Molecular modeling

Molecular modeling is the theme of this month’s issue of Drug Discovery Today’s Editor’s Choice newsletter. Molecular modeling is an established computational toolbox to assist early drug discovery and development. It can be used to generate ideas on a compounds or macromolecules 3D conformation, protein–ligand interactions, and to make predictions on biological activities. In close collaboration with medicinal chemistry and biological experiments, the incorporation of molecular modeling can bring helpful insights into the behavior of molecules and make early drug discovery more efficient.


Molecular modeling has become an integrated part of investigating, explaining, and predicting the properties of small organic molecules as potential drug candidates. Modeling techniques are applied in the fields of compound synthesis (conformational analysis and reaction planning), drug discovery (virtual screening), activity rationalization (docking and molecular dynamics simulations), and lead optimization including the prediction of antitarget effects.
To be successfully incorporated into the drug discovery and development process, all these methodologies require constant experimental feedback from medicinal chemistry and biological experiments to validate the results obtained by modeling to further improve these methods. This close interplay of disciplines is vital; however, it can be challenging to establish a vivid and cooperative communication between modelers, chemists, and biologists.
In the first free download of this Editor’s Choice, Timothy J. Ritchie and Iain M. McLay discuss ‘Should medicinal chemists do molecular modeling?’ from the viewpoints of medicinal chemists and computational chemists. Medicinal chemists can be encouraged to employ computational methods by providing them with easy-to-use, fast, and reliable tools, which do not require in-depth knowledge on molecular modeling. They can also be equipped with pregenerated computer-aided drug design data to support their work. For further support and more advanced calculations, a molecular modeler could be personally involved in each medicinal chemistry team or employed as a bridge between computational and medicinal chemistry groups. That way, most benefit can be generated from this constellation and possible pitfalls can be avoided. Successful results from molecular modeling-driven experiments conducted by medicinal chemists should be widely communicated to further encourage colleagues to use these methods.
In the context of computational tools which could be attractive to many medicinal chemists, two examples are featured in the other two articles. Christoph H. Schwab from Molecular Networks describes in his review ‘Conformations and 3D pharmacophore searching’ why 3D conformations of small molecules are relevant to modeling studies and how they are computed by commonly used commercial software packages. Most recent conformer generators combine rule- and data-based systems, systematic searches, numerical methods, random approaches, and genetic algorithms. The aim of conformer generation is to generate a set of low energy 3D structures which includes the so-called bioactive conformations of a molecule that are the conformations in which it binds to pharmacological targets.
The third review written by me describes the use of ‘3D pharmacophores as tools for activity profiling’. Using multiple models representing different targets in parallel can be used to predict a compounds activity profile. This concept can be implemented to generate starting ideas in drug repositioning, natural product profiling, the search for compounds targeting multiple proteins, and safety profiling.
Conformational analysis and activity profiling are excellent examples of applications that can rather simply be put into medicinal chemists’ hands by a front-end tool, but their development needs an expert team to ensure quality and monitor and/or evaluate the experiments and results obtained by these systems. Thus, easy-to-use, interdisciplinary tools enhance the interplay between modelers and chemists and are a good base for fruitful collaborations within the drug discovery and development environment.
Dr Daniela Schuster is currently University Assistant at the University of Innsbruck, Austria, where she heads the Computer-Aided Molecular Design Group at the Institute of Pharmacy. She is specialized on in silico activity predictions, which have already led to the discovery of numerous bioactive compounds. In 2010 she received the Prof. Ernst Brandl Award and the first Erika Cremer Habilitation Fellowship (by the University of Innsbruck) for the application of pharmacophore models to discover testosterone synthesis-disrupting UV-filter chemicals. Daniela is interested to apply pharmacophore models and alternative similarity search techniques to discover so far unknown bioactivities of small organic molecules, natural products, and environmental chemicals.

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