Structure

Physi-Chem Properties

Molecular Weight:  677.41
Volume:  682.239
LogP:  4.286
LogD:  2.768
LogS:  -3.75
# Rotatable Bonds:  8
TPSA:  166.22
# H-Bond Aceptor:  11
# H-Bond Donor:  5
# Rings:  7
# Heavy Atoms:  11

MedChem Properties

QED Drug-Likeness Score:  0.262
Synthetic Accessibility Score:  7.372
Fsp3:  0.946
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:  -5.044
MDCK Permeability:  0.00013399285671766847
Pgp-inhibitor:  0.974
Pgp-substrate:  0.995
Human Intestinal Absorption (HIA):  0.018
20% Bioavailability (F20%):  0.005
30% Bioavailability (F30%):  0.908

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.096
Plasma Protein Binding (PPB):  75.28789520263672%
Volume Distribution (VD):  0.918
Pgp-substrate:  23.508769989013672%

ADMET: Metabolism

CYP1A2-inhibitor:  0.012
CYP1A2-substrate:  0.653
CYP2C19-inhibitor:  0.015
CYP2C19-substrate:  0.768
CYP2C9-inhibitor:  0.009
CYP2C9-substrate:  0.021
CYP2D6-inhibitor:  0.006
CYP2D6-substrate:  0.218
CYP3A4-inhibitor:  0.508
CYP3A4-substrate:  0.352

ADMET: Excretion

Clearance (CL):  9.573
Half-life (T1/2):  0.022

ADMET: Toxicity

hERG Blockers:  0.482
Human Hepatotoxicity (H-HT):  0.645
Drug-inuced Liver Injury (DILI):  0.128
AMES Toxicity:  0.011
Rat Oral Acute Toxicity:  0.255
Maximum Recommended Daily Dose:  0.106
Skin Sensitization:  0.342
Carcinogencity:  0.492
Eye Corrosion:  0.003
Eye Irritation:  0.009
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: NPC9286

Natural Product ID:  NPC9286
Common Name*:   JXFGWSCYDZJNIC-YIGPFNBESA-N
IUPAC Name:   n.a.
Synonyms:  
Standard InCHIKey:  JXFGWSCYDZJNIC-YIGPFNBESA-N
Standard InCHI:  InChI=1S/C37H59NO10/c1-8-19(4)31(41)46-26-12-13-33(6)24-14-23(39)29-35(33,48-37(24,26)45)15-22-21-17-38-16-18(3)10-11-25(38)34(7,43)27(21)28(40)30(36(22,29)44)47-32(42)20(5)9-2/h18-30,39-40,43-45H,8-17H2,1-7H3/t18-,19+,20+,21-,22-,23-,24-,25-,26-,27+,28+,29+,30-,33-,34+,35+,36-,37-/m0/s1
SMILES:  CC[C@@H](C)C(=O)O[C@H]1CC[C@@]2(C)[C@@H]3C[C@@H]([C@@H]4[C@@]2(C[C@H]2[C@@H]5CN6C[C@@H](C)CC[C@H]6[C@](C)([C@H]5[C@H]([C@@H]([C@@]42O)OC(=O)[C@H](C)CC)O)O)O[C@]13O)O
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   n.a.
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000012] Lipids and lipid-like molecules
      • [CHEMONTID:0000258] Steroids and steroid derivatives
        • [CHEMONTID:0002724] Steroidal alkaloids
          • [CHEMONTID:0002729] Cerveratrum-type alkaloids

*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
NPO4373 Phyllanthus acuminatus Species Phyllanthaceae Eukaryota Roots n.a. n.a. PMID[2089115]
NPO2634 Tetrapleura tetraptera Species Fabaceae Eukaryota n.a. n.a. n.a. PMID[8289059]
NPO10815 Uncaria borneensis Species Rubiaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO4373 Phyllanthus acuminatus Species Phyllanthaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO4373 Phyllanthus acuminatus Species Phyllanthaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO10815 Uncaria borneensis Species Rubiaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO4373 Phyllanthus acuminatus Species Phyllanthaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO1718 Sarcodontia setosa Species Meruliaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO2634 Tetrapleura tetraptera Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO20796 Stemonoporus canaliculatus Species Dipterocarpaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO7675 Perezia cuernavacana Species Pereziidae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO1968 Delphinium ternatum Species Ranunculaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO8057 Bulnesia retama Species Zygophyllaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO4148 Artemisia spicigera Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO612 Pteronia stricta Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO9242 Bauhinia manca Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO4373 Phyllanthus acuminatus Species Phyllanthaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO10815 Uncaria borneensis Species Rubiaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO9373 Sigmadocia symbiotica Species Chalinidae 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 NPC9286 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 NPC9286 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