gmak: A Parameter-Space Mapping Strategy for Force-Field Calibration.

In the context of classical molecular simulations, the accuracy of a force field is highly influenced by the values of the relevant simulation parameters. In this work, a parameter-space mapping (PSM) workflow is proposed to aid in the calibration of force-field parameters, based mainly on the following features: (i) regular-grid discretization of the search space; (ii) partial sampling of the search-space grid; (iii) training of surrogate models to predict the estimates of the target properties for nonsampled parameter sets; (iv) post hoc interpretation of the results in terms of multiobjective optimization concepts; (v) attenuation of statistical errors achieved via empiric extension of the duration of the simulations; (vi) iterative search-space translation according to a user-defined scalar objective function that measures the accuracy of the force field (e.g., the weighted root-mean-square deviation of the target properties relative to the reference data). This combination of features results in a hybrid of a single- and a multiobjective optimization strategy, allowing for the approximate determination of both a local minimum of the chosen objective function and its neighboring Pareto efficient points. The PSM workflow is implemented in the extensible Python program gmak, which is made available in the Git repository at http://github.com/mssm-labmmol/gmak. Using this implementation, the PSM workflow was tested in a proof-of-concept fashion in the recalibration of the Lennard-Jones parameters of the 3-point Optimal Point Charge (OPC3) water model for compatibility with the GROMOS treatment of nonbonded interactions. The recalibrated model reproduces typical pure-liquid properties with an accuracy similar to the original OPC3 model and represents a significant improvement relative to the Simple Point Charge (SPC) model, which is the official recommendation for simulations using GROMOS force fields.

Comparison of the United- and All-Atom Representations of (Halo)alkanes Based on Two Condensed-Phase Force Fields Optimized against the Same Experimental Data Set.

The level of accuracy that can be achieved by a force field is influenced by choices made in the interaction-function representation and in the relevant simulation parameters. These choices, referred to here as functional-form variants (FFVs), include for example the model resolution, the charge-derivation procedure, the van der Waals combination rules, the cutoff distance, and the treatment of the long-range interactions. Ideally, assessing the effect of a given FFV on the intrinsic accuracy of the force-field representation requires that only the specific FFV is changed and that this change is performed at an optimal level of parametrization, a requirement that may prove extremely challenging to achieve in practice. Here, we present a first attempt at such a comparison for one specific FFV, namely the choice of a united-atom (UA) versus an all-atom (AA) resolution in a force field for saturated acyclic (halo)alkanes. Two force-field versions (UA vs AA) are optimized in an automated way using the CombiFF approach against 961 experimental values for the pure-liquid densities ρliq and vaporization enthalpies ΔHvap of 591 compounds. For the AA force field, the torsional and third-neighbor Lennard-Jones parameters are also refined based on quantum-mechanical rotational-energy profiles. The comparison between the UA and AA resolutions is also extended to properties that have not been included as parameterization targets, namely the surface-tension coefficient γ, the isothermal compressibility κT, the isobaric thermal-expansion coefficient αP, the isobaric heat capacity cP, the static relative dielectric permittivity ϵ, the self-diffusion coefficient D, the shear viscosity η, the hydration free energy ΔGwat, and the free energy of solvation ΔGche in cyclohexane. For the target properties ρliq and ΔHvap, the UA and AA resolutions reach very similar levels of accuracy after optimization. For the nine other properties, the AA representation leads to more accurate results in terms of η; comparably accurate results in terms of γ, κT, αP, ϵ, D, and ΔGche; and less accurate results in terms of cP and ΔGwat. This work also represents a first step toward the calibration of a GROMOS-compatible force field at the AA resolution.

Simultaneous parametrization of torsional and third-neighbor interaction terms in force-field development: The LLS-SC algorithm.

