Transferable Mixing of Atomistic and Coarse-Grained Water Models

Immunoinformatics-aided rational design of a multi-epitope vaccine targeting feline infectious peritonitis virus

Feline infectious peritonitis (FIP) is a grave and frequently lethal ailment instigated by feline coronavirus (FCoV) in wild and domestic feline species. The spike (S) protein of FCoV assumes a critical function in viral ingress and infection, thereby presenting a promising avenue for the development of a vaccine. In this investigation, an immunoinformatics approach was employed to ascertain immunogenic epitopes within the S-protein of FIP and formulate an innovative vaccine candidate. By subjecting the amino acid sequence of the FIP S-protein to computational scrutiny, MHC-I binding T-cell epitopes were predicted, which were subsequently evaluated for their antigenicity, toxicity, and allergenicity through in silico tools. Our analyses yielded the identification of 11 potential epitopes capable of provoking a robust immune response against FIPV. Additionally, molecular docking analysis demonstrated the ability of these epitopes to bind with feline MHC class I molecules. Through the utilization of suitable linkers, these epitopes, along with adjuvants, were integrated to design a multi-epitope vaccine candidate. Furthermore, the stability of the interaction between the vaccine candidate and feline Toll-like receptor 4 (TLR4) was established via molecular docking and molecular dynamics simulation analyses. This suggests good prospects for future experimental validation to ascertain the efficacy of our vaccine candidate in inducing a protective immune response against FIP.

Designing a multi-epitope candidate vaccine by employing immunoinformatics approaches to control African swine fever spread

The African swine fever virus has been circulating for decades and is highly infectious, often fatal to farmed and wild pigs. There is currently no approved vaccine or treatment for the disease, making prevention even more difficult. Therefore, vaccine development is necessary and urgent to limit the consequences of ASF and ensure the food chain and sustainability of the swine industry. This research study was conducted to design a multi-epitope vaccine for controlling veterinary diseases caused by the African swine fever virus. We employed the immunoinformatics approaches to reveal 37 epitopes from different viral proteins of ASFV. These epitopes were linked to adjuvants and linkers to form a full-fledged immunogenic vaccine construct. The tertiary structure of the final vaccine was predicted using a deep-learning approach. The molecular docking and molecular dynamics predicted stable interactions between the vaccine and immune receptor TLR5 of Sus scrofa (Pig). The MD simulation studies reflect that the calculated parameters like RMSD, RMSF, number of hydrogen bonds, and finally, the buried interface surface area for the complex remained stable throughout the simulation time. This analysis suggests the stability of interface interactions between the TLR5 and the multi-epitope vaccine construct. Further, the physiochemical analysis demonstrated that our designed vaccine construct was expected to have high stability and prolonged half-life time in mammalian cells. Traditional vaccine design experiments require significant time and financial input from the development stage to the final product. Studies like this can assist in accelerating vaccine development while minimizing the cost.Communicated by Ramaswamy H. Sarma.

Pragmatic Coarse-Graining of Proteins: Models and Applications

The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.

A morpheein equilibrium regulates catalysis in phosphoserine phosphatase SerB2 from Mycobacterium tuberculosis

Mycobacterium tuberculosis phosphoserine phosphatase MtSerB2 is of interest as a new antituberculosis target due to its essential metabolic role in L-serine biosynthesis and effector functions in infected cells. Previous works indicated that MtSerB2 is regulated through an oligomeric transition induced by L-Ser that could serve as a basis for the design of selective allosteric inhibitors. However, the mechanism underlying this transition remains highly elusive due to the lack of experimental structural data. Here we describe a structural, biophysical, and enzymological characterisation of MtSerB2 oligomerisation in the presence and absence of L-Ser. We show that MtSerB2 coexists in dimeric, trimeric, and tetrameric forms of different activity levels interconverting through a conformationally flexible monomeric state, which is not observed in two near-identical mycobacterial orthologs. This morpheein behaviour exhibited by MtSerB2 lays the foundation for future allosteric drug discovery and provides a starting point to the understanding of its peculiar multifunctional moonlighting properties.

