Hydration Thermodynamic Properties of Amino Acid Analogues: A Systematic Comparison of Biomolecular Force Fields and Water Models

Calculations of Absolute Free Energies, Enthalpies, and Entropies for Drug Binding

Computer simulation methods can aid in the rational design of drugs aimed at a specific target, typically a protein. The affinity of a drug for its target is given by the free energy of binding. Binding can be further characterized by the enthalpy and entropy changes in the process. Methods exist to determine exact free energies, enthalpies, and entropies that are dependent only on the quality of the potential model and adequate sampling of conformational degrees of freedom. Entropy and enthalpy are roughly an order of magnitude more difficult to calculate than the free energy. This project combines a replica exchange method for enhanced sampling, designed to be efficient for protein-sized systems, with free energy calculations. This approach, replica exchange with dynamical scaling (REDS), uses two conventional simulations at different temperatures so that the entropy can be found from the temperature dependence of the free energy. A third replica is placed between them, with a modified Hamiltonian that allows it to span the temperature range of the conventional replicas. REDS provides temperature-dependent data and aids in sampling. It is applied to the bromodomain-containing protein 4 (BRD4) system. We find that for the force fields used, the free energies are accurate but the entropies and enthalpies are not, with the entropic contribution being too positive. Reproducing the entropy and enthalpy of binding appears to be a more stringent test of the force fields than reproducing the free energy.

Unraveling Desmin's Head Domain Structure and Function

Understanding the structure and function of intermediate filaments (IFs) is necessary in order to explain why more than 70 related IF genes have evolved in vertebrates while maintaining such dramatically tissue-specific expression. Desmin is a member of the large multigene family of IF proteins and is specifically expressed in myocytes. In an effort to elucidate its muscle-specific behavior, we have used a yeast two-hybrid system in order to identify desmin's head binding partners. We described a mitochondrial and a lysosomal protein, NADH ubiquinone oxidoreductase core subunit S2 (NDUFS2), and saposin D, respectively, as direct desmin binding partners. In silico analysis indicated that both interactions at the atomic level occur in a very similar way, by the formation of a three-helix bundle with hydrophobic interactions in the interdomain space and hydrogen bonds at R16 and S32 of the desmin head domain. The interactions, confirmed also by GST pull-down assays, indicating the necessity of the desmin head domain and, furthermore, point out its role in function of mitochondria and lysosomes, organelles which are disrupted in myopathies due to desmin head domain mutations.

A dual computational and experimental strategy to enhance TSLP antibody affinity for improved asthma treatment

Thymic stromal lymphopoietin is a key cytokine involved in the pathogenesis of asthma and other allergic diseases. Targeting TSLP and its signaling pathways is increasingly recognized as an effective strategy for asthma treatment. This study focused on enhancing the affinity of the T6 antibody, which specifically targets TSLP, by integrating computational and experimental methods. The initial affinity of the T6 antibody for TSLP was lower than the benchmark antibody AMG157. To improve this, we utilized alanine scanning, molecular docking, and computational tools including mCSM-PPI2 and GEO-PPI to identify critical amino acid residues for site-directed mutagenesis. Subsequent mutations and experimental validations resulted in an antibody with significantly enhanced blocking capacity against TSLP. Our findings demonstrate the potential of computer-assisted techniques in expediting antibody affinity maturation, thereby reducing both the time and cost of experiments. The integration of computational methods with experimental approaches holds great promise for the development of targeted therapeutic antibodies for TSLP-related diseases.

Integrating multiscale and machine learning approaches towards the SAMPL9 log P challenge

The partition coefficient (log P) is an important physicochemical property that provides information regarding a molecule's pharmacokinetics, toxicity, and bioavailability. Methods to accurately predict the partition coefficient have the potential to accelerate drug design. In an effort to test current methods and explore new computational techniques, the statistical assessment of the modeling of proteins and ligands (SAMPL) has established a blind prediction challenge. The ninth iteration challenge was to predict the toluene-water partition coefficient (log Ptol/w) of sixteen drug molecules. Herein, three approaches are reported broadly under the categories of quantum mechanics (QM), molecular mechanics (MM), and data-driven machine learning (ML). The three blind submissions yield mean unsigned errors (MUE) ranging from 1.53-2.93 log Ptol/w units. The MUEs were reduced to 1.00 log Ptol/w for the QM methods. While MM and ML methods outperformed DFT approaches for challenge molecules with fewer rotational degrees of freedom, they suffered for the larger molecules in this dataset. Overall, DFT functionals paired with a triple-ζ basis set were the simplest and most effective tool to obtain quantitatively accurate partition coefficients.

