All of our software tools have been made open source. This is a policy that we strictly adhere as we believe that sharing software and technology ultimately leads to higher quality and faster progress in science.
​​
Shape-it is the shape-only rewrite of the original Pharao code [] code that was developed in 2008 by Silicos. It is based on the alignment method described by Grant and Pickup []. Shape-it is a shape-based virtual screening method to retrieve molecules with similar shape from different compound libraries. It is widely used and have been cited numerous times.
​​
Spectrophores are a novel class of descriptors calculated from the three-dimensional atomic properties of molecules [J. Cheminform. (2018), 10, 9]. The methodology finds its roots in the experimental affinity fingerprinting technology developed in the 1990’s by Terrapin Technologies. At Silicos, this was translated into a virtual approach using artificial affinity cages and a metric to calculate the interaction between these cages and atomic properties. Spectrophores are highly suitable for the calculation of a wide range of similarity measures for use in virtual screening and for the investigation of quantitative structure–activity relationships in combination with machine learning models.
​​
LEADD stands for Lamarckian Evolutionary Algorithm for de novo Drug Design. LEADD designs molecules as combinations of molecular fragments, bonded according to the topology of a graph. Atom pair compatibility rules are enforced by a novel set of genetic operators, biased according to the frequency of the fragments in drug-like matter. A Lamarckian evolutionary mechanism adjusts the future reproductive behavior of molecules based on the outcome of previous generations. LEADD attempts to strike a balance between optimization power, synthetic accessibility and computational performance [J. Cheminform. (2022) 14, 3].
​​
QED stands for Quantitative Estimation of Drug-likeness. The concept has originally been introduced by Richard Bickerton and coworkers []. This python module relies on as a chemoinformatics toolkit.
​​
FEPprep is a python-based alignment tool for the mapping of ligands to be used in free energy perturbation (FEP) calculations. The method uses a maximum common substructure (MCSS) approach to identify identical regions between the pair of compounds, followed by a constrained minimization to optimally align both ligands. This work is still in progress.