TY - JOUR
T1 - Toward the computational design of protein crystals with improved resolution
AU - Jeliazkov, Jeliazko R.
AU - Robinson, Aaron C.
AU - García-Moreno, Bertrand E.
AU - Bergera, James M.
AU - Gray, Jeffrey J.
N1 - Funding Information:
JRJ, ACR, JMB, BGME and JJG designed the research. JRJ and ACR performed the research. JRJ, ACR, JMB, BGME and JJG analyzed the data. JRJ, ACR, JMB, BGME and JJG wrote the paper. The authors would like to acknowledge Jesse B. Yoder for helpful discussion and Michael L. Love for help with instrumentation. The super-computing resources in this study have been provided in part by the Maryland Advanced Research Computing Center. Diffraction data were collected at the X-ray laboratory of the Department of Biophysics and Biophysical Chemistry, School of Medicine, Johns Hopkins University. JRJ was funded by NIGMS grants F31-GM123616 and T32- GM008403. JRJ and JJG were funded by NIGMS grant R01- GM078221. ACR and BGME were funded by NSF-MCB 1517378. JRJ, ACR, JMB, BGME and JJG were funded by a JHU Provost's Discovery Award.
Funding Information:
JRJ was funded by NIGMS grants F31-GM123616 and T32-GM008403. JRJ and JJG were funded by NIGMS grant R01-GM078221. ACR and BGME were funded by NSF-MCB 1517378. JRJ, ACR, JMB, BGME and JJG were funded by a JHU Provost’s Discovery Award.
Publisher Copyright:
© 2019 Wiley-Blackwell. All rights reserved.
PY - 2019/11/1
Y1 - 2019/11/1
N2 - Substantial advances have been made in the computational design of protein interfaces over the last 20 years. However, the interfaces targeted by design have typically been stable and high-affinity. Here, we report the development of a generic computational design method to stabilize the weak interactions at crystallographic interfaces. Initially, we analyzed structures reported in the Protein Data Bank to determine whether crystals with more stable interfaces result in higher resolution structures. We found that for 22 variants of a single protein crystallized by a single individual, the Rosetta-calculated 'crystal score' correlates with the reported diffraction resolution. We next developed and tested a computational design protocol, seeking to identify point mutations that would improve resolution in a highly stable variant of staphylococcal nuclease (SNase). Using a protocol based on fixed protein backbones, only one of the 11 initial designs crystallized, indicating modeling inaccuracies and forcing us to re-evaluate our strategy. To compensate for slight changes in the local backbone and side-chain environment, we subsequently designed on an ensemble of minimally perturbed protein backbones. Using this strategy, four of the seven designed proteins crystallized. By collecting diffraction data from multiple crystals per design and solving crystal structures, we found that the designed crystals improved the resolution modestly and in unpredictable ways, including altering the crystal space group. Post hoc, in silico analysis of the three observed space groups for SNase showed that the native space group was the lowest scoring for four of six variants (including the wild type), but that resolution did not correlate with crystal score, as it did in the preliminary results. Collectively, our results show that calculated crystal scores can correlate with reported resolution, but that the correlation is absent when the problem is inverted. This outcome suggests that more comprehensive modeling of the crystallographic state is necessary to design high-resolution protein crystals from poorly diffracting crystals.
AB - Substantial advances have been made in the computational design of protein interfaces over the last 20 years. However, the interfaces targeted by design have typically been stable and high-affinity. Here, we report the development of a generic computational design method to stabilize the weak interactions at crystallographic interfaces. Initially, we analyzed structures reported in the Protein Data Bank to determine whether crystals with more stable interfaces result in higher resolution structures. We found that for 22 variants of a single protein crystallized by a single individual, the Rosetta-calculated 'crystal score' correlates with the reported diffraction resolution. We next developed and tested a computational design protocol, seeking to identify point mutations that would improve resolution in a highly stable variant of staphylococcal nuclease (SNase). Using a protocol based on fixed protein backbones, only one of the 11 initial designs crystallized, indicating modeling inaccuracies and forcing us to re-evaluate our strategy. To compensate for slight changes in the local backbone and side-chain environment, we subsequently designed on an ensemble of minimally perturbed protein backbones. Using this strategy, four of the seven designed proteins crystallized. By collecting diffraction data from multiple crystals per design and solving crystal structures, we found that the designed crystals improved the resolution modestly and in unpredictable ways, including altering the crystal space group. Post hoc, in silico analysis of the three observed space groups for SNase showed that the native space group was the lowest scoring for four of six variants (including the wild type), but that resolution did not correlate with crystal score, as it did in the preliminary results. Collectively, our results show that calculated crystal scores can correlate with reported resolution, but that the correlation is absent when the problem is inverted. This outcome suggests that more comprehensive modeling of the crystallographic state is necessary to design high-resolution protein crystals from poorly diffracting crystals.
KW - Rosetta
KW - protein crystallography
KW - protein design
KW - staphylococcal nuclease
UR - http://www.scopus.com/inward/record.url?scp=85074572195&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85074572195&partnerID=8YFLogxK
U2 - 10.1107/S2059798319013226
DO - 10.1107/S2059798319013226
M3 - Article
C2 - 31692475
AN - SCOPUS:85074572195
SN - 0907-4449
VL - 75
SP - 1015
EP - 1027
JO - Acta Crystallographica Section D: Structural Biology
JF - Acta Crystallographica Section D: Structural Biology
ER -