Natural Product: NPC606426

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 NPC606426 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 NPC20505
0.8889 High Similarity NPC282169
0.8267 Intermediate Similarity NPC608742
0.7273 Intermediate Similarity NPC253685
0.7215 Intermediate Similarity NPC135277
0.6923 Remote Similarity NPC19709
0.6914 Remote Similarity NPC43211
0.6835 Remote Similarity NPC189142
0.6835 Remote Similarity NPC77660
0.6818 Remote Similarity NPC229409
0.6667 Remote Similarity NPC600989
0.6585 Remote Similarity NPC237435
0.6386 Remote Similarity NPC210094
0.6353 Remote Similarity NPC190003
0.631 Remote Similarity NPC115760
0.6207 Remote Similarity NPC606546
0.6197 Remote Similarity NPC108406
0.619 Remote Similarity NPC235260
0.619 Remote Similarity NPC155763
0.6118 Remote Similarity NPC610187
0.6071 Remote Similarity NPC101191
0.6044 Remote Similarity NPC64051
0.6 Remote Similarity NPC49344
0.6 Remote Similarity NPC210073
0.5976 Remote Similarity NPC473043
0.5976 Remote Similarity NPC331652
0.5904 Remote Similarity NPC39360
0.5904 Remote Similarity NPC29763
0.5904 Remote Similarity NPC210003
0.5843 Remote Similarity NPC8856
0.5806 Remote Similarity NPC65711
0.5789 Remote Similarity NPC605587
0.5747 Remote Similarity NPC601144
0.5699 Remote Similarity NPC46202
0.5698 Remote Similarity NPC27942
0.5591 Remote Similarity NPC115674
0.5568 Remote Similarity NPC22832
0.5529 Remote Similarity NPC261866
0.5517 Remote Similarity NPC138927
0.5506 Remote Similarity NPC311830
0.5495 Remote Similarity NPC107987
0.5465 Remote Similarity NPC95090
0.5465 Remote Similarity NPC27408
0.5402 Remote Similarity NPC181712
0.5349 Remote Similarity NPC238376
0.5287 Remote Similarity NPC277205
0.5287 Remote Similarity NPC37919
0.5287 Remote Similarity NPC136042
0.5227 Remote Similarity NPC58716
0.5227 Remote Similarity NPC84362
0.5227 Remote Similarity NPC45638
0.5222 Remote Similarity NPC243930
0.5213 Remote Similarity NPC44931
0.52 Remote Similarity NPC234133
0.52 Remote Similarity NPC484301
0.5169 Remote Similarity NPC201292
0.5114 Remote Similarity NPC168822
0.5056 Remote Similarity NPC271692
0.5055 Remote Similarity NPC264735
0.5051 Remote Similarity NPC270675
0.5051 Remote Similarity NPC195685

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC606426 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
0.6585 Remote Similarity NPD4338 Clinical (unspecified phase)

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