Structure

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Physi-Chem Properties

Molecular Weight:  764.47
Volume:  787.142
LogP:  6.638
LogD:  4.037
LogS:  -6.344
# Rotatable Bonds:  2
TPSA:  142.12
# H-Bond Aceptor:  12
# H-Bond Donor:  0
# Rings:  5
# Heavy Atoms:  12

MedChem Properties

QED Drug-Likeness Score:  0.216
Synthetic Accessibility Score:  7.416
Fsp3:  0.905
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:  -4.719
MDCK Permeability:  0.0002688831009436399
Pgp-inhibitor:  0.997
Pgp-substrate:  0.009
Human Intestinal Absorption (HIA):  0.001
20% Bioavailability (F20%):  0.002
30% Bioavailability (F30%):  0.009

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.001
Plasma Protein Binding (PPB):  84.68842315673828%
Volume Distribution (VD):  1.724
Pgp-substrate:  6.5886640548706055%

ADMET: Metabolism

CYP1A2-inhibitor:  0.003
CYP1A2-substrate:  0.06
CYP2C19-inhibitor:  0.013
CYP2C19-substrate:  0.765
CYP2C9-inhibitor:  0.009
CYP2C9-substrate:  0.016
CYP2D6-inhibitor:  0.004
CYP2D6-substrate:  0.041
CYP3A4-inhibitor:  0.867
CYP3A4-substrate:  0.705

ADMET: Excretion

Clearance (CL):  7.074
Half-life (T1/2):  0.003

ADMET: Toxicity

hERG Blockers:  0.258
Human Hepatotoxicity (H-HT):  0.985
Drug-inuced Liver Injury (DILI):  0.964
AMES Toxicity:  0.966
Rat Oral Acute Toxicity:  0.104
Maximum Recommended Daily Dose:  0.997
Skin Sensitization:  0.985
Carcinogencity:  0.13
Eye Corrosion:  0.004
Eye Irritation:  0.012
Respiratory Toxicity:  0.784

Download Data

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

  Natural Product: NPC253129

Natural Product ID:  NPC253129
Common Name*:   ZBDGIMZKOJALMU-HXUSMMTHSA-N
IUPAC Name:   n.a.
Synonyms:  
Standard InCHIKey:  ZBDGIMZKOJALMU-HXUSMMTHSA-N
Standard InCHI:  InChI=1S/C42H68O12/c1-9-29-21-33-13-17-35(51-33)25(5)39(43)47-24(4)20-32-12-16-38(50-32)28(8)42(46)54-30(10-2)22-34-14-18-36(52-34)26(6)40(44)48-23(3)19-31-11-15-37(49-31)27(7)41(45)53-29/h23-38H,9-22H2,1-8H3/t23-,24-,25-,26-,27+,28+,29+,30+,31-,32-,33+,34+,35-,36-,37+,38+/m0/s1
SMILES:  CC[C@@H]1C[C@H]2CC[C@@H]([C@H](C)C(=O)O[C@@H](C)C[C@@H]3CC[C@H]([C@@H](C)C(=O)O[C@H](CC)C[C@H]4CC[C@@H]([C@H](C)C(=O)O[C@@H](C)C[C@@H]5CC[C@H]([C@@H](C)C(=O)O1)O5)O4)O3)O2
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   6916048
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000261] Phenylpropanoids and polyketides
      • [CHEMONTID:0000147] Macrolides and analogues

*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 NPC253129 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 NPC253129 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