Improved consensus-fragment selection intemplate-assisted prediction of protein structureswith the UNRES force field in CASP13

Agnieszka Karczyńska , Karolina Zięba , Urszula Uciechowska , Magdalena Mozolewska , Paweł Krupa , Emilia Lubecka , Agnieszka Lipska , Celina Sikorska , Sergey Samsonov , Adam Sieradzan , Artur Giełdoń , Adam Liwo , Rafał Ślusarz , Magdalena Ślusarz , Jooyoung Lee , Keehyoung Joo , Cezary Czaplewski

Abstract

The method for protein-structure prediction, which combines the physics-based coarse-grained UNRES force field with knowledge-based modeling, has been developed further and tested in the 13th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP13). The method implements restraints from the consensus fragments common to server models. In this work, the server models to derive fragments have been chosen on the basis of quality assessment; a fully automatic fragment-selection procedure has been introduced, and Dynamic Fragment Assembly pseudopotentials have been fully implemented. The Global Distance Test Score (GDT_TS), averaged over our “Model 1” predictions, increased by over 10 units with respect to CASP12 for the free-modeling category to reach 40.82. Our “Model 1” predictions ranked 20 and 14 for all and free-modeling targets, respectively (upper 20.2% and 14.3% of all models submitted to CASP13 in these categories, respectively), compared to 27 (upper 21.1%) and 24 (upper 18.9%) in CASP12, respectively. For oligomeric targets, the Interface Patch Similarity (IPS) and Interface Contact Similarity (ICS) averaged over our best oligomer models increased from 0.28 to 0.36 and from 12.4 to 17.8, respectively, from CASP12 to CASP13, and top-ranking models of 2 targets (H0968 and T0997o) were obtained (none in CASP12). The improvement of our method in CASP13 over CASP12 was ascribed to the combined effect of the overall enhancement of server-model quality, our success in selecting server models and fragments to derive restraints, and improvements of the restraint and potential-energy functions.
Author Agnieszka Karczyńska (FCh/DTCh/LMM)
Agnieszka Karczyńska,,
- Laboratory of Molecular Modeling
, Karolina Zięba (FCh/DTCh/LSP)
Karolina Zięba,,
- Laboratory of Simulation of Polymers
, Urszula Uciechowska (FCh/DTCh/LMM)
Urszula Uciechowska,,
- Laboratory of Molecular Modeling
, Magdalena Mozolewska
Magdalena Mozolewska,,
-
, Paweł Krupa
Paweł Krupa,,
-
, Emilia Lubecka (FMPI/II)
Emilia Lubecka,,
- Institute of Informatics
, Agnieszka Lipska (FCh/DTCh/LMM)
Agnieszka Lipska,,
- Laboratory of Molecular Modeling
, Celina Sikorska (FCh/DTCh/LMM)
Celina Sikorska,,
- Laboratory of Molecular Modeling
, Sergey Samsonov (FCh/DTCh/LMM)
Sergey Samsonov,,
- Laboratory of Molecular Modeling
, Adam Sieradzan (FCh/DTCh/LMM)
Adam Sieradzan,,
- Laboratory of Molecular Modeling
et al.`
Journal seriesJournal of Chemical Information and Modeling, ISSN 1549-9596, e-ISSN 1549-960X, (N/A 100 pkt)
Issue year2020
Vol60
No3
Pages1844-1864
Publication size in sheets1.00
ASJC Classification3309 Library and Information Sciences; 1500 General Chemical Engineering; 1600 General Chemistry; 1706 Computer Science Applications
DOIDOI:10.1021/acs.jcim.9b00864
URL https://doi.org/10.1021/acs.jcim.9b00864
Languageen angielski
Score (nominal)100
Score sourcejournalList
ScoreMinisterial score = 100.0, 28-05-2020, ArticleFromJournal
Publication indicators WoS Citations = 0.000; Scopus SNIP (Source Normalised Impact per Paper): 2018 = 1.163; WoS Impact Factor: 2018 = 3.966 (2) - 2018=4.297 (5)
Citation count*
Cite
busy
Share Share

Get link to the record


* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
Back
Confirmation
Are you sure?