Spartan is a powerful tool for computer aided drug design. The easy-to-use interface delivers a new suite of molecular modelling features as well as quantum calculation tools for chemists working in drug discovery. Pharmaceutical scientists can perform conformational analysis and can quantify 3D molecular similarity based on structure, chemical function, and pharmacophore models. Many of the leading Pharmaceutical companies are already using Wavefunction software to fast-track development of new drugs.
Determine and quantify similarity with Spartan
Key Benefits for Pharmaceutical Research
Ease of Use
Spartan offers construction, manipulation, and analysis (both computational and statistical) from a single, user friendly interface. The end result is that Spartan is easier to master, without compromising the limitations of its functionality. This maximisies the return on investment for pharma research companies.
Seamless Databases Access
Spartan integrates access to the leading molecular and spectoscopy databases seamlessly from within the graphical interface.
Efficient Molecular Modelling
Spartan includes easy to use 3D builders for Organic, Inorganic, Peptides, and Nucleotides –it offers a new substituent builder for generating virtual libraries, and one can use ChemDraw (directly from within Spartan) to build in 2D and seamlessly convert the 2D molecule to 3D within Spartan.
Conformer Library Generation
A new capability has been added to provide generation of libraries of diverse conformers. This is based on a systematic search of conformation space using MMFF molecular mechanics, followed by a procedure to eliminate conformers that occupy “similar space”. Conformer libraries are intended for use in similarity analysis. Conformer libraries corresponding to common drugs (5,000 entries) and to the Maybridge compendium, “Compounds for Drug Discovery Chemistry” (70,000 entries) are provided via the Spartan Molecular Database (SMD).
A new capability has been developed for assessing and quantifying the similarity of one or more “templates” (either molecules or pharmacophores), to one or more “libraries” (including libraries of diverse conformers). Similarity between molecules may either be based on structure or on CFD’s, whereas similarity between molecules and pharmacophores is based solely on CFD’s. A scoring function based on rms deviations between selected atomic centers or between CFDs (automatically adjusted to account for unfavorable intramolecular interactions) has also been provided.