Structure

Physi-Chem Properties

Molecular Weight:  360.16
Volume:  347.969
LogP:  1.507
LogD:  1.55
LogS:  -4.469
# Rotatable Bonds:  0
TPSA:  82.06
# H-Bond Aceptor:  6
# H-Bond Donor:  1
# Rings:  6
# Heavy Atoms:  6

MedChem Properties

QED Drug-Likeness Score:  0.397
Synthetic Accessibility Score:  6.915
Fsp3:  0.8
Lipinski Rule-of-5:  Accepted
Pfizer Rule:  Accepted
GSK Rule:  Accepted
BMS Rule:  2
Golden Triangle Rule:  Accepted
Chelating Alert:  0
PAINS Alert:  0

ADMET Properties (ADMETlab2.0)

ADMET: Absorption

Caco-2 Permeability:  -5.25
MDCK Permeability:  8.379659448110033e-06
Pgp-inhibitor:  0.26
Pgp-substrate:  0.062
Human Intestinal Absorption (HIA):  0.005
20% Bioavailability (F20%):  0.005
30% Bioavailability (F30%):  0.462

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.577
Plasma Protein Binding (PPB):  58.7052001953125%
Volume Distribution (VD):  1.608
Pgp-substrate:  48.808799743652344%

ADMET: Metabolism

CYP1A2-inhibitor:  0.008
CYP1A2-substrate:  0.916
CYP2C19-inhibitor:  0.021
CYP2C19-substrate:  0.784
CYP2C9-inhibitor:  0.02
CYP2C9-substrate:  0.038
CYP2D6-inhibitor:  0.004
CYP2D6-substrate:  0.121
CYP3A4-inhibitor:  0.599
CYP3A4-substrate:  0.224

ADMET: Excretion

Clearance (CL):  2.088
Half-life (T1/2):  0.234

ADMET: Toxicity

hERG Blockers:  0.193
Human Hepatotoxicity (H-HT):  0.204
Drug-inuced Liver Injury (DILI):  0.502
AMES Toxicity:  0.614
Rat Oral Acute Toxicity:  0.413
Maximum Recommended Daily Dose:  0.916
Skin Sensitization:  0.334
Carcinogencity:  0.812
Eye Corrosion:  0.004
Eye Irritation:  0.034
Respiratory Toxicity:  0.956

Download Data

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

  Natural Product: NPC483216

Natural Product ID:  NPC483216
Common Name*:   VITOUEAQSWAQLD-YDBFMNHESA-N
IUPAC Name:   n.a.
Synonyms:  
Standard InCHIKey:  VITOUEAQSWAQLD-YDBFMNHESA-N
Standard InCHI:  InChI=1S/C20H24O6/c1-9-10-5-11(21)13-19(6-10,15(9)22)17(23)26-12-3-4-18(2)7-24-16-14(18)20(12,13)8-25-16/h10-14,16,21H,1,3-8H2,2H3/t10-,11+,12-,13+,14+,16-,18-,19-,20?/m0/s1
SMILES:  C=C1[C@H]2C[C@H]([C@@H]3[C@@](C2)(C1=O)C(=O)O[C@H]1CC[C@@]2(C)CO[C@@H]4[C@H]2C31CO4)O
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   127033176
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000012] Lipids and lipid-like molecules
      • [CHEMONTID:0000259] Prenol lipids
        • [CHEMONTID:0001283] Terpene lactones
          • [CHEMONTID:0001538] Diterpene lactones

*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
NPO25255 Isodon phyllostachys Species Lamiaceae Eukaryota n.a. n.a. n.a. PMID[26757019]
NPO25255 Isodon phyllostachys Species Lamiaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO25255 Isodon phyllostachys Species Lamiaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO25255 Isodon phyllostachys Species Lamiaceae 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
NPT81 Cell Line A549 Homo sapiens IC50 = 10200.0 nM PMID[26757019]
NPT83 Cell Line MCF7 Homo sapiens IC50 = 13700.0 nM PMID[26757019]
NPT660 Cell Line SW480 Homo sapiens IC50 > 40000.0 nM PMID[26757019]
NPT81 Cell Line A549 Homo sapiens GI = 50.0 % PMID[26757019]
NPT83 Cell Line MCF7 Homo sapiens GI = 50.0 % PMID[26757019]
NPT660 Cell Line SW480 Homo sapiens GI = 50.0 % PMID[26757019]
NPT113 Cell Line RAW264.7 Mus musculus IC50 = 3510.0 nM PMID[26757019]
NPT20529 NON-MOLECULAR NON-PROTEIN TARGET n.a. IC50 = 12500.0 nM PMID[26757019]
NPT20529 NON-MOLECULAR NON-PROTEIN TARGET n.a. IC50 = 14300.0 nM PMID[26757019]
NPT20529 NON-MOLECULAR NON-PROTEIN TARGET n.a. GI = 50.0 % PMID[26757019]

☑ 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 NPC483216 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 NPC483216 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