UNRES-GPU for physics-based coarse-grained simulations of protein systems at biological time- and size-scales.

SUMMARY: The UNited RESisdue (UNRES) package for coarse-grained simulations, which has recently been optimized to treat large protein systems, has been implemented on Graphical Processor Units (GPUs). An over 100-time speed-up of the GPU code (run on an NVIDIA A100) with respect to the sequential code and an 8.5 speed-up with respect to the parallel Open Multi-Processing (OpenMP) code (run on 32 cores of 2 AMD EPYC 7313 Central Processor Units (CPUs)) has been achieved for large proteins (with size over 10 000 residues). Due to the averaging over the fine-grain degrees of freedom, 1 time unit of UNRES simulations is equivalent to about 1000 time units of laboratory time; therefore, millisecond time scale of large protein systems can be reached with the UNRES-GPU code. AVAILABILITY AND IMPLEMENTATION: The source code of UNRES-GPU along with the benchmarks used for tests is available at https://projects.task.gda.pl/eurohpcpl-public/unres.

Integrating Explicit and Implicit Fullerene Models into UNRES Force Field for Protein Interaction Studies.

Fullerenes, particularly C60, exhibit unique properties that make them promising candidates for various applications, including drug delivery and nanomedicine. However, their interactions with biomolecules, especially proteins, remain not fully understood. This study implements both explicit and implicit C60 models into the UNRES coarse-grained force field, enabling the investigation of fullerene-protein interactions without the need for restraints to stabilize protein structures. The UNRES force field offers computational efficiency, allowing for longer timescale simulations while maintaining accuracy. Five model proteins were studied: FK506 binding protein, HIV-1 protease, intestinal fatty acid binding protein, PCB-binding protein, and hen egg-white lysozyme. Molecular dynamics simulations were performed with and without C60 to assess protein stability and investigate the impact of fullerene interactions. Analysis of contact probabilities reveals distinct interaction patterns for each protein. FK506 binding protein (1FKF) shows specific binding sites, while intestinal fatty acid binding protein (1ICN) and uteroglobin (1UTR) exhibit more generalized interactions. The explicit C60 model shows good agreement with all-atom simulations in predicting protein flexibility, the position of C60 in the binding pocket, and the estimation of effective binding energies. The integration of explicit and implicit C60 models into the UNRES force field, coupled with recent advances in coarse-grained modeling and multiscale approaches, provides a powerful framework for investigating protein-nanoparticle interactions at biologically relevant scales without the need to use restraints stabilizing the protein, thus allowing for large conformational changes to occur. These computational tools, in synergy with experimental techniques, can aid in understanding the mechanisms and consequences of nanoparticle-biomolecule interactions, guiding the design of nanomaterials for biomedical applications.

Long-time scale simulations of virus-like particles from three human-norovirus strains.

The dynamics of the virus like particles (VLPs) corresponding to the GII.4 Houston, GII.2 SMV, and GI.1 Norwalk strains of human noroviruses (HuNoV) that cause gastroenteritis was investigated by means of long-time (about 30 µs in the laboratory timescale) molecular dynamics simulations with the coarse-grained UNRES force field. The main motion of VLP units turned out to be the bending at the junction between the P1 subdomain (that sits in the VLP shell) and the P2 subdomain (that protrudes outside) of the major VP1 protein, this resulting in a correlated wagging motion of the P2 subdomains with respect to the VLP surface. The fluctuations of the P2 subdomain were found to be more pronounced and the P2 domain made a greater angle with the normal to the VLP surface for the GII.2 strain, which could explain the inability of this strain to bind the histo-blood group antigens (HBGAs).

Optimization of parallel implementation of UNRES package for coarse-grained simulations to treat large proteins.

We report major algorithmic improvements of the UNRES package for physics-based coarse-grained simulations of proteins. These include (i) introduction of interaction lists to optimize computations, (ii) transforming the inertia matrix to a pentadiagonal form to reduce computing and memory requirements, (iii) removing explicit angles and dihedral angles from energy expressions and recoding the most time-consuming energy/force terms to minimize the number of operations and to improve numerical stability, (iv) using OpenMP to parallelize those sections of the code for which distributed-memory parallelization involves unfavorable computing/communication time ratio, and (v) careful memory management to minimize simultaneous access of distant memory sections. The new code enables us to run molecular dynamics simulations of protein systems with size exceeding 100,000 amino-acid residues, reaching over 1 ns/day (1 µs/day in all-atom timescale) with 24 cores for proteins of this size. Parallel performance of the code and comparison of its performance with that of AMBER, GROMACS and MARTINI 3 is presented.

