Natural Product: NPC545871

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 NPC545871 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 NPC608554
0.8222 Intermediate Similarity NPC39426
0.7609 Intermediate Similarity NPC193792
0.75 Intermediate Similarity NPC38065
0.7255 Intermediate Similarity NPC294409
0.7255 Intermediate Similarity NPC490701
0.68 Remote Similarity NPC87545
0.6731 Remote Similarity NPC78341
0.6667 Remote Similarity NPC200316
0.6545 Remote Similarity NPC194653
0.6429 Remote Similarity NPC254702
0.6379 Remote Similarity NPC608523
0.6316 Remote Similarity NPC104728
0.625 Remote Similarity NPC481044
0.6182 Remote Similarity NPC239363
0.6071 Remote Similarity NPC309154
0.6 Remote Similarity NPC213659
0.6 Remote Similarity NPC326109
0.5965 Remote Similarity NPC279668
0.5965 Remote Similarity NPC278323
0.5902 Remote Similarity NPC606200
0.5893 Remote Similarity NPC19980
0.5873 Remote Similarity NPC474052
0.5862 Remote Similarity NPC142876
0.5862 Remote Similarity NPC483637
0.5862 Remote Similarity NPC264550
0.5833 Remote Similarity NPC238279
0.5806 Remote Similarity NPC475705
0.5806 Remote Similarity NPC233918
0.5781 Remote Similarity NPC107838
0.5781 Remote Similarity NPC600495
0.5714 Remote Similarity NPC479305
0.5593 Remote Similarity NPC476055
0.5593 Remote Similarity NPC45291
0.5556 Remote Similarity NPC268059
0.5538 Remote Similarity NPC74178
0.5484 Remote Similarity NPC85131
0.5484 Remote Similarity NPC232947
0.5469 Remote Similarity NPC128774
0.5417 Remote Similarity NPC65060
0.541 Remote Similarity NPC93552
0.541 Remote Similarity NPC167595
0.5362 Remote Similarity NPC156457
0.5303 Remote Similarity NPC231763
0.5303 Remote Similarity NPC482075
0.5303 Remote Similarity NPC303197
0.5283 Remote Similarity NPC234560
0.5263 Remote Similarity NPC131266
0.5263 Remote Similarity NPC269451
0.5224 Remote Similarity NPC52889
0.5172 Remote Similarity NPC303644
0.5102 Remote Similarity NPC185497
0.5098 Remote Similarity NPC201284

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC545871 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
0.8222 Intermediate Similarity NPD1510 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