The calibration of torsional interaction terms by fitting relative gas-phase conformational energies against their quantum-mechanical values is a common procedure in force-field development. However, much less attention has been paid to the optimization of third-neighbor nonbonded interaction parameters, despite their strong coupling with the torsions. This article introduces an algorithm termed LLS-SC, aimed at simultaneously parametrizing torsional and third-neighbor interaction terms based on relative conformational energies. It relies on a self-consistent (SC) procedure where each iteration involves a linear least-squares (LLS) regression followed by a geometry optimization of the reference structures. As a proof-of-principle, this method is applied to obtain torsional and third-neighbor interaction parameters for aliphatic chains in the context of the GROMOS 53A6 united-atom force field. The optimized parameter set is compared to the original one, which has been fitted manually against thermodynamic properties for small linear alkanes. The LLS-SC implementation is freely available under http://github.com/mssm-labmmol/profiler.

Computer Modeling Explains the Structural Reasons for the Difference in Reactivity of Amine Transaminases Regarding Prochiral Methylketones.

Amine transaminases (ATAs) are pyridoxal-5'-phosphate (PLP)-dependent enzymes that catalyze the transfer of an amino group from an amino donor to an aldehyde and/or ketone. In the past decade, the enzymatic reductive amination of prochiral ketones catalyzed by ATAs has attracted the attention of researchers, and more traditional chemical routes were replaced by enzymatic ones in industrial manufacturing. In the present work, the influence of the presence of an α,ß-unsaturated system in a methylketone model substrate was investigated, using a set of five wild-type ATAs, the (R)-selective from Aspergillus terreus (Atr-TA) and Mycobacterium vanbaalenii (Mva-TA), the (S)-selective from Chromobacterium violaceum (Cvi-TA), Ruegeria pomeroyi (Rpo-TA), V. fluvialis (Vfl-TA) and an engineered variant of V. fluvialis (ATA-256 from Codexis). The high conversion rate (80 to 99%) and optical purity (78 to 99% ee) of both (R)- and (S)-ATAs for the substrate 1-phenyl-3-butanone, using isopropylamine (IPA) as an amino donor, were observed. However, the double bond in the α,ß-position of 4-phenylbut-3-en-2-one dramatically reduced wild-type ATA reactivity, leading to conversions of <10% (without affecting the enantioselectivity). In contrast, the commercially engineered V. fluvialis variant, ATA-256, still enabled an 87% conversion, yielding a corresponding amine with >99% ee. Computational docking simulations showed the differences in orientation and intermolecular interactions in the active sites, providing insights to rationalize the observed experimental results.

pyPolyBuilder: Automated Preparation of Molecular Topologies and Initial Configurations for Molecular Dynamics Simulations of Arbitrary Supramolecules.

The construction of a molecular topology file is a prerequisite for any classical molecular dynamics simulation. However, the generation of such a file may be very challenging at times, especially for large supramolecules. While many tools are available to provide topologies for large proteins and other biomolecules, the scientific community researching nonbiological systems is not equally well equipped. Here, we present a practical tool to generate topologies for arbitrary supramolecules: The pyPolyBuilder. In addition to linear polymer chains, it also provides the possibility to generate topologies of arbitrary, large, branched molecules, such as, e.g., dendrimers. Furthermore, it also generates reasonable starting structures for simulations of these molecules. pyPolyBuilder is a standalone command-line tool implemented in python. Therefore, it may be easily incorporated in persisting simulation pipelines on any operating systems and with different simulation engines. pyPolyBuilder is freely available on github: https://github.com/mssm-labmmol/pypolybuilder.

Drug-Loading Capacity of PAMAM Dendrimers Encapsulating Quercetin Molecules: A Molecular Dynamics Study with the 2016H66 Force Field.

