A general method for the derivation of the functional forms of the effective energy terms in coarse-grained energy functions of polymers. III. Determination of scale-consistent backbone-local and correlation potentials in the UNRES force field and force-

Liwo, Adam,Sieradzan, Adam K.,Lipska, Agnieszka G.,Czaplewski, Cezary,Joung, InSuk,Ż,mudziń,ska, Wioletta,Hałabis, Anna,Ołdziej, Stanisław American Institute of Physics 2019 The Journal of chemical physics Vol.150 No.15

Prediction of DNA and RNA structure with the NARES-2P force field and conformational space annealing

Sieradzan, Adam K.,Golon, Łukasz,Liwo, Adam The Royal Society of Chemistry 2018 Physical chemistry chemical physics Vol.20 No.29

<P>A physics-based method for the prediction of the structures of nucleic acids, which is based on the physics-based 2-bead NARES-2P model of polynucleotides and global-optimization Conformational Space Annealing (CSA) algorithm has been proposed. The target structure is sought as the global-energy-minimum structure, which ignores the entropy component of the free energy but spares expensive multicanonical simulations necessary to find the conformational ensemble with the lowest free energy. The CSA algorithm has been modified to optimize its performance when treating both single and multi-chain nucleic acids. It was shown that the method finds the native fold for simple RNA molecules and DNA duplexes and with limited distance restraints, which can easily be obtained from the secondary-structure-prediction servers, complex RNA folds can be treated with using moderate computer resources.</P>

Use of Restraints from Consensus Fragments of Multiple Server Models To Enhance Protein-Structure Prediction Capability of the UNRES Force Field

Mozolewska, Magdalena A.,Krupa, Paweł,Zaborowski, Bartłomiej,Liwo, Adam,Lee, Jooyoung,Joo, Keehyoung,Czaplewski, Cezary American Chemical Society 2016 JOURNAL OF CHEMICAL INFORMATION AND MODELING Vol.56 No.11

<P>Recently, we developed a new approach to protein-structure prediction, which combines template-based modeling with the physics-based coarse-grained UNited RESidue (UNRES) force field. In this approach, restrained multiplexed replica exchange molecular dynamics simulations with UNRES, with the C-alpha-distance and virtual-bond-dihedral angle restraints derived from knowledge-based models are carried out. In this work, we report a test of this approach in the 11th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP11), in which we used the template-based models from early-stage predictions by the LEE group CASP11 server (group 038, called 'nns'), and further improvement of the method. The quality of the models obtained in CASP11 was better than that resulting from unrestrained UNRES simulations; however, the obtained models were generally worse than the final nns models. Calculations with the final nns models, performed after CASP11, resulted in substantial improvement, especially for multi-domain proteins. Based on these results, we modified the procedure by deriving restraints from models from multiple servers, in this study the four top-performing servers in CASP11 (nns, BAKER-ROSETTASERVER, Zhang-server, and QUARK), and implementing either all restraints or only the restraints on the fragments that appear similar in the majority of models (the consensus fragments), outlier models discarded. Tests with 29 CASP11 human-prediction targets with length less than 400 amino-acid residues demonstrated that the consensus-fragment approach gave better results, i.e., lower a-carbon root-mean-square deviation from the experimental structures, higher template modeling score, and global distance test total score values than the best of the parent server models. Apart from global improvement (repacking and improving the orientation of domains and other substructures), improvement was also reached for template-based modeling targets, indicating that the approach has refinement capacity. Therefore, the consensus-fragment analysis is able to remove lower-quality models and poor-quality parts of the models without knowing the experimental structure.</P>

Prediction of Protein Structure by Template-Based Modeling Combined with the UNRES Force Field

Krupa, Paweł,Mozolewska, Magdalena A.,Joo, Keehyoung,Lee, Jooyoung,Czaplewski, Cezary,Liwo, Adam American Chemical Society 2015 Journal of chemical information and modeling Vol.55 No.6

