The Current issue of “The view from here” is concerned with Informatics

The topic of this month’s newsletter from Drug Discovery Today is “Informatics”.

I would imagine that as the Pharmaceutical industry moved from a small scale, almost cottage industry, approach to screening compounds, many people would suggest that this was driven by improvements in methodology related to liquid handling and miniaturization amongst many other hardware related developments. While that represents a truism, all of these technological breakthroughs needed to be accompanied by a concomitant improvement in handling and visualizing the ever-increasing amounts of data generated by such high throughput systems. Although this is perhaps the most obvious and straightforward application of informatics to the drug discovery process, the field of informatics has been all-pervasive in facilitating drug design and obtaining data, that would in the past have been difficult, or impossible, to derive from existing data sets. This includes in house datasets, proprietary information and the scientific literature through data mining technology. This newsletter has a selection of articles highlighting how informatics impacts fields as diverse as chemoinformatics, molecular modeling and bibliometric analysis (in this case as applied to drug repurposing).


In the first article in this month’s offering, we touch upon the field of machine learning and its application to drug discovery. This is a relatively general article on chemoinformatics “Machine learning in chemoinformatics and drug discovery” from Yu-Chen Lo, Stefano E. Rensi, Wen Torng and Russ B. Altman of Stanford University, California, USA. It is a particularly useful introduction to the field for those interested in an introduction to the field and examines the basic principles and highlights them with some case studies. This is a great gatekeeper article for those wishing to get a good understanding of where this approach is currently heading.


The next article, “Protein–peptide docking: opportunities and challenges” from Maciej Ciemny, Mateusz Kurcinski, Karol Kamel, Andrzej Kolinski, Nawsad Alam, Ora Schueler-Furman and Sebastian Kmiecik of various institutes in Poland and Israel moves away from the chemoinformatics arena and deals with another field that has benefitted massively from the influence of informatics, namely that of molecular modeling. This particular paper deals with protein-peptide docking. This particular avenue of modeling is of great importance at the moment as a result of recent interest in developing peptide-related compounds that may offer significant advantages over current low molecular weight organic chemistry approaches to drug discovery. The article highlights fundamental approaches to, and limitations and applications of such docking functions. They outline many of the challenges in developing drugs by this route, including conformational changes, binding and scoring and the integration of modeling into the overall drug discovery project plan.


The final article this month “A bibliometric review of drug repurposing” deviates somewhat from the previous two in that it deals less with the utilization of informatics to design novel active compounds and more with how to derive information that may allow alternative (or improved) utilization of existing compounds. As publishers, this is obviously something of great interest and a great example of how such data mining approaches can be used to generate value from existing information. The authors, Nancy C. Baker, Sean Ekins, Antony J. Williams and Alexander Tropsha are established experts in informatics as applied to drug discovery look at a very large number of articles in PubMed to identify how many drugs or drug candidates have been used in multiple diseases and how some have been used in a very wide range of conditions indeed. Although most of the compounds identified are generally applied to broadly similar indications, there were some surprisingly successful uses in somewhat unexpected areas. The article really supports the value of such an informatic/bibliographic approach to derive useful information from historic datasets.




Steve Carney was born in Liverpool, England and studied Biochemistry at Liverpool University, obtaining a BSc.(Hons) and then read for a PhD on the Biochemistry and Pathology of Connective Tissue Diseases in Manchester University, in the Departments of Medical Biochemistry and Histopathology. On completion of his PhD he moved to the Kennedy Institute of Rheumatology, London, where he worked with Professor Helen Muir FRS and Professor Tim Hardingham, on the biochemistry of experimental Osteoarthritis. He joined Eli Lilly and Co. and held a number of positions in Biology R&D, initially in the Connective Tissue Department, but latterly in the Neuroscience Department. He left Lilly to take up his present position as Managing Editor, Drug Discovery Today, at Elsevier. Currently, he also holds an honorary lectureship in Drug Discovery at the University of Surrey, UK. He has authored over 50 articles in peer-reviewed journals, written several book chapters and has held a number of patents. On the media front, Dr. Carney has been busy on some hush-hush projects that will be reported on later in the year.


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