The complexation of quercetin molecules with poly(amidoamine) (PAMAM) dendrimers of generation 0-3 was studied by molecular dynamics simulations. Three main points were addressed: (i) the effect of starting from different initial structures; (ii) the performance of the 2016H66 force field (recently validated in the context of dendrimer simulations) in predicting the experimental drug(quercetin)-loading capacity of PAMAM dendrimers; and (iii) the stability of quercetin-PAMAM complexes and their interactions. Initial structures generated by different restraint protocols led to faster convergence compared to initial structures generated by randomly placing the drug molecules in the simulation box. The simulations yielded meta-stable complexes where the loading numbers have converged to average values and were compared to experimentally obtained values. Once the first meta-stable state was reached, the drug-dendrimer complexes did not deviate significantly throughout the simulation. They were characterized in terms of structural properties, such as the radius of gyration and radial distribution functions. The results suggest that quercetin molecules interact mostly with the internal dendrimer monomers rather than to their surface.

On the Effect of the Various Assumptions and Approximations used in Molecular Simulations on the Properties of Bio-Molecular Systems: Overview and Perspective on Issues.

Computer simulations of molecular systems enable structure-energy-function relationships of molecular processes to be described at the sub-atomic, atomic, supra-atomic or supra-molecular level and plays an increasingly important role in chemistry, biology and physics. To interpret the results of such simulations appropriately, the degree of uncertainty and potential errors affecting the calculated properties must be considered. Uncertainty and errors arise from (1) assumptions underlying the molecular model, force field and simulation algorithms, (2) approximations implicit in the interatomic interaction function (force field), or when integrating the equations of motion, (3) the chosen values of the parameters that determine the accuracy of the approximations used, and (4) the nature of the system and the property of interest. In this overview, advantages and shortcomings of assumptions and approximations commonly used when simulating bio-molecular systems are considered. What the developers of bio-molecular force fields and simulation software can do to facilitate and broaden research involving bio-molecular simulations is also discussed.

Systematic Optimization of a Fragment-Based Force Field against Experimental Pure-Liquid Properties Considering Large Compound Families: Application to Saturated Haloalkanes.

Direct optimization against experimental condensed-phase properties concerning small organic molecules still represents the most reliable way to calibrate the empirical parameters of a force field. However, compared to a corresponding calibration against quantum-mechanical (QM) calculations concerning isolated molecules, this approach is typically very tedious and time-consuming. The present article describes an integrated scheme for the automated refinement of force-field parameters against experimental condensed-phase data, considering entire classes of organic molecules constructed using a fragment library via combinatorial isomer enumeration. The main steps of the scheme, referred to as CombiFF, are as follows: (i) definition of a molecule family; (ii) combinatorial enumeration of all isomers; (iii) query for experimental data; (iv) automatic construction of the molecular topologies by fragment assembly; and (v) iterative refinement of the force-field parameters considering the entire family. As a first application, CombiFF is used here to design a GROMOS-compatible united-atom force field for the saturated acyclic haloalkane family. This force field relies on an electronegativity-equalization scheme for the atomic partial charges and involves no specific terms for σ-holes and halogen bonding. A total of 749 experimental liquid densities ρliq and vaporization enthalpies ΔHvap concerning 486 haloalkanes are considered for calibration and validation. The resulting root-mean-square deviations from experiment are 49.8 (27.6) kg·m-3 for ρliq and 2.7 (1.8) kJ·mol-1 for ΔHvap for the calibration (validation) set. The values are lower for the validation set which contains larger molecules (stronger influence of purely aliphatic interactions). The trends in the optimized parameters along the halogen series and across the compound family are in line with chemical intuition based on considerations related to size, polarizability, softness, electronegativity, induction, and hyperconjugation. This observation is particularly remarkable considering that the force-field calibration did not involve any QM calculation. Once the time-consuming task of target-data selection/curation has been performed, the optimization of a force field only takes a few days. As a result, CombiFF enables an easy assessment of the consequences of functional-form decisions on the accuracy of a force field at an optimal level of parametrization.

Evaluating Classical Force Fields against Experimental Cross-Solvation Free Energies.