The SIRAH force field: A suite for simulations of complex biological systems at the coarse-grained and multiscale levels

The different combinations of molecular dynamics simulations with coarse-grained representations have acquired considerable popularity among the scientific community. Especially in biocomputing, the significant speedup granted by simplified molecular models opened the possibility of increasing the diversity and complexity of macromolecular systems, providing realistic insights on large assemblies for more extended time windows. However, a holistic view of biological ensembles' structural and dynamic features requires a self-consistent force field, namely, a set of equations and parameters that describe the intra and intermolecular interactions among moieties of diverse chemical nature (i.e., nucleic and amino acids, lipids, solvent, ions, etc.). Nevertheless, examples of such force fields are scarce in the literature at the fully atomistic and coarse-grained levels. Moreover, the number of force fields capable of handling simultaneously different scales is restricted to a handful. Among those, the SIRAH force field, developed in our group, furnishes a set of topologies and tools that facilitate the setting up and running of molecular dynamics simulations at the coarse-grained and multiscale levels. SIRAH uses the same classical pairwise Hamiltonian function implemented in the most popular molecular dynamics software. In particular, it runs natively in AMBER and Gromacs engines, and porting it to other simulation packages is straightforward. This review describes the underlying philosophy behind the development of SIRAH over the years and across families of biological molecules, discussing current limitations and future implementations.

Secreted Aspartyl Proteinases Targeted Multi-Epitope Vaccine Design for Candida dubliniensis Using Immunoinformatics

Candida dubliniensis is an opportunistic pathogen associated with oral and invasive fungal infections in immune-compromised individuals. Furthermore, the emergence of C. dubliniensis antifungal drug resistance could exacerbate its treatment. Hence, in this study a multi-epitope vaccine candidate has been designed using an immunoinformatics approach by targeting C. dubliniensis secreted aspartyl proteinases (SAP) proteins. In silico tools have been utilized to predict epitopes and determine their allergic potential, antigenic potential, toxicity, and potential to elicit interleukin-2 (IL2), interleukin-4 (IL4), and IFN-γ. Using the computational tools, eight epitopes have been predicted that were then linked with adjuvants for final vaccine candidate development. Computational immune simulation has depicted that the immunogen designed emerges as a strong immunogenic candidate for a vaccine. Further, molecular docking and molecular dynamics simulation analyses revealed stable interactions between the vaccine candidate and the human toll-like receptor 5 (TLR5). Finally, immune simulations corroborated the promising candidature of the designed vaccine, thus calling for further in vivo investigation.

Solvent-scaling as an alternative to coarse-graining in adaptive-resolution simulations: The adaptive solvent-scaling (AdSoS) scheme

A new approach termed Adaptive Solvent-Scaling (AdSoS) is introduced for performing simulations of a solute embedded in a fine-grained (FG) solvent region itself surrounded by a coarse-grained (CG) solvent region, with a continuous FG ↔ CG switching of the solvent resolution across a buffer layer. Instead of relying on a distinct CG solvent model, the AdSoS scheme is based on CG models defined by a dimensional scaling of the FG solvent by a factor s, accompanied by an s-dependent modulation of the atomic masses and interaction parameters. The latter changes are designed to achieve an isomorphism between the dynamics of the FG and CG models, and to preserve the dispersive and dielectric solvation properties of the solvent with respect to a solute at FG resolution. This scaling approach offers a number of advantages compared to traditional coarse-graining: (i) the CG parameters are immediately related to those of the FG model (no need to parameterize a distinct CG model); (ii) nearly ideal mixing is expected for CG variants with similar s-values (ideal mixing holding in the limit of identical s-values); (iii) the solvent relaxation timescales should be preserved (no dynamical acceleration typical for coarse-graining); (iv) the graining level N_G (number of FG molecules represented by one CG molecule) can be chosen arbitrarily (in particular, N_G = s³ is not necessarily an integer); and (v) in an adaptive-resolution scheme, this level can be varied continuously as a function of the position (without requiring a bundling mechanism), and this variation occurs at a constant number of particles per molecule (no occurrence of fractional degrees of freedom in the buffer layer). By construction, the AdSoS scheme minimizes the thermodynamic mismatch between the different regions of the adaptive-resolution system, leading to a nearly homogeneous scaled solvent density s³ρ. Residual density artifacts in and at the surface of the boundary layer can easily be corrected by means of a grid-based biasing potential constructed in a preliminary pure-solvent simulation. This article introduces the AdSoS scheme and provides an initial application to pure atomic liquids (no solute) with Lennard-Jones plus Coulomb interactions in a slab geometry.