Kallistatin as an inhibitory protein against colorectal cancer cells through binding to LRP6

Kallistatin (KL) is a member of the serine proteinase inhibitor (serpin) family regulating oxidative stress, vascular relaxation, inflammation, angiogenesis, cell proliferation, and invasion. The heparin-binding site of Kallistatin has an important role in the interaction with LRP6 leading to the blockade of the Wnt signaling pathway. In this study, we aimed to explore the structural basis of the Kallistatin-LRP6E1E4 complex using in silico approaches and evaluating the anti-proliferative, apoptotic, and cell cycle arrest activities of Kallistatin in colon cancer lines. The molecular docking showed Kallistatin could bind to the LRP6E3E4 much stronger than LRP6E1E2. The Kallistatin-LRP6E1E2 and Kallistatin-LRP6E3E4 complexes were stable during Molecular Dynamics (MD) simulation. The Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) showed that the Kallistatin-LRP6E3E4 has a higher binding affinity compared to Kallistatin-LRP6E1E2. Kallistatin induced higher cytotoxicity and apoptosis in HCT116 compared to the SW480 cell line. This protein-induced cell-cycle arrest in both cell lines at the G1 phase. The B-catenin, cyclin D1, and c-Myc expression levels were decreased in response to treatment with Kallistatin in both cell lines while the LRP6 expression level was decreased in the HCT116 cell line. Kallistatin has a greater effect on the HCT116 cell line compared to the SW480 cell line. Kallistatin can be used as a cytotoxic and apoptotic-inducing agent in colorectal cancer cell lines.

Scrutinizing the protein hydration shell from molecular dynamics simulations against consensus small-angle scattering data

Biological macromolecules in solution are surrounded by a hydration shell, whose structure differs from the structure of bulk solvent. While the importance of the hydration shell for numerous biological functions is widely acknowledged, it remains unknown how the hydration shell is regulated by macromolecular shape and surface composition, mainly because a quantitative probe of the hydration shell structure has been missing. We show that small-angle scattering in solution using X-rays (SAXS) or neutrons (SANS) provide a protein-specific probe of the protein hydration shell that enables quantitative comparison with molecular simulations. Using explicit-solvent SAXS/SANS predictions, we derived the effect of the hydration shell on the radii of gyration Rg of five proteins using 18 combinations of protein force field and water model. By comparing computed Rg values from SAXS relative to SANS in D2O with consensus SAXS/SANS data from a recent worldwide community effort, we found that several but not all force fields yield a hydration shell contrast in remarkable agreement with experiments. The hydration shell contrast captured by Rg values depends strongly on protein charge and geometric shape, thus providing a protein-specific footprint of protein-water interactions and a novel observable for scrutinizing atomistic hydration shell models against experimental data.

Complex role of chemical nature and tacticity in the adsorption free energy of carboxylic acid polymers at the oil-water interface: molecular dynamics simulations

Scientific understanding of the molecular structure and adsorption of polymers at oil-water liquid interfaces is very limited. In this study the adsorption free energy at the oil (CCl4)-water interface was estimated using umbrella sampling molecular dynamics simulations for six carboxylate type vinyl polymers differing in hydrophobic nature and tacticity: isotactic and syndiotactic poly(acrylic acid) (i-PAA, s-PAA), isotactic and syndiotactic poly(methacrylic acid) (i-PMA, s-PMA), and atactic and syndiotactic poly(ethylacrylic acid) (a-PEA, s-PEA). ΔGads values are in the order i-PMA < a-PEA < s-PEA < s-PAA < i-PAA < s-PMA. The results show the significant and complex influence of the chemical nature as well as tacticity of the polymer on its adsorption free energy as related to hydrogen bonding and orientation of bonds with respect to oil and water phases. The influence of tacticity is found to be the highest for PMA, which is interpreted to occur due to the balance between interactions among side groups and those occurring between side groups and solvent. Interactions between side-groups are crucial for determining the conformation of PAA (most hydrophilic) and the solvation of the side-group in water is crucial for determining the conformation of PEA (most hydrophobic). The adsorption of PMA represents the transition between these two dominating effects. The molecular contributions to the enthalpy of adsorption indicate that adsorption is favored mainly through two interactions: polymer-CCl4 and water-water.

