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.

Targeting the HVEM protein using a fragment of glycoprotein D to inhibit formation of the BTLA/HVEM complex.

Cancer immunotherapy using blockade of immune checkpoints is mainly based on monoclonal antibodies. Despite the tremendous success achieved by using those molecules to block immune checkpoint proteins, antibodies possess some weaknesses, which means that there is still a need to search for new compounds as alternatives to antibodies. Many current approaches are focused on use of peptides/peptidomimetics to destroy receptor/ligand interactions. Our studies concern blockade of the BTLA/HVEM complex, which generates an inhibitory effect on the immune response resulting in tolerance to cancer cells. To design inhibitors of such proteins binding we based our work on the amino acid sequence and structure of a ligand of HVEM protein, namely glycoprotein D, which possesses the same binding site on HVEM as BTLA protein. To disrupt the BTLA and HVEM interaction we designed several peptides, all fragments of glycoprotein D, and tested their binding to HVEM using SPR and their ability to inhibit the BTLA/HVEM complex formation using ELISA tests and cellular reporter platforms. That led to identification of two peptides, namely gD(1-36)(K10C-D30C) and gD(1-36)(A12C-L25C), which interact with HVEM and possess blocking capacities. Both peptides are not cytotoxic to human PBMCs, and show stability in human plasma. We also studied the 3D structure of the gD(1-36)(K10C-D30C) peptide using NMR and molecular modeling methods. The obtained data reveal that it possesses an unstructured conformation and binds to HVEM in the same location as gD and BTLA. All these results suggest that peptides based on the binding fragment of gD protein represent promising immunomodulation agents for future cancer immunotherapy.

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.

Theoretical Investigation of the Coronavirus SARS-CoV-2 (COVID-19) Infection Mechanism and Selectivity.

The SARS-CoV-2 virus, commonly known as COVID-19, first occurred in December 2019 in Wuhan, Hubei Province, China. Since then, it has become a tremendous threat to human health. With a pandemic threat, it is in the significant interest of the scientific world to establish its method of infection. In this manuscript, we combine knowledge of the infection mechanism with theoretical methods to answer the question of the virus's selectivity. We proposed a two-stage infection mechanism. In the first step, the virus interacts with the ACE2 receptor, with the "proper strength". When the interaction is too strong, the virus will remain in an "improper position"; if the interaction is too weak, the virus will "run away" from the cell. We also indicated three residues (positions 30, 31, and 353) located on the ACE2 protein-binding interface, which seems to be crucial for successful infection. Our results indicate that these residues are necessary for the initiation of the infection process.

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.

Fragments of gD Protein as Inhibitors of BTLA/HVEM Complex Formation-Design, Synthesis, and Cellular Studies.

One of the major current trends in cancer immunotherapy is the blockade of immune checkpoint proteins that negatively regulate the immune response. This has been achieved through antibodies blocking PD-1/PD-L1 and CTLA-4/CD80/CD86 interactions. Such antibodies have revolutionized oncological therapy and shown a new way to fight cancer. Additional (negative) immune checkpoints are also promising targets in cancer therapy and there is a demand for inhibitors for these molecules. Our studies are focused on BTLA/HVEM complex, which inhibits T-cell proliferation and cytokine production and therefore has great potential as a new target for cancer treatment. The goal of the presented studies was the design and synthesis of compounds able to block BTLA/HVEM interactions. For that purpose, the N-terminal fragment of glycoprotein D (gD), which interacts with HVEM, was used. Based on the crystal structure of the gD/HVEM complex and MM/GBSA analysis performed on it, several peptides were designed and synthesized as potential inhibitors of the BTLA/HVEM interaction. Affinity tests, ELISA tests, and cellular-based reporter assays were performed on these compounds to check their ability to bind to HVEM and to inhibit BTLA/HVEM complex formation. For leading peptides candidates, all-atom and subsequent docking simulations with a coarse-grained force field were performed to determine their binding modes. To further evaluate their potential as drug candidates, their stability in plasma and their cytotoxicity effects on PBMCs were assessed. Our data indicate that the peptide gD(1-36)(K10C-T29C) is the best candidate as a future drug. It interacts with HVEM protein, blocks the BTLA/HVEM interaction, and is nontoxic to cells. The present study provides a new perspective on the development of BTLA/HVEM inhibitors that disrupt protein interactions.

Disulfide-Linked Peptides for Blocking BTLA/HVEM Binding.

Immune checkpoints are crucial in the maintenance of antitumor immune responses. The activation or blockade of immune checkpoints is dependent on the interactions between receptors and ligands; such interactions can provide inhibitory or stimulatory signals, including the enhancement or suppression of T-cell proliferation, differentiation, and/or cytokine secretion. B-and T-lymphocyte attenuator (BTLA) is a lymphoid-specific cell surface receptor which is present on T-cells and interacts with herpes virus entry mediator (HVEM), which is present on tumor cells. The binding of HVEM to BTLA triggers an inhibitory signal which attenuates the immune response. This feature is interesting for studying the molecular interactions between HVEM and BTLA, as they may be targeted for novel immunotherapies. This work was based on the crystal structure of the BTLA/HVEM complex showing that BTLA binds the N-terminal cysteine-rich domain of HVEM. We investigated the amino acid sequence of HVEM and used molecular modeling methods to develop inhibitors of the BTLA/HVEM interaction. We synthesized novel compounds and determined their ability to interact with the BTLA protein and inhibit the formation of the BTLA/HVEM complex. Our results suggest that the HVEM (14-39) peptide is a potent inhibitor of the formation of the BTLA/HVEM protein complex.

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.

The molecular mechanism of structural changes in the antimicrobial peptide CM15 upon complex formation with drug molecule suramin: a computational analysis.

Dynamic increase of resistant bacterial infectious diseases continuously requires development of novel compounds against them. The molecular level understanding of the mechanism and interactions of natural host-defense peptides or antimicrobial peptides (AMPs) is an important step towards rational design and development of compounds inspired by their function. A particular set of these peptides have disordered structure, the ordering of which may modify their antimicrobial properties. Recent experiments demonstrate that such conformational transitions of AMPs could be mediated by the presence of small organic compounds, such as approved drug molecules. However, the molecular mechanisms underlying these structural changes are unclear. In this study, we apply molecular docking and molecular dynamics-based approaches to rigorously analyze the interactions between the drug suramin and the AMP CM15, a synthetic unstructured hybrid peptide. We characterize the energetic properties of putative CM15-suramin complexes revealing particular impacts of CM15 residues as well as the parts of suramin on these interactions. We find that α-helical content of the peptide is increased in the presence of suramin, which is in agreement with the experimental data. Kinetics analysis from canonical molecular dynamics and metadynamics simulations suggest that the effect of suramin does not promote the formation of α-helix but rather results from its ability to stabilize the α-helical population in the conformational pool of the peptide. Potentially, understanding the physico-chemical basis underlying the interactions between drug molecules and disordered AMPs will prove useful in strategies for antimicrobial compound development. Further on, the given computational protocol for the analysis of such flexible systems provide a basis for future theoretical investigation of similar biomolecular complexes.

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.