Implementing and Assessing an Alchemical Method for Calculating Protein-Protein Binding Free Energy

Protein-protein binding is fundamental to most biological processes. It is important to be able to use computation to accurately estimate the change in protein-protein binding free energy due to mutations in order to answer biological questions that would be experimentally challenging, laborious, or time-consuming. Although nonrigorous free-energy methods are faster, rigorous alchemical molecular dynamics-based methods are considerably more accurate and are becoming more feasible with the advancement of computer hardware and molecular simulation software. Even with sufficient computational resources, there are still major challenges to using alchemical free-energy methods for protein-protein complexes, such as generating hybrid structures and topologies, maintaining a neutral net charge of the system when there is a charge-changing mutation, and setting up the simulation. In the current study, we have used the pmx package to generate hybrid structures and topologies, and a double-system/single-box approach to maintain the net charge of the system. To test the approach, we predicted relative binding affinities for two protein-protein complexes using a nonequilibrium alchemical method based on the Crooks fluctuation theorem and compared the results with experimental values. The method correctly identified stabilizing from destabilizing mutations for a small protein-protein complex, and a larger, more challenging antibody complex. Strong correlations were obtained between predicted and experimental relative binding affinities for both protein-protein systems.

β-Amyloid (1-42) peptide adsorbs but does not insert into ganglioside-containing phospholipid membranes in the liquid-disordered state: modelling and experimental studies

β-Amyloid (Aβ) is a 39-43 residue peptide involved in the pathogenesis of Alzheimer's disease. Aβ deposits onto the cells and gives rise to the plaques that are characteristic of the disease. In an effort to understand the molecular mechanism of plaque formation, we have examined the interaction of Aβ42, considered to be the most pathogenic of the peptides, with lipid bilayers consisting of 1-palmitoyl-2-oleoyl phosphatidylcholine (POPC) to which small amounts of GM1 ganglioside (1-5 mol%) were incorporated. POPC bilayers exist in the fluid, or liquid-disordered state at room temperature, mimicking the fluidity of cell membranes. An Aβ42 preparation consisting essentially of peptide monomers was used. A combination of molecular dynamics (MD), isothermal calorimetry and Langmuir balance measurements was applied. Our results show that Aβ binds POPC bilayers, and that binding increases (ΔG of binding decreases) with GM1, but only up to 3 mol% of the ganglioside, larger concentrations appearing to have a lower effect. MD and Langmuir balance measurements concur in showing that the peptide adsorbs onto the bilayer surface, but does not become inserted into it at surface pressures compatible with the cell membrane conditions. Thioflavin T measurements agree with MD in revealing a very low degree of peptide oligomerization/aggregation under our conditions. This is in contrast with previous studies showing peptide aggregation and insertion when interacting with membranes in the liquid-ordered state. The present contribution underlines the importance of bilayer lipid composition and properties for Aβ plaque formation.

Influence of the presence of the heme cofactor on the JK-loop structure in indoleamine 2,3-dioxygenase 1

Indoleamine 2,3-dioxygenase 1 has sparked interest as an immunotherapeutic target in cancer research. Its structure includes a loop, named the JK-loop, that controls the orientation of the substrate or inhibitor within the active site. However, little has been reported about the crystal structure of this loop. In the present work, the conformation of the JK-loop is determined for the first time in the presence of the heme cofactor in the active site through X-ray diffraction experiments (2.44 Å resolution). Molecular-dynamics trajectories were also obtained to provide dynamic information about the loop according to the presence of cofactor. This new structural and dynamic information highlights the importance of the JK-loop in confining the labile heme cofactor to the active site.

From quantum to subcellular scales: multi-scale simulation approaches and the SIRAH force field

Modern molecular and cellular biology profits from astonishing resolution structural methods, currently even reaching the whole cell level. This is encompassed by the development of computational methods providing a deep view into the structure and dynamics of molecular processes happening at very different scales in time and space. Linking such scales is of paramount importance when aiming at far-reaching biological questions. Computational methods at the interface between classical and coarse-grained resolutions are gaining momentum with several research groups dedicating important efforts to their development and tuning. An overview of such methods is addressed herein, with special emphasis on the SIRAH force field for coarse-grained and multi-scale simulations. Moreover, we provide proof of concept calculations on the implementation of a multi-scale simulation scheme including quantum calculations on a classical fine-grained/coarse-grained representation of double-stranded DNA. This opens the possibility to include the effect of large conformational fluctuations in chromatin segments on, for instance, the reactivity of particular base pairs within the same simulation framework.

