Natural Product: NPC603601

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 NPC603601 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
0.9245 High Similarity NPC606965
0.8909 High Similarity NPC488235
0.8727 High Similarity NPC600724
0.8276 Intermediate Similarity NPC473204
0.7101 Intermediate Similarity NPC162569
0.7101 Intermediate Similarity NPC35160
0.7 Intermediate Similarity NPC171598
0.6957 Remote Similarity NPC473399
0.6957 Remote Similarity NPC473216
0.6935 Remote Similarity NPC488236
0.6557 Remote Similarity NPC472189
0.6508 Remote Similarity NPC88507
0.6508 Remote Similarity NPC318917
0.6508 Remote Similarity NPC481019
0.6508 Remote Similarity NPC602188
0.6364 Remote Similarity NPC473545
0.6308 Remote Similarity NPC471366
0.6308 Remote Similarity NPC476800
0.6308 Remote Similarity NPC488649
0.6308 Remote Similarity NPC488237
0.625 Remote Similarity NPC471362
0.625 Remote Similarity NPC471372
0.6212 Remote Similarity NPC201880
0.6212 Remote Similarity NPC311166
0.6212 Remote Similarity NPC81567
0.6212 Remote Similarity NPC488652
0.619 Remote Similarity NPC481018
0.6154 Remote Similarity NPC472186
0.6094 Remote Similarity NPC481020
0.6 Remote Similarity NPC488659
0.6 Remote Similarity NPC604149
0.597 Remote Similarity NPC316974
0.597 Remote Similarity NPC481017
0.597 Remote Similarity NPC329623
0.597 Remote Similarity NPC609711
0.5942 Remote Similarity NPC488964
0.5942 Remote Similarity NPC184512
0.5909 Remote Similarity NPC472188
0.5882 Remote Similarity NPC330003
0.5882 Remote Similarity NPC470321
0.5882 Remote Similarity NPC264867
0.5882 Remote Similarity NPC473207
0.5882 Remote Similarity NPC609715
0.5738 Remote Similarity NPC609097
0.5735 Remote Similarity NPC311223
0.5735 Remote Similarity NPC134270
0.5735 Remote Similarity NPC488654
0.5714 Remote Similarity NPC472187
0.5526 Remote Similarity NPC230331
0.5526 Remote Similarity NPC470024
0.5507 Remote Similarity NPC488660
0.5507 Remote Similarity NPC488657
0.5507 Remote Similarity NPC609880
0.5493 Remote Similarity NPC252296
0.5441 Remote Similarity NPC488653
0.5429 Remote Similarity NPC488658
0.5429 Remote Similarity NPC488655
0.5352 Remote Similarity NPC48548
0.5325 Remote Similarity NPC267469
0.5217 Remote Similarity NPC488656
0.5205 Remote Similarity NPC119550
0.5125 Remote Similarity NPC486755
0.507 Remote Similarity NPC479491
0.5063 Remote Similarity NPC109376

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC603601 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