Natural Product: NPC604354

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 NPC604354 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 NPC48863
1.0 High Similarity NPC251981
1.0 High Similarity NPC13745
0.7347 Intermediate Similarity NPC299144
0.7059 Intermediate Similarity NPC69513
0.6792 Remote Similarity NPC215833
0.6735 Remote Similarity NPC217854
0.6667 Remote Similarity NPC49074
0.6545 Remote Similarity NPC162093
0.6471 Remote Similarity NPC152722
0.6429 Remote Similarity NPC210478
0.6271 Remote Similarity NPC470236
0.6207 Remote Similarity NPC95392
0.6207 Remote Similarity NPC84013
0.6207 Remote Similarity NPC55715
0.6207 Remote Similarity NPC35877
0.62 Remote Similarity NPC276195
0.619 Remote Similarity NPC479447
0.6102 Remote Similarity NPC232673
0.6 Remote Similarity NPC95292
0.5763 Remote Similarity NPC479029
0.5714 Remote Similarity NPC166040
0.5714 Remote Similarity NPC228907
0.569 Remote Similarity NPC472024
0.566 Remote Similarity NPC153149
0.5636 Remote Similarity NPC608788
0.5556 Remote Similarity NPC479030
0.5556 Remote Similarity NPC25817
0.5538 Remote Similarity NPC216129
0.5538 Remote Similarity NPC130449
0.5538 Remote Similarity NPC248132
0.5517 Remote Similarity NPC218685
0.5469 Remote Similarity NPC164857
0.5455 Remote Similarity NPC190730
0.5424 Remote Similarity NPC270849
0.5385 Remote Similarity NPC475096
0.537 Remote Similarity NPC192810
0.537 Remote Similarity NPC294470
0.5357 Remote Similarity NPC226712
0.5333 Remote Similarity NPC26653
0.5333 Remote Similarity NPC80600
0.5312 Remote Similarity NPC486107
0.5283 Remote Similarity NPC212729
0.5283 Remote Similarity NPC604498
0.5263 Remote Similarity NPC145900
0.5246 Remote Similarity NPC248355
0.5231 Remote Similarity NPC146803
0.5217 Remote Similarity NPC51328
0.5217 Remote Similarity NPC55158
0.5185 Remote Similarity NPC269242
0.5179 Remote Similarity NPC609376
0.5167 Remote Similarity NPC479028
0.5167 Remote Similarity NPC23084
0.5167 Remote Similarity NPC479031
0.5161 Remote Similarity NPC55040
0.5161 Remote Similarity NPC104167
0.5152 Remote Similarity NPC475084
0.5132 Remote Similarity NPC486547
0.5088 Remote Similarity NPC12308
0.5085 Remote Similarity NPC40377
0.5085 Remote Similarity NPC310661
0.5085 Remote Similarity NPC9912
0.5082 Remote Similarity NPC164599
0.5082 Remote Similarity NPC65942
0.5082 Remote Similarity NPC248307
0.5079 Remote Similarity NPC302378
0.5079 Remote Similarity NPC34456
0.5075 Remote Similarity NPC485147
0.507 Remote Similarity NPC199539

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC604354 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
0.5357 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