Multi-resolution dimer models in heat baths with short-range and long-range interactions

This work investigates multi-resolution methodologies for simulating dimer models. The solvent particles which make up the heat bath interact with the monomers of the dimer either through direct collisions (short-range) or through harmonic springs (long-range). Two types of multi-resolution methodologies are considered in detail: (a) describing parts of the solvent far away from the dimer by a coarser approach; (b) describing each monomer of the dimer by using a model with different level of resolution. These methodologies are then used to investigate the effect of a shared heat bath versus two uncoupled heat baths, one for each monomer. Furthermore, the validity of the multi-resolution methods is discussed by comparison to dynamics of macroscopic Langevin equations.

Crystal structures and snapshots along the reaction pathway of human phosphoserine phosphatase

The equilibrium between phosphorylation and dephosphorylation is one of the most important processes that takes place in living cells. Human phosphoserine phosphatase (hPSP) is a key enzyme in the production of serine by the dephosphorylation of phospho-L-serine. It is directly involved in the biosynthesis of other important metabolites such as glycine and D-serine (a neuromodulator). hPSP is involved in the survival mechanism of cancer cells and has recently been found to be an essential biomarker. Here, three new high-resolution crystal structures of hPSP (1.5–2.0 Å) in complexes with phosphoserine and with serine, which are the substrate and the product of the reaction, respectively, and in complex with a noncleavable substrate analogue (homocysteic acid) are presented. New types of interactions take place between the enzyme and its ligands. Moreover, the loop involved in the open/closed state of the enzyme is fully refined in a totally unfolded conformation. This loop is further studied through molecular-dynamics simulations. Finally, all of these analyses allow a more complete reaction mechanism for this enzyme to be proposed which is consistent with previous publications on the subject.

The SIRAH 2.0 Force Field: Altius, Fortius, Citius

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 its application, we undertook the structural and dynamical analysis of the most abundant and conserved calcium-binding protein, calmodulin (CaM). CaM is composed of two calcium-binding motifs called EF-hands, which in the 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 near-native 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 from 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 shows the capacity to handle a number of structurally and dynamically challenging situations, including metal ion coordination, unbiased conformational sampling, and specific protein-peptide recognition.

Investigating cyclic peptides inhibiting CD2-CD58 interactions through molecular dynamics and molecular docking methods

The CD2-CD58 protein-protein interaction is known to favor the recognition of antigen presenting cells by T cells. The structural, energetics, and dynamical properties of three known cyclic CD58 ligands, named P6, P7, and RTD-c, are studied through molecular dynamics (MD) simulations and molecular docking calculations. The ligands are built so as to mimic the C and F β-strands of protein CD2, connected via turn inducers. The MD analyses focus on the location of the ligands with respect to the experimental binding site and on the direct and water-mediated hydrogen bonds (H bonds) they form with CD58. Ligand P6, with a sequence close to the experimental β-strands of CD2, presents characteristics that explain its higher experimental affinity, e.g., the lower mobility and flexibility at the CD58 surface, and the larger number and occurrence frequency of ligand-CD58 H bonds. For the two other ligands, the structural modifications lead to changes in the binding pattern with CD58 and its dynamics. In parallel, a large set of molecular docking calculations, carried out with various search spaces and docking algorithms, are compared to provide a consensus view of the preferred ligand binding modes. The analysis of the ligand side chain locations yields results that are consistent with the CD2-CD58 crystal structure and suggests various binding modes of the experimentally identified hot spot of the ligands, i.e., Tyr86. P6 is shown to form a number of contacts that are also present in the experimental CD2-CD58 structure.

Multiscale modelization in a small virus: Mechanism of proton channeling and its role in triggering capsid disassembly

In this work, we assess a previously advanced hypothesis that predicts the existence of ion channels in the capsid of small and non-enveloped icosahedral viruses. With this purpose we examine Triatoma Virus (TrV) as a case study. This virus has a stable capsid under highly acidic conditions but disassembles and releases the genome in alkaline environments. Our calculations range from a subtle sub-atomic proton interchange to the dismantling of a large-scale system representing several million of atoms. Our results provide structure-based explanations for the three roles played by the capsid to enable genome release. First, we observe, for the first time, the formation of a hydrophobic gate in the cavity along the five-fold axis of the wild-type virus capsid, which can be disrupted by an ion located in the pore. Second, the channel enables protons to permeate the capsid through a unidirectional Grotthuss-like mechanism, which is the most likely process through which the capsid senses pH. Finally, assuming that the proton leak promotes a charge imbalance in the interior of the capsid, we model an internal pressure that forces shell cracking using coarse-grained simulations. Although qualitatively, this last step could represent the mechanism of capsid opening that allows RNA release. All of our calculations are in agreement with current experimental data obtained using TrV and describe a cascade of events that could explain the destabilization and disassembly of similar icosahedral viruses.

