Structure

Physi-Chem Properties

Molecular Weight:  550.28
Volume:  538.794
LogP:  0.855
LogD:  0.958
LogS:  -2.898
# Rotatable Bonds:  4
TPSA:  170.05
# H-Bond Aceptor:  10
# H-Bond Donor:  6
# Rings:  6
# Heavy Atoms:  10

MedChem Properties

QED Drug-Likeness Score:  0.24
Synthetic Accessibility Score:  5.446
Fsp3:  0.828
Lipinski Rule-of-5:  Rejected
Pfizer Rule:  Accepted
GSK Rule:  Rejected
BMS Rule:  1
Golden Triangle Rule:  Rejected
Chelating Alert:  0
PAINS Alert:  0

ADMET Properties (ADMETlab2.0)

ADMET: Absorption

Caco-2 Permeability:  -6.257
MDCK Permeability:  3.812569411820732e-05
Pgp-inhibitor:  0.003
Pgp-substrate:  0.996
Human Intestinal Absorption (HIA):  0.92
20% Bioavailability (F20%):  0.977
30% Bioavailability (F30%):  0.994

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.428
Plasma Protein Binding (PPB):  67.12567138671875%
Volume Distribution (VD):  0.606
Pgp-substrate:  20.47055435180664%

ADMET: Metabolism

CYP1A2-inhibitor:  0.002
CYP1A2-substrate:  0.939
CYP2C19-inhibitor:  0.004
CYP2C19-substrate:  0.152
CYP2C9-inhibitor:  0.003
CYP2C9-substrate:  0.066
CYP2D6-inhibitor:  0.002
CYP2D6-substrate:  0.065
CYP3A4-inhibitor:  0.43
CYP3A4-substrate:  0.164

ADMET: Excretion

Clearance (CL):  2.686
Half-life (T1/2):  0.162

ADMET: Toxicity

hERG Blockers:  0.172
Human Hepatotoxicity (H-HT):  0.374
Drug-inuced Liver Injury (DILI):  0.022
AMES Toxicity:  0.066
Rat Oral Acute Toxicity:  0.903
Maximum Recommended Daily Dose:  0.961
Skin Sensitization:  0.191
Carcinogencity:  0.892
Eye Corrosion:  0.003
Eye Irritation:  0.007
Respiratory Toxicity:  0.977

Download Data

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

  Natural Product: NPC71747

Natural Product ID:  NPC71747
Common Name*:   HULMNSIAKWANQO-RMBZBVRKSA-N
IUPAC Name:   n.a.
Synonyms:  
Standard InCHIKey:  HULMNSIAKWANQO-RMBZBVRKSA-N
Standard InCHI:  InChI=1S/C29H42O10/c1-15-22(32)23(33)24(34)25(38-15)39-17-3-8-27(14-30)19-4-7-26(2)18(16-11-21(31)37-13-16)6-10-29(26,36)20(19)5-9-28(27,35)12-17/h11,14-15,17-20,22-25,32-36H,3-10,12-13H2,1-2H3/t15?,17-,18+,19?,20?,22+,23?,24?,25-,26+,27-,28-,29-/m0/s1
SMILES:  CC1[C@H](C(C([C@@H](O1)O[C@H]1CC[C@]2(C=O)C3CC[C@]4(C)[C@H](CC[C@@]4(C3CC[C@@]2(C1)O)O)C1=CC(=O)OC1)O)O)O
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   20341
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000012] Lipids and lipid-like molecules
      • [CHEMONTID:0000258] Steroids and steroid derivatives
        • [CHEMONTID:0001125] Steroid lactones
          • [CHEMONTID:0001555] Cardenolides and derivatives
            • [CHEMONTID:0001559] Cardenolide glycosides and derivatives

*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
NPO8369 Antiaris toxicaria Species Moraceae Eukaryota n.a. n.a. n.a. PMID[20553004]
NPO8369 Antiaris toxicaria Species Moraceae Eukaryota latex Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Yunnan Province, China 2011-Mar PMID[24033101]
NPO8369 Antiaris toxicaria Species Moraceae Eukaryota trunk bark Yunnan, China n.a. PMID[24582402]
NPO23135 Formica fusca Species Formicidae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO8369 Antiaris toxicaria Species Moraceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO16884 Convallaria keiskei Species Asparagaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO8369 Antiaris toxicaria Species Moraceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO23135 Formica fusca Species Formicidae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO16884 Convallaria keiskei Species Asparagaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO16884 Convallaria keiskei Species Asparagaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO23135 Formica fusca Species Formicidae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO8369 Antiaris toxicaria Species Moraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO23135 Formica fusca Species Formicidae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO16884 Convallaria keiskei Species Asparagaceae 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 NPC71747 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 NPC71747 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