Relaxation of backbone bond geometry improves protein energy landscape modeling

By Patrick Conway, Michael D. Tyka, Frank DiMaio, David E. Konerding, David Baker. 2014

399 citations recorded by the source corpus.

Subfields: Materials Chemistry, Molecular Biology, Spectroscopy, Computational Chemistry & Drug Discovery, AI for Physical Sciences

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Materials Chemistry

1. David Baker
2. Jeffrey J. Gray
3. Tanja Kortemme
4. Frank DiMaio
5. Hahnbeom Park
6. Sergey Ovchinnikov
7. David E. Kim
8. Yang Zhang

In Molecular Biology

1. David Baker
2. Tanja Kortemme
3. Jeffrey J. Gray
4. Sergey Ovchinnikov
5. Frank DiMaio
6. Hahnbeom Park
7. Po-Ssu Huang
8. Yang Zhang

In Spectroscopy

1. David Baker
2. Sergey Ovchinnikov
3. Hahnbeom Park
4. Frank DiMaio
5. David E. Kim
6. Richard Bonneau
7. Brian Kuhlman
8. Jeffrey J. Gray

In Computational Chemistry & Drug Discovery

1. Hahnbeom Park
2. Jeffrey J. Gray
3. David Baker
4. Frank DiMaio
5. Sergey Ovchinnikov
6. Tanja Kortemme
7. David E. Kim
8. Po-Ssu Huang

In AI for Physical Sciences

1. Sergey Ovchinnikov
2. Hahnbeom Park
3. David Baker
4. David E. Kim
5. Brian D. Weitzner
6. Frank DiMaio
7. Mohammed Alquraishi
8. Tanja Kortemme

Citations in the corpus

• Improved protein structure refinement guided by deep learning based accuracy estimation (2020, methodology): “Next, Rosetta FastRelax (29) is run by imposing residue-pair restraints from estograms brought from either the partner or the seed interpolated into pair potentials (see above).”
• The Rosetta all-atom energy function for macromolecular modeling and design (2017, background): “88 These data suggest that capturing non-ideal bond lengths and angles can be important for accurate modeling of minimum-energy protein conformations.”
• Robust and accurate prediction of residue–residue interactions across protein interfaces using evolutionary information (2014, methodology): “The top 5 models by restraint score were energy-minimized in cartesian space using both inter and intra restraints with cycles of minimization and side chain repacking using Rosetta as described in Conway et al. (2014) .”
• Automatically fixing errors in glycoprotein structures with Rosetta (2018, positive): “First, previous work (DiMaio et al., 2013; Conway et al., 2014) demonstrated that Cartesian-space refinement allowing for deviations in bond angle and geometry is important in both structure refinement and native structure discrimination tasks.”
• RosettaAntibodyDesign (RAbD): A general framework for computational antibody design (2017, methodology): “Rosetta has been developed and used for a variety of modeling and design tasks, such as loop modeling[55,56], protein–protein docking[57,58], structure refinement[59-62], de novo protein design[63], enzyme design[64-66], and interface design[67-69].”