MARTINI Force Field Research Articles

Applicability of the MARTINI coarse-grained force field for simulations of protein oligomers in crystallization solution

The molecular dynamics of two types of lysozyme octamers was simulated under crystallization conditions in the MARTINI coarse-grained force field. Comparative analysis of the obtained results with the simulation data for the same octamers modelled in the all-atom field Amber99sb-ildn showed that octamer “A” demonstrates greater stability compared to octamer “B” in both force fields. Thus, the results of molecular dynamics simulations of octamers using both force fields are consistent. Despite several differences in the behavior of the protein in different fields, they do not affect the validity of the data obtained using MARTINI. This confirms the applicability of the MARTINI force field for studying crystallization solutions of proteins.

Dispersion of Hydrophilic Nanoparticles in Natural Rubber with Phospholipids

Coarse-grained molecular dynamics (CGMD) simulations were employed to investigate the effects of phospholipids on the aggregation of hydrophilic, modified carbon-nanoparticle fillers in cis-polyisoprene (cis-PI) composites. The MARTINI force field was applied to model dipalmitoylphosphatidylcholine (DPPC) lipids and hydrophilic modified fullerenes (HMFs). The simulations of DPPC in cis-PI composites show that the DPPC lipids self-assemble to form a reverse micelle in a rubber matrix. Moreover, HMF molecules readily aggregate into a cluster, in agreement with the previous studies. Interestingly, the mixture of the DPPC and HMF in the rubber matrix shows a cluster of HMF is encapsulated inside the DPPC reverse micelle. The HMF encapsulated micelles disperse well in the rubber matrix, and their sizes are dependent on the lipid concentration. Mechanical and thermal properties of the composites were analyzed by calculating the diffusion coefficients (D), bulk modulus (κ), and glass transition temperatures (Tg). The results suggest that DPPC acts as a plasticizer and enhances the flexibility of the HMF-DPPC rubber composites. These findings provide valuable insights into the design and process of high-performance rubber composites, offering improved mechanical and thermal properties for various applications.

Enhanced particle removal ability of two representative nonionic surfactants: A reasonable interpretation based on DFT and coarse-grained molecular dynamics methods

Cleaning of copper surfaces after chemical mechanical polishing is indispensable for removing particle residues, which is a critical step in integrated circuits manufacturing. This paper introduces two nonionic surfactants, coconut oil diethanolamine (CDEA) and fatty alcohol polyoxyethylene ether (AEO-9), into a basic alkaline cleaning solution comprising tetraethyl ammonium hydroxide and lysine to investigate their abilities to enhance particle removal performance. Cleaning performance was measured with scanning electron microscopy, which showed that the two surfactants achieved excellent particle removal efficiency (above 95 %), with CDEA performing slightly better in all tested concentrations. Concerning critical micelle concentration, surface tension tests showed that CDEA (at 1500 ppm) had superior wettability and dispersive capacity compared with AEO-9 (at 2000 ppm) and could prevent particle redeposition more effectively. Using density functional theory, CDEA was found to have more polar groups to form hydrogen bonds with the hydrophilic surface of colloidal silica particles or bond with the copper substrate, explaining CDEA’s ability to lower the surface tension of the cleaning solution and improve the zeta potential between particles and the copper substrate. Finally, based on the Martini forcefield, simulations of coarse-grained molecular dynamics provided valuable theoretical insights into the different dispersion abilities of the two nonionic surfactants that CDEA had a more significant diffusion coefficient (0.073 Å2/ps) and was able to form micelles more efficiently in solution compared with that of AEO-9 (0.066 Å2/ps).

Role of terminal beads in fracture of topological gels: A coarse-grained molecular dynamics study

Topological gels feature movable cross-linking sites which yield great deformation capability, but we show that their long-term performance would be undesirable. Because a long backbone chain has only 2 terminal beads to restrict sliding of rings, the entire chain would fail by just a small debonding. Chain segmentation by adding terminal beads is a promising strategy to improve durability. In this work, we develop a coarse-grained (CG) model of topological gels based on MARTINI force field, to simulate tensile behaviors of the gel. The developed CG model accurately predicts elastic modulus of typical topological gels with different crosslinking densities. Based on the model, we show that adding terminal beads to the chain can effectively improve mechanical properties of topological gels after initial debonding. With analyses on distribution of ring molecules along the chain and effective load-bearing chains during tensile deformation, mechanism of the improvement on durability is discussed.

