OSPREY: protein design with ensembles, flexibility, and provable algorithms.
By Pablo Gainza, Kyle E. Roberts, I. Georgiev, R. Lilien, Daniel A. Keedy, Cheng-Yu Chen, F. Reza, Amy C. Anderson, David C Richardson, Jane S. Richardson and 1 more. 2013
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- B. Hintze
- Jane S. Richardson
- Steven M. Lewis
- David C Richardson
- Yunan Luo
- Pablo Gainza
- Hunter M. Nisonoff
- Bruce Randall Donald
Citations in the corpus
- Evolutionary context-integrated deep sequence modeling for protein engineering (2020, background): “, FoldX [42] and OSPREY [4] ).”
- Algorithms for Protein Design (2016, methodology): “These algorithms are implemented in the Toulbar2 program [53 ,54,55], with support only for discrete flexibility models, and in the Osprey protein design program [39,68] (with full support for continuous flexibility models, described in the next section [64 ,69 ]).”
- MolProbity’s Ultimate Rotamer-Library Distributions for Model Validation (2016, methodology): “…in v space around the low-energy mean of each rotamer, which allowed development of the influential Dead-End Elimination method in protein design.22 ,23 A third type of rotamer soft-ware19,24 evaluates a given side-chain conformation by its position in a multi-dimensional probability distribution.”
- De Novo Protein Design for Novel Folds using Guided Conditional Wasserstein Generative Adversarial Networks (gcWGAN) (2019, unknown): “Currentprotein(re)designalgorithmsfall inthreeclasses: 1)exactalgorithmssuchasdead-endelimination, A ∗ , and costfunctionnetworks(Gainza etal.”