Plant and animal small non-enveloped viruses are composed of a capsid shell that encloses the genome. One of the multiple functions played by the capsid is to protect the genome against host defenses and to withstand environmental aggressions, such as dehydration. This highly specialized capsule selectively recognizes and binds to the target tissue infected by the virus. In the viral cycle, the ultimate function of the capsid is to release the genome. Observations of many viruses demonstrate that the pH of the medium can trigger genome release. Nevertheless, the mechanism underlying this process at the atomic level is poorly understood. In this work, we computationally modeled the mechanism by which the capsid senses environmental pH and the destabilization process that permits genome release. Our calculations predict that a cavity that traverses the capsid functions as a hydrophobic gate, a feature already observed in membrane ion channels. Moreover, our results predict that this cavity behaves as a proton diode because the proton transit can only occur from the capsid interior to the exterior. In turn, our calculations describe a cascade of events that could explain the destabilization and dismantling of an insect virus, but this description could also apply to many vertebrate viruses.

Multiscale Simulation of Protein Hydration Using the SWINGER Dynamical Clustering Algorithm

To perform computationally efficient concurrent multiscale simulations of biological macromolecules in solution, where the all-atom (AT) models are coupled to supramolecular coarse-grained (SCG) solvent models, previous studies resorted to modified AT water models, such as the bundled-simple point charge (SPC) models, that use semiharmonic springs to restrict the relative movement of water molecules within a cluster. Those models can have a significant impact on the simulated biomolecules and can lead, for example, to a partial unfolding of a protein. In this work, we employ the recently developed alternative approach with a dynamical clustering algorithm, SWINGER, which enables a direct coupling of original unmodified AT and SCG water models. We perform an adaptive resolution molecular dynamics simulation of a Trp-Cage miniprotein in multiscale water, where the standard SPC water model is interfaced with the widely used MARTINI SCG model, and demonstrate that, compared to the corresponding full-blown AT simulations, the structural and dynamic properties of the solvated protein and surrounding solvent are well reproduced by our approach.

Adaptive resolution simulations of biomolecular systems

In this review article, we discuss and analyze some recently developed hybrid atomistic-mesoscopic solvent models for multiscale biomolecular simulations. We focus on the biomolecular applications of the adaptive resolution scheme (AdResS), which allows solvent molecules to change their resolution back and forth between atomistic and coarse-grained representations according to their positions in the system. First, we discuss coupling of atomistic and coarse-grained models of salt solution using a 1-to-1 molecular mapping-i.e., one coarse-grained bead represents one water molecule-for development of a multiscale salt solution model. In order to make use of coarse-grained molecular models that are compatible with the MARTINI force field, one has to resort to a supramolecular mapping, in particular to a 4-to-1 mapping, where four water molecules are represented with one coarse-grained bead. To this end, bundled atomistic water models are employed, i.e., the relative movement of water molecules that are mapped to the same coarse-grained bead is restricted by employing harmonic springs. Supramolecular coupling has recently also been extended to polarizable coarse-grained water models with explicit charges. Since these coarse-grained models consist of several interaction sites, orientational degrees of freedom of the atomistic and coarse-grained representations are coupled via a harmonic energy penalty term. The latter aligns the dipole moments of both representations. The reviewed multiscale solvent models are ready to be used in biomolecular simulations, as illustrated in a few examples.

