Coarse-grained Force Field Research Articles

Ribonucleic Acid Folding Prediction Based on Iterative Multiscale Simulation

RNA folding prediction is a challenge. Currently, many RNA folding models are coarse-grained (CG) with the potential derived from the known RNA structures. However, this potential is not suitable for modified and entirely new RNA. It is also not suitable for the folding simulation of RNA in the real cellular environment, including many kinds of molecular interactions. In contrast, our proposed model has the potential to address these issues, which is a multiscale simulation scheme based on all-atom (AA) force fields. We fit the CG force field using the trajectories generated by the AA force field and then iteratively perform molecular dynamics (MD) simulations of the two scales. The all-atom molecular dynamics (AAMD) simulation is mainly responsible for the correction of RNA structure, and the CGMD simulation is mainly responsible for efficient conformational sampling. On the basis of this scheme, we can successfully fold three RNAs belonging to a hairpin, a pseudoknot, and a four-way junction.

Ab initio predictions for 3D structure and stability of single- and double-stranded DNAs in ion solutions.

The three-dimensional (3D) structure and stability of DNA are essential to understand/control their biological functions and aid the development of novel materials. In this work, we present a coarse-grained (CG) model for DNA based on the RNA CG model proposed by us, to predict 3D structures and stability for both dsDNA and ssDNA from the sequence. Combined with a Monte Carlo simulated annealing algorithm and CG force fields involving the sequence-dependent base-pairing/stacking interactions and an implicit electrostatic potential, the present model successfully folds 20 dsDNAs (≤52nt) and 20 ssDNAs (≤74nt) into the corresponding native-like structures just from their sequences, with an overall mean RMSD of 3.4Å from the experimental structures. For DNAs with various lengths and sequences, the present model can make reliable predictions on stability, e.g., for 27 dsDNAs with/without bulge/internal loops and 24 ssDNAs including pseudoknot, the mean deviation of predicted melting temperatures from the corresponding experimental data is only ~2.0°C. Furthermore, the model also quantificationally predicts the effects of monovalent or divalent ions on the structure stability of ssDNAs/dsDNAs.

Consistent and Transferable Force Fields for Statistical Copolymer Systems at the Mesoscale.

The statistical trajectory matching (STM) method was applied successfully to derive coarse grain (CG) models for bulk properties of homopolymers. The extension of the methodology for building CG models for statistical copolymer systems is much more challenging. We present here the strategy for developing CG models for styrene-butadiene-rubber, and we compare the quality of the resulting CG force fields on the structure and thermodynamics at different chemical compositions. The CG models are used through the use of a genuine mesoscopic method called the dissipative particle dynamics method and compared to high-resolution molecular dynamics simulations. We conclude that the STM method is able to produce coarse-grained potentials that are transferable in composition by using only a few reference systems. Additionally, this methodology can be applied on any copolymer system.

Effect of Disulfide Bridge on the Binding of SARS-CoV-2 Fusion Peptide to Cell Membrane: A Coarse-Grained Study.

In this paper, we present the parameterization of the CAVS coarse-grained (CG) force field for 20 amino acids, and our CG simulations show that the CAVS force field could accurately predict the amino acid tendency of the secondary structure. Then, we used the CAVS force field to investigate the binding of a severe acute respiratory syndrome-associated coronavirus fusion peptide (SARS-CoV-2 FP) to a phospholipid bilayer: a long FP (FP-L) containing 40 amino acids and a short FP (FP-S) containing 26 amino acids. Our CAVS CG simulations displayed that the binding affinity of the FP-L to the bilayer is higher than that of the FP-S. We found that the FP-L interacted more strongly with membrane cholesterol than the FP-S, which should be attributed to the stable helical structure of the FP-L at the C-terminus. In addition, we discovered that the FP-S had one major and two minor membrane-bound states, in agreement with previous all-atom molecular dynamics (MD) studies. However, we found that both the C-terminal and N-terminal amino acid residues of the FP-L can strongly interact with the bilayer membrane. Furthermore, we found that the disulfide bond formed between Cys840 and Cys851 stabilized the helices of the FP-L at the C-terminus, enhancing the interaction between the FP-L and the bilayer membrane. Our work indicates that the stable helical structure is crucial for binding the SARS-CoV-2 FP to cell membranes. In particular, the helical stability of FP should have a significant influence on the FP–membrane binding.