Coarse-Grained Simulations of Columnar Ionic Liquid Crystals: Comparison with Experiments.

We simulate a homologous series of guanidinium-based columnar ionic liquid crystals (ILCs) using coarse-grained molecular dynamics (MD) simulations with the Martini force field. We systematically vary the length of alkyl side chains, ILC-n (n = 8, 12, 16), and compare our results with previous experimental findings. Experimentally, ILC-8 exhibits a narrow mesophase window and weak columnar order, while ILC-12 and ILC-16 display a broad mesophase window and high columnar order. The MD simulations show that ILC-8 forms a percolated structure, whereas the longer chain analogues self-assemble into columns, with columnar assembly becoming more prominent as the side chain length increases, in qualitative agreement with the experiments. Furthermore, the intercolumnar distance increases monotonically with increasing side chain length and decreases with increasing temperature. Finally, we find that the diffusion coefficient and ionic conductivity decrease substantially with increasing chain length, consistent with experimental observations. We attribute this decrease in mobility to the formation of hexagonally ordered columns, which restrict transport more than percolated networks.

A comparative study of polyethylene oxide (PEO) using different coarse-graining methods.

Polyethylene oxide (PEO) holds significant importance in the field of batteries due to its high processability, intrinsic properties, and potential for high ionic conductivity. Achieving simulation at different scales is crucial for gaining a comprehensive understanding of its properties and thus improving them. In this context, we conducted a comparative study on the molecular physical structure, thermodynamic, and dynamic properties of PEO using three distinct coarse-grained (CG) procedures and all-atom (AA) simulations. The three CG simulation procedures involved modeling with MARTINI forcefield, SPICA forcefield, and an IBI derived potential from AA simulations. The AA simulation has been performed using the class 2 pcff+ forcefield. The ensuing simulated densities align significantly with the literature data, indicating the reliability of our approach. The solubility parameter from the AA simulation closely corresponds to literature reported values. MARTINI and SPICA yield almost similar solubility parameters, consistent with the similar density predicted by both the forcefields. Notably, SPICA forcefield closely reproduces the intermolecular structure of atomistic systems, as evidenced by radial distribution function (RDF). It also comprehensively replicates the distribution of radius of gyration (Rg) and the end-to-end distance (Re) of the atomistic samples. IBI ranks second to SPICA in emulating the structural properties of the atomistic systems, such as Rg, Re, and RDF. However, IBI falls short in accurately representing the solubility parameter of the amorphous PEO samples, while MARTINI does not provide an accurate representation of the structural properties of the systems. The use of SPICA forcefield results in enhanced dynamics of the systems in comparison with IBI and MARTINI.

Curvature Footprints of Transmembrane Proteins in Simulations with the Martini Force Field.

Membranes play essential roles in biological systems and are tremendously diverse in the topologies and chemical and elastic properties that define their functions. In many cases, a given membrane may display considerable heterogeneity, with localized clusters of lipids and proteins exhibiting distinct characteristics compared to adjoining regions. These lipid-protein assemblies can span nanometers to micrometers and are associated with cellular processes such as transport and signaling. While lipid-protein assemblages are dynamic, they can be stabilized by coupling between local membrane composition and shape. Due to the inherent difficulty in resolving atomistic details of membrane proteins in their native lipid environments, these complexes are notoriously challenging to study experimentally; however, molecular dynamics (MD) simulations might be a viable alternative. Here, we aim to assess the utility of coarse-grained (CG) MD simulations with the Martini force field for studying membrane curvature induced by transmembrane (TM) proteins that are reported to generate local curvature. The direction and magnitude of curvature induced by five different TM proteins, as well as certain lipid-protein and protein-protein interactions, were found to be in good agreement with available reference data.

