Natural Product: NPC608477

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 NPC608477 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 NPC248944
1.0 High Similarity NPC7479
1.0 High Similarity NPC257296
0.8 Intermediate Similarity NPC481427
0.7797 Intermediate Similarity NPC296734
0.7627 Intermediate Similarity NPC227260
0.7619 Intermediate Similarity NPC161035
0.7619 Intermediate Similarity NPC170438
0.6613 Remote Similarity NPC24556
0.6406 Remote Similarity NPC273290
0.6406 Remote Similarity NPC232044
0.6389 Remote Similarity NPC144790
0.6389 Remote Similarity NPC149400
0.6389 Remote Similarity NPC88962
0.6364 Remote Similarity NPC305808
0.6351 Remote Similarity NPC473774
0.6351 Remote Similarity NPC481418
0.6351 Remote Similarity NPC481419
0.6351 Remote Similarity NPC481417
0.6324 Remote Similarity NPC235126
0.6324 Remote Similarity NPC242419
0.6301 Remote Similarity NPC277715
0.6267 Remote Similarity NPC24960
0.5775 Remote Similarity NPC177818
0.5732 Remote Similarity NPC473616
0.5679 Remote Similarity NPC131693
0.5679 Remote Similarity NPC485591
0.5679 Remote Similarity NPC475436
0.5556 Remote Similarity NPC297348
0.5556 Remote Similarity NPC325828
0.5556 Remote Similarity NPC249204
0.5556 Remote Similarity NPC48339
0.5556 Remote Similarity NPC177834
0.5556 Remote Similarity NPC141769
0.5556 Remote Similarity NPC477547
0.5542 Remote Similarity NPC312678
0.5542 Remote Similarity NPC253268
0.5488 Remote Similarity NPC234352
0.5479 Remote Similarity NPC486119
0.5422 Remote Similarity NPC477451
0.5362 Remote Similarity NPC155985
0.5362 Remote Similarity NPC601115
0.5357 Remote Similarity NPC250393
0.5316 Remote Similarity NPC481420
0.5316 Remote Similarity NPC481421
0.5301 Remote Similarity NPC294686
0.5294 Remote Similarity NPC206003
0.5294 Remote Similarity NPC473610
0.5244 Remote Similarity NPC481424
0.5244 Remote Similarity NPC481422
0.5244 Remote Similarity NPC481423
0.5233 Remote Similarity NPC211354
0.5233 Remote Similarity NPC107188
0.5233 Remote Similarity NPC19400
0.5211 Remote Similarity NPC187159
0.5176 Remote Similarity NPC222731
0.5172 Remote Similarity NPC264101
0.5114 Remote Similarity NPC107962
0.5067 Remote Similarity NPC100451
0.506 Remote Similarity NPC181845
0.5056 Remote Similarity NPC6295

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC608477 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
1.0 High Similarity NPD6928 Phase 2
0.5584 Remote Similarity NPD7991 Discontinued
0.5556 Remote Similarity NPD8171 Phase 2

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