Experimental solvation free energies are nowadays commonly included as target properties in the validation and sometimes even in the calibration of condensed-phase force fields. However, this is often done in a nonsystematic fashion, by considering available solvation free energies involving an arbitrary collection of solutes in a limited set of solvents (e.g., water, octanol, chloroform, cyclohexane, or hexane). Here, this approach is made more systematic by introducing the concept of cross-solvation free energies ΔsGA:B⊖ for a set of N molecules that are all in the liquid state under ambient conditions, namely the matrix of N2 entries for ΔsGA:B⊖ considering each of the N molecules either as a solute (A) or as a solvent (B). Relying on available experimental literature followed by careful data curation, a complete ΔsGA:B⊖ matrix of 625 entries is constructed for 25 molecules with one to seven carbon atoms representative for alkanes, chloroalkanes, ethers, ketones, esters, alcohols, amines, and amides. This matrix is then used to compare the relative accuracies of four popular condensed-phase force fields: GROMOS-2016H66, OPLS-AA, AMBER-GAFF, and CHARMM-CGenFF. In broad terms, and in spite of very different force-field functional-form choices and parametrization strategies, the four force fields are found to perform similarly well. Relative to the experimental values, the root-mean-square errors range between 2.9 and 4.0 kJ·mol-1 (lowest value of 2.9 for GROMOS and OPLS), and the average errors range between -0.8 and +1.0 kJ·mol-1 (lowest magnitude of 0.2 for AMBER and CHARMM). These differences are statistically significant but not very pronounced, especially considering the influence of outliers, some of which possibly caused by inaccurate experimental data.

Are all-atom any better than united-atom force fields for the description of liquid properties of alkanes?

Alkanes are a fundamental part in empirical force fields (FF) not only due to their technological relevance, but also due to the prevalence of alkane moieties in organic molecules, e.g., compounds containing a saturated carbon chain. Therefore, a good description of alkane interactions is crucial for determining the quality of a FF. In this study, the performance of 12 empirical force fields (FF) was evaluated in the context of reproducing liquid properties of alkanes. More specifically, n-octane was chosen as a reference compound since it is a liquid in a broad temperature range and it has numerous experimental data for thermodynamic, transport, and structural properties, as well as for their temperature dependencies. A normalized root-mean-square deviation (NRMSD) analysis was used to rank the force fields in their ability to reproduce the experimental data. Five out of the six best force fields considered were united-atom models. The GROMOS force field showed the smallest deviation in terms of NRMSD, followed by TRAPPE-EH, NERD, CHARMM-UA, TRAPPE-UA, and OPLS-UA. This overall better performance of the united-atom force fields indicates that complexity does not always bring quality.

Predicting the Miscibility and Rigidity of Poly(lactic-co-glycolic acid)/Polyethylene Glycol Blends via Molecular Dynamics Simulations.

The addition of polyethylene glycol (PEG) chains to poly(lactic-co-glycolic acid) (PLGA) matrices is extensively used to modulate the biodegradation, drug loading and release, mechanical properties, and chemical stability of the original system. Multiple parameters, including the molecular weight, relative concentration, polarity, and solubility, affect the physicochemical properties of the polymer blend. Here, molecular dynamics simulations with the united-atom 2016H66 force field are used to model the behavior of PLGA and PEG chains and thus predict the overall physicochemical features of the resulting blend. First, the model accuracy is validated against fundamental properties of pure PLGA and PEG samples. In agreement with previous experimental and theoretical observations, the PLGA solubility results to be higher in acetonitrile than in water, with Flory parameters νACN = 0.63 ± 0.01 and νW = 0.21 ± 0.02, and the Young's modulus of PLGA and PEG equal to Y = 2.0 ± 0.43 and 0.32 ± 0.34 GPa, respectively. Next, four PEG/PLGA blending regimes are identified by varying the relative concentrations and molecular weights of the individual polymers. The computational results demonstrate that at low PEG concentrations (<8% w/w), homogeneous blends are generated for both low and high PEG molecular weights. In contrast, at comparable PEG and PLGA concentrations (∼50% w/w), short PEG chains are only partially miscible whereas long PEG chains segregate within the PLGA matrix. This behavior has been confirmed experimentally via differential scanning calorimetry and is in agreement with previous observations. Finally, the computed Young's modulus of PLGA/PEG blends is observed to decrease with the PEG content returning the lowest values for the partial and fully segregated regimens (Y ≈ 1.3 GPa). This work proposes a computational scheme for predicting the physicochemical properties of PLGA/PEG blends paving the way toward the rational design of polymer mixtures for biomedical applications.