Role of Unimers to Polymersomes Transition in Pluronic Blends for Controlled and Designated Drug Conveyance.

This study investigates the nanoscale self-assembly from mixtures of two symmetrical poly(ethylene oxide)-poly(propylene oxide)-pol(ethylene oxide) (PEO-PPO-PEO) block copolymers (BCPs) with different lengths of PEO blocks and similar PPO blocks. The blended BCPs (commercially known as Pluronic F88 and L81, with 80 and 10% PEO, respectively) exhibited rich phase behavior in an aqueous solution. The relative viscosity (ηrel) indicated significant variations in the flow behavior, ranging from fluidic to viscous, thereby suggesting a possible micellar growth or morphological transition. The tensiometric experiments provided insight into the intermolecular hydrophobic interactions at the liquid-air interface favoring the surface activity of mixed-system micellization. Dynamic light scattering (DLS) and small-angle neutron scattering (SANS) revealed the varied structural morphologies of these core-shell mixed micelles and polymersomes formed under different conditions. At a concentration of ≤5% w/v, Pluronic F88 exists as molecularly dissolved unimers or Gaussian chains. However, the addition of the very hydrophobic Pluronic L81, even at a much lower (<0.2%) concentration, induced micellization and promoted micellar growth/transition. These results were further substantiated through molecular dynamics (MD) simulations, employing a readily transferable coarse-grained (CG) molecular model grounded in the MARTINI force field with density and solvent-accessible surface area (SASA) profiles. These findings proved that F88 underwent micellar growth/transition in the presence of L81. Furthermore, the potential use of these Pluronic mixed micelles as nanocarriers for the anticancer drug quercetin (QCT) was explored. The spectral analysis provided insight into the enhanced solubility of QCT through the assessment of the standard free energy of solubilization (ΔG°), drug-loading efficiency (DL%), encapsulation efficiency (EE%), and partition coefficient (P). A detailed optimization of the drug release kinetics was presented by employing various kinetic models. The [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] MTT assay, a frequently used technique for assessing cytotoxicity in anticancer research, was used to gauge the effectiveness of these QCT-loaded mixed nanoaggregates.

Force matching and iterative Boltzmann inversion coarse grained force fields for ZIF-8.

Despite the intense activity at electronic and atomistic resolutions, coarse grained (CG) modeling of metal-organic frameworks remains largely unexplored. One of the main reasons for this is the lack of adequate CG force fields. In this work, we present iterative Boltzmann inversion and force matching (FM) force fields for modeling ZIF-8 at three different coarse grained resolutions. Their ability to reproduce structure, elastic tensor, and thermal expansion is evaluated and compared with that of MARTINI force fields considered in previous work [Alvares et al., J. Chem. Phys. 158, 194107 (2023)]. Moreover, MARTINI and FM are evaluated for their ability to depict the swing effect, a subtle phase transition ZIF-8 undergoes when loaded with guest molecules. Overall, we found that all our force fields reproduce structure reasonably well. Elastic constants and volume expansion results are analyzed, and the technical and conceptual challenges of reproducing them are explained. Force matching exhibits promising results for capturing the swing effect. This is the first time these CG methods, widely applied in polymer and biomolecule communities, are deployed to model porous solids. We highlight the challenges of fitting CG force fields for these materials.

Exploring Free Energies of Specific Protein Conformations Using the Martini Force Field.

Coarse-grained (CG) level molecular dynamics simulations are routinely used to study various biomolecular processes. The Martini force field is currently the most widely adopted parameter set for such simulations. The functional form of this and several other CG force fields enforces secondary protein structure support by employing a variety of harmonic potentials or restraints that favor the protein's native conformation. We propose a straightforward method to calculate the energetic consequences of transitions between predefined conformational states in systems in which multiple factors can affect protein conformational equilibria. This method is designed for use within the Martini force field and involves imposing conformational transitions by linking a Martini-inherent elastic network to the coupling parameter λ. We demonstrate the applicability of our method using the example of five biomolecular systems that undergo experimentally characterized conformational transitions between well-defined structures (Staphylococcal nuclease, C-terminal segment of surfactant protein B, LAH4 peptide, and β2-adrenergic receptor) as well as between folded and unfolded states (GCN4 leucine zipper protein). The results show that the relative free energy changes associated with protein conformational transitions, which are affected by various factors, such as pH, mutations, solvent, and lipid membrane composition, are correctly reproduced. The proposed method may be a valuable tool for understanding how different conditions and modifications affect conformational equilibria in proteins.