The role of hydrophobic interactions in the molten globule state of globular protein modulated by surfactants

In order to highlight the role of hydrophobic interactions in the molten globule (MG) state of globular protein modulated by surfactants, the interactions of bovine α-lactalbumin (α-LA) with alkyl trimethylammonium bromides (CnTAB, n = 10, 12, 14, and 16) have been studied by experimental and theoretical techniques. Isothermal titration calorimetry (ITC) showed that the enthalpy changes (ΔH) and area of the enthalpogram increased with increasing the chain length of CnTAB. The result of fluorescence, circular dichroism (CD) and 1H nuclear magnetic resonance (NMR) spectrum suggested that C10TAB and C12TAB unfolded α-LA partially, C14TAB reconstructed protein with a native-like secondary structure content, and C16TAB induced an MG state α-LA. The SAXS results confirmed that the tertiary structure of α-LA was disrupted by C16TAB forming an MG state complex with a micelle-like structure even at the surfactants concentrations below CMC. As indicated by MD results, the β-domain and unstructured region(s) were involved in the MG state α-LA modulated by CnTAB. This work not only provides molecular insights into the role of hydrophobic interactions in the MG state of a globular protein but also helps understand the mechanism of preparing α-LA based biomacromolecule modulated by hydrophobic interactions.

On the Path to Optimal Alchemistry

Alchemical free energy calculations have become a standard and widely used tool, in particular for calculating and comparing binding affinities of drugs. Although methods to compute such free energies have improved significantly over the last decades, the choice of path between the end states of interest is usually still the same as two decades ago. We will show that there is a fundamentally arbitrary, implicit choice of parametrization of this path. To address this, the notion of the length of a path or a metric is required. A metric recently introduced in the context of the accelerated weight histogram method also proves to be very useful here. We demonstrate that this metric can not only improve the efficiency of sampling along a given path, but that it can also be used to improve the actual choice of path. For a set of relevant use cases, the combination of these improvements can increase the efficiency of alchemical free energy calculations by up to a factor 16.

Structural evolution of water-in-propylene carbonate mixtures revealed by polarized Raman spectroscopy and molecular dynamics

The liquid structure of systems wherein water is limited in concentration or through geometry is of great interest in various fields such as biology, materials science, and electrochemistry. Here, we present a combined polarized Raman and molecular dynamics investigation of the structural changes that occur as water is added incrementally to propylene carbonate (PC), a polar, aprotic solvent that is important in lithium-ion batteries. Polarized Raman spectra of PC solutions were collected for water mole fractions 0.003 ≤ χwater ≤ 0.296, which encompasses the solubility range of water in PC. The novel approach taken herein provides additional hydrogen bond and solvation characterization of this system that has not been achievable in previous studies. Analysis of the polarized carbonyl Raman band in conjunction with simulations demonstrated that the bulk structure of the solvent remained unperturbed upon the addition of water. Experimental spectra in the O-H stretching region were decomposed through Gaussian fitting into sub-bands and comparison to studies of dilute HOD in D2O. With the aid of simulations, we identified these different bands as water arrangements having different degrees of hydrogen bonding. The observed water structure within PC indicates that water tends to self-aggregate, forming a hydrogen bond network that is distinctly different from the bulk and dependent on concentration. For example, at moderate concentrations, the most likely aggregate structures are chains of water molecules, each with two hydrogen bonds.

