Structure

Physi-Chem Properties

Molecular Weight:  886.57
Volume:  923.026
LogP:  5.005
LogD:  3.751
LogS:  -3.027
# Rotatable Bonds:  37
TPSA:  231.13
# H-Bond Aceptor:  15
# H-Bond Donor:  7
# Rings:  2
# Heavy Atoms:  15

MedChem Properties

QED Drug-Likeness Score:  0.024
Synthetic Accessibility Score:  5.353
Fsp3:  0.83
Lipinski Rule-of-5:  Rejected
Pfizer Rule:  Accepted
GSK Rule:  Rejected
BMS Rule:  2
Golden Triangle Rule:  Rejected
Chelating Alert:  0
PAINS Alert:  0

ADMET Properties (ADMETlab2.0)

ADMET: Absorption

Caco-2 Permeability:  -5.293
MDCK Permeability:  1.7783964722184464e-05
Pgp-inhibitor:  0.001
Pgp-substrate:  0.294
Human Intestinal Absorption (HIA):  0.68
20% Bioavailability (F20%):  1.0
30% Bioavailability (F30%):  1.0

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.007
Plasma Protein Binding (PPB):  99.92415618896484%
Volume Distribution (VD):  1.211
Pgp-substrate:  1.161062479019165%

ADMET: Metabolism

CYP1A2-inhibitor:  0.005
CYP1A2-substrate:  0.059
CYP2C19-inhibitor:  0.02
CYP2C19-substrate:  0.04
CYP2C9-inhibitor:  0.102
CYP2C9-substrate:  0.926
CYP2D6-inhibitor:  0.042
CYP2D6-substrate:  0.042
CYP3A4-inhibitor:  0.32
CYP3A4-substrate:  0.011

ADMET: Excretion

Clearance (CL):  1.832
Half-life (T1/2):  0.923

ADMET: Toxicity

hERG Blockers:  0.844
Human Hepatotoxicity (H-HT):  0.133
Drug-inuced Liver Injury (DILI):  0.017
AMES Toxicity:  0.821
Rat Oral Acute Toxicity:  0.005
Maximum Recommended Daily Dose:  0.012
Skin Sensitization:  0.972
Carcinogencity:  0.263
Eye Corrosion:  0.003
Eye Irritation:  0.009
Respiratory Toxicity:  0.162

Download Data

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

  Natural Product: NPC210477

Natural Product ID:  NPC210477
Common Name*:   UQNHXSCEVWBPSL-RRPNLBNLSA-N
IUPAC Name:   n.a.
Synonyms:  
Standard InCHIKey:  UQNHXSCEVWBPSL-RRPNLBNLSA-N
Standard InCHI:  InChI=1S/C35H36N2O6/c1-37-13-11-22-17-30(40-2)31-19-25(22)27(37)15-21-6-9-28(38)29(16-21)42-24-7-4-20(5-8-24)14-26-33-23(10-12-36-26)18-32(41-3)34(39)35(33)43-31/h4-9,16-19,26-27,36,38-39H,10-15H2,1-3H3/t26-,27+/m0/s1
SMILES:  CN1CCc2cc(c3cc2[C@H]1Cc1ccc(c(c1)Oc1ccc(cc1)C[C@H]1c2c(CCN1)cc(c(c2O3)O)OC)O)OC
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   46872348
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0001392] Lignans, neolignans and related compounds

*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
NPO10590.1 Morus alba var. multicaulis Varieties Moraceae Eukaryota Fruits Zhenjiang, Jiangsu Province, China PMID[23060696]
NPO5921 Xestospongia caycedoi Species Petrosiidae Eukaryota n.a. Fijian n.a. PMID[3430171]
NPO6484 Alstonia venenata Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO10681 Pycnarrhena longifolia Species Menispermaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO6484 Alstonia venenata Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO10681 Pycnarrhena longifolia Species Menispermaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO6484 Alstonia venenata Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO10681 Pycnarrhena longifolia Species Menispermaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO10590.1 Morus alba var. multicaulis Varieties Moraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO7219 Vernonia potamophila Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO2307 Trigonella corniculata Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO6484 Alstonia venenata Species Apocynaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO4954.1 Eleutherococcus divaricatus var. chiisanensis Varieties Araliaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO16133 Hymenoxys richardsonii Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO7772 Conyza aegyptiaca Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO1357 Cussonia paniculata Species Araliaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO279 Mahonia morrisonensis n.a. n.a. n.a. n.a. n.a. n.a. Database[UNPD]
NPO5485 Rothmannia globosa Species Rubiaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO7938 Merendera manissadjianii Species Colchicaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO5921 Xestospongia caycedoi Species Petrosiidae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO7284 Machilus glaucescens Species Lauraceae 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 NPC210477 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 NPC210477 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