4 ms·

A huge source of uncertainty in molecular dynamics comes from the force model, which are crude approximations of electronic structure. There is a great deal of

A huge source of uncertainty in molecular dynamics comes from the force model, which are crude approximations of electronic structure. There is a great deal of active research on improved force models, many of which are implemented in AMBER (http://ambermd.org http://ambermd.org) and can be used from most popular MD packages. Other approximations, such as the cut-off for short- vs long-range force evaluation, must also be validated. Anton is built for a very specific configuration; the modeling assumptions may or may not be valid for a given scientific or engineering experiment. Its value is in being able to rapidly experiments for which the modeling assumptions have already been validated (and run those configurations for longer simulated time), but not for questioning the modeling assumptions or for developing better models.

p4wnc6 11y ago
This is a very underappreciated point. For example, in pharmaceutical drug discovery, what often matters most is the ability to play around with different modeling assumptions, and to do large-scale "search engine" work on different compound properties and how they might affect desired overall properties of the final product. I wonder if one reason why this highly specific computational architecture is only deployed in two places (as far as I can tell) is because it's actually not very applicable to mainstream molecular dynamics use cases? A lot of the business around pharma drug discovery seems to be pushing for more cloud computing solutions that offer better analytics APIs for engineers, rather than beefing up hardware for larger-scale simulations.
dekhn 11y ago
I don't see how this follows from the design. Anton is general enough that a wide range of force field terms can be implemented efficiently, so frankly, I'd be using it to validate terms, rather than predict anything.

p4wnc6 11y ago

This is a very underappreciated point. For example, in pharmaceutical drug discovery, what often matters most is the ability to play around with different modeling assumptions, and to do large-scale "search engine" work on different compound properties and how they might affect desired overall properties of the final product. I wonder if one reason why this highly specific computational architecture is only deployed in two places (as far as I can tell) is because it's actually not very applicable to mainstream molecular dynamics use cases? A lot of the business around pharma drug discovery seems to be pushing for more cloud computing solutions that offer better analytics APIs for engineers, rather than beefing up hardware for larger-scale simulations.

dekhn 11y ago

I don't see how this follows from the design. Anton is general enough that a wide range of force field terms can be implemented efficiently, so frankly, I'd be using it to validate terms, rather than predict anything.