Natural Product: NPC604870

Natural Product IDNPC604870
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
 HRYWITBPMMQCBB-UHFFFAOYSA-N
IUPAC Name n.a.
Synonyms
Synthetic Gene Cluster n.a.
ChEMBL Identifier CHEMBL3397397
PubChem CID n.a.
Chemical Classification
  • CHEMONTID:0000000 [Organic compounds]

The Chemical Classification was calculated by Classyfire, a software for chemical taxonomy calculation. Reference: DOI:10.1186/s13321-016-0174-y.

  Chemical Representations

Standard InCHIKey HRYWITBPMMQCBB-UHFFFAOYSA-N
Standard InCHI InChI=1S/C19H16O5/c1-19(2)4-3-14-17-11(7-15(22)18(14)24-19)8-16(23-17)10-5-12(20)9-13(21)6-10/h3-9,20-22H,1-2H3
SMILES CC1(C)C=Cc2c(c(O)cc3cc(-c4cc(O)cc(O)c4)oc23)O1

  Calculated Properties

Physi-Chem Properties

Molecular Weight:   324.1 Volume:   325.814
?
Van der Waals volume.
Dense:   0.995 LogP:   3.484
?
The logarithm of the n-octanol/water distribution coefficients.
logD7.4:   3.13
?
The logarithm of the n-octanol/water distribution coefficient at pH=7.4.
 LogS:   -3.778
?
The logarithm of aqueous solubility value.
Rotatable Bonds:   1.0 Rigid Bonds:   21.0
TPSA:   83.06
?
Topological Polar Surface Area.
 H-Bond Acceptor:   5.0
H-Bond Donor:   3.0 Rings:   4.0
Heavy Atoms:   5.0

MedChem Properties

QED Drug-Likeness Score:   0.618 GASA:   0.0
?
GASA represents the probability of being difficult to synthesize, ranging from 0 to 1.
Synthetic Accessibility Score:   3.084 Fsp3:   0.158
MCE-18:   50.182
?
MCE-18 stands for medicinal chemistry evolution.MCE-18≥45 is considered a suitable value.
 Lipinski Rule-of-5:   Rejected
Pfizer Rule:   Rejected GSK Rule:   Rejected
Golden Triangle Rule:   Rejected BMS Rule:   0
Chelating Alert:   1 PAINS Alert:   0
Colloidal aggregators:   0.857 Fluc inhibitor:   0.735
?
The fluc inhibitor value is the probability of being fLuc inhibitors, within the range of 0 to 1.
Blue fluorescence:   0.984
?
The blue fluorescence value is the probability of being blue fluorescence, within the range of 0 to 1
 Green fluorescence:   0.833
?
The green fluorescence value is the probability of being green fluorescence, within the range of 0 to 1
Reactive compounds:   0.481 Promiscuous compounds:   0.212

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

Caco-2 Permeability:   -5.017 MDCK Permeability:   -4.754
Pgp-inhibitor:   0.006 Pgp-substrate:   0.104
PAMPA:   0.53
?
The experimental data for Peff was logarithmically transformed (logPeff). Molecules with log Peff values below 2.0 were classified as low-permeability (Category 0), while those with log Peff values exceeding 2.5 were classified as high-permeability (Category 1).
 Human Intestinal Absorption (HIA):   0.002
20% Bioavailability (F20%):   0.679 30% Bioavailability (F30%):   0.863
50% Bioavailability (F50%):   0.991

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):   0.125 MRP1:   0.735
Plasma Protein Binding (PPB):   95.083% Volume Distribution (VD):   0.028
Fu: 5.289%
?
The fraction unbound in plasms.
 OATP1B1 inhibitor:   0.946
OATP1B3 inhibitor:   0.923 BCRP inhibitor:   0.395
BSEP inhibitor:   0.44

ADMET: Metabolism

CYP1A2-inhibitor:   0.005 CYP1A2-substrate:   0.941
CYP2C19-inhibitor:   0.008 CYP2C19-substrate:   0.649
CYP2C9-inhibitor:   0.901 CYP2C9-substrate:   0.027
CYP2D6-inhibitor:   0.245 CYP2D6-substrate:   0.946
CYP3A4-inhibitor:   0.0 CYP3A4-substrate:   0.991
CYP2B6-substrate:   0.0 CYP2C8-inhibitor:   0.999
HLM stability:   0.973
?
Human liver microsomal (HLM) stability. Category 0: stable+ (HLM > 30 min); Category 1: unstable- (HLM ≤ 30 min). The output value is the probability of human liver microsomal instability, where a value closer to 1 indicates a higher likelihood of instability.