gem-Dichlorocyclopropanation of Dicarbonyl Derivatives.

A novel methodology for the 1,1-dichlorocyclopropanation of dicarbonyl conjugated olefins was described. The developed protocol is simple and uses readily accessible starting materials, allowing the isolation of the desired adducts in moderate to excellent yields (up to 99 %). Furthermore, the reaction tolerated scale up to the gram scale; thus highlighting the synthetic potential of this transformation. Control experiments and DFT studies revealed that the reaction proceeded through a Michael-initiated ring-closure process, in which reaction temperature played a crucial role. Finally, these gem-dichlorocyclopropanes were also employed in the preparation of a trisubstituted naphthyl derivative and a diastereoselective reduction was also demonstrated.

Molecular Dynamics Simulations of PAMAM and PPI Dendrimers Using the GROMOS-Compatible 2016H66 Force Field.

A systematic evaluation of the accuracy of the GROMOS-compatible 2016H66 force field in the simulation of dendrimers is performed. More specifically, the poly(amido amine) (PAMAM) and the poly(propyleneimine) (PPI) are considered because of the availability of experimental data and simulation results in the literature. A total of 36 molecular systems are simulated and the radius of gyration, asphericity, density profiles, and the self-diffusion coefficient are monitored in terms of the generation number and pH (low, medium, and high) condition. Overall, the results support the recommendation of the 2016H66 force field for the simulation of dendrimer systems. The natural building-block based strategy adopted in the definition of 2016H66, together with a careful parametrization of the chemical functional groups to reproduce thermodynamic properties in environments of different polarity, and also the ability to accurately reproduce the expected structural and dynamic features of dendrimers, as shown in the present work, make this force field an attractive option for the simulation of such systems.

Influence of the Treatment of Nonbonded Interactions on the Thermodynamic and Transport Properties of Pure Liquids Calculated Using the 2016H66 Force Field.

The effect of different treatments of the nonbonded interactions in simulations employing the recently introduced GROMOS-compatible 2016H66 force field is evaluated based on calculations carried out with the GROMACS software. This is done considering four thermodynamic and transport properties (pure liquid density, vaporization enthalpy, surface-tension coefficient, and self-diffusion constant) of 58 organic liquids representative of the chemical groups alcohol, ether, aldehyde, ketone, carboxylic acid, ester, amine, amide, thiol, sulfide, disulfide, and aromatic compounds, also including water (SPC model). A dipalmitoylphosphatidylcholine bilayer system is considered as well. The simulated properties are found to be very sensitive to the treatment of the long-range dispersion interactions, notably for the least polar systems. In general, the treatment of the long-range electrostatic or Lennard-Jones interactions using homogeneous correction terms or lattice-sum approaches yield similar results, with punctual discrepancies. The combination of a lattice-sum approach for the electrostatic interactions with a straight-cutoff truncation of the Lennard-Jones interactions at a distance of at least 1.2 nm is found to represent a good compromise setup within GROMACS for achieving compatibility with the reference results obtained using GROMOS as well as a comparable level of agreement with the experimental data. This study also reveals two potential issues with the GROMACS software, related to an incorrect calculation of the pressure when using LINCS in version 4.0.7 and an inadequate implementation of the twin-range scheme in version 5.1.2.

Solvent effects on the decarboxylation of trichloroacetic acid: insights from ab initio molecular dynamics simulations.