Design, synthesis and biological evaluation of PD-1 derived peptides as inhibitors of PD-1/PD-L1 complex formation for cancer therapy.

Over the past few years, many molecules such as monoclonal antibodies, affibodies, nanobodies, and small compounds have been designed and tested as inhibitors of PD-1/PD-L1 complex formation. Some of them have been successfully implemented into clinical oncology practice. However, the majority of these compounds have disadvantages and limitations, such as high production price, potential for immunogenicity and/or prolonged clearance. Thus, new inhibitors of the PD-1/PD-L1 immune checkpoints are needed. Recently, peptides emerged as potential novel approach for blocking receptor/ligand interaction. In the presented studies we have designed, synthesised and tested peptides, which are potential inhibitors of the PD-1/PD-L1 axis. The amino acid sequences of the designed peptides were based on the binding sites of PD-1 to PD-L1, as determined by the crystal structure of the protein complex and also based on MM/GBSA analysis. Interactions of the peptides with PD-L1 protein were confirmed using SPR, while their inhibitory properties were studied using cell-based PD-1/PD-L1 immune checkpoint blockade assays. The characterization of the peptides has shown that the peptides PD-1(119-142)T120C-E141C, PD-1(119-142)C123-S137C and PD-1(122-138)C123-S137C strongly bind to PD-L1 protein and disrupt the interaction of the proteins. PD-1(122-138)C123-S137C peptide was shown to have the best inhibitory potential from the panel of peptides. Its 3D NMR structure was determined and the binding site to PD-L1 was established using molecular modelling methods. Our results indicate that the PD-1 derived peptides are able to mimic the PD-1 protein and inhibit PD-1/PD-L1 complex formation.

Mitochondrial potassium channels: A novel calcitriol target.

BACKGROUND: Calcitriol (an active metabolite of vitamin D) modulates the expression of hundreds of human genes by activation of the vitamin D nuclear receptor (VDR). However, VDR-mediated transcriptional modulation does not fully explain various phenotypic effects of calcitriol. Recently a fast non-genomic response to vitamin D has been described, and it seems that mitochondria are one of the targets of calcitriol. These non-classical calcitriol targets open up a new area of research with potential clinical applications. The goal of our study was to ascertain whether calcitriol can modulate mitochondrial function through regulation of the potassium channels present in the inner mitochondrial membrane. METHODS: The effects of calcitriol on the potassium ion current were measured using the patch-clamp method modified for the inner mitochondrial membrane. Molecular docking experiments were conducted in the Autodock4 program. Additionally, changes in gene expression were investigated by qPCR, and transcription factor binding sites were analyzed in the CiiiDER program. RESULTS: For the first time, our results indicate that calcitriol directly affects the activity of the mitochondrial large-conductance Ca2+-regulated potassium channel (mitoBKCa) from the human astrocytoma (U-87 MG) cell line but not the mitochondrial calcium-independent two-pore domain potassium channel (mitoTASK-3) from human keratinocytes (HaCaT). The open probability of the mitoBKCa channel in high calcium conditions decreased after calcitriol treatment and the opposite effect was observed in low calcium conditions. Moreover, using the AutoDock4 program we predicted the binding poses of calcitriol to the calcium-bound BKCa channel and identified amino acids interacting with the calcitriol molecule. Additionally, we found that calcitriol influences the expression of genes encoding potassium channels. Such a dual, genomic and non-genomic action explains the pleiotropic activity of calcitriol. CONCLUSIONS: Calcitriol can regulate the mitochondrial large-conductance calcium-regulated potassium channel. Our data open a new chapter in the study of non-genomic responses to vitamin D with potential implications for mitochondrial bioenergetics and cytoprotective mechanisms.

Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment.

