Standards of Proof

Here are some slides from Anthony Nicholls of OpenEye, from his recent presentation here in Cambridge on his problems with molecular dynamics calcuations. Here's his cri du coeur (note: fixed a French typo from the original post there):

. . .as a technique MD has many attractive attributes that have nothing to do with its actual predictive capabilities (it makes great movies, it’s “Physics”, calculations take a long time, it takes skill to do right, “important” people develop it, etc). As I repeatedly mentioned in the talk, I would love MD to be a reliable tool - many of the things modelers try to do would become much easier. I just see little objective, scientific evidence for this as yet. In particular, it bothers me that MD is not held to the same standards of proof that many simpler, empirical approaches are - and this can’t be good for the field or MD.

I suspect he'd agree with the general principle that while most things that are worthwhile are hard, not everything that's hard is worthwhile. His slides are definitely fun to read, and worthwhile even if you don't give a hoot about molecular dynamics. The errors he's warning about apply to all fields of science. For example,he starts off with the definition of cognitive dissonance from Wikipedia, and proposes that a lot of the behavior you see in the molecular dynamics field fits the definitions of how people deal with this. He also maintains that the field seems to spend too much of its time justifying data...

Source: In the Pipeline - December 10, 2013 Category: Chemists Tags: In Silico Source Type: blogs