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

Krupa, Paweł; Hałabis, Anna; Żmudzińska, Wioletta; Ołdziej, Stanisław; Scheraga, Harold A.; Liwo, Adam

doi:10.1021/acs.jcim.7b00254

Cited by 43 publications

(55 citation statements)

References 86 publications

(220 reference statements)

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“…The data‐assisted‐prediction protocol developed in the laboratory of the KIAS‐Gdansk group and described in reference was used. The main step of this protocol is extensive conformational search by using the multiplexed replica‐exchange molecular dynamics (MREMD) method with the coarse‐grained UNRES force field . MD and MREMD were implemented in UNRES in our earlier work.…”

Section: Resultsmentioning

confidence: 99%

“…vertical not significantly better than horizontal; White: not enough shared targets between groups; Gray: vertical and horizontal are the same group the multiplexed replica-exchange molecular dynamics (MREMD) method 28,29 with the coarse-grained UNRES force field. [30][31][32]34 and MREMD 35 were implemented in UNRES in our earlier work.…”

Section: Overall Group Performance At Casp13mentioning

confidence: 99%

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Assessment of chemical‐crosslink‐assisted protein structure modeling in CASP13

et al. 2019

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With the advance of experimental procedures obtaining chemical crosslinking information is becoming a fast and routine practice. Information on crosslinks can greatly enhance the accuracy of protein structure modeling. Here, we review the current state of the art in modeling protein structures with the assistance of experimentally determined chemical crosslinks within the framework of the 13th meeting of Critical Assessment of Structure Prediction approaches. This largest‐to‐date blind assessment reveals benefits of using data assistance in difficult to model protein structure prediction cases. However, in a broader context, it also suggests that with the unprecedented advance in accuracy to predict contacts in recent years, experimental crosslinks will be useful only if their specificity and accuracy further improved and they are better integrated into computational workflows.

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Section: Resultsmentioning

confidence: 99%

Section: Overall Group Performance At Casp13mentioning

confidence: 99%

Assessment of chemical‐crosslink‐assisted protein structure modeling in CASP13

et al. 2019

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“…Regardless the case, the computational speed up, comes at the cost of resigning atomistic resolution 14,15 . Therefore, continuous efforts are devoted by several groups to improve even well established CG force fields 5,[16][17][18][19][20] . During the last years, our group has developed a CG force field called SIRAH (http:// www.sirahff.com).…”

Section: Introductionmentioning

confidence: 99%

The SIRAH force field 2.0: Altius, Fortius, Citius

Machado

Klein

et al. 2018

Preprint

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A new version of the coarse-grained (CG) SIRAH force field for proteins has been developed. Modifications to bonded and non-bonded interactions on the existing molecular topologies significantly ameliorate the structural description and flexibility of a non-redundant set of proteins. The SIRAH 2.0 force field has also been ported to the popular simulation package AMBER, which along with the former implementation in GROMACS expands significantly the potential range of users and performance of this CG force field on CPU/GPU codes. As a non-trivial example of application, we undertook the structural and dynamical analysis of the most abundant and conserved calcium-binding protein, namely, Calmodulin (CaM). CaM is constituted by two calcium-binding motifs called EF-hands, which in presence of Calcium specifically recognize a cognate peptide by embracing it. CG simulations of CaM bound to four Calcium ions in the presence or absence of a binding peptide (holo and apo forms, respectively), resulted in good and stable ion coordination. The simulation of the holo form starting from an experimental structure sampled nearnative conformations, retrieving quasi-atomistic precision. Removing the binding peptide enabled the EF-hands to perform large reciprocal movements, comparable to those observed in NMR structures. On the other hand, the isolated peptide starting from the helical conformation experienced spontaneous unfolding, in agreement with previous experimental data. However, repositioning the peptide in the neighborhood of one EF-hand not only prevented the peptide unfolding but also drove CaM to a fully bound conformation with both EF-hands embracing the cognate peptide, resembling the experimental holo structure. Therefore, SIRAH 2.0 showed the capacity to handle a number of structurally and dynamically challenging situations including metal ion coordination, unbiased conformational sampling, and specific protein-peptide recognition. 1-28TOC. 2-28 METHODS Re-parameterization of the Model.SIRAH uses a classical Hamiltonian common to most all-atoms potentials to describe particle-particle interactions. Briefly, bonds and angles were described by harmonic terms (e.g.: k b /2*(r-r b ) 2 , with force constant k b and equilibrium values r b ), while Fourier expansions were used for dihedrals. Non-bonded contributions were accounted by Coulomb and Particle Mesh Ewald summation (PME 34,35 ), while Lennard-Jones (LJ) terms were calculated using the standard 12-6 expression (i.e.: 4**[(/r) 12 -(/r) 6 ]). Lorentz-Berthelot combination rules were used for most atom-types pairs. However, specific LJ parameters were set for tuning interactions between some bead pairs (see below). The AMBER scaling factors SCEE=1.2 and SCNB=2.0 were used for the 1-4 non-bonded interactions.3-28 7-28 22-28

