Protocol for Simulations of PEGylated Proteins with Martini 3

Bartender: Martini 3 Bonded Terms via Quantum Mechanics-Based Molecular Dynamics

Coarse-grained (CG) molecular dynamics (MD) simulations have grown in applicability over the years. The recently released version of the Martini CG force field (Martini 3) has been successfully applied to simulate many processes, including protein-ligand binding. However, the current ligand parametrization scheme is manual and requires an a priori reference all-atom (AA) simulation for benchmarking. For systems with suboptimal AA parameters, which are often unknown, this translates into a CG model that does not reproduce the true dynamical behavior of the underlying molecule. Here, we present Bartender, a quantum mechanics (QM)/MD-based parametrization tool written in Go. Bartender harnesses the power of QM simulations and produces reasonable bonded terms for Martini 3 CG models of small molecules in an efficient and user-friendly manner. For small, ring-like molecules, Bartender generates models whose properties are indistinguishable from the human-made models. For more complex, drug-like ligands, it is able to fit functional forms beyond simple harmonic dihedrals and thus better captures their dynamical behavior. Bartender has the power to both increase the efficiency and the accuracy of Martini 3-based high-throughput applications by producing numerically stable and physically realistic CG models.

Computational and experimental validation of phthalocyanine and hypericin as effective SARS-CoV-2 fusion inhibitors

Phthalocyanine and hypericin have been previously identified as possible SARS-CoV-2 Spike glycoprotein fusion inhibitors through a virtual screening procedure. In this paper, atomistic simulations of metal-free phthalocyanines and atomistic and coarse-grained simulations of hypericins, placed around a complete model of the Spike embedded in a viral membrane, allowed to further explore their multi-target inhibitory potential, uncovering their binding to key protein functional regions and their propensity to insert in the membrane. Following computational results, pre-treatment of a pseudovirus expressing the SARS-CoV-2 Spike protein with low compounds concentrations resulted in a strong inhibition of its entry into cells, suggesting the activity of these molecules should involve the direct targeting of the viral envelope surface. The combination of computational and in vitro results hence supports the role of hypericin and phthalocyanine as promising SARS-CoV-2 entry inhibitors, further endorsed by literature reporting the efficacy of these compounds in inhibiting SARS-CoV-2 activity and in treating hospitalized COVID-19 patients.Communicated by Ramaswamy H. Sarma.

Building complex membranes with Martini 3

The Martini model is a popular force field for coarse-grained simulations. Membranes have always been at the center of its development, with the latest version, Martini 3, showing great promise in capturing more and more realistic behavior. In this chapter we provide a step-by-step tutorial on how to construct starting configurations, run initial simulations and perform dedicated analysis for membrane-based systems of increasing complexity, including leaflet asymmetry, curvature gradients and embedding of membrane proteins.

Optimizing the Martini 3 Force Field Reveals the Effects of the Intricate Balance between Protein-Water Interaction Strength and Salt Concentration on Biomolecular Condensate Formation

Condensation/dissolution has become a widely acknowledged biological macromolecular assembly phenomenon in subcellular compartmentalization. The MARTINI force field offers a coarse-grained protein model with a resolution that preserves molecular details with an explicit (CG) solvent. Despite its relatively higher resolution, it can still achieve condensate formation in a reasonable computing time with explicit solvent and ionic species. Therefore, it is highly desirable to tune this force field to be able to reproduce the experimentally observed properties of the condensate formation. In this work, we studied the condensate formation of the low-sequence complexity domain of fused in sarcoma protein using a MARTINI 3 force field by systematically modifying (increasing) the protein-water interaction strength and varying the salt concentration. We found that the condensate formation is sensitive both to the protein-water interaction strength and the presence of salt. While the unmodified MARTINI force field yields a complete collapse of proteins into one dense phase (i.e., no dilute phase), we reported a range of modified protein-water interaction strength that is capable of capturing the experimentally found transfer free energy between dense and dilute phases. We also found that the condensates lose their spherical shape upon the addition of salt, especially when the protein-water interactions are weak. Interchain amino acid contact map analysis showed one explanation for this observation: the protein-protein contact fraction reduces as salt is added to systems (when the protein-water interactions are weak), consistent with electrostatic screening effects. This reduction might be responsible for the condensates becoming nonspherical upon the addition of salt by reducing the need for minimizing the interfacial area. However, as the protein-water interactions become stronger to the extent that makes the transfer free energy agree well with experimentally observed transfer free energy, we found an increase in the protein-protein contact fraction upon the addition of salt, consistent with the salting-out effects. Therefore, we concluded that there is an intricate balance between screening effects and salting-out effects upon the addition of salt and this balance is highly sensitive to the strength of protein-water interactions.

