Structure

Physi-Chem Properties

Molecular Weight:  184.07
Volume:  176.995
LogP:  -0.76
LogD:  -0.041
LogS:  -0.305
# Rotatable Bonds:  1
TPSA:  69.92
# H-Bond Aceptor:  4
# H-Bond Donor:  3
# Rings:  2
# Heavy Atoms:  4

MedChem Properties

QED Drug-Likeness Score:  0.475
Synthetic Accessibility Score:  4.915
Fsp3:  0.556
Lipinski Rule-of-5:  Accepted
Pfizer Rule:  Accepted
GSK Rule:  Accepted
BMS Rule:  0
Golden Triangle Rule:  Rejected
Chelating Alert:  0
PAINS Alert:  0

ADMET Properties (ADMETlab2.0)

ADMET: Absorption

Caco-2 Permeability:  -5.124
MDCK Permeability:  0.0007732458179816604
Pgp-inhibitor:  0.0
Pgp-substrate:  0.012
Human Intestinal Absorption (HIA):  0.377
20% Bioavailability (F20%):  0.008
30% Bioavailability (F30%):  0.841

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.562
Plasma Protein Binding (PPB):  18.39818572998047%
Volume Distribution (VD):  0.689
Pgp-substrate:  72.18387603759766%

ADMET: Metabolism

CYP1A2-inhibitor:  0.033
CYP1A2-substrate:  0.075
CYP2C19-inhibitor:  0.015
CYP2C19-substrate:  0.594
CYP2C9-inhibitor:  0.003
CYP2C9-substrate:  0.087
CYP2D6-inhibitor:  0.002
CYP2D6-substrate:  0.11
CYP3A4-inhibitor:  0.024
CYP3A4-substrate:  0.142

ADMET: Excretion

Clearance (CL):  2.584
Half-life (T1/2):  0.906

ADMET: Toxicity

hERG Blockers:  0.024
Human Hepatotoxicity (H-HT):  0.138
Drug-inuced Liver Injury (DILI):  0.961
AMES Toxicity:  0.049
Rat Oral Acute Toxicity:  0.542
Maximum Recommended Daily Dose:  0.791
Skin Sensitization:  0.161
Carcinogencity:  0.956
Eye Corrosion:  0.003
Eye Irritation:  0.252
Respiratory Toxicity:  0.878

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General Info & Identifiers & Properties  
Structure MOL file  
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Biological Activities  
Similar NPs/Drugs  

  Natural Product: NPC268075

Natural Product ID:  NPC268075
Common Name*:   HAXXAUGQIKCLFE-YNPJLNQOSA-N
IUPAC Name:   n.a.
Synonyms:  
Standard InCHIKey:  HAXXAUGQIKCLFE-YNPJLNQOSA-N
Standard InCHI:  InChI=1S/C29H38O7/c1-25-14-15-28(17-24(32)34-19-28)36-26(25,2)16-22(27(3)21(25)10-7-13-29(27,33)18-30)35-23(31)12-11-20-8-5-4-6-9-20/h4-6,8-9,11-12,21-22,30,33H,7,10,13-19H2,1-3H3/b12-11+/t21-,22+,25-,26+,27+,28-,29+/m1/s1
SMILES:  C[C@@]12CC[C@]3(CC(=O)OC3)O[C@@]2(C)C[C@@H]([C@]2(C)[C@@H]1CCC[C@@]2(CO)O)OC(=O)/C=C/c1ccccc1
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   50908028
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
NPO28260 Senna alexandrina Species Fabaceae Eukaryota n.a. seed n.a. PMID[17345316]
NPO1347 Maackia amurensis Species Fabaceae Eukaryota n.a. stem n.a. PMID[19252325]
NPO11549 Paramuricea clavata Species Paramuriceidae Eukaryota n.a. n.a. n.a. PMID[21939218]
NPO1347 Maackia amurensis Species Fabaceae Eukaryota n.a. n.a. n.a. PMID[24252334]
NPO11697 Cirsium setosum Species Asteraceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO9077 Uncaria lanosa Species Rubiaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO1347 Maackia amurensis Species Fabaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO21988 Penicillium steckii Species Aspergillaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO28260 Senna alexandrina Species Fabaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO9077 Uncaria lanosa Species Rubiaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO1347 Maackia amurensis Species Fabaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO11697 Cirsium setosum Species Asteraceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO28260 Senna alexandrina Species Fabaceae Eukaryota n.a. n.a. n.a. Database[TM-MC]
NPO11697 Cirsium setosum Species Asteraceae Eukaryota n.a. n.a. n.a. Database[TM-MC]
NPO9077 Uncaria lanosa Species Rubiaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO1347 Maackia amurensis Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO11549 Paramuricea clavata Species Paramuriceidae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO11697 Cirsium setosum Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO23883 Penicillium abidjanum Species Aspergillaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO28260 Senna alexandrina Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO21988 Penicillium steckii Species Aspergillaceae 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 NPC268075 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 NPC268075 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