Martini 3 model of surface modified cellulose nanocrystals: investigation of aqueous colloidal stability

The Martini coarse-grained force field is one of the most popular coarse-grained models for molecular dynamics (MD) modelling in biology, chemistry, and material science. Recently, a new force field version, Martini 3, had been reported with improved interaction balance and many new bead types. Here, we present a new cellulose nanocrystal (CNC) model based on Martini 3. The calculated CNC structures, lattice parameters, and mechanical properties reproduce experimental measurements well and provide an improvement over previous CNC models. Then, surface modifications with COO− groups and interactions with Na+ ions were fitted based on the atomistic MD results to reproduce the interactions between surface-modified CNCs. Finally, the colloidal stability and dispersion properties were studied with varied NaCl concentrations and a good agreement with experimental results was found. Our work brings new progress toward CNC modelling to describe different surface modifications and colloidal solutions that were not available in previous coarse-grained models.Graphical abstract

Importance of molecular dynamics equilibrium protocol on protein-lipid interaction near channel pore

Multiscale molecular dynamics simulations using Martini coarse-grained (CG) and all-atom (AA) force fields are commonly used in membrane protein studies. In particular, reverse mapping an equilibrated CG model to an AA model offers an efficient way for preparing large membrane protein systems with complex protein shapes and lipid compositions. Here, we report that this hybrid CG-equilibrium-AA-production protocol may artificially increase lipid density and decrease hydration in ion channel pores walled with transmembrane gaps. To understand the origin of this conundrum, we conducted replicas of CG, AA, and CG reverse-mapped AA simulations of the pore domain of the mechanosensitive Piezo1 channel in a nonconducting conformation. Lipid/water density analysis and free energy calculations reveal that the lack of initial pore hydration allows excessive lipids to enter the upper pore lumen through gaps between pore helices during CG simulation. Due to the mismatch between CG and AA lipid kinetics, these pore lipids remain trapped in the subsequent AA simulations, despite unfavorable binding free energy. We tested several CG equilibrium protocols and found that a protocol restraining the whole lipid produces pore hydration consistent with AA results, thus eliminating this artifact for further studies of lipid gating and protein-lipid interactions.

Contrastive Learning of Coarse-Grained Force Fields.

Coarse-grained models have proven helpful for simulating complex systems over long time scales to provide molecular insights into various processes. Methodologies for systematic parametrization of the underlying energy function or force field that describes the interactions among different components of the system are of great interest for ensuring simulation accuracy. We present a new method, potential contrasting, to enable efficient learning of force fields that can accurately reproduce the conformational distribution produced with all-atom simulations. Potential contrasting generalizes the noise contrastive estimation method with umbrella sampling to better learn the complex energy landscape of molecular systems. When applied to the Trp-cage protein, we found that the technique produces force fields that thoroughly capture the thermodynamics of the folding process despite the use of only α-carbons in the coarse-grained model. We further showed that potential contrasting could be applied over large data sets that combine the conformational ensembles of many proteins to improve force field transferability. We anticipate potential contrasting as a powerful tool for building general-purpose coarse-grained force fields.

Benchmarking coarse-grained models of organic semiconductors via deep backmapping.

The potential of mean force is an effective coarse-grained potential, which is often approximated by pairwise potentials. While the approximated potential reproduces certain distributions of the reference all-atom model with remarkable accuracy, important cross-correlations are typically not captured. In general, the quality of coarse-grained models is evaluated at the coarse-grained resolution, hindering the detection of important discrepancies between the all-atom and coarse-grained ensembles. In this work, the quality of different coarse-grained models is assessed at the atomistic resolution deploying reverse-mapping strategies. In particular, coarse-grained structures for Tris-Meta-Biphenyl-Triazine are reverse-mapped from two different sources: 1) All-atom configurations projected onto the coarse-grained resolution and 2) snapshots obtained by molecular dynamics simulations based on the coarse-grained force fields. To assess the quality of the coarse-grained models, reverse-mapped structures of both sources are compared revealing significant discrepancies between the all-atom and the coarse-grained ensembles. Specifically, the reintroduced details enable force computations based on the all-atom force field that yield a clear ranking for the quality of the different coarse-grained models.

Mechanical Stability of Ribonuclease A Heavily Depends on the Redox Environment.

