Natural Product: NPC606745

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 NPC606745 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 NPC171204
0.878 High Similarity NPC611318
0.7347 Intermediate Similarity NPC470755
0.7347 Intermediate Similarity NPC298801
0.7045 Intermediate Similarity NPC97516
0.66 Remote Similarity NPC481909
0.66 Remote Similarity NPC158756
0.66 Remote Similarity NPC601035
0.6226 Remote Similarity NPC469910
0.6222 Remote Similarity NPC58956
0.6222 Remote Similarity NPC163003
0.6222 Remote Similarity NPC295633
0.6222 Remote Similarity NPC269206
0.6182 Remote Similarity NPC481911
0.6122 Remote Similarity NPC476028
0.6122 Remote Similarity NPC270126
0.6038 Remote Similarity NPC605339
0.5849 Remote Similarity NPC281132
0.5636 Remote Similarity NPC131669
0.5625 Remote Similarity NPC167881
0.5625 Remote Similarity NPC98557
0.5577 Remote Similarity NPC151770
0.5577 Remote Similarity NPC250940
0.5577 Remote Similarity NPC165383
0.5577 Remote Similarity NPC169575
0.5556 Remote Similarity NPC266957
0.5556 Remote Similarity NPC482131
0.549 Remote Similarity NPC609300
0.549 Remote Similarity NPC610417
0.5472 Remote Similarity NPC473390
0.5472 Remote Similarity NPC194871
0.5472 Remote Similarity NPC488296
0.5455 Remote Similarity NPC482130
0.5455 Remote Similarity NPC482128
0.5455 Remote Similarity NPC482129
0.5385 Remote Similarity NPC470256
0.5385 Remote Similarity NPC50637
0.5385 Remote Similarity NPC476355
0.537 Remote Similarity NPC178702
0.5357 Remote Similarity NPC481806
0.5357 Remote Similarity NPC269509
0.5357 Remote Similarity NPC17585
0.5283 Remote Similarity NPC116177
0.5283 Remote Similarity NPC7563
0.5273 Remote Similarity NPC482126
0.5273 Remote Similarity NPC320630
0.5273 Remote Similarity NPC250315
0.5263 Remote Similarity NPC40746
0.52 Remote Similarity NPC140287
0.5179 Remote Similarity NPC307411
0.5172 Remote Similarity NPC134725
0.5172 Remote Similarity NPC48657
0.5172 Remote Similarity NPC483718
0.5098 Remote Similarity NPC301477
0.5098 Remote Similarity NPC25684
0.5098 Remote Similarity NPC488306
0.5094 Remote Similarity NPC600792
0.5094 Remote Similarity NPC610427
0.5091 Remote Similarity NPC473619
0.5091 Remote Similarity NPC272814
0.5088 Remote Similarity NPC482127

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC606745 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
NPD

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