Sorption-Deformation Interplay in Hierarchical Porous Polymeric Structures Composed of a Slit Pore in an Amorphous Matrix

Prevailing absorbents like wood-derived porous scaffolds or polymeric aerogels are normally featured with hierarchical porous structures. In former molecular simulation studies, sorption, deformation, and coupled sorption-deformation have been studied for single-scale materials, but scarcely for materials where micropores (<2 nm) and mesopores (2-50 nm) coexist. The present work, dealing with a mesoscopic slit pore between two slabs of microporous amorphous cellulose (AC), aims at modeling sorption-deformation interplay in hierarchical porous cellulosic structures inspired by polymeric modern adsorbents. Specifically, the atomic system is modeled by a hybrid workflow combining molecular dynamics (MD) and grand canonical Monte Carlo (GCMC) simulations. The results clarify the multiple sorption/deformation mechanisms in porous materials with different slit-pore sizes, including water filling in micropores, surface covering at the solid-air interface, and subsequent capillary condensation in mesopores. In particular, before the onset of capillary condensation, the sorption behavior of the AC matrix in the hybrid system is almost the same as that of bulk AC, in which sorption and deformation enhance each other through sorption-induced swelling and additional sorption in the newly created voids. Upon capillary condensation, the interaction between the micropores and the mesopore emerges. Water molecules in the mesopore exert a negative hydrostatic pressure perpendicular to the slab surface on the matrices, resulting in an increase in porosity and water content, a decrease in distance between the centers of mass (COMs) of the slabs, and thus a thinning of the slit pore. As described by Bangham's Law, the surface area of the rough slit-pore slab increases proportionally to the surface energy variation during surface covering. For a system composed of a compliant polymer like AC, however, the surface area enlargement does not result in an in-plane swelling as expected but instead in an in-plane shrinkage along with an increase in local roughness or irregularity (an accordion effect).

Solvation thermodynamics from cavity shapes of amino acids

According to common physical chemistry wisdom, the solvent cavities hosting a solute are tightly sewn around it, practically coinciding with its van der Waals surface. Solvation entropy is primarily determined by the surface and the volume of the cavity while enthalpy is determined by the solute-solvent interaction. In this work, we challenge this picture, demonstrating by molecular dynamics simulations that the cavities surrounding the 20 amino acids deviate significantly from the molecular surface. Strikingly, the shape of the cavity alone can be used to predict the solvation free energy, entropy, enthalpy, and hydrophobicity. Solute-solvent interactions involving the different chemical moieties of the amino acid, determine indirectly the cavity shape, and the properties of the branches but do not have to be taken explicitly into account in the prediction model.

Structure and interaction of therapeutic proteins in solution: a combined simulation and experimental study

The aggregation of therapeutic proteins in solution has attracted significant interest, driving efforts to understand the relationship between microscopic structural changes and protein-protein interactions determining aggregation processes in solution. Additionally, there is substantial interest in being able to predict aggregation based on protein structure as part of molecular developability assessments. Molecular Dynamics provides theoretical tools to complement experimental studies and to interrogate and identify the microscopic mechanisms determining aggregation. Here we perform all-atom MD simulations to study the structure and inter-protein interaction of the Fab and Fc fragments of the monoclonal antibody (mAb) COE3. We unravel the role of ion-protein interactions in building the ionic double layer and determining effective inter-protein interaction. Further, we demonstrate, using various state-of-the-art force fields (charmm, gromos, amber, opls/aa), that the protein solvation, ionic structure and protein-protein interaction depend significantly on the force field parameters. We perform SANS and Static Light Scattering experiments to assess the accuracy of the different forcefields. Comparison of the simulated and experimental results reveal significant differences in the forcefields' performance, particularly in their ability to predict the protein size in solution and inter-protein interactions quantified through the second virial coefficients. In addition, the performance of the forcefields is correlated with the protein hydration structure.

Mechanism Exploration of Amyloid-β-42 Disaggregation by Single-Chain Variable Fragments of Alzheimer's Disease Therapeutic Antibodies

Alzheimer's disease (AD) is a specific neurodegenerative disease. This study adopts single-chain variable fragments (scFvs) as a potential immunotherapeutic precursor for AD. According to the remarkable effects of monoclonal antibodies, such as the depolymerization or promotion of Aβ42 efflux by Crenezumab, Solanezumab, and 12B4, it is attractive to prepare corresponding scFvs targeting amyloid-β-42 protein (Aβ42) and investigate their biological activities. Crenezumab-like scFv (scFv-C), Solanezumab-like scFv (scFv-S), and 12B4-like scFv (scFv-12B4) were designed and constructed. The thermal stabilities and binding ability to Aβ42 of scFv-C, scFv-S, and scFv-12B4 were evaluated using unfolding profile and enzyme-linked immunosorbent assay. As the results indicated that scFv-C could recognize Aβ42 monomer/oligomer and promote the disaggregation of Aβ42 fiber as determined by the Thioflavin-T assay, the potential mechanism of its interaction with Aβ42 was investigated using molecular dynamics analysis. Interactions involving hydrogen bonds and salt bonds were predicted between scFv-C and Aβ42 pentamer, suggesting the possibility of inhibiting further aggregation of Aβ42. The successfully prepared scFvs, especially scFv-C, with favorable biological activity targeting Aβ42, might be developed for a potentially efficacious clinical application for AD.