ADMET: Excretion

Clearance (CL):  5.847 Half-life (T1/2):  1.63

ADMET: Toxicity

hERG Blockers:  0.147 hERG Blockers (10um):  0.573
Human Hepatotoxicity (H-HT):  0.484 Drug-induced Liver Injury (DILI):  0.495
AMES Toxicity:  0.558 Rat Oral Acute Toxicity:  0.534
Maximum Recommended Daily Dose:  0.794 Skin Sensitization:  0.81
Carcinogencity:  0.83 Eye Corrosion:  0.174
Eye Irritation:  0.994 Respiratory Toxicity:  0.781
Drug-induced Neurotoxicity:  0.131 Ototoxicity:  0.156
Hematotoxicity:  0.062 Drug-induced Nephrotoxicity:  0.048
Genotoxicity:  0.855 RPMI-8226 Immunitoxicity:  0.057
A549 Cytotoxicity:  0.203 Hek293 Cytotoxicity:  0.753
BCF:   1.596
?
Bioconcentration factors are used for considering secondary poisoning potential and assessing risks to human health via the food chain. The unit is -log10[(mg/L)/(1000*MW)].
 IGC50:   4.265
?
48 hour Tetrahymena pyriformis IGC50. The unit of IGC50 is -log10[(mg/L)/(1000*MW)].
LC50DM:   5.621
?
48 hour Daphnia magna LC50. The unit of LC50DM is -log10[(mg/L)/(1000*MW)].
 LC50FM:   5.102
?
96 hour fathead minnow LC50. The unit of LC50FM is -log10[(mg/L)/(1000*MW)].

  Species Source

Organism ID Organism Name Taxonomy Level Family SuperKingdom Isolation Part Collection Location Collection Time Reference
NPO28265 Morus alba Species Moraceae Eukaryota n.a. n.a. n.a. PMID[20815207]
NPO28265 Morus alba Species Moraceae Eukaryota n.a. bark n.a. PMID[21319773]
NPO28265 Morus alba Species Moraceae Eukaryota n.a. root n.a. PMID[21319773]
NPO28265 Morus alba Species Moraceae Eukaryota n.a. leaf n.a. PMID[21319773]
NPO28265 Morus alba Species Moraceae Eukaryota n.a. leaf n.a. PMID[22207282]
NPO28265 Morus alba Species Moraceae Eukaryota n.a. root n.a. PMID[23806866]
NPO28265 Morus alba Species Moraceae Eukaryota root bark University of Veterinary and Pharmaceutical Sciences Brno (UVPS Brno), Brno, Czech Republic 2011-APR PMID[24901948]
NPO28265 Morus alba Species Moraceae Eukaryota n.a. Konya, Turkey 2007-APR PMID[24901948]
NPO28265 Morus alba Species Moraceae Eukaryota leaves Chungbuk, Korea n.a. PMID[25935644]
NPO28265 Morus alba Species Moraceae Eukaryota n.a. root n.a. PMID[25981820]
NPO28265 Morus alba Species Moraceae Eukaryota n.a. latex n.a. PMID[27294120]
NPO28265 Morus alba Species Moraceae Eukaryota Root barks n.a. n.a. PMID[3097265]
NPO40890 Morus sp. Species Sulidae Eukaryota Leaves n.a. n.a. PMID[31393724]
NPO40890 Morus sp. Species Sulidae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO28265 Morus alba Species Moraceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO28265 Morus alba Species Moraceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO28265 Morus alba Species Moraceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO28265 Morus alba Species Moraceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO28265 Morus alba Species Moraceae Eukaryota n.a. n.a. n.a. Database[TM-MC]
NPO28265 Morus alba Species Moraceae Eukaryota n.a. n.a. n.a. Database[UNPD]

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
NPT173 Organism Klebsiella pneumoniae Klebsiella pneumoniae MIC > 100.0 ug.mL-1 PMID[25461329]
NPT19 Organism Escherichia coli Escherichia coli MIC > 100.0 ug.mL-1 PMID[25461329]
NPT18 Organism Pseudomonas aeruginosa Pseudomonas aeruginosa MIC > 100.0 ug.mL-1 PMID[25461329]

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 NPC604870 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
0.6 Remote Similarity NPC472462
0.5821 Remote Similarity NPC603014
0.5672 Remote Similarity NPC259456
0.5556 Remote Similarity NPC236419
0.5362 Remote Similarity NPC482696
0.5161 Remote Similarity NPC604684

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC604870 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