Computational Chemistry can have a major impact on all stages of the drug discovery process, whether it be providing small desktop tools to enable scientists to access information more easily, calculation of physicochemical properties, virtual screening, structure-based design, QSAR analysis of both the desired target but also off-target activities.
There are a huge number of tools available, ranging in price from free to many $100,000s, here I’ll describe some of the tools I have used so whilst it is not comprehensive it might provide a useful stating point, the focus is on tools that a medicinal chemist might use. I always like the option to extend or integrate tools into workflows, so a scripting interface is very important.
See also Examples of Fingerprints and Descriptors.
Applications
Vortex
Vortex is a chemically aware data analysis and spreadsheet tool from Dotmatics. You can import files or from a SQL database and do substructure or structural similarity searches. Calculate many physicochemical properties and perform data analysis and display. Vortex can handle many millions of structures and is ideal for sifting through high-throughput screening data as well as project sized datasets.
The ability to have multiple interactive plots of the data alongside grids of the highlighted structures is an enormous aid to understanding the data. All plots are linked such that selection in one plot is automatically selected in all other plots and spreadsheets.
One of the very attractive features of Vortex is the availability of scripts that extend the capabilities of the applications. These can be used to extend the number of chemical descriptors available and also link to molecular modelling programs like MOE, statistical packages like R, or search and import information from databases and interact with web services. They can also be used to link to external AI/ML predictive models.
Other options
Chemical Computing Group
MOE (Molecular Operating Environment) is my main Computational Chemistry tool and it provides nearly all the functionality required for drug discovery. MOE is a software system designed to support Cheminformatics, Molecular Modelling, Bioinformatics, Virtual Screening, Structure-based-design, Fragment-based design. I’ve written a couple of reviews of MOE here. There are also tools for the automatic generation of SAR reports and data visualisation.
In addition the SVL scripting language also provides a powerful means to extend the capabilities of MOE and to build new tools, or to integrate or exchange data with external programs. SVL Exchange, a repository of programs and code samples written in the Scientific Vector Language (SVL) by users and developers of the Molecular Operating Environment. The SVL Exchange is a valuable resource for users seeking specialized applications, utilities, or customizations for MOE. For users who program in SVL, the files in the SVL Exchange can also serve as examples of SVL programming. An example of the use of SVL can be found on the analysis of the Malaria screening where the two result sets were compared using a SVL script (dbnbmols_incommon) that identifies identical compounds in multiple databases, showing there were 49 identical compounds in the two results sets.
Other options
Open Source tools
There are now a variety of very useful open source tools that can be used for drug discovery. The Royal Society of Chemistry Chemical Information and Computer Applications Group have run a series of over 20 workshops highlighting different tools, these are all now freely available on YouTube https://www.youtube.com/c/RSCCICAG and have been watched over 50,000 times.
Python and cheminformatics toolkits
There are a number of open-source cheminformatics toolkits https://macinchem.org/2023/02/17/open-source-cheminformatics-toolkits/ many with python api. These can be accessed using Jupyter notebooks to calculate properties, build workflows, or AI/ML models, visualise molecules.
Many of these Jupyter Notebooks are freely available
https://macinchem.org/category/jupyter-notebook
https://github.com/volkamerlab/TeachOpenCADD
https://iwatobipen.wordpress.com
https://greglandrum.github.io/rdkit-blog
There is also an online database https://opensourcemolecularmodeling.github.io that covers most aspects of computational drug discovery
Molecule Viewers
These are used to view the 3-dimensional structure of a molecule, many are also capable of displaying biological macro,molecules such as proteins.
PyMol, VIDA, Chem3D, ChimeraX, Jmol, JSmol, AstexViewer, CN3D, CylView, DINO, ICM Browser. Molgro Viewer, Mol*, Qutemol, VMD, Yasara, ICM Browser, 3Dmol.js
There are also big computational software companies like Schrödinger (https://www.schrodinger.com/company/about/) , Chemical Computing Group (https://www.chemcomp.com/en/index.htm) and Cresset (https://cresset-group.com/software/)