Structure

Physi-Chem Properties

Molecular Weight:  718.23
Volume:  664.985
LogP:  -0.75
LogD:  -0.537
LogS:  -1.738
# Rotatable Bonds:  17
TPSA:  305.73
# H-Bond Aceptor:  19
# H-Bond Donor:  9
# Rings:  3
# Heavy Atoms:  19

MedChem Properties

QED Drug-Likeness Score:  0.071
Synthetic Accessibility Score:  5.288
Fsp3:  0.613
Lipinski Rule-of-5:  Rejected
Pfizer Rule:  Accepted
GSK Rule:  Rejected
BMS Rule:  1
Golden Triangle Rule:  Rejected
Chelating Alert:  1
PAINS Alert:  0

ADMET Properties (ADMETlab2.0)

ADMET: Absorption

Caco-2 Permeability:  -6.612
MDCK Permeability:  0.00015748896112199873
Pgp-inhibitor:  0.0
Pgp-substrate:  1.0
Human Intestinal Absorption (HIA):  0.931
20% Bioavailability (F20%):  0.926
30% Bioavailability (F30%):  1.0

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.22
Plasma Protein Binding (PPB):  30.67522621154785%
Volume Distribution (VD):  0.3
Pgp-substrate:  32.39324188232422%

ADMET: Metabolism

CYP1A2-inhibitor:  0.007
CYP1A2-substrate:  0.046
CYP2C19-inhibitor:  0.004
CYP2C19-substrate:  0.048
CYP2C9-inhibitor:  0.0
CYP2C9-substrate:  0.238
CYP2D6-inhibitor:  0.002
CYP2D6-substrate:  0.065
CYP3A4-inhibitor:  0.037
CYP3A4-substrate:  0.004

ADMET: Excretion

Clearance (CL):  1.493
Half-life (T1/2):  0.911

ADMET: Toxicity

hERG Blockers:  0.088
Human Hepatotoxicity (H-HT):  0.578
Drug-inuced Liver Injury (DILI):  0.87
AMES Toxicity:  0.048
Rat Oral Acute Toxicity:  0.001
Maximum Recommended Daily Dose:  0.327
Skin Sensitization:  0.026
Carcinogencity:  0.018
Eye Corrosion:  0.003
Eye Irritation:  0.007
Respiratory Toxicity:  0.01

Download Data

Data Type Select
General Info & Identifiers & Properties  
Structure MOL file  
Source Organisms  
Biological Activities  
Similar NPs/Drugs  

  Natural Product: NPC276493

Natural Product ID:  NPC276493
Common Name*:   DVXSAERWIRPNNF-KOOVRBLHSA-N
IUPAC Name:   n.a.
Synonyms:  
Standard InCHIKey:  DVXSAERWIRPNNF-KOOVRBLHSA-N
Standard InCHI:  InChI=1S/C45H61N7O8/c1-5-28(4)38-42(57)46-32(25-29-12-7-6-8-13-29)39(54)35-14-9-23-52(35)45(60)48-33(24-27(2)3)43(58)50-21-10-15-36(50)40(55)47-34(26-30-17-19-31(53)20-18-30)44(59)51-22-11-16-37(51)41(56)49-38/h6-8,12-13,17-20,27-28,32-38,53H,5,9-11,14-16,21-26H2,1-4H3,(H,46,57)(H,47,55)(H,48,60)(H,49,56)/t28-,32-,33-,34-,35-,36-,37-,38-/m0/s1
SMILES:  CC[C@H](C)[C@H]1C(=N[C@@H](Cc2ccccc2)C(=O)[C@@H]2CCCN2C(=N[C@@H](CC(C)C)C(=O)N2CCC[C@H]2C(=N[C@@H](Cc2ccc(cc2)O)C(=O)N2CCC[C@H]2C(=N1)O)O)O)O
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   n.a.
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000264] Organic acids and derivatives
      • [CHEMONTID:0000265] Carboxylic acids and derivatives
        • [CHEMONTID:0000013] Amino acids, peptides, and analogues
          • [CHEMONTID:0000348] Peptides
            • [CHEMONTID:0001995] Cyclic peptides

*Note: the InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
**Note: the Chemical Classification was calculated by NPClassifier Version 1.5. Reference: PMID:34662515.

  Species Source

Organism ID Organism Name Taxonomy Level Family SuperKingdom Isolation Part Collection Location Collection Time Reference
NPO17228 Streptosporangium sibiricum Species Streptosporangiaceae Bacteria n.a. n.a. n.a. PMID[21612226]
NPO17228 Streptosporangium sibiricum Species Streptosporangiaceae Bacteria n.a. n.a. n.a. PMID[25960001]
NPO10821 Magnolia praecocissima Species Magnoliaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO13082 Veratrum californicum Species Melanthiaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO10821 Magnolia praecocissima Species Magnoliaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO13082 Veratrum californicum Species Melanthiaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO13082 Veratrum californicum Species Melanthiaceae Eukaryota n.a. n.a. n.a. Database[TCM_Taiwan]
NPO16568 Vernonia cotoneaster Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO17379 Lepidium syvaschicum Species Brassicaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO17927 Streptomyces thioluteus Species Streptomycetaceae Bacteria n.a. n.a. n.a. Database[UNPD]
NPO17228 Streptosporangium sibiricum Species Streptosporangiaceae Bacteria n.a. n.a. n.a. Database[UNPD]
NPO5061 Rhaphiolepis indica Species Rosaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO11624 Didymella lethalis Species Didymellaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO13082 Veratrum californicum Species Melanthiaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO261 Sulfurospirillum multivorans Species Campylobacteraceae Bacteria n.a. n.a. n.a. Database[UNPD]
NPO10821 Magnolia praecocissima Species Magnoliaceae 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 NP ID 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

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference

☑ Note for Activity Records:
☉ The quantitative biological activities were primarily integrated from ChEMBL (Version-30) database and were also directly collected from PubMed literature. PubMed PMID was provided as the reference link for each activity record.

  Chemically structural similarity: I. Similar Active Natural Products in NPASS

Top-200 similar NPs were calculated against the active-NP-set (includes 4,3285 NPs with experimentally-derived bioactivity available in NPASS)

Similarity level is defined by Tanimoto coefficient (Tc) between two molecules. Tc lies between [0, 1] where '1' indicates the highest similarity. What is Tanimoto coefficient

●  The left chart: Distribution of similarity level between NPC276493 and all remaining natural products in the NPASS database.
●  The right table: Most similar natural products (Tc>=0.56 or Top200).

Similarity Score Similarity Level Natural Product ID

  Chemically structural similarity: II. Similar Clinical/Approved Drugs

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

●  The left chart: Distribution of similarity level between NPC276493 and all drugs/candidates.
●  The right table: Most similar clinical/approved drugs (Tc>=0.56 or Top200).

Similarity Score Similarity Level Drug ID Developmental Stage

  Bioactivity similarity: Similar Natural Products in NPASS

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