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Consensus RAPDF rTAD Refinement Successes & Failures

Consensus RAPDF rTAD Refinement Successes & Failures. Jeremy Horst Ram Samudrala ’s CompBio Group University of Washington. Consensus RAPDF rTAD Refinement. Derive interatomic distances. Bayesian probabilities. Distance bin. Nonredundant structure set. Atom type. Atom type.

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Consensus RAPDF rTAD Refinement Successes & Failures

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  1. Consensus RAPDF rTAD RefinementSuccesses & Failures Jeremy Horst Ram Samudrala’sCompBio Group University of Washington

  2. Consensus RAPDF rTAD Refinement Derive interatomic distances Bayesian probabilities Distance bin Nonredundant structure set Atom type Atom type J.Horst & R.Samudrala

  3. Consensus RAPDF rTAD Refinement - RESULTS TR488 TR464 2.111.46 aRMSD0.870.91 GDT-TS 2.943.51 aaRMSD0.610.68 GDT-TS J.Horst & R.Samudrala

  4. Consensus RAPDF rTAD Refinement – SIDE CHAIN PACKING J.Horst & R.Samudrala

  5. CASP8R Perks + no focus on specific regions; automated + never much worse (454) CASP8 FM targets Perks + absolute best on 5/96targets (407,409,414,455,510) + always better than 2ndbest initial model (on ~all servers)

  6. Needs - Larger loop search space (looser/less constraints) - De-constrain problem areas (Seq vs. Str entropy) - Functional sites (?functional refinement target?) Advice  Benchmark on past CASPs (in papers)  Do not avoid hard targets (show limits)  Expensive methods should be iteratable  Combine Methods • Focus physics based methods here. • We need a new way to move atoms (according to Nicolay Grishin) • Are heuristics and regression / SVM okay?

  7. Acknowledgements Folks who wrote code • Ram Samudrala • Tianyun Liu • Charles Mader • Ling-Hong Hung Idea bouncers ++ • Michal Guerquin • Brady Bernard • WeerayuthKittichotirat • Stewart Moughon

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