Disulfide bonds are covalent bonds that connect nonlocal fragments of proteins, and they are unique post-translational modifications of proteins. They require the oxidizing environment to be stable, which occurs for example during oxidative stress; however, in a cell the reductive environment is maintained, lowering their stability. Despite many years of research on disulfide bonds, their role in the protein life cycle is not fully understood and seems to strictly depend on a system or process in which they are involved. In this article, coarse-grained UNited RESidue (UNRES), and all-atom Assisted Model Building with Energy Refinement (AMBER) force fields were applied to run a series of steered molecular dynamics (SMD) simulations of one of the most studied, but still not fully understood, proteins—ribonuclease A (RNase A). SMD simulations were performed to study the mechanical stability of RNase A in different oxidative–reductive environments. As disulfide bonds (and any other covalent bonds) cannot break/form in any classical all-atom force field, we applied additional restraints between sulfur atoms of reduced cysteines which were able to mimic the breaking of the disulfide bonds. On the other hand, the coarse-grained UNRES force field enables us to study the breaking/formation of the disulfide bonds and control the reducing/oxidizing environment owing to the presence of the designed distance/orientation-dependent potential. This study reveals that disulfide bonds have a strong influence on the mechanical stability of RNase A only in a highly oxidative environment. However, the local stability of the secondary structure seems to play a major factor in the overall stability of the protein. Both our thermal unfolding and mechanical stretching studies show that the most stable disulfide bond is Cys65–Cys72. The breaking of disulfide bonds Cys26–Cys84 and Cys58–Cys110 is associated with large force peaks. They are structural bridges, which are mostly responsible for stabilizing the RNase A conformation, while the presence of the remaining two bonds (Cys65–Cys72 and Cys40–Cys95) is most likely connected with the enzymatic activity rather than the structural stability of RNase A in the cytoplasm. Our results prove that disulfide bonds are indeed stabilizing fragments of the proteins, but their role is strongly redox environment-dependent.

Significant Effect of Rugosity on Transport of Hydrocarbon Liquids in Carbonaceous Nanopores

We report the results of modeling the transport of n-octane and n-hexadecane and their mixtures through carbonaceous nanopores at high-pressure conditions. Pores are modeled as smooth slit sheets with perturbations added as ridges and steps and a version of the statistical associating fluid theory (SAFT-γ Mie) is used both as equation of state and as a coarse-grained force field to account for fluid–fluid and fluid–solid molecular interactions. Molecular simulation allowed the description of transport diffusivities in terms of molecular flow, using boundary driven nonequilibrium molecular dynamics (BD-NEMD). Transport diffusivities are also independently calculated using equilibrium and external force nonequilibrium molecular dynamics (EF-NEMD) simulations, after accounting for the adsorption on the pores. We show consistency between the approaches for quantifying transport in terms of permeabilities (Darcy flows) and transport diffusivities. We find that smooth slit carbon pore models, which are commonly employed in the literature as surrogates for kerogen regions in shale, are an inadequate representation of ultraconfined natural pores. For slit pores, the flow patterns are characterized by a fully mutualized pluglike flow and fast transport. However, by incorporating even a small amount of rugosity (roughness) into the solid walls, the diffusion coefficients decrease dramatically, with surface roughness significantly affecting the characteristic transport and velocity profiles inside the pores. In all cases, it is seen that there are important cross-correlation effects, influencing the way components of the mixture flow together. Calculated self-diffusivities are orders of magnitude smaller than the observed transport diffusivities for liquid mixtures. This work has a direct impact on the understanding and modeling of unconventional hydrocarbon recovery and flow in organic shale rocks.

Stability and Existence of Noncanonical I-motif DNA Structures in Computer Simulations Based on Atomistic and Coarse-Grained Force Fields.

Cytosine-rich DNA sequences are able to fold into noncanonical structures, in which semi-protonated cytosine pairs develop extra hydrogen bonds, and these bonds are responsible for the overall stability of a structure called the i-motif. The i-motif can be formed in many regions of the genome, but the most representative is the telomeric region in which the CCCTAA sequences are repeated thousands of times. The ability to reverse folding/unfolding in response to pH change makes the above sequence and i-motif very promising components of nanomachines, extended DNA structures, and drug carriers. Molecular dynamics analysis of such structures is highly beneficial due to direct insights into the microscopic structure of the considered systems. We show that Amber force fields for DNA predict the stability of the i-motif over a long timescale; however, these force fields are not able to predict folding of the cytosine-rich sequences into the i-motif. The reason is the kinetic partitioning of the folding process, which makes the transitions between various intermediates too time-consuming in atomistic force field representation. Application of coarse-grained force fields usually highly accelerates complex structural transitions. We, however, found that three of the most popular coarse-grained force fields for DNA (oxDNA, 3SPN, and Martini) were not able to predict the stability of the i-motif structure. Obviously, they were not able to accelerate the folding of unfolded states into an i-motif. This observation must be strongly highlighted, and the need to develop suitable extensions of coarse-grained force fields for DNA is pointed out. However, it will take a great deal of effort to successfully solve these problems.

