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 [J. Mol. Graph. Model. (2008) 27, 161] code that was developed in 2008 by Silicos. It is based on the alignment method described by Grant and Pickup [J. Phys. Chem. (1995), 99, 3503]. 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 [Nature Chemistry (2012) 4, 90]. This python module relies on RDKit 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.