Our Offer

Our offer is based on SAFAN-ISP (In Silico Profiling), our proprietary technology that:

  • finds new targets for your molecule
  • finds potential off-targets
  • elucidates the biological mechanism of your compound
  • helps planning your future experiments.

Our fragment based predictions allow you to:

  • patent new compounds
  • get information comparable to lab experiments at lower cost. 

Starting from the structure of a list of compounds or peptides, we deliver the binding affinities for protein targets.

  • We connect the specific interaction with:
    • Disease database for repositioning opportunities
    • Side Effect database for toxicology predictions

Here you can find an example of the computational profiling output.

Here is a slides deck describing our approach and its validation.

We have an ongoing partnership with Humana Biosciences to perform experimental validation of our computational results.

Virtual Screening

In the Virtual Screening process a library of compounds is screened against one single protein target to find the compounds most likely to bind with it.

Protein Target

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SMALL MOLECULES DATABASE

Profiling

The profiling process starts from a single small molecule or peptide and screens a protein target library to find the  protein that most likely will bind it

Small Molecule
Peptite

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PROTEIN TARGETS DATABASE

Our platform comes in two specialized variations: SAFAN-ISPSM for small molecules and SAFAN-ISPPEPT for peptides. They quickly and efficiently profile their compound, calculating the binding affinities between each ligand and more than 4500 targets from 15 different protein classes. They rely on our proprietary algorithm to forecast affinities through fragments weight assignment using a ligand-based approach. We work with a refactored bioactivity database derived from the CHEMBL25 database.

Compounds: SAFAN-ISPSM

Peptides: SAFAN-ISPPEPT

  • You can get a selection of SAFAN-ISPSM profiles ready to download concerning:
    • 9488 from DrugBank
    • 26510 from FooDB
    • 75000 Natural
  • Or we can profile your proprietary small molecule libraries.

Peptide-protein interactions play a critical role in the protein-protein interaction network with significant involvement in signal transduction and regulation. Many of these interactions are promising candidates as new leads for drug targets. However,

  • Peptides often lack a distinct fold
  • In many cases there is no data regarding the peptide binding site and/or the peptide backbone conformation.
  • Structure-based modeling of these interactions is very challenging.

Using a ligand-based approach, SAFAN-ISPPEPT overcomes these challenges, to predict protein:peptides binding affinity quantitatively.

Our Technology Validation

SAFAN-ISPSM and SAFAN-ISPPEPT results were validated by the leave-one-out method, resulting in a Pearson correlation with experimental data higher than 0.9 and 0.8 respectively.

SAFAN-ISPSM

65936
#data
21090
#Compounds

Pearson Correlation 0.91

SAFAN-ISPPEPT

6079
#data
4382
Peptides

Pearson Correlation 0.87

pChEMBL is defined as: -Log(molar IC50, XC50, EC50, AC50, Ki, Kd or Potency)

Expected binding predictions (pChEMBL) with error <1

Here you can see the expected  error according to the known percentage of the small molecule. For instance, if we know only 40% of the input molecule, we can expect 84% of the predictions to have an error of less than 1.

Here you can see the expected  error according to the known percentage of the peptide. For instance, if we know only 40% of the input peptide, we can expect 76% of the predictions to have an error less than 1.

Testimonials

"I profiled 250000 compounds for my project. Using SAFAN-ISPSM output I easily selected 8 compounds for experimental validation and ONE was active! To plan the subsequent experiments it was of great help to know the concentration range I had to work with."
Wolfgang Schlattl
PhD Student, ESR CASR BIOMEDICINE TRAINING NETWORK
"SAFAN-ISPSM profiling output outlined some unwanted off-targets and I was able to more carefully in-license compounds."
Ceo, Biotech Company

Integrated Projects

Our expertise, based on many years of experience in basic and applied research in chemoinformatics and structural bioinformatics, can help you succeed in your research projects – including difficult homology modeling projects.

  • Help in difficult homology modeling projects.
  • Analysis of  the dynamic properties of proteins and nucleic acids by molecular dynamic simulations.

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