Computationally exploring the mechanism of bacteriophage T7 gp4 helicase translocating along ssDNA.

Bacteriophage T7 gp4 helicase has served as a model system for understanding mechanisms of hexameric replicative helicase translocation. The mechanistic basis of how nucleoside 5'-triphosphate hydrolysis and translocation of gp4 helicase are coupled is not fully resolved. Here, we used a thermodynamically benchmarked coarse-grained protein force field, Associative memory, Water mediated, Structure and Energy Model (AWSEM), with the single-stranded DNA (ssDNA) force field 3SPN.2C to investigate gp4 translocation. We found that the adenosine 5'-triphosphate (ATP) at the subunit interface stabilizes the subunit-subunit interaction and inhibits subunit translocation. Hydrolysis of ATP to adenosine 5'-diphosphate enables the translocation of one subunit, and new ATP binding at the new subunit interface finalizes the subunit translocation. The LoopD2 and the N-terminal primase domain provide transient protein-protein and protein-DNA interactions that facilitate the large-scale subunit movement. The simulations of gp4 helicase both validate our coarse-grained protein-ssDNA force field and elucidate the molecular basis of replicative helicase translocation.

Extending the Martini 3 Coarse-Grained Force Field to Carbohydrates.

Carbohydrates play an essential role in a large number of chemical and biochemical processes. High structural diversity and conformational heterogeneity make it problematic to link their measurable properties to molecular features. Molecular dynamics simulations carried out at the level of classical force fields are routinely applied to study the complex processes occurring in carbohydrate-containing systems, while the usefulness of such simulations relies on the accuracy of the underlying theoretical model. In this article, we present the coarse-grained force field dedicated to glucopyranose-based carbohydrates and compatible with the recent version of the Martini force field (v. 3.0). The parameterization was based on optimizing bonded and nonbonded parameters with a reference to the all-atom simulation results and the experimental data. Application of the newly developed coarse-grained carbohydrate model to oligosaccharides curdlan and cellulose displays spontaneous formation of aggregates of experimentally identified features. In contact with other biomolecules, the model is capable of recovering the protective effect of glucose monosaccharides on a lipid bilayer and correctly identifying the binding pockets in carbohydrate-binding proteins. The features of the newly proposed model make it an excellent candidate for further extensions, aimed at modeling more complex, functionalized, and biologically relevant carbohydrates.

Plastics and sustainability in the same breath: Machine learning-assisted optimization of coarse-grained models for polyvinyl chloride as a common polymer in the built environment

The fast-growing construction industry has a vast potential to rise to the plastics challenge by using them in both primary and recycled forms as a sustainable solution to some challenges in the built environment. Improving existing plastics and developing innovative polymers and polymer nanocomposites requires knowledge of interatomic interactions and their influence on macroscopic properties. Coarse-grained (CG) models offer a more computationally efficient alternative to their all-atom counterparts for simulating larger, more representative models of these materials. However, the parameterization and calibration process of CG force fields (CG-FFs) commonly entails solving a nonconvex optimization problem involving numerous local minima, rendering traditional optimization techniques impractical and iterations based on educated guesses inefficient. Here, we develop an approach to efficiently parameterize a CG-FF by coupling a metaheuristic algorithm as the calibrator (optimizer) with support vector regression-based surrogate models trained using molecular dynamics data. The merit of the approach is demonstrated by parameterizing a CG-FF potential for polyvinyl chloride (PVC) as a representative general-purpose plastic with many applications in the construction industry. The generalizability of the CG-FF to large PVC models in both pristine and carbon nanotube-filled composite forms is demonstrated. The CG-FF also accurately reproduces glass transition temperature and thermal conductivity as unseen properties of PVC.

