Structure

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Physi-Chem Properties

Molecular Weight:  386.93
Volume:  256.382
LogP:  1.323
LogD:  1.454
LogS:  -2.743
# Rotatable Bonds:  0
TPSA:  75.65
# H-Bond Aceptor:  6
# H-Bond Donor:  3
# Rings:  4
# Heavy Atoms:  8

MedChem Properties

QED Drug-Likeness Score:  0.704
Synthetic Accessibility Score:  4.922
Fsp3:  0.455
Lipinski Rule-of-5:  Accepted
Pfizer Rule:  Accepted
GSK Rule:  Accepted
BMS Rule:  0
Golden Triangle Rule:  Accepted
Chelating Alert:  0
PAINS Alert:  0

ADMET Properties (ADMETlab2.0)

ADMET: Absorption

Caco-2 Permeability:  -5.216
MDCK Permeability:  1.812471600715071e-05
Pgp-inhibitor:  0.001
Pgp-substrate:  0.024
Human Intestinal Absorption (HIA):  0.253
20% Bioavailability (F20%):  0.044
30% Bioavailability (F30%):  0.355

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.614
Plasma Protein Binding (PPB):  80.74636840820312%
Volume Distribution (VD):  0.892
Pgp-substrate:  30.17064666748047%

ADMET: Metabolism

CYP1A2-inhibitor:  0.369
CYP1A2-substrate:  0.447
CYP2C19-inhibitor:  0.488
CYP2C19-substrate:  0.121
CYP2C9-inhibitor:  0.435
CYP2C9-substrate:  0.254
CYP2D6-inhibitor:  0.438
CYP2D6-substrate:  0.283
CYP3A4-inhibitor:  0.824
CYP3A4-substrate:  0.368

ADMET: Excretion

Clearance (CL):  3.237
Half-life (T1/2):  0.736

ADMET: Toxicity

hERG Blockers:  0.006
Human Hepatotoxicity (H-HT):  0.131
Drug-inuced Liver Injury (DILI):  0.802
AMES Toxicity:  0.411
Rat Oral Acute Toxicity:  0.996
Maximum Recommended Daily Dose:  0.926
Skin Sensitization:  0.34
Carcinogencity:  0.982
Eye Corrosion:  0.003
Eye Irritation:  0.015
Respiratory Toxicity:  0.875

Download Data

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

  Natural Product: NPC28096

Natural Product ID:  NPC28096
Common Name*:   Dibromophakellin
IUPAC Name:   n.a.
Synonyms:   (+/-)-Dibromophakellin; (-)-Dibromophakellin; Dibromophakellin
Standard InCHIKey:  MKCFBJDWCJAOTN-GXSJLCMTSA-N
Standard InCHI:  InChI=1S/C11H11Br2N5O/c12-5-4-6-8(19)17-3-1-2-11(17)9(15-10(14)16-11)18(6)7(5)13/h4,9H,1-3H2,(H3,14,15,16)/t9-,11+/m0/s1
SMILES:  N=C1N[C@@H]2[C@@]3(N1)CCCN3C(=O)c1n2c(Br)c(c1)Br
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   CHEMBL447696
PubChem CID:   42636938
11417878
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000264] Organic acids and derivatives
      • [CHEMONTID:0000265] Carboxylic acids and derivatives
        • [CHEMONTID:0001093] Carboxylic acid derivatives
          • [CHEMONTID:0000475] Carboxylic acid amides
            • [CHEMONTID:0004817] 2-heteroaryl carboxamides

*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

☑ 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

☑ 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

☑ 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 NPC28096 and all remaining natural products in the NPASS database.
●  The right table: Most similar natural products (Tc>=0.56 or Top200).

  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 NPC28096 and all drugs/candidates.
●  The right table: Most similar clinical/approved drugs (Tc>=0.56 or Top200).

  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