We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70-75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70-80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.

Improved Consensus-Fragment Selection in Template-Assisted Prediction of Protein Structures with the UNRES Force Field in CASP13.

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.

UNRES server for physics-based coarse-grained simulations and prediction of protein structure, dynamics and thermodynamics.

A server implementation of the UNRES package (http://www.unres.pl) for coarse-grained simulations of protein structures with the physics-based UNRES model, coined a name UNRES server, is presented. In contrast to most of the protein coarse-grained models, owing to its physics-based origin, the UNRES force field can be used in simulations, including those aimed at protein-structure prediction, without ancillary information from structural databases; however, the implementation includes the possibility of using restraints. Local energy minimization, canonical molecular dynamics simulations, replica exchange and multiplexed replica exchange molecular dynamics simulations can be run with the current UNRES server; the latter are suitable for protein-structure prediction. The user-supplied input includes protein sequence and, optionally, restraints from secondary-structure prediction or small x-ray scattering data, and simulation type and parameters which are selected or typed in. Oligomeric proteins, as well as those containing D-amino-acid residues and disulfide links can be treated. The output is displayed graphically (minimized structures, trajectories, final models, analysis of trajectory/ensembles); however, all output files can be downloaded by the user. The UNRES server can be freely accessed at http://unres-server.chem.ug.edu.pl.

Structural Characterization of Covalently Stabilized Human Cystatin C Oligomers.

Human cystatin C (HCC), a cysteine-protease inhibitor, exists as a folded monomer under physiological conditions but has the ability to self-assemble via domain swapping into multimeric states, including oligomers with a doughnut-like structure. The structure of the monomeric HCC has been solved by X-ray crystallography, and a covalently linked version of HCC (stab-1 HCC) is able to form stable oligomeric species containing 10-12 monomeric subunits. We have performed molecular modeling, and in conjunction with experimental parameters obtained from atomic force microscopy (AFM), transmission electron microscopy (TEM) and small-angle X-ray scattering (SAXS) measurements, we observe that the structures are essentially flat, with a height of about 2 nm, and the distance between the outer edge of the ring and the edge of the central cavity is ~5.1 nm. These dimensions correspond to the height and diameter of one stab-1 HCC subunit and we present a dodecamer model for stabilized cystatin C oligomers using molecular dynamics simulations and experimentally measured parameters. Given that oligomeric species in protein aggregation reactions are often transient and very highly heterogeneous, the structural information presented here on these isolated stab-1 HCC oligomers may be useful to further explore the physiological relevance of different structural species of cystatin C in relation to protein misfolding disease.

Assessment of chemical-crosslink-assisted protein structure modeling in CASP13.

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.

Molecular dynamics insights into protein-glycosaminoglycan systems from microsecond-scale simulations.

Heparin is a key player in cell signaling via its physical interactions with protein targets in the extracellular matrix. However, basic molecular level understanding of these highly biologically relevant intermolecular interactions is still incomplete. In this study, for the first time, microsecond-scale MD simulations are reported for a complex between fibroblast growth factor 1 and heparin. We rigorously analyze this molecular system in terms of the conformational space, structural, energetic, and dynamic characteristics. We reveal that the conformational selection mechanism of binding denotes a recognition specificity determinant. We conclude that the length of the simulation could be crucial for evaluation of some of the analyzed parameters. Our data provide novel significant insights into the interactions in the fibroblast growth factor 1 complex with heparin, in particular, and into the physical-chemical nature of protein-glycosaminoglycan systems in general, which have potential applicability for biomaterials development in the area of regenerative medicine.

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-field calibration and validation.