<P>A new approach to the prediction of protein structures that uses distance and backbone virtual-bond dihedral angle restraints derived from template-based models and simulations with the united residue (UNRES) force field is proposed. The approach combines the accuracy and reliability of template-based methods for the segments of the target sequence with high similarity to those having known structures with the ability of UNRES to pack the domains correctly. Multiplexed replica-exchange molecular dynamics with restraints derived from template-based models of a given target, in which each restraint is weighted according to the accuracy of the prediction of the corresponding section of the molecule, is used to search the conformational space, and the weighted histogram analysis method and cluster analysis are applied to determine the families of the most probable conformations, from which candidate predictions are selected. To test the capability of the method to recover template-based models from restraints, five single-domain proteins with structures that have been well-predicted by template-based methods were used; it was found that the resulting structures were of the same quality as the best of the original models. To assess whether the new approach can improve template-based predictions with incorrectly predicted domain packing, four such targets were selected from the CASP10 targets; for three of them the new approach resulted in significantly better predictions compared with the original template-based models. The new approach can be used to predict the structures of proteins for which good templates can be found for sections of the sequence or an overall good template can be found for the entire sequence but the prediction quality is remarkably weaker in putative domain-linker regions.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/jcisd8/2015/jcisd8.2015.55.issue-6/acs.jcim.5b00117/production/images/medium/ci-2015-00117f_0010.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/ci5b00117'>ACS Electronic Supporting Info</A></P>

Maximum Likelihood Calibration of the UNRES Force Field for Simulation of Protein Structure and Dynamics

Krupa, Paweł,Hałabis, Anna,Ż,mudziń,ska, Wioletta,Ołdziej, Stanisław,Scheraga, Harold A.,Liwo, Adam American Chemical Society 2017 JOURNAL OF CHEMICAL INFORMATION AND MODELING Vol.57 No.9

<P>By using the maximum likelihood method for force-field calibration recently developed in our laboratory, which is aimed at achieving the agreement between the simulated conformational ensembles of selected training proteins and the corresponding ensembles determined experimentally at various temperatures, the physics-based coarse-grained UNRES force field for simulations of protein structure and dynamics was optimized with seven small training proteins exhibiting a variety of secondary and tertiary structures. Four runs of optimization, in which the number of optimized force-field parameters was gradually increased, were carried out, and the resulting force fields were subsequently tested with a set of 22 alpha-, 12 beta-, and 12 alpha + beta-proteins not used in optimization. The variant in which energy-term weights, local, and correlation potentials, side-chain radii, and anisotropies were optimized turned out to be the most transferable and outperformed all previous versions of UNRES on the test set.</P>

Use of the UNRES force field in template-assisted prediction of protein structures and the refinement of server models: Test with CASP12 targets

Karczyń,ska, Agnieszka,Mozolewska, Magdalena A.,Krupa, Paweł,Giełdoń,, Artur,Bojarski, Krzysztof K.,Zaborowski, Bartłomiej,Liwo, Adam,Ś,lusarz, Rafał,Ś,lusarz, Magdalena,Lee, Jooyo Elsevier 2018 Journal of molecular graphics & modelling Vol.83 No.-

<P><B>Abstract</B></P> <P>Knowledge-based methods are, at present, the most effective ones for the prediction of protein structures; however, their results heavily depend on the similarity of a target sequence to those of proteins with known structures. On the other hand, the physics-based methods, although still less accurate and more expensive to execute, are independent of databases and give reasonable results where the knowledge-based methods fail because of weak sequence similarity. Therefore, a plausible approach seems to be the use of knowledge-based methods to determine the sections of the structures that correspond to sufficient sequence similarity and physics-based methods to determine the remaining structure. By participating in the 12th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP12) as the KIAS-Gdansk group, we tested our recently developed hybrid approach, in which protein-structure prediction is carried out by using the physics-based UNRES coarse-grained energy function, with restraints derived from the server models. Best predictions among all groups were obtained for 2 targets and 80% of our models were in the upper 50% of the models submitted to CASP. Our method was also able to exclude, with about 70% confidence, the information from the servers that performed poorly on a given target. Moreover, the method resulted in the best models of 2 refinement targets and performed remarkably well on oligomeric targets.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Hybrid (physics- and template-based) approach to protein structure prediction. </LI> <LI> Molecular dynamics with coarse-grained UNRES model, restraints from templates. </LI> <LI> Restraints derived from similar fragments of multiple templates. </LI> <LI> Method able filter out information from poor templates (70% confidence). </LI> <LI> Outstanding prediction obtained for some targets. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>