Coarse-Grained Model of Glycosaminoglycans for Biomolecular Simulations.

Proteoglycans contain glycosaminoglycans (GAGs) which are negatively charged linear polymers made of repeating disaccharide units of uronic acid and hexosamine units. They play vital roles in numerous physiological and pathological processes, particularly in governing cellular communication and attachment. Depending on their sulfonation state, acetylation, and glycosidic linkages, GAGs belong to different families. The high molecular weight, heterogeneity, and flexibility of GAGs hamper their characterization at atomic resolution, but this may be circumvented via coarse-grained (CG) approaches. In this work, we report a CG model for a library of common GAG types in their isolated or proteoglycan-linked states compatible with version 2.2 (v2.2) of the widely popular CG Martini force field. The model reproduces conformational and thermodynamic properties for a wide variety of GAGs, as well as matching structural and binding data for selected proteoglycan test systems. The parameters developed here may thus be employed to study a range of GAG-containing biomolecular systems, thereby benefiting from the efficiency and broad applicability of the Martini framework.

Martini on the Rocks: Can a Coarse-Grained Force Field Model Crystals?

Computational chemistry is an important tool in numerous scientific disciplines, including drug discovery and structural biology. Coarse-grained models offer simple representations of molecular systems that enable simulations of large-scale systems. Because there has been an increase in the adoption of such models for simulations of biomolecular systems, critical evaluation is warranted. Here, the stability of the amyloid peptide and organic crystals is evaluated using the Martini 3 coarse-grained force field. The crystals change shape drastically during the simulations. Radial distribution functions show that the distance between backbone beads in β-sheets increases by ∼1 Å, breaking the crystals. The melting points of organic compounds are much too low in the Martini force field. This suggests that Martini 3 lacks the specific interactions needed to accurately simulate peptides or organic crystals without imposing artificial restraints. The problems may be exacerbated by the use of the 12-6 potential, suggesting that a softer potential could improve this model for crystal simulations.

Diffusion Coefficients of Variable-Size Amphiphilic Additives in a Glass-Forming Polyethylene Matrix.

Diffusion of additives in polymers is an important issue in the plastics industry since migratory-type molecules are widely used to tune the properties of polymeric composites. Predicting the diffusional behavior of new additives can minimize the need for repetitive experiments. This work presents molecular dynamics simulations at the microsecond time scale and uses the MARTINI force field to estimate self-diffusion coefficients, D, of six monounsaturated amides and their analogs carboxylic acids in polyethylene matrices (PE, MW = 5600 Da). The results are strongly influenced by the glass-forming properties of the PE matrix, which we characterize by three distinct temperatures. The metastability region (T < 325 K), the glass transition temperature (Tg = 256-260 K), and the end of the transition (T ≅ 200 K). Self-diffusion mechanisms are inferred from the results of the dependence of D on the molecular mass of the additive, observing a Rouse-like behavior at high temperatures and deviations from it within the metastability region of the matrix. Interestingly, D values are nonsensitive to the nature of the considered polar head for additives of similar size. The temperature-dependent behavior of D follows, at fixed additive size, a linear Arrhenius pattern at high temperatures and a super Arrhenius trend at lower temperatures, which is well represented with a power law equation as predicted by the Mode Coupling Theory (MCT). We offer a conceptual explanation for the observed super-Arrhenius behavior. This explanation draws on Truhlar and Kohen's interpretation of the available energies at both the initial and the transition states along the diffusion pathway. The matrix's mobility significantly affects solute self-diffusion, yielding equal activation enthalpies for the Arrhenius region or the same power law parameters for the super-Arrhenius regime. Finally, we establish a one-to-one time-equivalence of the self-diffusion processes between CG and all-atom systems for the largest additives and the PE matrix in the high-temperature regime.