The kinetics of trichloroacetic acid (TCA) decarboxylation strongly depends on the solvent in which it occurs, proceeding faster in polar aprotic solvents compared to protic solvents. In particular, the reaction is known to be fast in DMSO even at room temperature and is rather slow in water even at higher temperatures. In order to understand the role of the solvent in the kinetics of TCA decarboxylation, the present study investigates this reaction using both ab initio molecular dynamics (AIMD) simulations in explicit solvents and static electronic structure calculations with the SMD polarizable continuum model, considering DMSO and water as solvents. Both methodologies yield activation free energies in good agreement with experimental data, however they differ with respect to the reaction profile for the process occurring in water. The simulations suggest that DMSO does not participate chemically in the reaction and that the high reaction rate in DMSO can be explained by differential solvation of the reactant and transition state. In water, a protonation step was observed along the simulation trajectory, indicating chemical participation of the solvent in this case. Moreover, the continuum model has shown to be useful to predict the reaction rates in other solvents, suggesting that reaction rates increase upon decreasing solvent polarity up to the point where the apolar solvents are not able to efficiently screen the strong electrostatic interactions to form the required isolated ionic species.

New insights into flavivirus biology: the influence of pH over interactions between prM and E proteins.

Diseases caused by flaviviruses, such as dengue and zika, are globally recognized as major threats. During infection, a critical point in their replicative cycle is the maturation step, which occurs throughout the cellular exocytic pathway. This step is a pH-dependent process that involves the modification of the viral envelope by converting prM (pre-membrane) into M (membrane) proteins with the release of a "pr peptide". After this reaction, the pr peptides remain bound to the viral envelope while the virions cross the acidic trans-Golgi network, and are released only at neutral pH after secretion of the virus particles. Despite this current knowledge, the molecular basis of the flavivirus maturation step is largely unknown. Here, based on the crystal structure of the dengue pr-E complex ("pr peptide" bound to virus envelope protein) and using molecular dynamics simulations, we found that the pH shift from acidic to neutral yields considerable structural changes in the system. Dynamic cross correlation maps and root mean square deviation analyses revealed that the pr-E junction is clearly unstable under neutral pH. Secondary structure analysis also revealed that the fusion loop region, present in the E protein, is sensitive to pH and tends to unstructure at a neutral environment. Moreover, we found that five residues present in the E protein, Gly102, His244, Thr70, Thr68 and Asn67 are critical to confer stability to the pr-E complex while inside the Golgi apparatus. This work brings details about the dynamical behavior of the pr-E system, helps to better understand the flavivirus biology and may also be of use in the development of novel antiviral strategies.

Simulating Bilayers of Nonionic Surfactants with the GROMOS-Compatible 2016H66 Force Field.

Polyoxyethylene glycol alkyl ether amphiphiles (CiEj) are important nonionic surfactants, often used for biophysical and membrane protein studies. In this work, we extensively test the GROMOS-compatible 2016H66 force field in molecular dynamics simulations involving the lamellar phase of a series of CiEj surfactants, namely C12E2, C12E3, C12E4, C12E5, and C14E4. The simulations reproduce qualitatively well the monitored structural properties and their experimental trends along the surfactant series, although some discrepancies remain, in particular in terms of the area per surfactant, the equilibrium phase of C12E5, and the order parameters of C12E3, C12E4, and C12E5. The polar head of the CiEj surfactants is highly hydrated, almost like a single polyethyleneoxide (PEO) molecule at full hydration, resulting in very compact conformations. Within the bilayer, all CiEj surfactants flip-flop spontaneously within tens of nanoseconds. Water-permeation is facilitated, and the bending rigidity is 4 to 5 times lower than that of typical phospholipid bilayers. In line with another recent theoretical study, the simulations show that the lamellar phase of CiEj contains large hydrophilic pores. These pores should be abundant in order to reproduce the comparatively low NMR order parameters. We show that their contour length is directly correlated to the order parameters, and we estimate that they should occupy approximately 7-10% of the total membrane area. Due to their highly dynamic nature (rapid flip-flops, high water permeability, observed pore formation), CiEj surfactant bilayers are found to represent surprisingly challenging systems in terms of modeling. Given this difficulty, the results presented here show that the 2016H66 parameters, optimized independently considering pure-liquid as well as polar and nonpolar solvation properties of small organic molecules, represent a good starting point for simulating these systems.

