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Recipe: Simulated Annealing 5.0
Created by KarenCH 67 54
Your rating: None Average: 5 (3 votes)


Name: Simulated Annealing 5.0
ID: 104020
Created on: Tue, 09/29/2020 - 14:50
Updated on: Tue, 09/29/2020 - 21:50

Very fancy script that tries to "solve poses" - give it a plausible starting pose, it will improve it to a good end result.

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KarenCH's picture
User offline. Last seen 8 hours 41 min ago. Offline
Joined: 07/14/2012

Simply clicking OK to the first and second menu popups will cause it to perform a sequence of operations that should carry a provided pose to a good semi-final shape. (It will stop short of doing High Wiggle Power endgame actions, though it does provide a version of this as a separate set of actions).

It is a complex script that is capable of many many things. The first menu shows the "known-good" choices, but offers "Other actions" if you want to explore.

The second menu is the "dragons" menu - it uses "here be dragon" descriptions of the options to give a picture of how complicated the path will get.

1. It preserves user bands, cuts, and frozen sections, and accepts the current Clash Importance as a max value. For bands, if SASequence is requested, the "SA Run parameters" (under "big dragons") leads to an option of disabling the bands after the early phases. Its normal actions include qstab-fusing, but it can be disabled by choosing the correct option under the "baby dragons" header.
2. It uses the simulated annealing algorithm to create sessions of 12-15 actions - score drops can happen during the session, but at the end of one, it takes the largest score it saw during that session.
3. For a reasonably good computer, doing a full SASequence on a small protein will take a bit more than a day (28-30 hours). It goes faster if the original pose is closer to correct.

Hanto's picture
User offline. Last seen 3 weeks 12 hours ago. Offline
Joined: 05/10/2008
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Mighty Powerful recipe

When used with multiple isolated clients.

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Developed by: UW Center for Game Science, UW Institute for Protein Design, Northeastern University, Vanderbilt University Meiler Lab, UC Davis
Supported by: DARPA, NSF, NIH, HHMI, Amazon, Microsoft, Adobe, RosettaCommons