Assessment of the MARTINI 3 Performance for Short Peptide Self-Assembly.

The coarse-grained MARTINI force field, initially developed for membranes, has proven to be an exceptional tool for investigating supramolecular peptide assemblies. Over the years, the force field underwent refinements to enhance accuracy, enabling, for example, the reproduction of protein-ligand interactions and constant pH behavior. However, these protein-focused improvements seem to have compromised its ability to model short peptide self-assembly. In this study, we assess the performance of MARTINI 3 in reproducing peptide self-assembly using the well-established diphenylalanine (FF) as our test case. Unlike its success in version 2.1, FF does not even exhibit aggregation in version 3. By systematically exploring parameters for the aromatic side chains and charged backbone beads, we established a parameter set that effectively reproduces tube formation. Remarkably, these parameter adjustments also replicate the self-assembly of other di- and tripeptides and coassemblies. Furthermore, our analysis uncovers pivotal insights for enhancing the performance of MARTINI in modeling short peptide self-assembly. Specifically, we identify issues stemming from overestimated hydrophilicity arising from charged termini and disruptions in π-stacking interactions due to insufficient planarity in aromatic groups and a discrepancy in intermolecular distances between this and backbone-backbone interactions. This investigation demonstrates that strategic modifications can harness the advancements offered by MARTINI 3 for the realm of short peptide self-assembly.

Coarse-Graining Waters: Unveiling The Effective Hydrophilicity/Hydrophobicity of Individual Protein Atoms and The Roles of Waters' Hydrogens.

There have been many coarse-graining methods developed that aim to reduce the sizes of simulated systems and their computational costs. In this work, we develop a new coarse-graining method, called coarse-graining-delta (or δ-CG in short), that reduces the degrees of freedom of the potential energy surface by coarse-graining relative locations of atoms from their unit centers. Our method extends and generalizes the methods used in the coarse-grained normal mode analysis and enables us to study the roles of the individual removed atoms in a system, which have been difficult to study in molecular dynamics simulations. By applying δ-CG to coarse-grain three-point water molecules into single-point solvent particles, we successfully identify the effective hydrophilicity and hydrophobicity of all the individual protein atom types, which collectively correlate well with the known hydrophilic, hydrophobic, and amphipathic characteristics of amino acids. Moreover, our investigation shows that water's hydrogens have two roles in interacting with protein atoms. First, water molecules adjust their poses around different amino acids and their atoms, and the statistical preferences of the hydrogen poses near the atoms determine the effective hydrophilicity and hydrophobicity of the atoms, which have not been successfully addressed before. Second, the collective dynamics of the hydrogens assist the water molecules in escaping from the potential energy wells of the hydrophilic atoms. Our method also shows that coarse-graining a system mathematically leads to breaking antisymmetry of the nonbonded interactions; as a result, two interacting coarse-grained units exert different forces on each other. Our study indicates that the accuracy of coarse-grained force fields, such as the MARTINI force field and the UNRES force field, can be improved in two ways: (i) refining their potential energy functions and coefficients by analyzing the coarse-grained potential energy surface using δ-CG, and (ii) introducing non-antisymmetric interactions.

Automatic Optimization of Lipid Models in the Martini Force Field Using SwarmCG.

After two decades of continued development of the Martini coarse-grained force field (CG FF), further refinment of the already rather accurate Martini lipid models has become a demanding task that could benefit from integrative data-driven methods. Automatic approaches are increasingly used in the development of accurate molecular models, but they typically make use of specifically designed interaction potentials that transfer poorly to molecular systems or conditions different than those used for model calibration. As a proof of concept, here, we employ SwarmCG, an automatic multiobjective optimization approach facilitating the development of lipid force fields, to refine specifically the bonded interaction parameters in building blocks of lipid models within the framework of the general Martini CG FF. As targets of the optimization procedure, we employ both experimental observables (top-down references: area per lipid and bilayer thickness) and all-atom molecular dynamics simulations (bottom-up reference), which respectively inform on the supra-molecular structure of the lipid bilayer systems and on their submolecular dynamics. In our training sets, we simulate at different temperatures in the liquid and gel phases up to 11 homogeneous lamellar bilayers composed of phosphatidylcholine lipids spanning various tail lengths and degrees of (un)saturation. We explore different CG representations of the molecules and evaluate improvements a posteriori using additional simulation temperatures and a portion of the phase diagram of a DOPC/DPPC mixture. Successfully optimizing up to ∼80 model parameters within still limited computational budgets, we show that this protocol allows the obtainment of improved transferable Martini lipid models. In particular, the results of this study demonstrate how a fine-tuning of the representation and parameters of the models may improve their accuracy and how automatic approaches, such as SwarmCG, may be very useful to this end.

