Andrew M. Watkins

TL;DR: This Perspective reviews tools developed over the past five years in the Rosetta software, including over 80 methods, and discusses improvements to the score function, user interfaces and usability.

TL;DR: The developed computational methods for accurate de novo design of conformationally restricted peptides and the use of these methods to design 18–47 residue, disulfide-crosslinked peptides, a subset of which are heterochiral and/or N–C backbone-cyclized, provide the basis for development of a new generation of peptide-based drugs.

TL;DR: The Atomic Rotationally Equivariant Scorer (ARES) as mentioned in this paper is a machine learning approach that enables identification of accurate structural models without assumptions about their defining characteristics, despite being trained with only 18 known RNA structures.

TL;DR: In 16 of 21 RNA-Puzzles revisited without experimental data or expert intervention, FARFAR2 recovers native-like structures more accurate than models submitted during the RNA- Puzzles trials, and preregistered blind models for adenovirus VA-I RNA and five riboswitch complexes predicted native- like folds with 3- to 14 Å root-mean-square deviation accuracies.

TL;DR: It is demonstrated that cryo-electron microscopy can routinely resolve maps of RNA-only systems and that these maps enable subnanometer-resolution coordinate estimation when complemented with multidimensional chemical mapping and Rosetta DRRAFTER computational modeling.