Automated protein structure modeling in CASP9 by I-TASSER pipeline combined with QUARK-based ab initio folding and FG-MD-based structure refinement

By Dong Xu, Jian Zhang, Ambrish Roy, Yang Zhang. 2011

161 citations recorded by the source corpus.

I‐TASSER is an automated pipeline for protein tertiary structure prediction using multiple threading alignments and iterative structure assembly simulations. In CASP9 experiments, two new algorithms, QUARK and fragment‐guided molecular dynamics (FG‐MD), were added to the I‐TASSER pipeline for improving the structural modeling accuracy. QUARK is a de novo structure prediction algorithm used for structure modeling of proteins that lack detectable template structures. For distantly homologous targets, QUARK models are found useful as a reference structure for selecting good threading alignments and guiding the I‐TASSER structure assembly simulations. FG‐MD is an atomic‐level structural refinement program that uses structural fragments collected from the PDB structures to guide molecular dynamics simulation and improve the local structure of predicted model, including hydrogen‐bonding networks, torsion angles, and steric clashes. Despite considerable progress in both the template‐based and template‐free structure modeling, significant improvements on protein target classification, domain parsing, model selection, and ab initio folding of β‐proteins are still needed to further improve the I‐TASSER pipeline. Proteins 2011; © 2011 Wiley‐Liss, Inc.

Subfields: Materials Chemistry, Molecular Biology

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In Materials Chemistry

1. Yang Zhang
2. David Baker
3. Robin Pearce
4. Jinbo Xu
5. Frank DiMaio
6. David E. Kim
7. Chengxin Zhang
8. Sergey Ovchinnikov

In Molecular Biology

1. Yang Zhang
2. Robin Pearce
3. David Baker
4. Jinbo Xu
5. Chengxin Zhang
6. Frank DiMaio
7. David E. Kim
8. Yang Li

Citations in the corpus

• High resolution comparative modeling with RosettaCM (2013, methodology): “Many excellent methods for comparative modeling have been developed, including the widely used MODELLER program(Eswar et al., 2006; Sali and Blundell, 1993) and, more recently, I-Tasser(Xu et al., 2011) and other methods that explicitly recombine multiple templates.”
• A position-specific distance-dependent statistical potential for protein structure and functional study (2012, background): “These 18 servers are BAKER- ROSETTASERVER (Raman et al., 2009), chunk-TASSER (Zhou et al., 2009), chuo-fams (Kanou et al., 2009), CLEF-Server (Shao et al., 2011), FAMSD (Kanou et al., 2009), gws (Joo et al., 2009), HHpredA (Hildebrand et al., 2009), Jiang_Assembly (Hu et al., 2011), MULTICOM-CLUSTER”
• Assessment of the model refinement category in CASP12 (2017, background): “8 – 15 Lately, due to increasingly accurate physics-based force fields 10,16 – 21 and faster parallel computers and GPUs, MD in combination with physics-based force fields and smart constraints is increasingly used in successful refinement pipelines.”
• Atomic-Accuracy Prediction of Protein Loop Structures through an RNA-Inspired Ansatz (2012, background): “However, as assessed in blind trials, these computational algorithms achieve atomic accuracy only in favorable cases [5–7] or when guided by experimental data [8–10], even with the application of new kinds of specialized supercomputers [11].”
• In silico methods and tools for drug discovery (2021, methodology): “I-TASER I-TASER [144], Robetta server [145], and QUARK [146] are some of the available web servers for ab initio structure prediction.”
• ResQ: An approach to unified estimation of B-factor and residue-specific error in protein structure prediction (2015, result): “7 Å; these modeling results are largely consistent with the results from the I-TASSER modeling in the recent CASP experiments [9,10].”
• Protein Structure and Function Prediction Using I-TASSER (2015, methodology): “Starting from the SPICKER clusters, a second round of structure reassembly is performed to refine the structural models, with the low free-energy conformations refined by full-atomic simulations using FG-MD (Zhang et al., 2011) and ModRefiner (Xu and Zhang, 2011).”
• I-TASSER-MTD: a deep-learning-based platform for multi-domain protein structure and function prediction (2022, background): “Predicted distance/interface map for domain assembly ● Timing 5 min 36 Scroll down to see the predicted distance/interface map section for the domain model assembly (Fig.”