Natural Product: NPC607237

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

  Chemical Representations

  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

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

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 NPC607237 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 NPC215833
0.7959 Intermediate Similarity NPC69513
0.7547 Intermediate Similarity NPC80600
0.72 Intermediate Similarity NPC299144
0.6885 Remote Similarity NPC479447
0.6875 Remote Similarity NPC199539
0.6792 Remote Similarity NPC48863
0.6792 Remote Similarity NPC251981
0.6792 Remote Similarity NPC13745
0.6607 Remote Similarity NPC26653
0.66 Remote Similarity NPC217854
0.6545 Remote Similarity NPC49074
0.6429 Remote Similarity NPC162093
0.6346 Remote Similarity NPC152722
0.6316 Remote Similarity NPC210478
0.614 Remote Similarity NPC472024
0.614 Remote Similarity NPC270849
0.6102 Remote Similarity NPC95392
0.6102 Remote Similarity NPC84013
0.6102 Remote Similarity NPC55715
0.6102 Remote Similarity NPC35877
0.6078 Remote Similarity NPC276195
0.6 Remote Similarity NPC232673
0.5902 Remote Similarity NPC470236
0.5893 Remote Similarity NPC95292
0.5818 Remote Similarity NPC608788
0.5789 Remote Similarity NPC9912
0.5781 Remote Similarity NPC475096
0.5667 Remote Similarity NPC479029
0.5634 Remote Similarity NPC217635
0.5614 Remote Similarity NPC166040
0.5606 Remote Similarity NPC148273
0.56 Remote Similarity NPC228907
0.5556 Remote Similarity NPC153149
0.5507 Remote Similarity NPC227902
0.5493 Remote Similarity NPC605526
0.5484 Remote Similarity NPC34456
0.5469 Remote Similarity NPC479030
0.5469 Remote Similarity NPC486107
0.5455 Remote Similarity NPC216129
0.5455 Remote Similarity NPC130449
0.5455 Remote Similarity NPC25817
0.5455 Remote Similarity NPC248132
0.5435 Remote Similarity NPC63083
0.5424 Remote Similarity NPC218685
0.5362 Remote Similarity NPC61594
0.5357 Remote Similarity NPC60589
0.5357 Remote Similarity NPC469708
0.5303 Remote Similarity NPC210192
0.5286 Remote Similarity NPC56735
0.5273 Remote Similarity NPC192810
0.5263 Remote Similarity NPC226712
0.5224 Remote Similarity NPC485147
0.5185 Remote Similarity NPC212729
0.5185 Remote Similarity NPC604498
0.5172 Remote Similarity NPC145900
0.5161 Remote Similarity NPC248355
0.5152 Remote Similarity NPC146803
0.5152 Remote Similarity NPC164857
0.5143 Remote Similarity NPC51328
0.5143 Remote Similarity NPC55158
0.5122 Remote Similarity NPC485746
0.5091 Remote Similarity NPC269242
0.5088 Remote Similarity NPC190730
0.5088 Remote Similarity NPC609376
0.5082 Remote Similarity NPC479028
0.5082 Remote Similarity NPC23084
0.5082 Remote Similarity NPC479031
0.5079 Remote Similarity NPC55040
0.5079 Remote Similarity NPC104167
0.5077 Remote Similarity NPC134260
0.5075 Remote Similarity NPC475084
0.507 Remote Similarity NPC106625

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC607237 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
0.5263 Remote Similarity NPD1091 Pre-clinical

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