Natural Product: NPC606582

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 NPC606582 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 NPC482741
1.0 High Similarity NPC482745
1.0 High Similarity NPC482743
1.0 High Similarity NPC146753
0.9 High Similarity NPC482747
0.9 High Similarity NPC202666
0.9 High Similarity NPC471961
0.9 High Similarity NPC242015
0.8061 Intermediate Similarity NPC482755
0.8021 Intermediate Similarity NPC471965
0.8021 Intermediate Similarity NPC482749
0.7979 Intermediate Similarity NPC482748
0.7912 Intermediate Similarity NPC482752
0.77 Intermediate Similarity NPC262199
0.7576 Intermediate Similarity NPC14617
0.732 Intermediate Similarity NPC482750
0.7273 Intermediate Similarity NPC482746
0.7255 Intermediate Similarity NPC482734
0.7255 Intermediate Similarity NPC182342
0.7255 Intermediate Similarity NPC482727
0.7255 Intermediate Similarity NPC471964
0.7143 Intermediate Similarity NPC309780
0.71 Intermediate Similarity NPC482717
0.6792 Remote Similarity NPC247315
0.6792 Remote Similarity NPC482728
0.6667 Remote Similarity NPC482751
0.6635 Remote Similarity NPC285091
0.6598 Remote Similarity NPC471967
0.6574 Remote Similarity NPC482737
0.6509 Remote Similarity NPC482722
0.6509 Remote Similarity NPC471963
0.6509 Remote Similarity NPC482729
0.6509 Remote Similarity NPC482742
0.6509 Remote Similarity NPC482744
0.6486 Remote Similarity NPC471962
0.6436 Remote Similarity NPC482726
0.6422 Remote Similarity NPC482735
0.6121 Remote Similarity NPC482736
0.6121 Remote Similarity NPC482738
0.6034 Remote Similarity NPC482739
0.5934 Remote Similarity NPC4036
0.5934 Remote Similarity NPC65120
0.5934 Remote Similarity NPC145067
0.5934 Remote Similarity NPC233455
0.5934 Remote Similarity NPC158030
0.5752 Remote Similarity NPC482740
0.5638 Remote Similarity NPC482712
0.5638 Remote Similarity NPC74751
0.5505 Remote Similarity NPC275343
0.5269 Remote Similarity NPC96095
0.5143 Remote Similarity NPC224121
0.5126 Remote Similarity NPC120116
0.5086 Remote Similarity NPC118440
0.5044 Remote Similarity NPC472949
0.5043 Remote Similarity NPC131469

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC606582 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
0.9 High Similarity NPD8328 Phase 2
0.5934 Remote Similarity NPD7515 Phase 2
0.5638 Remote Similarity NPD7748 Pre-clinical
0.5354 Remote Similarity NPD7902 Phase 4

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