_(cropped).jpg)
This is the question that Anthony Nicholls of OpenEye Scientific Software will try to answer tomorrow at the OpenEye offices in Cambridge, MA. Well, ok, not exactly this question but a more nuanced version thereof.
As those in the field would probably know, Anthony who is one of the leaders in the field of industrial computational chemistry has had a history of offering pointed, articulate and informed criticism on what is rapidly becoming an important tool in the drug industry. In the last few years MD has captured the imagination of many, especially through the efforts of researchers like David Shaw and Vijay Pande who have enabled simulations to approach realistic time scales approximating large-scale conformational changes in proteins and protein-ligand binding. Nonetheless it remains a technique that often sparks a range of responses among its practitioners and critics, which to me makes it even more interesting because it's no fun when everyone agrees or disagrees, right?
I am not an expert when it comes to MD (that's precisely why I want to hear from the experts) but I am instead like the vast majority of scientists who use the technique, find it useful to varying degrees and are intrigued by what the fundamental issues in the field exactly are. What makes this issue even more interesting for me is that it seems to tread into some of the more relevant questions from the philosophy of science, including evergreen gems like "What is utility?", "What do you mean when you say a technique 'works', and is this definition the same for different techniques?", "What is more important, prediction or understanding?" and the ultimate zinger, "What is science, exactly?". I am particularly interested in the question of how exactly you validate a 'correct' prediction for a complex system like a protein-drug interaction where there can be considerable uncertainty. I am sure Anthony will have more to say about this since he has made extremely valuable contributions to pointing out the key role of statistics in molecular modeling.
In any case, I have no doubt that the talk will be characteristically stimulating and provocative. If you want to attend you should RSVP to Scott Parker at OpenEye. Derek also mentioned this on his blog. And of course, I will be there and will have a summary here soon, so watch this space.
Update: My report on the talk is here.
As those in the field would probably know, Anthony who is one of the leaders in the field of industrial computational chemistry has had a history of offering pointed, articulate and informed criticism on what is rapidly becoming an important tool in the drug industry. In the last few years MD has captured the imagination of many, especially through the efforts of researchers like David Shaw and Vijay Pande who have enabled simulations to approach realistic time scales approximating large-scale conformational changes in proteins and protein-ligand binding. Nonetheless it remains a technique that often sparks a range of responses among its practitioners and critics, which to me makes it even more interesting because it's no fun when everyone agrees or disagrees, right?
I am not an expert when it comes to MD (that's precisely why I want to hear from the experts) but I am instead like the vast majority of scientists who use the technique, find it useful to varying degrees and are intrigued by what the fundamental issues in the field exactly are. What makes this issue even more interesting for me is that it seems to tread into some of the more relevant questions from the philosophy of science, including evergreen gems like "What is utility?", "What do you mean when you say a technique 'works', and is this definition the same for different techniques?", "What is more important, prediction or understanding?" and the ultimate zinger, "What is science, exactly?". I am particularly interested in the question of how exactly you validate a 'correct' prediction for a complex system like a protein-drug interaction where there can be considerable uncertainty. I am sure Anthony will have more to say about this since he has made extremely valuable contributions to pointing out the key role of statistics in molecular modeling.
In any case, I have no doubt that the talk will be characteristically stimulating and provocative. If you want to attend you should RSVP to Scott Parker at OpenEye. Derek also mentioned this on his blog. And of course, I will be there and will have a summary here soon, so watch this space.
Update: My report on the talk is here.
I suspect this will be very entertaining, it would be nice to have it recorded.
ReplyDeletecan we stream this event? or possibly set up google hangouts?
ReplyDeleteThey taped the lecture so hopefully it should be available online soon.
ReplyDeleteIf you don't like the cats, it's simply you don't know how to cook them )
ReplyDelete