Small ionic radii limit time step in Martini 3 molecular dynamics simulations.

Among other improvements, the Martini 3 coarse-grained force field provides a more accurate description of the solvation of protein pockets and channels through the consistent use of various bead types and sizes. Here, we show that the representation of Na+ and Cl- ions as "tiny" (TQ5) beads limits the accessible time step to 25fs. By contrast, with Martini 2, time steps of 30-40fs were possible for lipid bilayer systems without proteins. This limitation is relevant for systems that require long equilibration times. We derive a quantitative kinetic model of time-integration instabilities in molecular dynamics (MD) as a function of the time step, ion concentration and mass, system size, and simulation time. We demonstrate that ion-water interactions are the main source of instability at physiological conditions, followed closely by ion-ion interactions. We show that increasing the ionic masses makes it possible to use time steps up to 40fs with minimal impact on static equilibrium properties and dynamical quantities, such as lipid and solvent diffusion coefficients. Increasing the size of the bead representing the ions (and thus changing their hydration) also permits longer time steps. For a soluble protein, we find that increasing the mass of tiny beads also on the protein permits simulations with 30-fs time steps. The use of larger time steps in Martini 3 results in a more efficient exploration of configuration space. The kinetic model of MD simulation crashes can be used to determine the maximum allowed time step upfront for an efficient use of resources and whenever sampling efficiency is critical.

Exploring the Interplay between Disordered and Ordered Oligomer Channels on the Aggregation Energy Landscapes of α-Synuclein.

The abnormal aggregation of α-synulcein is associated with multiple neurodegenerative diseases such as Parkinson's disease. The hydrophobic non-amyloid component (NAC) region of α-synuclein comprises the core of the fibril in vitro and in vivo. In this work, we study the aggregation landscape of the hydrophobic NAC region of α-synuclein using a transferrable coarse-grained force field, the associative memory water-mediated structure, and energy model (AWSEM). Using structural similarity, we can group metastable states on the free energy landscape of aggregation into three types of oligomers: disordered oligomers, prefibrillar oligomers with disordered tips, and ordered prefibrillar oligomers. The prefibrillar oligomers with disordered tips have more in-register parallel β strands than do the fully disordered oligomers but have fewer in-register parallel β strands than the ordered prefibrillar oligomers. Along with the ordered prefibrillar species, the disordered oligomeric states dominate at small oligomer sizes while the prefibrillar species with disordered tips thermodynamically dominate with the growth of oligomers. The topology of the aggregation landscape and observations in simulations suggest there is backtracking between ordered prefibrillar oligomers and other kinds of oligomers as the aggregation proceeds. The significant structural differences between the ordered prefibrillar oligomers and the disordered oligomers support the idea that the growth of these two kinds of oligomers involves kinetically independent parallel pathways. In contrast, the overall structural similarity between the fully ordered prefibrillar oligomers and the prefibrillar oligomers with disordered tips implies that two channels can interconvert on slower time scales. We also evaluate the effects of phosphorylation on the aggregation free energy landscape using statistical mechanical perturbation theory.

Transferable and Polarizable Coarse Grained Model for Proteins─ProMPT.

The application of classical molecular dynamics (MD) simulations at atomic resolution (fine-grained level, FG), to most biomolecular processes, remains limited because of the associated computational complexity of representing all the atoms. This problem is magnified in the presence of protein-based biomolecular systems that have a very large conformational space, and MD simulations with fine-grained resolution have slow dynamics to explore this space. Current transferable coarse grained (CG) force fields in literature are either limited to only peptides with the environment encoded in an implicit form or cannot capture transitions into secondary/tertiary peptide structures from a primary sequence of amino acids. In this work, we present a transferable CG force field with an explicit representation of the environment for accurate simulations with proteins. The force field consists of a set of pseudoatoms representing different chemical groups that can be joined/associated together to create different biomolecular systems. This preserves the transferability of the force field to multiple environments and simulation conditions. We have added electronic polarization that can respond to environmental heterogeneity/fluctuations and couple it to protein's structural transitions. The nonbonded interactions are parametrized with physics-based features such as solvation and partitioning free energies determined by thermodynamic calculations and matched with experiments and/or atomistic simulations. The bonded potentials are inferred from corresponding distributions in nonredundant protein structure databases. We present validations of the CG model with simulations of well-studied aqueous protein systems with specific protein fold types─Trp-cage, Trpzip4, villin, WW-domain, and β-α-β. We also explore the applications of the force field to study aqueous aggregation of Aβ 16-22 peptides.