Insights into CC Chemokine Ligand 2/Chemokine Receptor 2 Molecular Recognition: A Step Forward toward Antichemotactic Agents.

Chemokine ligand 2 (CCL2), also known as monocyte chemoattractant protein 1 (MCP-1), is a chemokine that recruits immune cells to inflammatory sites by interacting with G protein-coupled receptor CCR2. The CCL2/CCR2 axis is also involved in pathological processes such as tumor growth and metastasis and hence is currently considered as an important drug target. CCL2 exists in a dynamic monomer-dimer equilibrium that is modulated by CCR2 binding. We used solution nuclear magnetic resonance (NMR) spectroscopy and molecular dynamics simulations to study the interactions between CCL2 and a sulfopeptide corresponding to the N-terminal sequence of CCR2 (CCR218-31). Peptide binding induced the dissociation of CCL2 into monomers, forming stable CCL2/CCR218-31 complexes. NMR relaxation measurements indicated that residues around the CCR218-31 binding site, which are located at the dimer interface, undergo a complex regime of motions. NMR data were used to construct a three-dimensional structural model of the CCL2/CCR218-31 complex, revealing that CCR218-31 occupies a binding site juxtaposed to the dimer interface, partially replacing monomer-monomer contacts, explaining why CCR218-31 binding weakens the dimer interface and induces dissociation. We found that the main interactions governing receptor binding are highly stable salt bridges with conserved chemokine residues as well as hydrophobic interactions. These data provide new insights into the structure-function relationship of the CCL2-CCR2 interaction and may be helpful for the design of novel antichemotactic agents.

The flavivirus capsid protein: Structure, function and perspectives towards drug design.

Flaviviruses, such as dengue and zika viruses, are etiologic agents transmitted to humans mainly by arthropods and are of great epidemiological interest. The flavivirus capsid protein is a structural element required for the viral nucleocapsid assembly that presents the classical function of sheltering the viral genome. After decades of research, many reports have shown its different functionalities and influence over cell normal functioning. The subcellular distribution of this protein, which involves accumulation around lipid droplets and nuclear localization, also corroborates with its multi-functional characteristic. As flavivirus diseases are still in need of global control and in view of the possible key functionalities that the capsid protein promotes over flavivirus biology, novel considerations arise towards anti-flavivirus drug research. This review covers the main aspects concerning structural and functional features of the flavivirus C protein, ultimately, highlighting prospects in drug discovery based on this viral target.

The mechanism by which P250L mutation impairs flavivirus-NS1 dimerization: an investigation based on molecular dynamics simulations.

The flavivirus non-structural protein 1 (NS1) is a conserved glycoprotein with as yet undefined biological function. This protein dimerizes when inside infected cells or associated to cell membranes but also forms lipid-associated hexamers when secreted to the extracellular space. A single amino acid substitution (P250L) is capable of preventing the dimerization of NS1 resulting in lower virulence and slower virus replication. In this work, based on molecular dynamics simulations of the dengue-2 virus NS1 [Formula: see text]-ladder monomer as a core model, we found that this mutation can induce several conformational changes that importantly affect critical monomer-monomer interactions. Based on additional simulations, we suggest a mechanism by which a highly orchestrated sequence of events propagate the local perturbations around the mutation site towards the dimer interface. The elucidation of such a mechanism could potentially support new strategies for rational production of live-attenuated vaccines and highlights a step forward in the development of novel anti-flavivirus measures.