Resources
Technical Support
We do our best to provide technical support within 24-48 hours. Please email us or fill out the form on our Contact page.
MFI’s predictive software is built in C++ with a front-end JavaScript-based GUI. Our code can also be executed from the command-line and scripted to integrate into any workflow. We use standard input and output file formats to make collaboration quick and easy.
- Windows 8/10/11 (64-bit architecture)
- 4 GB of RAM (8 GB recommended)
- Java 1.6, 1.7 or 1.8 (Java Runtime Environment 8) for user interface
- Ubuntu 18.04 (64-bit architecture) and higher versions
- 4 GB of RAM (8 GB recommended)
- Java 1.6 (latest version) for user interface
- Yosemite 10.10 (64-bit architecture only) and higher versions
- 4 GB of RAM (8 GB recommended)
- Java 1.6 (latest version) for user interface
- Xterm needs to be installed. (XQuartz project)
Is the software free for academics?
We are committed to giving back and developing the next generation of scientists and leaders. That’s why we provide academic licenses free of charge with a professor’s signature.
All we ask is that users reporting results with our programs cite MFI appropriately.
Do I need a special computer to run MFI’s software solutions?
If you are screening many compounds or running multiple virtual experiments simultaneously, we recommend having an appropriate desktop or server solution. If you are unsure, please contact us with your specific questions.
I’ve set up my virtual experiment and it won’t execute (run). What’s wrong?
This is likely due to a user not having the necessary permission for running the software. We highly recommend a user had read/write permissions in their account for the software to run properly.
If your permissions are correctly set up and the software still won’t execute, please contact us at info@molecularforecaster.com with the e-mail header “Software won’t execute”, followed by a description of your operating system and your account permissions.
The graphical user interface won’t start. What do I do?
If you still have problems running the Java interface even if your prerequisites are installed, you can use the portable Java interface we ship with our software.
How do I define the protein active site?
The protein active site is automatically determined by ProCESS if a ligand is present in the PDB structure. Alternatively, you can define your own active site using the following keywords:
AutoFind_Site N
Binding_Site number-of-residues [be as exhaustive as possible]
residue-#1_name [this must be the 3 letter amino acid name followed by the number i.e., ASP000]
residue-#2-name
Grid_Center x y z [the centre of the cavity you want to define, Cartesian coordinates]
For more options see “Parameter” below.
What is the difference between the score and the energy values in FITTED?
Fitted uses several metrics to define the quality of the binding poses it generates.
Energy is a measure of the binding affinity of a ligand to the target. The lower the energy, the better. In Fitted, the lowest energy binding pose is considered the best one.
RankScore is a set of scoring functions which are based on energy terms and other terms which are all scaled to better model the observed binding free energies.
MatchScore is a measure of how well the ligand fits inside the active site, based on the interaction sites generated by ProCESS. The higher the score (i.e., more positive), the better the ligand matches the protein interaction sites.
FITTED_Score is a composite score based on RankScore and MatchScore. It thus provides a measure of how the ligand interacts with the active site from an energetic and geometric point of view. It should be the metric of choice when ranking compounds.
Note: Comparing energies and scores of ligands between different targets has little to no meaning. These metrics should be used to rank ligands within the same target.
2024 Q1 Patch Update
IMPACTS: Addition of four new CYP isoforms for SoM predictions (2A6, 2B6, 2C8, and 2E1). Use of SASA correction factor to improve activation energy assignment. SELECT: Use of Tversky index in addition to Tanimoto coefficient for seach similarity. CONVERT: Can convert...
2022 Q1 Patch Update
ACE/FITTED/IMPACTS: New energy optimization algorithm (LBFGS) has been implemented leading to substantial increases in speed (ca. 2x-3x). SELECT: Fingerprints can be pre-computed and stored when comparing libraries. Library diversity can now be computed. Entire...
2021 Q3 patch release
Our 2021 Q3 patch release is now available using your download credentials. Impacts has been updated to predict CYP inhibition by small molecules.
Please remember to cite MFI appropriately when reporting results with our programs. We suggest the following, in addition to any other papers you deem necessary. See a complete list of publications and other references here.
FITTED:
Moitessier N., Pottel J., Therrien E., Englebienne P., Liu Z., Tomberg A., Corbeil C.R. Medicinal Chemistry Projects Requiring Imaginative Structure-Based Drug Design Methods Acc. Chem. Res. (2016), 49 (9), 1646-1657
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IMPACTS:
Campagna-Slater V., Pottel J., Therrien E., Cantin L.-D., Moitessier N. Development of a computational tool to rival experts in the prediction of sites of metabolism of xenobiotics by P450s J. Chem. Inf. Model. (2012), 52, 9, 2471-2483
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FORECASTER and other tools:
Therrien E., Englebienne P., Arrowsmith A.G., Mendoza-Sanchez R., Corbeil C.R., Weill N., Campagna-Slater V., Moitessier N. Integrating medicinal chemistry, organic/combinatorial chemistry, and computational chemistry for the discovery of selective estrogen receptor modulators with FORECASTER, a novel platform for drug discovery J. Chem. Inf. Model. (2012), 52, 1, 210-224
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FINDERS and REACT2D:
Pottel J., Moitessier N. Customizable Generation of Synthetically Accessible, Local Chemical Subspaces J. Chem. Inf. Model. (2017), 2017, 57, 454-467
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