Natural Product: NPC93297

Natural Product IDNPC93297
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
 ZLQADKTVJQXDIG-UHFFFAOYSA-N
IUPAC Name n.a.
Synonyms
Synthetic Gene Cluster n.a.
ChEMBL Identifier n.a.
PubChem CID 527157
Chemical Classification
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000012] Lipids and lipid-like molecules
      • [CHEMONTID:0000259] Prenol lipids
        • [CHEMONTID:0001550] Sesquiterpenoids
          • [CHEMONTID:0002051] Agarofurans

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 ZLQADKTVJQXDIG-UHFFFAOYSA-N
Standard InCHI InChI=1S/C15H24O/c1-11-6-5-8-14(4)9-7-12-10-15(11,14)16-13(12,2)3/h6,12H,5,7-10H2,1-4H3
SMILES CC1=CCCC2(C)CCC3CC12OC3(C)C

  Calculated Properties

Physi-Chem Properties

Molecular Weight:   220.18 Volume:   248.481
?
Van der Waals volume.
Dense:   0.886 LogP:   3.223
?
The logarithm of the n-octanol/water distribution coefficients.
logD7.4:   2.835
?
The logarithm of the n-octanol/water distribution coefficient at pH=7.4.
 LogS:   -2.716
?
The logarithm of aqueous solubility value.
Rotatable Bonds:   0.0 Rigid Bonds:   14.0
TPSA:   9.23
?
Topological Polar Surface Area.
 H-Bond Acceptor:   1.0
H-Bond Donor:   0.0 Rings:   3.0
Heavy Atoms:   1.0

MedChem Properties

QED Drug-Likeness Score:   0.559 GASA:   1.0
?
GASA represents the probability of being difficult to synthesize, ranging from 0 to 1.
Synthetic Accessibility Score:   5.57 Fsp3:   0.867
MCE-18:   72.857
?
MCE-18 stands for medicinal chemistry evolution.MCE-18≥45 is considered a suitable value.
 Lipinski Rule-of-5:   Rejected
Pfizer Rule:   Accepted GSK Rule:   Rejected
Golden Triangle Rule:   Rejected BMS Rule:   0
Chelating Alert:   0 PAINS Alert:   0
Colloidal aggregators:   0.068 Fluc inhibitor:   0.0
?
The fluc inhibitor value is the probability of being fLuc inhibitors, within the range of 0 to 1.
Blue fluorescence:   0.003
?
The blue fluorescence value is the probability of being blue fluorescence, within the range of 0 to 1
 Green fluorescence:   0.014
?
The green fluorescence value is the probability of being green fluorescence, within the range of 0 to 1
Reactive compounds:   0.928 Promiscuous compounds:   0.092

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

Caco-2 Permeability:   -4.531 MDCK Permeability:   -4.667
Pgp-inhibitor:   0.887 Pgp-substrate:   0.009
PAMPA:   0.033
?
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):   0.005
20% Bioavailability (F20%):   0.144 30% Bioavailability (F30%):   0.294
50% Bioavailability (F50%):   0.807

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):   0.944 MRP1:   0.936
Plasma Protein Binding (PPB):   90.389% Volume Distribution (VD):   0.58
Fu: 8.895%
?
The fraction unbound in plasms.
 OATP1B1 inhibitor:   0.968
OATP1B3 inhibitor:   0.853 BCRP inhibitor:   0.2
BSEP inhibitor:   0.985

ADMET: Metabolism

CYP1A2-inhibitor:   0.367 CYP1A2-substrate:   0.944
CYP2C19-inhibitor:   0.89 CYP2C19-substrate:   0.483
CYP2C9-inhibitor:   0.888 CYP2C9-substrate:   0.139
CYP2D6-inhibitor:   0.978 CYP2D6-substrate:   0.058
CYP3A4-inhibitor:   0.009 CYP3A4-substrate:   0.952
CYP2B6-substrate:   0.963 CYP2C8-inhibitor:   0.637
HLM stability:   0.962
?
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):  10.198 Half-life (T1/2):  0.699

ADMET: Toxicity

hERG Blockers:  0.061 hERG Blockers (10um):  0.438
Human Hepatotoxicity (H-HT):  0.373 Drug-induced Liver Injury (DILI):  0.326
AMES Toxicity:  0.341 Rat Oral Acute Toxicity:  0.371
Maximum Recommended Daily Dose:  0.323 Skin Sensitization:  0.818
Carcinogencity:  0.464 Eye Corrosion:  0.748
Eye Irritation:  0.943 Respiratory Toxicity:  0.589
Drug-induced Neurotoxicity:  0.475 Ototoxicity:  0.3
Hematotoxicity:  0.23 Drug-induced Nephrotoxicity:  0.101
Genotoxicity:  0.073 RPMI-8226 Immunitoxicity:  0.041
A549 Cytotoxicity:  0.112 Hek293 Cytotoxicity:  0.175
BCF:   2.804
?
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:   4.457
?
48 hour Tetrahymena pyriformis IGC50. The unit of IGC50 is -log10[(mg/L)/(1000*MW)].
LC50DM:   5.173
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48 hour Daphnia magna LC50. The unit of LC50DM is -log10[(mg/L)/(1000*MW)].
 LC50FM:   5.242
?
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
NPO14558 Aquilaria sinensis Species Thymelaeaceae Eukaryota n.a. n.a. n.a. PMID[27128895]
NPO14558 Aquilaria sinensis Species Thymelaeaceae Eukaryota Resinous Wood n.a. n.a. PMID[29227647]
NPO14558 Aquilaria sinensis Species Thymelaeaceae Eukaryota n.a. n.a. n.a. PMID[38792158]
NPO14558 Aquilaria sinensis Species Thymelaeaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO12265 Aquilaria agallochum Species Thymelaeaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO14558 Aquilaria sinensis Species Thymelaeaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO14558 Aquilaria sinensis Species Thymelaeaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO12265 Aquilaria agallochum Species Thymelaeaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO14558 Aquilaria sinensis Species Thymelaeaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO14558 Aquilaria sinensis Species Thymelaeaceae Eukaryota n.a. n.a. n.a. Database[TM-MC]
NPO12265 Aquilaria agallochum Species Thymelaeaceae Eukaryota n.a. n.a. n.a. Database[TM-MC]
NPO12265 Aquilaria agallochum Species Thymelaeaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO14558 Aquilaria sinensis Species Thymelaeaceae 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

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 NPC93297 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
NPC

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC93297 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