:  0.965
CYP2C19-substrate:  0.081
CYP2C9-inhibitor:  0.948
CYP2C9-substrate:  0.984
CYP2D6-inhibitor:  0.935
CYP2D6-substrate:  0.866
CYP3A4-inhibitor:  0.681
CYP3A4-substrate:  0.438

ADMET: Excretion

Clearance (CL):  4.255
Half-life (T1/2):  0.65

ADMET: Toxicity

hERG Blockers:  0.153
Human Hepatotoxicity (H-HT):  0.279
Drug-inuced Liver Injury (DILI):  0.151
AMES Toxicity:  0.568
Rat Oral Acute Toxicity:  0.389
Maximum Recommended Daily Dose:  0.992
Skin Sensitization:  0.946
Carcinogencity:  0.24
Eye Corrosion:  0.003
Eye Irritation:  0.619
Respiratory Toxicity:  0.442

Download Data

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

  Natural Product: NPC13601

Natural Product ID:  NPC13601
Common Name*:   VIHJUBYCOAJPQW-CJIDPTHHSA-N
IUPAC Name:   n.a.
Synonyms:  
Standard InCHIKey:  VIHJUBYCOAJPQW-CJIDPTHHSA-N
Standard InCHI:  InChI=1S/C35H34O7/c1-42-32-22-31(40)33(35(41)34(32)30(39)21-13-24-11-17-27(37)18-12-24)29(25-14-19-28(38)20-15-25)9-5-8-26(36)16-10-23-6-3-2-4-7-23/h2-7,9,11-15,17-22,26,29,36-38,40-41H,8,10,16H2,1H3/b9-5+,21-13+/t26-,29+/m0/s1
SMILES:  COc1cc(c([C@H](/C=C/C[C@@H](CCc2ccccc2)O)c2ccc(cc2)O)c(c1C(=O)/C=C/c1ccc(cc1)O)O)O
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   56601272
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000261] Phenylpropanoids and polyketides
      • [CHEMONTID:0002650] Diarylheptanoids
        • [CHEMONTID:0002651] Linear diarylheptanoids
          • [CHEMONTID:0000356] Curcuminoids

*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
NPO10494 Alpinia katsumadai Species Staphylinidae Eukaryota n.a. n.a. n.a. PMID[10654416]
NPO10494 Alpinia katsumadai Species Staphylinidae Eukaryota n.a. seed n.a. PMID[14577694]
NPO10494 Alpinia katsumadai Species Staphylinidae Eukaryota n.a. n.a. n.a. PMID[20014777]
NPO10494 Alpinia katsumadai Species Staphylinidae Eukaryota n.a. seed n.a. PMID[21942765]
NPO10494 Alpinia katsumadai Species Staphylinidae Eukaryota seeds n.a. n.a. PMID[21942765]
NPO10494 Alpinia katsumadai Species Staphylinidae Eukaryota n.a. n.a. n.a. PMID[22459211]
NPO10494 Alpinia katsumadai Species Staphylinidae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO10494 Alpinia katsumadai Species Staphylinidae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO10494 Alpinia katsumadai Species Staphylinidae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO10494 Alpinia katsumadai Species Staphylinidae Eukaryota n.a. n.a. n.a. Database[TM-MC]
NPO10494 Alpinia katsumadai Species Staphylinidae 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 NPC13601 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 NPC13601 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