Improved performance in CAPRI round 37 using LZerD docking and template-based modeling with combined scoring functions.

ABSTRACT: We report our group's performance for protein-protein complex structure prediction and scoring in Round 37 of the Critical Assessment of PRediction of Interactions (CAPRI), an objective assessment of protein-protein complex modeling. We demonstrated noticeable improvement in both prediction and scoring compared to previous rounds of CAPRI, with our human predictor group near the top of the rankings and our server scorer group at the top. This is the first time in CAPRI that a server has been the top scorer group. To predict protein-protein complex structures, we used both multi-chain template-based modeling (TBM) and our protein-protein docking program, LZerD. LZerD represents protein surfaces using 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D f

SUBMITTER: Peterson LX 

PROVIDER: S-EPMC5820220 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature