Caffeine

2D Structure
3D Structure
Source:
General
Identifier MM00040
SMILES Cn1c(=O)c2c(ncn2C)n(C)c1=O
InChIKey RYYVLZVUVIJVGH-UHFFFAOYSA-N
MW [Da] 194.19

Automatically obtained from RDkit software.

LogP -1.03

Automatically obtained from RDkit software.

Links

PubChem

2519

DrugBank

DB00201

ChEBI

27732

PDB

CFF

ChEMBL

CHEMBL113

No data

Methods

Computed
Mechanistic
CPapp

Mechanistic model describing apparent permeabilities (Papp) based on different resistances solutes encounters when permeationg a cell monolayers. Moled is taking account a cytosolic, paracellular and lateral pathway with different resistances to a solute. The final Papp is than derived describing apparent cell permeability through Caco-2/MDCK cell monolayer at pH 7.4.

Q-based
CCM15

COSMOmic describes micelles or biomembranes as liquid layers. COSMOmic provides detailed information about the distribution of neutral and ionic species in micellar systems and biomembranes based on the structures obtained from molecular dynamics simulation of membranes and micelles. 

CCM18

COSMOmic describes micelles or biomembranes as liquid layers. COSMOmic provides detailed information about the distribution of neutral and ionic species in micellar systems and biomembranes based on the structures obtained from molecular dynamics simulation of membranes and micelles. COSMOperm adds fast calculation of diffusion profile, which in addition to free energy profile allows estimation of the membrane permeability. 

QSAR
CVOLSURF

A classical quantitative structure–activity relationship (QSAR) approach with simple physicochemical parameters and 3D-QSAR, VolSurf.

QSAR-HB

QSAR model for prediction of Human intestinal absorption (HIA) and permeability based H-bond donor/acceptor capacieties, Jurs term and Ghose-Crippen octanol-water partition coefficients. Validated on experimental CACO2 permeabilities.

QSAR-PSA

QSAR model for prediction of Human intestinal absorption (HIA) and permeability based on polar wan der Waals surface area (PSA) and MW. Validated on experimental CACO2 permeabilities. 

 

XLOGP3

XLOGP3 is a QSAR model for calculation of the logarithmic value of partition coefficient for octanol/water mixture. XLOGP3 has implemented an optimized atom typing scheme and is calibrated on a much larger training set. More importantly, based on the assumption that compounds with similar structures have similar properties, XLOGP3 introduces a new strategy by predicting logP value of a query compound based on the known logP value of a structural analog. 
It is widely used as a benchmark calculation of logP in PubChem. 

Experimental
Permeability
ECACO

Caco-2 is a well-established cell line derived from human colon carcinoma. Upon cultivation, the cells spontaneously differentiate into monolayers of polarised enterocytes. Caco-2 cells are widely used as an in vitro model for predicting human drug absorption. The permeability can be determined with LC-MS.

ECALU3

Calu-3 is a well-established cell line derived from human lung cancer cells (bronchial submucosal gland carcinoma). Upon cultivation, the cells spontaneously differentiate into adherent monolayers. Calu-2 cells are widely used as both in vitro and in vivo models for predicting human drug absorption and in drug development against lung cancer.

EFDC

One of the most common techniques for measuring absorption in vitro is the application of the test substance in an appropriate formulation (may be radiolabeled) to the surface of a membrane (skin, artificial membrane...), which is mounted as a barrier between the donor compartment and the receptor compartment of a diffusion cell. Diffusion cells may be of static or flow-through.

 Static diffusion cells sample this chamber and replace it with new perfusate at each time point. Flow-through cells use a pump to pass perfusate through the receptor chamber and collect flux by repeatedly collecting perfusate.


 

EMDCK

MDCK (Madin Darby Canine Kidney) permeability assay is one of drug absorption screening methods. Compared to Caco-2 cells, MDCK cells can form cell monolayer with tight junction much faster, with lower transporters expression and metabolic activities.

EPAM

Experimental method that allows to measure permeability from donor compartment through artificial membrane into an acceptor compartment. After an incubation period the membrane is separated and the amount of compound is measured in both compartments. Hence it is possible to calculate how much drug remained in the membrane.

EPAMOL

The molecular PAMPA describes intrinsic permeability for method PAMPA. 

Simulated
Atomistic MD
MDC36

CHARMM36 is an all atom (AA) force field for lipid simulation with redefined parameters for lipid headgroups (choline and ethanolamine) and both saturated and unsaturated lipid chains based on quantum mechanical and experimental data. Newly derived parameters were tested on fully hydrated bilayers. Parameters for sphingolipids were added.

