Integration of QUARK and I‐TASSER for Ab Initio Protein Structure Prediction in CASP11

Abstract

We tested two pipelines developed for template-free protein structure prediction in the CASP11 experiment. First, the QUARK pipeline constructs structure models by reassembling fragments of continuously distributed lengths excised from unrelated proteins. Five free-modeling (FM) targets have the model successfully constructed by QUARK with a TM-score above 0.4, including the first model of T0837-D1, which has a TM-score=0.736 and RMSD=2.9 Å to the native. Detailed analysis showed that the success is partly attributed to the high-resolution contact map prediction derived from fragment-based distance-profiles, which are mainly located between regular secondary structure elements and loops/turns and help guide the orientation of secondary structure assembly. In the Zhang-Server pipeline, weakly scoring threading templates are re-ordered by the structural similarity to the ab initio folding models, which are then reassembled by I-TASSER based structure assembly simulations; 60% more domains with length up to 204 residues, compared to the QUARK pipeline, were successfully modeled by the I-TASSER pipeline with a TM-score above 0.4. The robustness of the I-TASSER pipeline can stem from the composite fragment-assembly simulations that combine structures from both ab initio folding and threading template refinements. Despite the promising cases, challenges still exist in long-range beta-strand folding, domain parsing, and the uncertainty of secondary structure prediction; the latter of which was found to affect nearly all aspects of FM structure predictions, from fragment identification, target classification, structure assembly, to final model selection. Significant efforts are needed to solve these problems before real progress on FM could be made.

Deep‐learning contact‐map guided protein structure prediction in CASP13

“…For each of these models, we obtain different rankings from seven Model Quality Assurance Programs (MQAP) based on the C‐score, structural consensus (the average TM‐score of the target model to all other models), the contact satisfaction between the model contacts and predicted contacts, and four statistical energy functions (RWplus, GOAP, DOPE and ROTAS). The final model rankings are determined by ascending order of overall MQAP score.…”

OPUS‐SSF: A side‐chain‐inclusive scoring function for ranking protein structural models

“…Beside the 11 commonly used decoy sets used in GOAP and OPUS‐CSF, including decoy sets of 4state_reduced, fisa, fisa_casp3, hg_structal, ig_structal and ig_structal_hires (R. Samudrala, E. Huang, and M. Levitt, unpublished), I‐TASSER, lattice_ssfit, lmds, MOULDER, and ROSETTA, we also tested OPUS‐SSF on casp‐good set (that contains 143 protein targets generated during CASP5‐CASP8) and I‐TASSER9, I‐TASSER10, I‐TASSER11 sets (decoy sets generated by I‐TASSER server from CASP9, CASP10, CASP11, downloaded from the website of Dr. Yang Zhang's group).…”

Ergodicity and model quality in template‐restrained canonical and temperature/Hamiltonian replica exchange coarse‐grained molecular dynamics simulations of proteins

“…To determine whether the use of HREMD, which exhibits better ergodicity compared to MREMD, can improve the quality of the resulting models, we tried the four CASP11 targets: T0767, T0771, T0802, and T0828, which were treated in our latest work . For each of these proteins, 5 models from each of the nns, BAKER‐ROSETTASERVER, Zhang‐Server, and QUARK servers were used. As mentioned in the Introduction, because the server models of these targets were very divergent, we imposed the restraints only on those fragments which were found to overlap well for all server models.…”

“…None of the server models used to derive the restraints captures the entire fold. In our previous study, using the consensus‐fragments from the nns, BAKER‐ROSETTASERVER, Zhang‐Server, and QUARK server models, we produced a model of better quality for T0828 but not for the remaining three proteins.…”

“…An area where restrained simulations are very widely applied is the prediction of protein structures from amino‐acid sequences . Because of insufficient supply of the structures of newly‐discovered proteins by the experimental methods, research on this subject is an important branch of computational chemistry and biology.…”