Differences in solvation thermodynamics of oxygenates at Pt/Al2O3 perimeter versus Pt(111) terrace sites

A prominent role of water in aqueous-phase heterogeneous catalysis is to modify free energies; however, intuition about how is based largely on pure metal surfaces or even homogeneous solutions. Using multiscale modeling with explicit liquid water molecules, we show that the influence of water on the free energies of adsorbates at metal/support interfaces is different than that on pure metal surfaces. We specifically compute free energies of solvation for methanol and its constituents on a Pt/Al₂O₃ catalyst and compare the results to analogous values calculated on a pure Pt catalyst. We find that the more hydrophilic Pt/Al₂O₃ interface leads to smaller (more positive) free energies of solvation due to an increased entropy penalty resulting from the additional work necessary to disrupt the interfacial water structure and accommodate the interfacial species. The results will be of interest in other fields, including adsorption and proteins.

Electric Field-Controlled Peptide Self-Assembly through Funnel-Shaped Two-Dimensional Nanopores

Self-assembly of biomolecules is critical for the realization of biological functions. Thus, the precise control of self-assembly has great significance in the design of biochips and biomedical agents. In this report, we design a Y-shaped funnel on a two-dimensional (2D) heterostructure, called 2D funnel, based on monolayered polyaniline carbon nitride (C₃N) and boron carbide (BC₃), and study its application in the self-assembly state regulation of the peptide oligomer, using Aβ_16-21 as the representative model. Structurally, the 2D funnel is composed of three regions: channel area, triangle area, and barrier area. The channel and triangle areas show higher binding affinity to the peptide than that of the barrier area, which leads to the confinement of the peptide in the 2D funnel. Our results show that when an external electric field is applied along the 2D funnel, the oligomer is driven to migrate across the funnel. Its trajectory is confined inside the narrow channel area, which effectively causes peptide dissociation into the individual peptide chains. Then, when the external electric field is turned off, the separated peptide chains spontaneously assemble in the triangle area and tend to reunite. Our present findings propose a novel heterostructure platform, which enables the manipulation of the self-assembly state of peptides by switching the electric field, which could guide the design and fabrication of nanodevices for sensing and sequencing applications.

Understanding the role of water on temperature-dependent structural modifications of SARS CoV-2 main protease binding sites

Thermally stable and labile proteases are found in microorganisms. Protease mediates the cleavage of polyproteins in the virus replication and transcription process. 6 µs MD simulations were performed for monomer/dimer SARS CoV-2 main protease system in both SPC/E and mTIP3P water model to analyse the temperature-dependent behaviour of the protein. It is found that maximum conformational changes are observed at 348 K which is near the melting temperature. Network distribution of evolved conformations shows an increase in the number of communities with the rise in the temperature. The global conformation of the protein was found to be intact whereas a local conformational space evolved due to thermal fluctuations. The global conformational change in the free energy ΔΔG value for the monomer and the dimer between 278 K and 383 K is found to be 2.51 and 2.10 kJ/mol respectively. A detailed analysis was carried out on the effect of water on the temperature-dependent structural modifications of four binding pockets of SARS CoV-2 main protease namely, catalytic dyad, substrate-binding site, dimerization site and allosteric site. It is found that the water structure around the binding sites is altered with temperature. The water around the dimer sites is more ordered than the monomer sites regardless of the rise in temperature due to structural rigidity. The energy expense of binding the small molecules at substrate binding is less compared to the allosteric site. The water-water hydrogen bond lifetime is found to be more near the cavity of His41. Also, it is observed that mTIP3P water molecules have a similar effect to that of SPC/E water molecules on the main protease.

