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An article just appeared which summarizes (and includes case examples for) some important lessons for the application of computational methods in drug design. I write about it here because it includes important messages also for the materials modelling and design field. There are differences of course since materials innovation is not always about new materials design. Nevertheless some of the key points are still valid and at least worth considering. I like the ‘principle of parsimony’, and also the conclusion about the importance of good software design. Much needed in the materials field as well.
Here are some key quotes and extracts from the paper .
The value of qualitative statements. Frequently, a single new idea or a pointer in a new direction is sufficient guidance for a project team. Most project impact comes from qualitative work, from sharing an insight or a hypothesis rather than a calculated number or a priority order. The importance of this observation cannot be overrated in a field that has invested enormously in quantitative prediction methods. We believe that quantitative prediction alone is a misleading mission statement for molecular design. …
Shaping chemical space. At any given point during a project, a team’s focus is either on expanding chemical space or on narrowing it down, for different aspects of problem solving and optimization. Broadening chemical space requires methods that create new ideas within a set of constraints. ….Narrowing down chemical space can be a simple filtering process or can be based on a specific hypothesis. Within a given project context, it is important to understand whether it is required to broaden or narrow down chemical space and to choose tools and approaches accordingly. As projects progress towards candidate selection, the “amplitudes” of narrowing and broadening space typically become smaller, but the concept stays the same.
The principle of parsimony. Molecular design is a conceptual process and therefore always at risk of losing touch with reality. The scientific questions should lead to the method, and not vice versa. To achieve this, it is a helpful guiding principle to keep things as simple as possible. Choosing the simplest possible explanation and the simplest possible computational protocol leads to agility and to a better focus on the key questions at hand. …
Annotation is half the battle. … Contextual information can add value almost anywhere. A good deal of frontloading work—computational, organizational—is often required to bring data into a useful shape. Proper frontloading work can turn sophisticated queries into simple lookup processes or visualization steps. There is a significant growth potential in this area.
Staying close to experiment. One way of keeping things as simple as possible is to preferentially utilize experimental data that may support a project, wherever this is meaningful. … Rational drug design has a lot to do with clever recycling. If consistently applied, these guidelines have significant implications for the current practice of molecular design.
Let us look at some of the more problematic aspects as well. Many computational methods introduce additional parameters and thus potential sources of error that make the predictive value harder to extract. …..
What is special about molecular design is the need to build solid hypotheses and to simultaneously foster creative thinking in medicinal chemistry. If we accept this, our focus may shift from the many semi-quantitative prediction tools that we have to methods supporting this creative process. Further improvements in computational methods may then have less to do with science than with good software engineering and interface design. The tools are a just means to an end. Good science is what happens when they are appropriately employed.
 A Real-World Perspective on Molecular Design. Bernd Kuhn, Wolfgang Guba, Jérôme Hert, David W. Banner, Caterina Bissantz, Simona Maria Ceccarelli, Wolfgang Haap, Matthias Körner, Andreas Kuglstatter, Christian D. Lerner, Patrizio Mattei, Werner Neidhart, Emmanuel Pinard, Markus G. Rudolph, Tanja Schulz-Gasch, Thomas J. Woltering, and Martin Stahl
J. Med. Chem., DOI: 10.1021/acs.jmedchem.5b01875 • Publication Date (Web): 15 Feb 2016