Data files

PDB file of the prepared human dihydrofolate reductase docking receptor based on chain A of PDB-ID 1u72 with a conserved set of structural waters.

PDB file of the prepared human dihydrofolate reductase docking receptor based on chain A of PDB-ID 1u72 without additional water molecules.

PDB file of the prepared Leishmania major dihydrofolate reductase docking receptor based on a published homology model of LmDHFR (Panecka-Hofman et al. (2017) Biochim Biophys Acta Gen Subj. 1861(12), 3215-3230. DOI: 10.1016/j.bbagen.2017.09.012) without water molecules.

PDB file of the prepared Leishmania major pteridine reductase 1 docking receptor based on chain A of PDB-ID 1e92 with a conserved set of structural waters.

PDB file of the prepared Leishmania major pteridine reductase 1docking receptor based on chain A of PDB-ID 1e92 without additional water molecules.

PDB file of the prepared Trypanosoma brucei dihydrofolate reductase docking receptor based on chain A of PDB-ID 3rg9 without water molecules.

PDB file of the prepared Trypanosoma brucei pteridine reductase 1 docking receptor based on chain A of PDB-ID 2x9g with a conserved set of structural waters.

PDB file of the prepared Trypanosoma brucei pteridine reductase 1 docking receptor based on chain A of PDB-ID 2x9g without additional water molecules.

Summary of fragments that were used to construct an in silico pteridine library with corresponding fragment identifiers. Connections between the fragments are shown outside the colored boxes. Compounds were composed of a core fragment (C1-C3), an N10 fragment (N1-N7), a PABA fragment (P1-P10) and, for any PABA fragment except P8, P9 and P10, a tail fragment (T1E1-T7).

Results of default run of Schrödinger QikProp (Schrödinger, LLC, New York, NY, Schrödinger Release 2015-4, 2015, QikProp v4.6.) for the entire in silico pteridine library. QikProp in silico predicts various physico-chemical compound properties and advanced descriptors related to administration, distribution, metabolism, excretion and toxicity of the compounds.

Zip file with Python module used to correlate compound descriptors predicted with Schroedinger QikProp with observed anti-parasitic effect against T. brucei brucei bloodstream forms. The script allows a leave-one-out analysis in addition to the default correlation analysis, where data for each compound is skipped once before the correlation analysis is re-performed. An example config file is provided with the zip-archive. For further instructions and information on the available settings, also ...

Zip-file with Python module used to calculate trivariate statistics between the inhibition of parasitic target enzymes pteridine reductase 1 and dihydrofolate reductase and the corresponding inhibition of T. brucei brucei bloodstream forms. The script makes use of an expansion of pairwise Pearson or Spearman correlations. For further details, also refer to the README file.

Note: "FigSM.A.1_Model-A.cps" corresponds to "SM-A-no design FigSM.A.1_Model-A.cps" in Suppl. Inform.

Python script wrapping up (executing) all the steps of the workflow the user enters in it. Together with "names.py" this script requires input files to be located in a folder called "input" in the same directory.

Input data (viscosities, in .csv format) for the modelling workflow, collected from literature, see associated publication for details.

Resulting data from the modelling workflow, see associated publication.

The modelling workflow used on the input data, which leads to the results, see associated publication.

Python script allowing the user to define the names of the input files to be used. Together with "wrapper.py" this script requires input files to be located in a folder called "input" in the same directory.