Nathan Brown

I lead the In Silico Medicinal Chemistry group in the Cancer Research UK Cancer Therapeutics Unit at The Institute of Cancer Research in London, supporting Chemoinformatics, Molecular Modelling, Chemometrics, and Computational Chemistry within the Medicinal Chemistry department. My primary interests are in the development and application of software tools to push forward the progress of drug discovery with a particular focus on simultaneously optimising multiple objectives. At the ICR, our group supports the activities of over 50 PhD medicinal chemists spread over a number of teams and therapeutic areas working towards novel oncology therapeutics.

I have also recently conducted research at the Universities of Sheffield, UK and Erlangen-Nuremberg, Germany, andEli Lilly & Co. in Ascot, UK, Avantium Technologies in Amsterdam, Netherlands, and most recently the Novartis Institutes for BioMedical Research in Basel, Switzerland.

I have a wide range of experience as a software designer and developer in many different programming languages. Using these skills I have developed a variety of novel algorithms and tools to maximise the impact of our experimental data. I have a particular interest in data visualisation using novel statistical and charting methods to disseminate information as appropriately as possible for the intended audience.

My primary interests are: virtual ligand docking, de novo molecular design, multi-objective optimisation, molecular descriptors, predictive modelling, graph theory, machine learning, evolutionary algorithms, molecular similarity and diversity, bioisosteric replacement, and scaffold hopping.

I currently review for Drug Discovery Today, Future Medicinal Chemistry, Journal of Chemical Information and Modeling, Journal of Medicinal Chemistry, Journal of Molecular Graphics and Modelling, Journal of Cheminformatics,Medicinal Chemistry Communications, PLoS One, QSAR and Combinatorial Science, Regulatory Toxicology and Pharmacology, Dental Materials, Combinatorial Chemistry and High-Throughput Screening, and Chemical Engineering Science.