TY - JOUR
T1 - Protein Structure Determination by Assembling Super-Secondary Structure Motifs Using Pseudocontact Shifts
AU - Pilla, Kala Bharath
AU - Otting, Gottfried
AU - Huber, Thomas
N1 - Publisher Copyright:
© 2017 Elsevier Ltd
PY - 2017/3/7
Y1 - 2017/3/7
N2 - Computational and nuclear magnetic resonance hybrid approaches provide efficient tools for 3D structure determination of small proteins, but currently available algorithms struggle to perform with larger proteins. Here we demonstrate a new computational algorithm that assembles the 3D structure of a protein from its constituent super-secondary structural motifs (Smotifs) with the help of pseudocontact shift (PCS) restraints for backbone amide protons, where the PCSs are produced from different metal centers. The algorithm, DINGO-PCS (3D assembly of Individual Smotifs to Near-native Geometry as Orchestrated by PCSs), employs the PCSs to recognize, orient, and assemble the constituent Smotifs of the target protein without any other experimental data or computational force fields. Using a universal Smotif database, the DINGO-PCS algorithm exhaustively enumerates any given Smotif. We benchmarked the program against ten different protein targets ranging from 100 to 220 residues with different topologies. For nine of these targets, the method was able to identify near-native Smotifs.
AB - Computational and nuclear magnetic resonance hybrid approaches provide efficient tools for 3D structure determination of small proteins, but currently available algorithms struggle to perform with larger proteins. Here we demonstrate a new computational algorithm that assembles the 3D structure of a protein from its constituent super-secondary structural motifs (Smotifs) with the help of pseudocontact shift (PCS) restraints for backbone amide protons, where the PCSs are produced from different metal centers. The algorithm, DINGO-PCS (3D assembly of Individual Smotifs to Near-native Geometry as Orchestrated by PCSs), employs the PCSs to recognize, orient, and assemble the constituent Smotifs of the target protein without any other experimental data or computational force fields. Using a universal Smotif database, the DINGO-PCS algorithm exhaustively enumerates any given Smotif. We benchmarked the program against ten different protein targets ranging from 100 to 220 residues with different topologies. For nine of these targets, the method was able to identify near-native Smotifs.
KW - 3D structure determination
KW - DINGO-PCS
KW - Pseudocontact shifts
KW - Smotifs
UR - http://www.scopus.com/inward/record.url?scp=85012871712&partnerID=8YFLogxK
U2 - 10.1016/j.str.2017.01.011
DO - 10.1016/j.str.2017.01.011
M3 - Article
SN - 0969-2126
VL - 25
SP - 559
EP - 568
JO - Structure
JF - Structure
IS - 3
ER -