No data

Hide empty columns:
Target
Uniprot ID
Type
pKm
pEC50
pKi
pIC50
Primary
reference
Secondary
reference
Note
ABCC2
Non-inhibitor
3.88

Morgan RE, van Staden CJ, Chen Y, Kalyanaraman N, Kalanzi J, Dunn RT, Afshari CA, Hamadeh HK.: A multifactorial approach to hepatobiliary transporter assessment enables improved therapeutic compound development. Toxicol Sci, Volume 136 (1), 2013

Morgan RE, van Staden CJ, Chen Y, Kalyanaraman N, Kalanzi J, Dunn RT, Afshari CA, Hamadeh HK.: A multifactorial approach to hepatobiliary transporter assessment enables improved therapeutic compound development. Toxicol Sci, Volume 136 (1), 2013

Zdrazil B, Felix E, Hunter F, Manners EJ, Blackshaw J, Corbett S, de Veij M, Ioannidis H, Lopez DM, Mosquera JF, Magarinos MP, Bosc N, Arcila R, Kizilören T, Gaulton A, Bento AP, Adasme MF, Monecke P, Landrum GA, Leach AR.: The ChEMBL Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods. Nucleic Acids Res, Volume 52 (d1), D1180-D1192, 2024

Zdrazil B, Felix E, Hunter F, Manners EJ, Blackshaw J, Corbett S, de Veij M, Ioannidis H, Lopez DM, Mosquera JF, Magarinos MP, Bosc N, Arcila R, Kizilören T, Gaulton A, Bento AP, Adasme MF, Monecke P, Landrum GA, Leach AR.: The ChEMBL Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods. Nucleic Acids Res, Volume 52 (d1), D1180-D1192, 2024

ABCC3
Non-inhibitor
3.88

Morgan RE, van Staden CJ, Chen Y, Kalyanaraman N, Kalanzi J, Dunn RT, Afshari CA, Hamadeh HK.: A multifactorial approach to hepatobiliary transporter assessment enables improved therapeutic compound development. Toxicol Sci, Volume 136 (1), 2013

Morgan RE, van Staden CJ, Chen Y, Kalyanaraman N, Kalanzi J, Dunn RT, Afshari CA, Hamadeh HK.: A multifactorial approach to hepatobiliary transporter assessment enables improved therapeutic compound development. Toxicol Sci, Volume 136 (1), 2013

Zdrazil B, Felix E, Hunter F, Manners EJ, Blackshaw J, Corbett S, de Veij M, Ioannidis H, Lopez DM, Mosquera JF, Magarinos MP, Bosc N, Arcila R, Kizilören T, Gaulton A, Bento AP, Adasme MF, Monecke P, Landrum GA, Leach AR.: The ChEMBL Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods. Nucleic Acids Res, Volume 52 (d1), D1180-D1192, 2024

Zdrazil B, Felix E, Hunter F, Manners EJ, Blackshaw J, Corbett S, de Veij M, Ioannidis H, Lopez DM, Mosquera JF, Magarinos MP, Bosc N, Arcila R, Kizilören T, Gaulton A, Bento AP, Adasme MF, Monecke P, Landrum GA, Leach AR.: The ChEMBL Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods. Nucleic Acids Res, Volume 52 (d1), D1180-D1192, 2024

ABCC4
Non-inhibitor
3.88

Morgan RE, van Staden CJ, Chen Y, Kalyanaraman N, Kalanzi J, Dunn RT, Afshari CA, Hamadeh HK.: A multifactorial approach to hepatobiliary transporter assessment enables improved therapeutic compound development. Toxicol Sci, Volume 136 (1), 2013

Morgan RE, van Staden CJ, Chen Y, Kalyanaraman N, Kalanzi J, Dunn RT, Afshari CA, Hamadeh HK.: A multifactorial approach to hepatobiliary transporter assessment enables improved therapeutic compound development. Toxicol Sci, Volume 136 (1), 2013

Zdrazil B, Felix E, Hunter F, Manners EJ, Blackshaw J, Corbett S, de Veij M, Ioannidis H, Lopez DM, Mosquera JF, Magarinos MP, Bosc N, Arcila R, Kizilören T, Gaulton A, Bento AP, Adasme MF, Monecke P, Landrum GA, Leach AR.: The ChEMBL Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods. Nucleic Acids Res, Volume 52 (d1), D1180-D1192, 2024

Zdrazil B, Felix E, Hunter F, Manners EJ, Blackshaw J, Corbett S, de Veij M, Ioannidis H, Lopez DM, Mosquera JF, Magarinos MP, Bosc N, Arcila R, Kizilören T, Gaulton A, Bento AP, Adasme MF, Monecke P, Landrum GA, Leach AR.: The ChEMBL Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods. Nucleic Acids Res, Volume 52 (d1), D1180-D1192, 2024