Temperature induced change of TMAO effects on hydrophobic hydration

The effect of trimethylamine-N-oxide (TMAO) on hydrophobic solvation and hydrophobic interactions of methane has been studied with Molecular Dynamics simulations in the temperature range between 280 and 370 K at 1 bar ambient pressure. We observe a temperature transition in the effect of TMAO on the aqueous solubility of methane. At low temperature (280 K), methane is preferentially hydrated, causing TMAO to reduce its solubility in water, while above 320 K, methane preferentially interacts with TMAO, causing TMAO to promote its solubility in water. Based on a statistical-mechanical analysis of the excess chemical potential of methane, we find that the reversible work of creating a repulsive methane cavity opposes the solubility of methane in TMAO/water solution more than in pure water. Below 320 K, this solvent-excluded volume effect overcompensates the contribution of methane–TMAO van der Waals interactions, which promote the solvation of methane and are observed at all temperatures. These van der Waals interactions with the methyl groups of TMAO tip the balance above 320 K where the effect of TMAO on solvent-excluded volume is smaller. We furthermore find that the effective attraction between dissolved methane solutes increases with the increasing TMAO concentration. This observation correlates with a reduction in the methane solubility below 320 K but with an increase in methane solubility at higher temperatures.

Exploration of the Interactions between Maltase–Glucoamylase and Its Potential Peptide Inhibitors by Molecular Dynamics Simulation

Diabetes mellitus, a chronic metabolic disorder, represents a serious threat to human health. The gut enzyme maltase–glucoamylase (MGAM) has attracted considerable attention as a potential therapeutic target for the treatment of type 2 diabetes. Thus, developing novel inhibitors of MGAM holds the promise of improving clinical management. The dipeptides, Thr-Trp (TW) and Trp-Ala (WA), are known inhibitors of MGAM; however, studies on how they interact with MGAM are lacking. The work presented here explored these interactions by utilizing molecular docking and molecular dynamics simulations. Results indicate that the active center of the MGAM could easily accommodate the flexible peptides. Interactions involving hydrogen bonds, cation-π, and hydrophobic interactions are predicted between TW/WA and residues including Tyr1251, Trp1355, Asp1420, Met1421, Glu1423, and Arg1510 within MGAM. The electrostatic energy was recognized as playing a dominant role in both TW-MGAM and WA-MGAM systems. The binding locations of TW/WA are close to the possible acid-base catalytic residue Asp1526 and might be the reason for MGAM inhibition. These findings provide a theoretical structural model for the development of future inhibitors.

How does excess phenylalanine affect the packing density and fluidity of a lipid membrane?

Phenylketonuria (PKU) is an autosomal recessive error of phenylalanine (Phe) metabolism, where untreated Phe becomes cytotoxic. Previous experiments found that excess Phe decreases the packing density and increases the fluidity and permeability of a lipid membrane. It was proposed that Phe forms cytotoxic nanoscopic amyloid-like fibrils. In another study, the Phe fibrils were not visible near the lipid membrane. So, what leads to the deleterious effect of Phe on the lipid membrane? We put forward a molecular mechanism for the observed effect of excess Phe on the lipid membrane using all-atom molecular dynamics simulation. This study suggests that Phe monomers spontaneously intercalate into the membrane and form small hydrogen-bonded clusters, some of which locally perturb the membrane. These local effects result in an overall reduction in the membrane packing density, enhancement of membrane fluidity, and an increase of water permeability, observed in experiments. The present study does not observe any effect of the nanoscopic fibrillar structure of Phe on the membrane. This study, therefore, provides alternative insights into the excess Phe cytotoxicity in PKU disease.

Phospholipids dock SARS-CoV-2 spike protein via hydrophobic interactions: a minimal in-silico study of lecithin nasal spray therapy

Understanding the physical and chemical properties of viral infections at molecular scales is a major challenge for the scientific community more so with the outbreak of global pandemics. There is currently a lot of effort being placed in identifying molecules that could act as putative drugs or blockers of viral molecules. In this work, we computationally explore the importance in antiviral activity of a less studied class of molecules, namely surfactants. We employ all-atoms molecular dynamics simulations to study the interaction between the receptor-binding domain of the SARS-CoV-2 spike protein and the phospholipid lecithin (POPC), in water. Our microsecond simulations show a preferential binding of lecithin to the receptor-binding motif of SARS-CoV-2 with binding free energies significantly larger than [Formula: see text]. Furthermore, hydrophobic interactions involving lecithin non-polar tails dominate these binding events, which are also accompanied by dewetting of the receptor binding motif. Through an analysis of fluctuations in the radius of gyration of the receptor-binding domain, its contact maps with lecithin molecules, and distributions of water molecules near the binding region, we elucidate molecular interactions that may play an important role in interactions involving surfactant-type molecules and viruses. We discuss our minimal computational model in the context of lecithin-based liposomal nasal sprays as putative mitigating therapies for COVID-19.