A New Mixed All-Atom/Coarse-Grained Model: Application to Melittin Aggregation in Aqueous Solution

We introduce a new mixed resolution, all-atom/coarse-grained approach (AACG), for modeling peptides in aqueous solution and apply it to characterizing the aggregation of melittin. All of the atoms in peptidic components are represented, while a single site is used for each water molecule. With the full flexibility of the peptide retained, our AACG method achieves speedups by a factor of 3-4 for CPU time reduction and another factor of roughly 7 for diffusion. An Ewald treatment permits the inclusion of long-range electrostatic interactions. These characteristics fit well with the requirements for studying peptide association and aggregation, where the system sizes and time scales require considerable computational resources with all-atom models. In particular, AACG is well suited for biologics since changes in peptide shape and long-range electrostatics may play an important role. The application of AACG to melittin, a 26-residue peptide with a well-known propensity to aggregate in solution, serves as an initial demonstration of this technology for studying peptide aggregation. We observed the formation of melittin aggregates during our simulations and characterized the time-evolution of aggregate size distribution, buried surface areas, and residue contacts. Key interactions including π-cation and π-stacking involving TRP19 were also examined. Our AACG simulations demonstrated a clear salt effect and a moderate temperature effect on aggregation and support the molten globule model of melittin aggregates. As a showcase, this work illustrates the useful role for AACG in investigations of peptide aggregation and its potential to guide formulation and design of biologics.

Flexible Boundaries for Multiresolution Solvation: An Algorithm for Spatial Multiscaling in Molecular Dynamics Simulations

An algorithm is proposed for performing molecular dynamics (MD) simulations of a biomolecular solute represented at atomistic resolution surrounded by a surface layer of atomistic fine-grained (FG) solvent molecules within a bulk represented by coarse-grained (CG) solvent beads. The method, called flexible boundaries for multiresolution solvation (FBMS), is based on: (i) a three-region layering of the solvent around the solute, involving an FG layer surrounded by a mixed FG-CG buffer layer, itself surrounded by a bulk CG region; (ii) a definition of the layer boundary that relies on an effective distance to the solute surface and is thus adapted to the shape of the solute as well as adjusts to its conformational changes. The effective surface distance is defined by inverse-nth power averaging over the distances to all non-hydrogen solute atoms, and the layering is enforced by means of half-harmonic distance restraints, attractive for the FG molecules and repulsive for the CG beads. A restraint-free region at intermediate distances enables the formation of the buffer layer, where the FG and CG solvents can mix freely. The algorithm is tested and validated using the GROMOS force field and the associated FG (SPC) and CG (polarizable CGW) water models. The test systems include pure-water systems, where one FG molecule plays the role of a solute, and a deca-alanine peptide with two widely different solute shapes considered, α-helical and fully extended. In particular, as the peptide unfolds, the number of FG molecules required to fill its close-range solvation layer increases, with the additional molecules being provided by the buffer layer. Further validation involves simulations of four proteins in multiresolution FG/CG mixtures. The resulting structural, energetic, and solvation properties are found to be similar to those observed in corresponding pure FG simulations.

A simple and transferable all-atom/coarse-grained hybrid model to study membrane processes

We present an efficient all-atom/coarse-grained hybrid model and apply it to membrane processes. This model is an extension of the all-atom/ELBA model applied previously to processes in water. Here, we improve the efficiency of the model by implementing a multiple-time step integrator that allows the atoms and the coarse-grained beads to be propagated at different timesteps. Furthermore, we fine-tune the interaction between the atoms and the coarse-grained beads by computing the potential of mean force of amino acid side chain analogs along the membrane normal and comparing to atomistic simulations. The model was independently validated on the calculation of small-molecule partition coefficients. Finally, we apply the model to membrane peptides. We studied the tilt angle of the Walp23 and Kalp23 helices in two different model membranes and the stability of the glycophorin A dimer. The model is efficient, accurate, and straightforward to use, as it does not require any extra interaction particles, layers of atomistic solvent molecules or tabulated potentials, thus offering a novel, simple approach to study membrane processes.

Exploring LacI-DNA dynamics by multiscale simulations using the SIRAH force field

The lac repressor protein (LacI) together with its target regulatory sequence are a common model for studying DNA looping and its implications on transcriptional control in bacteria. Owing to the molecular size of this system, standard all-atom (AA) simulations are prohibitive for achieving relevant biological time scales. As an alternative, multiscale models, which combine AA descriptions at particular regions with coarse-grained (CG) representations of the remaining components, were used to address this computational challenge while preserving the relevant details of the system. In this work, we implement a new multiscale approach based on the SIRAH force field to gain deeper insights into the dynamics of the LacI-DNA system. Our methodology allows for a dual resolution treatment of the solute and solvent, explicitly representing the protein, DNA, and solvent environment without compromising the AA region. Starting from the P1 loop configuration in an undertwisted conformation, we were able to observe the transition to the more stable overtwisted state. Additionally, a detailed characterization of the conformational space sampled by the DNA loop was done. In agreement with experimental and theoretical evidence, we observed the transient formation of kinks at the loop, which were stabilized by the presence of counterions at the minor groove. We also show that the loop's intrinsic flexibility can account for reported FRET measurements and bent conformations required to bind the CAP transcription factor.