The general theory of the construction of scale-consistent energy terms in the coarse-grained force fields presented in Paper I of this series has been applied to the revision of the UNRES force field for physics-based simulations of proteins. The potentials of mean force corresponding to backbone-local and backbone-correlation energy terms were calculated from the ab initio energy surfaces of terminally blocked glycine, alanine, and proline, and the respective analytical expressions, derived by using the scale-consistent formalism, were fitted to them. The parameters of all these potentials depend on single-residue types, thus reducing their number and preventing over-fitting. The UNRES force field with the revised backbone-local and backbone-correlation terms was calibrated with a set of four small proteins with basic folds: tryptophan cage variant (TRP1; α), Full Sequence Design (FSD; α + ß), villin headpiece (villin; α), and a truncated FBP-28 WW-domain variant (2MWD; ß) (the NEWCT-4P force field) and, subsequently, with an enhanced set of 9 proteins composed of TRP1, FSD, villin, 1BDC (α), 2I18 (α), 1QHK (α + ß), 2N9L (α + ß), 1E0L (ß), and 2LX7 (ß) (the NEWCT-9P force field). The NEWCT-9P force field performed better than NEWCT-4P in a blind-prediction-like test with a set of 26 proteins not used in calibration and outperformed, in a test with 76 proteins, the most advanced OPT-WTFSA-2 version of UNRES with former backbone-local and backbone-correlation terms that contained more energy terms and more optimizable parameters. The NEWCT-9P force field reproduced the bimodal distribution of backbone-virtual-bond angles in the simulated structures, as observed in experimental protein structures.

A new protein nucleic-acid coarse-grained force field based on the UNRES and NARES-2P force fields.

Based on the coarse-grained UNRES and NARES-2P models of proteins and nucleic acids, respectively, developed in our laboratory, in this work we have developed a coarse-grained model of systems containing proteins and nucleic acids. The UNRES and NARES-2P effective energy functions have been applied to the protein and nucleic-acid components of a system, respectively, while protein-nucleic-acid interactions have been described by the respective coarse-grained potentials developed in our recent work (Yin et al., J. Chem Theory Comput. 2015, 11, 1792). The Debye-Hückel screening has been applied to the electrostatic-interaction energy between the phosphate groups and charged amino-acid side chains. The model has been integrated into the UNRES package for coarse-grained molecular dynamics simulations of proteins and the implementation has been tested for energy conservation in microcanonical molecular dynamics runs and for temperature conservation in canonical molecular dynamics runs. Two case studies were performed: (i) the dynamics of the Ku protein heterodimer bound to DNA, for which it was found that the Ku70/Ku80 protein complex plays an active role in DNA repairing and (ii) conformational changes of the multiple antibiotic resistance (MarA) protein occurring during DNA binding, for which the functionally important motions occurring during this process were identified. © 2018 Wiley Periodicals, Inc.

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

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.

Introduction of steered molecular dynamics into UNRES coarse-grained simulations package.

In this article, an implementation of steered molecular dynamics (SMD) in coarse-grain UNited RESidue (UNRES) simulations package is presented. Two variants of SMD have been implemented: with a constant force and a constant velocity. The huge advantage of SMD implementation in the UNRES force field is that it allows to pull with the speed significantly lower than the accessible pulling speed in simulations with all-atom representation of a system, with respect to a reasonable computational time. Therefore, obtaining pulling speed closer to those which appear in the atomic force spectroscopy is possible. The newly implemented method has been tested for behavior in a microcanonical run to verify the influence of introduction of artificial constrains on keeping total energy of the system. Moreover, as time dependent artificial force was introduced, the thermostat behavior was tested. The new method was also tested via unfolding of the Fn3 domain of human contactin 1 protein and the I27 titin domain. Obtained results were compared with Gø-like force field, all-atom force field, and experimental results. © 2017 Wiley Periodicals, Inc.

Performance of protein-structure predictions with the physics-based UNRES force field in CASP11.

Participating as the Cornell-Gdansk group, we have used our physics-based coarse-grained UNited RESidue (UNRES) force field to predict protein structure in the 11th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP11). Our methodology involved extensive multiplexed replica exchange simulations of the target proteins with a recently improved UNRES force field to provide better reproductions of the local structures of polypeptide chains. All simulations were started from fully extended polypeptide chains, and no external information was included in the simulation process except for weak restraints on secondary structure to enable us to finish each prediction within the allowed 3-week time window. Because of simplified UNRES representation of polypeptide chains, use of enhanced sampling methods, code optimization and parallelization and sufficient computational resources, we were able to treat, for the first time, all 55 human prediction targets with sizes from 44 to 595 amino acid residues, the average size being 251 residues. Complete structures of six single-domain proteins were predicted accurately, with the highest accuracy being attained for the T0769, for which the CαRMSD was 3.8 Å for 97 residues of the experimental structure. Correct structures were also predicted for 13 domains of multi-domain proteins with accuracy comparable to that of the best template-based modeling methods. With further improvements of the UNRES force field that are now underway, our physics-based coarse-grained approach to protein-structure prediction will eventually reach global prediction capacity and, consequently, reliability in simulating protein structure and dynamics that are important in biochemical processes. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://www.unres.pl/ CONTACT: has5@cornell.edu.