Investigating Intrinsically Disordered Proteins With Brownian Dynamics.

Intrinsically disordered proteins (IDPs) have recently become systems of great interest due to their involvement in modulating many biological processes and their aggregation being implicated in many diseases. Since IDPs do not have a stable, folded structure, however, they cannot be easily studied with experimental techniques. Hence, conducting a computational study of these systems can be helpful and be complementary with experimental work to elucidate their mechanisms. Thus, we have implemented the coarse-grained force field for proteins (COFFDROP) in Browndye 2.0 to study IDPs using Brownian dynamics (BD) simulations, which are often used to study large-scale motions with longer time scales and diffusion-limited molecular associations. Specifically, we have checked our COFFDROP implementation with eight naturally occurring IDPs and have investigated five (Glu-Lys)25 IDP sequence variants. From measuring the hydrodynamic radii of eight naturally occurring IDPs, we found the ideal scaling factor of 0.786 for non-bonded interactions. We have also measured the entanglement indices (average C α distances to the other chain) between two (Glu-Lys)25 IDP sequence variants, a property related to molecular association. We found that entanglement indices decrease for all possible pairs at excess salt concentration, which is consistent with long-range interactions of these IDP sequence variants getting weaker at increasing salt concentration.

Multiscale Simulation of Ternary Stratum Corneum Lipid Mixtures: Effects of Cholesterol Composition.

Molecular dynamics simulations of mixtures of the ceramide nonhydroxy-sphingosine (NS), cholesterol, and a free fatty acid are performed to gain molecular-level understanding of the structure of the lipids found in the stratum corneum layer of skin. A new coarse-grained force field for cholesterol was developed using the multistate iterative Boltzmann inversion (MS-IBI) method. The coarse-grained cholesterol force field is compatible with previously developed coarse-grained force fields for ceramide NS, free fatty acids, and water and validated against atomistic simulations of these lipids using the CHARMM force field. Self-assembly simulations of multilayer structures using these coarse-grained force fields are performed, revealing that a large fraction of the ceramides adopt extended conformations, which cannot occur in the single bilayer in water structures typically studied using molecular simulation. Cholesterol fluidizes the membrane by promoting packing defects, and an increase in cholesterol content is found to reduce the bilayer thickness due to an increase in interdigitation of the C24 lipid tails, consistent with experimental observations. Using a reverse-mapping procedure, a self-assembled coarse-grained multilayer system is used to construct an equivalent structure with atomistic resolution. Simulations of this atomistic structure are found to closely agree with experimentally derived neutron scattering length density profiles. Significant interlayer hydrogen bonding is observed in the inner layers of the atomistic multilayer structure that are not found in the outer layers in contact with water or in equivalent bilayer structures. This work highlights the importance of simulating multilayer structures, as compared to the more commonly studied bilayer systems, to enable more appropriate comparisons with multilayer experimental membranes. These results also provide validation of the efficacy of the MS-IBI derived coarse-grained force fields and the framework for multiscale simulation.

Current Rectification and Ionic Selectivity of α-Hemolysin: Coarse-Grained Molecular Dynamics Simulations.

In order to understand the physical processes of nanopore experiments at the molecular level, microscopic information from molecular dynamics is greatly needed. Coarse-grained models are a good alternative to classical all-atom models since they allow longer and faster simulations. We performed coarse-grained molecular dynamics of the ionic transport through the α-hemolysin protein nanopore, inserted into a lipid bilayer surrounded by solvent and ions. For this purpose, we used the MARTINI coarse-grained force field and its polarizable water solvent (PW). Moreover, the electric potential difference applied experimentally was mimicked by the application of an electric field to the system. We present, in this study, the results of 1.5 μs long-molecular dynamics simulations of 12 different systems for which different charged amino acids were neutralized, each of them in the presence of nine different electric fields ranging between ±0.04 V/nm (a total of around 100 simulations). We were able to observe several specific features of this pore, current asymmetry and anion selectivity, in agreement with previous studies and experiments, and we identified the charged amino acids responsible for these current behaviors, therefore validating our coarse-grain approach to study ionic transport through nanopores. We also propose a microscopic explanation of these ionic current features using ionic density maps.