Natural Product: NPC16970

Natural Product IDNPC16970
Common Name
?
The InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
NKYKOCKNAQIWRZ-QKYHNZPSSA-N
IUPAC Name n.a.
Synonyms
Synthetic Gene Cluster n.a.
ChEMBL Identifier n.a.
PubChem CID 124079396
Chemical Classification
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000012] Lipids and lipid-like molecules
      • [CHEMONTID:0000259] Prenol lipids
        • [CHEMONTID:0002049] Terpene glycosides

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 NKYKOCKNAQIWRZ-QKYHNZPSSA-N
Standard InCHI InChI=1S/C30H32O15/c1-28-10-18(33)15-9-30(28,29(15,27(40)45-28)12-42-24(38)13-5-3-2-4-6-13)44-26-23(37)22(36)21(35)19(43-26)11-41-25(39)14-7-16(31)20(34)17(32)8-14/h2-8,15,18-19,21-23,26,31-37H,9-12H2,1H3/t15-,18+,19+,21+,22-,23+,26-,28-,29-,30-/m0/s1
SMILES C[C@]12C[C@H]([C@@H]3C[C@]1([C@]3(COC(=O)c1ccccc1)C(=O)O2)O[C@H]1[C@@H]([C@H]([C@@H]([C@@H](COC(=O)c2cc(c(c(c2)O)O)O)O1)O)O)O)O

  Calculated Properties

Physi-Chem Properties

Molecular Weight:   632.17 Volume:   584.223
?
Van der Waals volume.
Dense:   1.082 LogP:   0.994
?
The logarithm of the n-octanol/water distribution coefficients.
logD7.4:   1.342
?
The logarithm of the n-octanol/water distribution coefficient at pH=7.4.
LogS:   -2.732
?
The logarithm of aqueous solubility value.
Rotatable Bonds:   10.0 Rigid Bonds:   32.0
TPSA:   238.97
?
Topological Polar Surface Area.
H-Bond Acceptor:   15.0
H-Bond Donor:   7.0 Rings:   7.0
Heavy Atoms:   15.0

MedChem Properties

QED Drug-Likeness Score:   0.11 GASA:   1.0
?
GASA represents the probability of being difficult to synthesize, ranging from 0 to 1.
Synthetic Accessibility Score:   6.049 Fsp3:   0.5
MCE-18:   148.4
?
MCE-18 stands for medicinal chemistry evolution.MCE-18≥45 is considered a suitable value.
Lipinski Rule-of-5:   Accepted
Pfizer Rule:   Rejected GSK Rule:   Accepted
Golden Triangle Rule:   Accepted BMS Rule:   0
Chelating Alert:   1 PAINS Alert:   1
Colloidal aggregators:   0.693 Fluc inhibitor:   0.256
?
The fluc inhibitor value is the probability of being fLuc inhibitors, within the range of 0 to 1.
Blue fluorescence:   0.074
?
The blue fluorescence value is the probability of being blue fluorescence, within the range of 0 to 1
Green fluorescence:   0.334
?
The green fluorescence value is the probability of being green fluorescence, within the range of 0 to 1
Reactive compounds:   0.05 Promiscuous compounds:   0.123

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

Caco-2 Permeability:   -6.325 MDCK Permeability:   -5.409
Pgp-inhibitor:   0.002 Pgp-substrate:   0.014
PAMPA:   0.974
?
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):   0.0
20% Bioavailability (F20%):   0.64 30% Bioavailability (F30%):   0.918
50% Bioavailability (F50%):   0.998

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):   0.138 MRP1:   1.0
Plasma Protein Binding (PPB):   74.026% Volume Distribution (VD):   -0.635
Fu: 29.856%
?
The fraction unbound in plasms.
OATP1B1 inhibitor:   1.0
OATP1B3 inhibitor:   1.0 BCRP inhibitor:   0.259
BSEP inhibitor:   0.113