Concentration effects on the self-assembly of tyrosine molecules

Molecular self-assembly is a ubiquitous phenomenon in which individual atoms or molecules set up an ordered structure. It is of high interest for understanding the biology and a variety of diseases at the molecular level. In this work, we studied the self-assembly of tyrosine molecules via extensive molecular dynamics simulations. The formation of structures by self-assembly was systematically studied at various concentrations, from very low to very high. The temperature was kept constant, at which, in our former studies, we have already observed well-formed self-assembled structures. Depending on the concentration, the system displays a wide range of different structures, ranging from freely scattered monomers to very well formed four-fold structures. Different regimes of concentration dependence are observed. The results are proved by calculating the moments of inertia of the structures and the number of hydrogen bonds formed. Free energy landscapes calculated for the number of hydrogen bonds versus the number of contacts within a criterion provide insights into the structures observed.

Propensity, free energy contributions and conformation of primary n-alcohols at a water surface

Atmospheric aerosols contain organic molecules that serve as cloud condensation nucleation sites and affect the climate. Several experimental and simulation studies have been dedicated to investigate their surface propensity, but the mechanisms that drive them to the water surface are still not fully understood. In this molecular dynamics (MD) simulation study, primary alcohols are considered as a model system representing polar organic molecules. We find that the surface affinity of n-alcohols increases linearly with the length of the hydrophobic tail. By decomposing the adsorption free energy into enthalpy and entropy contributions, we find that the transition from bulk to surface is entropically driven, compatible with the fact that the hydrophobic effect of small solutes is of entropic origin. The enthalpy of surface adsorption is nearly invariant among different n-alcohols because the loss of solvent-alcohol interactions is balanced by a gain in solvent-solvent interactions. Structural analysis shows that, at the surface, the linear alcohols prefer an orientation with the hydrophobic tail pointing out from the surface, whereas the hydroxyl group remains buried in the water. This general behaviour is likely transferable to other small molecules with similar structures but other functional groups that are present in the atmosphere. Therefore, the present study is a step forward toward a general description of organic molecules in aerosols.

Force Field Benchmark of Amino Acids. 3. Hydration with Scaled Lennard-Jones Interactions

Classical protein force fields were reported with too weak protein-water interactions relative to protein-protein interactions, leading to more compact structures and artificial protein aggregation. Here we investigated the impacts of scaled Lennard-Jones (LJ) interactions on the hydration of amino acids and the simulation of folded and intrinsically disordered proteins (IDPs). The obtained optimal scaling parameters reproduce accurately hydration free energies of neutral amino acid side chain analogues and do not affect the compactness and structural stability of folded proteins significantly. The scaling leads to less compact IDPs and varies from case to case. Strengthening the interactions between protein and water oxygen or hydrogen atoms by increasing the interacting LJ well depth (ε) appears more effective than weakening protein-protein interactions by reducing the interacting dispersion coefficients (C₆). We demonstrate that weakening water-water interactions is a solution as well to obtaining more favorable protein-water interactions in an indirect way, although modern force fields like Amber ff19SB and a99SB-disp tend to use water models with strong water-water interactions. This is likely a compromise between strong protein-protein interactions and strong water-water interactions. Independent optimization of protein force fields and water models is therefore needed to make both interactions more close to reality, leading to good accuracy without bias or scaling.

