Natural Product: NPC606550

Natural Product IDNPC606550
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
 VSJCDPYIMBSOKN-LSDHHAIUSA-N
IUPAC Name n.a.
Synonyms
Synthetic Gene Cluster n.a.
ChEMBL Identifier CHEMBL482975
PubChem CID n.a.
Chemical Classification
  • CHEMONTID:0000000 [Organic compounds]

The Chemical Classification was calculated by Classyfire, a software for chemical taxonomy calculation. Reference: DOI:10.1186/s13321-016-0174-y.

  Chemical Representations

Standard InCHIKey VSJCDPYIMBSOKN-LSDHHAIUSA-N
Standard InCHI InChI=1S/C15H12O7/c16-7-1-2-8-11(5-7)22-15(14(21)12(8)19)6-3-9(17)13(20)10(18)4-6/h1-5,14-18,20-21H/t14-,15+/m0/s1
SMILES O=C1c2ccc(O)cc2O[C@H](c2cc(O)c(O)c(O)c2)[C@H]1O

  Calculated Properties

Physi-Chem Properties

MedChem Properties

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

ADMET: Distribution

ADMET: Metabolism

ADMET: Excretion

ADMET: Toxicity

  Species Source

Organism ID Organism Name Taxonomy Level Family SuperKingdom Isolation Part Collection Location Collection Time Reference
NPO6062 Acacia mearnsii Species Fabaceae Eukaryota n.a. bark n.a. PMID[21192716]
NPO6062 Acacia mearnsii Species Fabaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO14975 Adenanthera pavonina Species Fabaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO6062 Acacia mearnsii Species Fabaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO14975 Adenanthera pavonina Species Fabaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO14975 Adenanthera pavonina Species Fabaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO6062 Acacia mearnsii Species Fabaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO6062 Acacia mearnsii Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO14975 Adenanthera pavonina Species Fabaceae 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 Organism Name 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

Molecular-level activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference

In vitro activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference
NPT113 Cell line RAW264.7 Mus musculus IC50 > 100000.0 nM PMID[27955927]

In vivo activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference





 Experimental ADME

Experiment Model Experiment Tissue ADME Type ADME Relation ADME Value ADME Unit Reference





 Experimental Toxicity

Quantitative toxicity

Experiment Model Experiment Organism Toxicity Type Toxicity Relation Toxicity Value Toxicity Unit Reference

Common Abbreviations:
LC: Lethal Concentration; LD: Lethal Dose; LT:Lethal Time; NOAEL: No-observed-adverse-effect Level; BMDL: Benchmark Dose Lower Confidence Limit; BMD: Benchmark Dose; BMC:Benchmark Concentration; LOAEL: Lowest Observed Adverse Effect Level; RfD:Reference Dose; RfC:Reference Concentration; MRL: Minimal Risk Level; MEG: Maximum Exposure Guideline; PAC: Protective Action Criteria

Categorical toxicity labels

Hepatotoxicity Carcinogenicity Mutagenicity Cardiotoxicity Respiratory Toxicity Eye Irritation Endocrine Disruption
Hepatotoxicity Carcinogenicity Mutagenicity Cardiotoxicity Respiratory Toxicity Eye Irritation Endocrine Disruption

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 toxicity records from domain-specific databases. These databases include:
☉ ToxValDB: a curated database that compiles quantitative toxicity values for chemicals from diverse public sources to support toxicological research and risk assessment.
☉ TOXRIC: a comprehensive, free-to-access, online database providing toxicological/feature data. The toxicity labels are retrieved from this database. [PMID: 36400569]


  Chemically structural similarity

Similar Active Natural Products in NPASS

Top-200 similar NPs were calculated against the active-NP-set (includes approximately 50,000 NPs with experimentally-derived bioactivity available in NPASS)

Similarity is measured using the Tanimoto coefficient (Tc) , which compares the binary fingerprints of two molecules. Tc is calculated as the intersection divided by the union of '1' bits in the fingerprints, ranging from 0 to 1, with 1 indicating highest similarity.

●  The left chart: Distribution of similarity level between NPC606550 and all remaining natural products in the NPASS database.
●  The right table: Most similar natural products (Tc>=0.5 or Top200).

Similarity Score Similarity Level Natural Product ID
1.0 High Similarity NPC325028
1.0 High Similarity NPC256346
0.8298 Intermediate Similarity NPC246328
0.8298 Intermediate Similarity NPC27532
0.7826 Intermediate Similarity NPC1940
0.76 Intermediate Similarity NPC609065
0.75 Intermediate Similarity NPC148011
0.6863 Remote Similarity NPC19721
0.6667 Remote Similarity NPC52530
0.6 Remote Similarity NPC36835
0.6 Remote Similarity NPC246162
0.6 Remote Similarity NPC9743
0.6 Remote Similarity NPC260491
0.6 Remote Similarity NPC61506
0.6 Remote Similarity NPC240476
0.5926 Remote Similarity NPC201837
0.5741 Remote Similarity NPC62290
0.5741 Remote Similarity NPC142731
0.5741 Remote Similarity NPC326506
0.5614 Remote Similarity NPC611035
0.5556 Remote Similarity NPC21835
0.5455 Remote Similarity NPC1612
0.5455 Remote Similarity NPC183959
0.5455 Remote Similarity NPC600246
0.5263 Remote Similarity NPC176869
0.5263 Remote Similarity NPC3779
0.5185 Remote Similarity NPC601844
0.5179 Remote Similarity NPC279417
0.5179 Remote Similarity NPC4152
0.5179 Remote Similarity NPC49130
0.5172 Remote Similarity NPC250922
0.5091 Remote Similarity NPC268266
0.5091 Remote Similarity NPC42760
0.5091 Remote Similarity NPC220825
0.5091 Remote Similarity NPC268342

Similar Clinical/Approved Drugs

Similarity level is defined by Tanimoto coefficient (Tc) between two molecules.

●  The left chart: Distribution of similarity level between NPC606550 and all drugs/candidates.
●  The right table: Most similar clinical/approved drugs (Tc>=0.5 or Top200).

Similarity Score Similarity Level Drug ID Developmental Stage
NPD

Bioactivity similarity

  Bioactivity similarity

Similar Natural Products in NPASS

Similarity level is defined by 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