1 / 7

Consensus RAPDF rTAD Refinement Successes & Failures

This study by Jeremy Horst and Ram Samudrala from the University of Washington discusses the Consensus RAPDF rTAD refinement process, highlighting both its successes and failures in predicting interatomic distances and modeling structures. The results demonstrate improvements in metrics like RMSD and GDT-TS across various targets, showcasing the method’s effectiveness against competitors. Insights into side chain packing, loop search strategies, and the importance of addressing challenging targets are presented, alongside recommendations for future benchmarks and methodologies. The work emphasizes the need for more innovative approaches in atomic movement and functional site refinement.

rune
Télécharger la présentation

Consensus RAPDF rTAD Refinement Successes & Failures

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

More Related