ADMET: Metabolism

CYP1A2-inhibitor:   0.0 CYP1A2-substrate:   0.0
CYP2C19-inhibitor:   0.0 CYP2C19-substrate:   0.143
CYP2C9-inhibitor:   0.0 CYP2C9-substrate:   0.0
CYP2D6-inhibitor:   0.0 CYP2D6-substrate:   0.148
CYP3A4-inhibitor:   0.0 CYP3A4-substrate:   0.903
CYP2B6-substrate:   0.0 CYP2C8-inhibitor:   1.0
HLM stability:   0.945
?
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):  2.516 Half-life (T1/2):  3.498

ADMET: Toxicity

hERG Blockers:  0.038 hERG Blockers (10um):  0.647
Human Hepatotoxicity (H-HT):  0.028 Drug-induced Liver Injury (DILI):  0.73
AMES Toxicity:  0.812 Rat Oral Acute Toxicity:  0.008
Maximum Recommended Daily Dose:  0.511 Skin Sensitization:  1.0
Carcinogencity:  0.544 Eye Corrosion:  0.0
Eye Irritation:  0.031 Respiratory Toxicity:  0.006
Drug-induced Neurotoxicity:  0.002 Ototoxicity:  0.986
Hematotoxicity:  0.004 Drug-induced Nephrotoxicity:  0.109
Genotoxicity:  0.551 RPMI-8226 Immunitoxicity:  0.021
A549 Cytotoxicity:  0.974 Hek293 Cytotoxicity:  0.445
BCF:   0.559
?
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:   3.487
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48 hour Tetrahymena pyriformis IGC50. The unit of IGC50 is -log10[(mg/L)/(1000*MW)].
LC50DM:   5.107
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48 hour Daphnia magna LC50. The unit of LC50DM is -log10[(mg/L)/(1000*MW)].
LC50FM:   4.509
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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
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Seeds Henan province, China DOI[10.1016/j.foodres.2020.109416]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Seeds Gansu province, China DOI[10.1016/j.foodres.2020.109416]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Seeds Anhui province, China DOI[10.1016/j.foodres.2020.109416]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Seeds Shanxi province, China DOI[10.1016/j.foodres.2020.109416]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Seeds Shandong province, China DOI[10.1016/j.foodres.2020.109416]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. DOI[10.2174/092986712800229032]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. n.a. n.a. PMID[19402674]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. PMID[19721258]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. PMID[19772486]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Roots n.a. n.a. PMID[20806783]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. PMID[21782011]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. PMID[22190295]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. seed n.a. PMID[23497864]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. PMID[26838074]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. PMID[27313650]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. root n.a. PMID[27429639]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Roots n.a. n.a. PMID[29741372]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Seeds HeZe, ShanDong, China early autumn (from August to the beginning of September PMID[32545196]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Roots n.a. n.a. PMID[32951423]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota Seeds Xinjiang,China PMID[33063333]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. n.a. n.a. Database[COCONUT]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO9798 Paeonia lactiflora Species Paeoniaceae Eukaryota n.a. n.a. n.a. Database[TM-MC]
NPO9798 Paeonia lactiflora Species Paeoniaceae 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 NPC16970 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
0.8816 High Similarity NPC469399
0.7407 Intermediate Similarity NPC133430
0.716 Intermediate Similarity NPC478832
0.6813 Remote Similarity NPC469418
0.6559 Remote Similarity NPC80360
0.6489 Remote Similarity NPC260300
0.5979 Remote Similarity NPC195114
0.5824 Remote Similarity NPC469417
0.5789 Remote Similarity NPC469419
0.5714 Remote Similarity NPC469448
0.567 Remote Similarity NPC469396
0.567 Remote Similarity NPC469458
0.567 Remote Similarity NPC149002
0.5652 Remote Similarity NPC469477
0.5591 Remote Similarity NPC34066
0.5591 Remote Similarity NPC190862
0.5532 Remote Similarity NPC469422
0.5258 Remote Similarity NPC88176
0.5253 Remote Similarity NPC469420
0.5238 Remote Similarity NPC188217
0.519 Remote Similarity NPC92117
0.5165 Remote Similarity NPC476017
0.5165 Remote Similarity NPC478831
0.505 Remote Similarity NPC469398

Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC16970 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