A general method for the derivation of the functional forms of the effective energy terms in coarse-grained energy functions of polymers. I. Backbone potentials of coarse-grained polypeptide chains.

A general and systematic method for the derivation of the functional expressions for the effective energy terms in coarse-grained force fields of polymer chains is proposed. The method is based on the expansion of the potential of mean force of the system studied in the cluster-cumulant series and expanding the all-atom energy in the Taylor series in the squares of interatomic distances about the squares of the distances between coarse-grained centers, to obtain approximate analytical expressions for the cluster cumulants. The primary degrees of freedom to average about are the angles for collective rotation of the atoms contained in the coarse-grained interaction sites about the respective virtual-bond axes. The approach has been applied to the revision of the virtual-bond-angle, virtual-bond-torsional, and backbone-local-and-electrostatic correlation potentials for the UNited RESidue (UNRES) model of polypeptide chains, demonstrating the strong dependence of the torsional and correlation potentials on virtual-bond angles, not considered in the current UNRES. The theoretical considerations are illustrated with the potentials calculated from the ab initiopotential-energysurface of terminally blocked alanine by numerical integration and with the statistical potentials derived from known protein structures. The revised torsional potentials correctly indicate that virtual-bond angles close to 90° result in the preference for the turn and helical structures, while large virtual-bond angles result in the preference for polyproline II and extended backbone geometry. The revised correlation potentials correctly reproduce the preference for the formation of ß-sheet structures for large values of virtual-bond angles and for the formation of α-helical structures for virtual-bond angles close to 90°.

Molecular dynamics of protein A and a WW domain with a united-residue model including hydrodynamic interaction.

The folding of the N-terminal part of the B-domain of staphylococcal protein A (PDB ID: 1BDD, a 46-residue three-α-helix bundle) and the formin-binding protein 28 WW domain (PDB ID: 1E0L, a 37-residue three-stranded anti-parallel ß protein) was studied by means of Langevin dynamics with the coarse-grained UNRES force field to assess the influence of hydrodynamic interactions on protein-folding pathways and kinetics. The unfolded, intermediate, and native-like structures were identified by cluster analysis, and multi-exponential functions were fitted to the time dependence of the fractions of native and intermediate structures, respectively, to determine bulk kinetics. It was found that introducing hydrodynamic interactions slows down both the formation of an intermediate state and the transition from the collapsed structures to the final native-like structures by creating multiple kinetic traps. Therefore, introducing hydrodynamic interactions considerably slows the folding, as opposed to the results obtained from earlier studies with the use of Go-like models.

Lessons from application of the UNRES force field to predictions of structures of CASP10 targets.

The performance of the physics-based protocol, whose main component is the United Residue (UNRES) physics-based coarse-grained force field, developed in our laboratory for the prediction of protein structure from amino acid sequence, is illustrated. Candidate models are selected, based on probabilities of the conformational families determined by multiplexed replica-exchange simulations, from the 10th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP10). For target T0663, classified as a new fold, which consists of two domains homologous to those of known proteins, UNRES predicted the correct symmetry of packing, in which the domains are rotated with respect to each other by 180° in the experimental structure. By contrast, models obtained by knowledge-based methods, in which each domain is modeled very accurately but not rotated, resulted in incorrect packing. Two UNRES models of this target were featured by the assessors. Correct domain packing was also predicted by UNRES for the homologous target T0644, which has a similar structure to that of T0663, except that the two domains are not rotated. Predictions for two other targets, T0668 and T0684_D2, are among the best ones by global distance test score. These results suggest that our physics-based method has substantial predictive power. In particular, it has the ability to predict domain-domain orientations, which is a significant advance in the state of the art.