Molecular Dynamics Simulations for Rationalizing Polymer Bioconjugation Strategies: Challenges, Recent Developments, and Future Opportunities

The covalent modification of proteins with polymers is a well-established method for improving the pharmacokinetic properties of therapeutically valuable biologics. The conjugated polymer chains of the resulting hybrid represent highly flexible macromolecular structures. As the dynamics of such systems remain rather elusive for established experimental techniques from the field of protein structure elucidation, molecular dynamics simulations have proven as a valuable tool for studying such conjugates at an atomistic level, thereby complementing experimental studies. With a focus on new developments, this review aims to provide researchers from the polymer bioconjugation field with a concise and up to date overview of such approaches. After introducing basic principles of molecular dynamics simulations, as well as methods for and potential pitfalls in modeling bioconjugates, the review illustrates how these computational techniques have contributed to the understanding of bioconjugates and bioconjugation strategies in the recent past and how they may lead to a more rational design of novel bioconjugates in the future.

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.

Coarse-Grained Molecular Dynamics of pH-Sensitive Lipids

pH-sensitive lipids represent a class of lipids that can be protonated and destabilized in acidic environments, as they become positively charged in response to low-pH conditions. They can be incorporated into lipidic nanoparticles such as liposomes, which are able to change their properties and allow specific drug delivery at the acidic conditions encountered in some pathological microenvironments. In this work, we used coarse-grained molecular-dynamic simulations to study the stability of neutral and charged lipid bilayers containing POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) and various kinds of ISUCA ((F)2-(imidazol-1-yl)succinic acid)-derived lipids, which can act as pH-sensitive molecules. In order to explore such systems, we used a MARTINI-derived forcefield, previously parameterized using all-atom simulation results. We calculated the average area per lipid, the second-rank order parameter and the lipid diffusion coefficient of both lipid bilayers made of pure components and mixtures of lipids in different proportions, under neutral or acidic conditions. The results show that the use of ISUCA-derived lipids disturbs the lipid bilayer structure, with the effect being particularly marked under acidic conditions. Although more-in depth studies on these systems must be carried out, these initial results are encouraging and the lipids designed in this research could be a good basis for developing new pH-sensitive liposomes.

Martini 3 coarse-grained force field for poly(para-phenylene ethynylene)s

Poly(para-phenylene ethynylene)s, or short PPEs, are a class of conjugated and semi-flexible polymers with a strongly delocalized π electron system and increased chain stiffness. Due to this, PPEs have a wide range of technological applications. Although the material properties of single-chains or mixtures of few PPE chains have been studied in detail, the properties of large assemblies remain to be fully explored. Here, we developed a coarse-grained model for PPEs with the Martini 3 force field to enable computational studies of PPEs in large-scale assembly. We used an optimization geometrical approach to take the shape of the π conjugated backbone into account and also applied an additional angular potential to tune the mechanical bending stiffness of the polymer. Our Martini 3 model reproduces key structural and thermodynamic observables of single PPE chains and mixtures, such as persistence length, density, packing and stacking. We show that chain entanglement increases with the expense of nematic ordering with growing PPE chain length. With the Martini 3 PPE model at hand, we are now able to cover large spatio-temporal scales and thereby to uncover key aspects for the structural organization of PPE bulk systems. The model is also predicted to be of high applicability to investigate out-of-equilibrium behavior of PPEs under mechanical force.

Polyply; a python suite for facilitating simulations of macromolecules and nanomaterials

Molecular dynamics simulations play an increasingly important role in the rational design of (nano)-materials and in the study of biomacromolecules. However, generating input files and realistic starting coordinates for these simulations is a major bottleneck, especially for high throughput protocols and for complex multi-component systems. To eliminate this bottleneck, we present the polyply software suite that provides 1) a multi-scale graph matching algorithm designed to generate parameters quickly and for arbitrarily complex polymeric topologies, and 2) a generic multi-scale random walk protocol capable of setting up complex systems efficiently and independent of the target force-field or model resolution. We benchmark quality and performance of the approach by creating realistic coordinates for polymer melt simulations, single-stranded as well as circular single-stranded DNA. We further demonstrate the power of our approach by setting up a microphase-separated block copolymer system, and by generating a liquid-liquid phase separated system inside a lipid vesicle.