Natural Product: NPC531051

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 NPC531051 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 NPC609179
0.7925 Intermediate Similarity NPC50403
0.7818 Intermediate Similarity NPC606638
0.7736 Intermediate Similarity NPC219330
0.7636 Intermediate Similarity NPC54394
0.75 Intermediate Similarity NPC162351
0.7368 Intermediate Similarity NPC133953
0.7321 Intermediate Similarity NPC159103
0.7273 Intermediate Similarity NPC28274
0.7069 Intermediate Similarity NPC125062
0.6964 Remote Similarity NPC241838
0.661 Remote Similarity NPC474520
0.6545 Remote Similarity NPC179271
0.6364 Remote Similarity NPC169749
0.6364 Remote Similarity NPC20791
0.6182 Remote Similarity NPC116775
0.6182 Remote Similarity NPC187432
0.6102 Remote Similarity NPC62536
0.6102 Remote Similarity NPC601901
0.6102 Remote Similarity NPC610359
0.5932 Remote Similarity NPC123886
0.5806 Remote Similarity NPC177298
0.5806 Remote Similarity NPC52005
0.5806 Remote Similarity NPC12200
0.5806 Remote Similarity NPC603596
0.5789 Remote Similarity NPC601197
0.5714 Remote Similarity NPC481044
0.5645 Remote Similarity NPC200740
0.5645 Remote Similarity NPC82325
0.5645 Remote Similarity NPC29841
0.5574 Remote Similarity NPC120464
0.5574 Remote Similarity NPC483773
0.5556 Remote Similarity NPC93376
0.5556 Remote Similarity NPC206604
0.5479 Remote Similarity NPC254306
0.5469 Remote Similarity NPC183950
0.5469 Remote Similarity NPC279989
0.5455 Remote Similarity NPC606270
0.5424 Remote Similarity NPC216361
0.541 Remote Similarity NPC98661
0.541 Remote Similarity NPC184536
0.541 Remote Similarity NPC103342
0.5397 Remote Similarity NPC166753
0.5373 Remote Similarity NPC205046
0.5333 Remote Similarity NPC256042
0.5323 Remote Similarity NPC286342
0.5323 Remote Similarity NPC59951
0.5323 Remote Similarity NPC231772
0.5323 Remote Similarity NPC87125
0.5323 Remote Similarity NPC143799
0.5323 Remote Similarity NPC605755
0.5294 Remote Similarity NPC130955
0.5263 Remote Similarity NPC21100
0.5246 Remote Similarity NPC26227
0.5238 Remote Similarity NPC600900
0.5231 Remote Similarity NPC252933
0.5161 Remote Similarity NPC44079
0.5161 Remote Similarity NPC152042
0.5156 Remote Similarity NPC55205
0.5152 Remote Similarity NPC227192
0.5079 Remote Similarity NPC201451
0.5077 Remote Similarity NPC189179
0.5077 Remote Similarity NPC235215
0.5077 Remote Similarity NPC610401
0.5075 Remote Similarity NPC605634
0.5072 Remote Similarity NPC200694
0.5068 Remote Similarity NPC171821

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC531051 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
0.6364 Remote Similarity NPD1512 Phase 3

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