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“…A scheme illustrating the prediction procedure used in this work, which we established during the participation in previous CASP exercises is shown in Figure . As shown in the Figure , the prediction starts with performing multiplexed replica exchange runs with the coarse‐grained UNRES force field . In this work restraints derived from SAXS and server models were imposed; however, it should be noted that this stage can also be carried out in the ab initio mode, with no restraints .…”

Section: Methodsmentioning

confidence: 99%

“…As shown in the Figure 1, the prediction starts with performing multiplexed replica exchange runs with the coarsegrained UNRES force field. 26,31,32 In this work restraints derived from SAXS and server models were imposed; however, it should be noted that this stage can also be carried out in the ab initio mode, with no restraints. 30 The obtained ensemble of conformations is subsequently processed with weighted histogram analysis method (WHAM) 33 and the heat-capacity profile is calculated to determine the temperature at which the ensemble is analyzed, T a , which is taken as 20 K below the temperature of the major heat-capacity peak.…”

Section: Prediction Proceduresmentioning

confidence: 99%

Prediction of protein structure with the coarse‐grained UNRES force field assisted by small X‐ray scattering data and knowledge‐based information

et al. 2017

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A new approach to assisted protein-structure prediction has been proposed, which is based on running multiplexed replica exchange molecular dynamics simulations with the coarse-grained UNRES force field with restraints derived from knowledge-based models and distance distribution from small angle X-ray scattering (SAXS) measurements. The latter restraints are incorporated into the target function as a maximum-likelihood term that guides the shape of the simulated structures towards that defined by SAXS. The approach was first verified with the 1KOY protein, for which the distance distribution was calculated from the experimental structure, and subsequently used to predict the structures of 11 data-assisted targets in the CASP12 experiment. Major improvement of the GDT_TS was obtained for 2 targets, minor improvement for other 2 while, for 6 target GDT_TS deteriorated compared with that calculated for predictions without the SAXS data, partly because of assuming a wrong multimeric state (for Ts866) or because the crystal conformation was more compact than the solution conformation (for Ts942). Particularly good results were obtained for Ts909, in which use of SAXS data resulted in the selection of a correctly packed trimer and, subsequently, increased the GDT_TS of monomer prediction. It was found that running simulations with correct oligomeric state is essential for the success in SAXS-data-assisted prediction.

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

Cited by 43 publications

References 86 publications

Assessment of chemical‐crosslink‐assisted protein structure modeling in CASP13

Assessment of chemical‐crosslink‐assisted protein structure modeling in CASP13

The SIRAH force field 2.0: Altius, Fortius, Citius

Prediction of protein structure with the coarse‐grained UNRES force field assisted by small X‐ray scattering data and knowledge‐based information

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