Natural Product: NPC605477

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 NPC605477 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 NPC71061
0.8923 High Similarity NPC150908
0.8286 Intermediate Similarity NPC265624
0.8 Intermediate Similarity NPC215203
0.7714 Intermediate Similarity NPC72425
0.7714 Intermediate Similarity NPC303485
0.7361 Intermediate Similarity NPC14606
0.7313 Intermediate Similarity NPC138299
0.7123 Intermediate Similarity NPC186227
0.6986 Remote Similarity NPC290830
0.6711 Remote Similarity NPC601565
0.6667 Remote Similarity NPC194593
0.6615 Remote Similarity NPC231772
0.6528 Remote Similarity NPC254351
0.6452 Remote Similarity NPC50898
0.6447 Remote Similarity NPC159707
0.64 Remote Similarity NPC600972
0.6364 Remote Similarity NPC121649
0.6351 Remote Similarity NPC259757
0.6349 Remote Similarity NPC222713
0.6282 Remote Similarity NPC205026
0.625 Remote Similarity NPC288840
0.6143 Remote Similarity NPC67322
0.6087 Remote Similarity NPC52005
0.6087 Remote Similarity NPC12200
0.6049 Remote Similarity NPC55443
0.6026 Remote Similarity NPC272064
0.6 Remote Similarity NPC183950
0.6 Remote Similarity NPC610480
0.589 Remote Similarity NPC111112
0.5658 Remote Similarity NPC34089
0.5658 Remote Similarity NPC183
0.5658 Remote Similarity NPC196179
0.5652 Remote Similarity NPC62536
0.5652 Remote Similarity NPC120464
0.5652 Remote Similarity NPC483773
0.5652 Remote Similarity NPC601901
0.5641 Remote Similarity NPC248739
0.56 Remote Similarity NPC291746
0.557 Remote Similarity NPC603508
0.5556 Remote Similarity NPC610914
0.5522 Remote Similarity NPC279121
0.5507 Remote Similarity NPC241498
0.5488 Remote Similarity NPC18699
0.5455 Remote Similarity NPC78540
0.5429 Remote Similarity NPC234133
0.5417 Remote Similarity NPC606638
0.5405 Remote Similarity NPC605634
0.5395 Remote Similarity NPC112954
0.5316 Remote Similarity NPC606549
0.5309 Remote Similarity NPC158027
0.5294 Remote Similarity NPC274121
0.5286 Remote Similarity NPC301323
0.5286 Remote Similarity NPC103342
0.5185 Remote Similarity NPC601984
0.5172 Remote Similarity NPC604941
0.5139 Remote Similarity NPC600900
0.507 Remote Similarity NPC47815
0.506 Remote Similarity NPC63454
0.506 Remote Similarity NPC183851
0.5057 Remote Similarity NPC607079

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC605477 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
0.5522 Remote Similarity NPD1511 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