Nothing to sneeze at: a dynamic and integrative computational model of an influenza A virion

The influenza virus is surrounded by an envelope composed of a lipid bilayer and integral membrane proteins. Understanding the structural dynamics of the membrane envelope provides biophysical insights into aspects of viral function, such as the wide-ranging survival times of the virion in different environments. We have combined experimental data from X-ray crystallography, nuclear magnetic resonance spectroscopy, cryo-electron microscopy, and lipidomics to build a model of the intact influenza A virion. This is the basis of microsecond-scale coarse-grained molecular dynamics simulations of the virion, providing simulations at different temperatures and with varying lipid compositions. The presence of the Forssman glycolipid alters a number of biophysical properties of the virion, resulting in reduced mobility of bilayer lipid and protein species. Reduced mobility in the virion membrane may confer physical robustness to changes in environmental conditions. Our simulations indicate that viral spike proteins do not aggregate and thus are competent for multivalent immunoglobulin G interactions.

Identification of novel cyclic nucleotide binding proteins in Trypanosoma cruzi

Cyclic AMP has been implicated as second messenger in a wide range of cellular processes. In the protozoan parasite Trypanosoma cruzi, cAMP is involved in the development of the parasite's life cycle. While cAMP effectors have been widely studied in other eukaryotic cells, little is known about cAMP's mechanism of action in T. cruzi. To date, only a cAMP-dependent protein kinase A (PKA) has been cloned and characterised in this parasite; however experimental evidence indicates the existence of cAMP-dependent, PKA-independent events. In order to identify new cAMP binding proteins as potential cAMP effectors, we carried out in silico studies using the predicted T. cruzi proteome. Using a combination of search methods 27 proteins with putative cNMP binding domains (CBDs) were identified. Phylogenetic analysis of the CBDs presented a homogeneous distribution, with sequences segregated into two main branches: one containing kinases-like proteins and the other gathering hypothetical proteins with different function or no other known. Comparative modelling of the strongest candidates provides support for the hypothesis that these proteins may give rise to structurally viable cyclic nucleotide binding domains. Pull-down and nucleotide displacement assays strongly suggest that TcCLB.508523.80 could bind cAMP and eventually be a new putative PKA-independent cAMP effector in T. cruzi.

Direct Mixing of Atomistic Solutes and Coarse-Grained Water

We present a new dual-resolution approach for coupling atomistic and coarse-grained models in molecular dynamics simulations of hydrated systems. In particular, a coarse-grained point dipolar water model is used to solvate molecules represented with standard all-atom force fields. A unique characteristic of our methodology is that the mixing of resolutions is direct, meaning that no additional or ad hoc scaling factors, intermediate regions, or extra sites are required. To validate the methodology, we compute the hydration free energy of 14 atomistic small molecules (analogs of amino acid side chains) solvated by the coarse-grained water. Remarkably, our predictions reproduce the experimental data as accurately as the predictions from state-of-the-art fully atomistic simulations. We also show that the hydration free energy of the coarse-grained water itself is in comparable or better agreement with the experimental value than the predictions from all but one of the most common multisite atomistic models. The coarse-grained water is then applied to solvate a typical atomistic protein containing both α-helix and β-strand elements. Moreover, parallel tempering simulations are performed to investigate the folding free energy landscape of a representative α helical and a β hairpin structure. For the simulations considered in this work, our dual-resolution method is found to be 3 to 6 times more computationally efficient than corresponding fully atomistic approaches.

The OPEP protein model: from single molecules, amyloid formation, crowding and hydrodynamics to DNA/RNA systems

The OPEP coarse-grained protein model has been applied to a wide range of applications since its first release 15 years ago. The model, which combines energetic and structural accuracy and chemical specificity, allows the study of single protein properties, DNA-RNA complexes, amyloid fibril formation and protein suspensions in a crowded environment. Here we first review the current state of the model and the most exciting applications using advanced conformational sampling methods. We then present the current limitations and a perspective on the ongoing developments.