Coarse-grained modeling of zeolitic imidazolate framework-8 using MARTINI force fields.

In this contribution, the well-known MARTINI particle-based coarse graining approach is tested for its ability to model the ZIF-8 metal-organic framework. Its capability to describe structure, lattice parameters, thermal expansion, elastic constants and amorphization is evaluated. Additionally, the less coarsened models were evaluated for reproducing the swing effect and the host-guest interaction energies were analyzed. We find that MARTINI force fields successfully capture the structure of the Metal-Organic Framework (MOF) for different degrees of coarsening, with the exception of the MARTINI 2.0 models for the less coarse mapping. MARTINI 2.0 models predict more accurate values of C11 and C12, while MARTINI 3.0 has a tendency to underestimate them. Among the possibilities tested, the choice of bead flavors within a particular MARTINI version appears to have a less critical impact in the simulated properties of the empty framework. None of the coarse-grained (CG) models investigated were able to capture the amorphization nor the swing effect within the scope of MD simulations. A perspective on the importance of having a proper Lennard-Jones (LJ) parametrization for modeling guest-MOF and MOF-MOF interactions is highlighted.

Application of coarse-grained water model in the study of mixed collectors compounding mechanism in low-rank coal flotation

ABSTRACT The investigation of the compounding mechanisms of mixed collectors in low-rank coal flotation has gradually progressed from a macro to a micro level, and the accuracy of research outcomes significantly depends on the development of micro models. While All-Atom Molecular Dynamics (AAMD) simulations have been used for this purpose, the employment of an excessive amount of collector in the system leads to a failure in replicating the actual flotation process, which in turn, limits the practical applicability of research findings. To overcome this drawback, this paper suggests using the MARTINI Coarse-Grained force field (CGFF), developed by the S.J.Marrink group, to construct a simulation system that accurately mimics the amount of collector employed in practical flotation processes. In light of this, to make the MARTINI force field more applicable for research in the low-rank coal field, we employ density functional theory (DFT) and coarse-grained molecular dynamics (CGMD) methods to investigate water cluster interactions, identify magic number clusters, and fit the corresponding CGFF parameters to develop a CG water model suitable for exploring the compounding mechanism of mixed collectors. This research lays the groundwork for future investigations into the aggregation behavior of mixed collectors under actual usage conditions, as well as their synergistic adsorption at the coal/water interface.

Interdependence of cholesterol distribution and conformational order in lipid bilayers.

We show, via molecular simulations, that not only does cholesterol induce a lipid order, but the lipid order also enhances cholesterol localization within the lipid leaflets. Therefore, there is a strong interdependence between these two phenomena. In the ordered phase, cholesterol molecules are predominantly present in the bilayer leaflets and orient themselves parallel to the bilayer normal. In the disordered phase, cholesterol molecules are mainly present near the center of the bilayer at the midplane region and are oriented orthogonal to the bilayer normal. At the melting temperature of the lipid bilayers, cholesterol concentration in the leaflets and the bilayer midplane is equal. This result suggests that the localization of cholesterol in the lipid bilayers is mainly dictated by the degree of ordering of the lipid bilayer. We validate our findings on 18 different lipid bilayer systems, obtained from three different phospholipid bilayers with varying concentrations of cholesterol. To cover a large temperature range in simulations, we employ the Dry Martini force field. We demonstrate that the Dry and the Wet Martini (with polarizable water) force fields produce comparable results.

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.