Charge State Dependence of Amino Acid Propensity at Water Surface: Mechanisms Elucidated by Molecular Dynamics Simulations

Atmospheric aerosols contain a variety of compounds, among them free amino acids and salt ions. The pH of the aerosol droplets depends on their origin and environment. Consequently, compounds like free amino acids found in the droplets will be at different charge states, since these states to a great extent depend on the surrounding pH condition. In droplets of marine origin, amino acids are believed to drive salt ions to the water surface and a pH-dependent amino acid surface propensity will, therefore, indirectly affect many processes in atmospheric chemistry and physics such as for instance cloud condensation. To understand the surface propensity of glycine, valine, and phenylalanine at acidic, neutral, and basic pH, we used molecular dynamics (MD) simulations to investigate them at three different charge states in water. Their respective surface propensities were obtained by the means of a potential of mean force (PMF) in an umbrella sampling approach. Glycine was found to have no preference for the surface, while both valine and phenylalanine showed high propensities. Among the charge states of the surface-enriched ones, the cation, representing the amino acids at low pH, was found to have the highest affinity. Free energy decomposition revealed that the driving forces depend strongly on the nature of the amino acid and its charge state. In phenylalanine, the main factor was found to be a substantial entropy gain, likely related to the side chain, whereas in valine, hydrogen bonding to the functional groups leads to favorable energies and, in turn, affects the surface propensity. A significant gain in water-water enthalpy was seen for both valine and phenylalanine.

Three- and four-site models for heavy water: SPC/E-HW, TIP3P-HW, and TIP4P/2005-HW

Heavy water or deuterium oxide, D₂O, is used as a solvent in various biophysical and chemical experiments. To model such experiments with molecular dynamics simulations, effective pair potentials for heavy water are required, which reproduce the well-known physicochemical differences relative to light water. We present three effective pair potentials for heavy water, denoted SPC/E-HW, TIP3P-HW, and TIP4P/2005-HW. The models were parameterized by modifying the widely used three- and four-site models for light water, with the aim of maintaining the specific characteristics of the light water models. At room temperature, SPC/E-HW and TIP3P-HW capture the modulations relative to light water of the mass and electron densities, heat of vaporization, diffusion coefficient, and water structure. TIP4P/2005-HW captures, in addition, the density of heavy water over a wide temperature range.

Xanthone glucoside 2-β-D-glucopyranosyl-1,3,6,7-tetrahydroxy-9H-xanthen-9-one binds to the ATP-binding pocket of glycogen synthase kinase 3β and inhibits its activity: implications in prostate cancer and associated cardiovascular disease risk

Glycogen synthase kinase 3 (GSK3) is a serine/threonine kinase which in the presence of ATP in its ATP-binding pocket transfers a phosphate to a primed substrate. GSK3β is an isoform of GSK3 which has been projected as a potent therapeutic target in human diseases including cancers and metabolic syndrome. Incidentally, cardiovascular disease is a common cause of non-cancer related deaths in prostate cancer (PCa) patients, mainly due to the effects of androgen-deprivation therapy (ADT), a mainstay for PCa treatment. Several small molecular inhibitors of GSK3 are either ATP-competitive (bind to the ATP-binding pocket), or non-ATP-competitive inhibitors (binding to the substrate-binding site of the enzyme). In this study, 2-β-D-glucopyranosyl-1,3,6,7-tetrahydroxy-9H-xanthen-9-one (βDGT), a natural xanthonoid present in many plant species, is reported to bind to the ATP-binding pocket of GSK3β and inhibit its activity, as demonstrated by the molecular docking and molecular dynamics simulation analysis and experimental validation in vitro. A comparison of the binding affinities with five known ATP-competitive inhibitors of GSK3β suggested similarity in binding site residues in the ATP-binding pocket of the enzyme. The optimum inhibitory concentration of the xanthonoid as determined by the luminescent kinase assay was 200 µM. The study envisages the use of βDGT as a natural ATP-competitive inhibitor of GSK3β and implicates its use in PCa patients on ADT, a cardiovascular disease risk, and other pathological conditions where GSK3 inhibition may be clinically important. HighlightsGSK3β is a multifaceted kinase known for its role in cancers, cardiovascular, and other diseases.In this study, βDGT, a xanthonoid, is reported to bind to the ATP-binding pocket of GSK3β.A comparison of βDGT binding with 5 known ATP-competitive inhibitors of GSK3β suggested the involvement of residues at the ATP binding site.The binding site analysis suggested an ATP-competitive mechanism of enzyme inhibition.Study envisages the use of βDGT as a natural ATP-competitive inhibitor of GSK3β and implicates its use in prostate cancer patients on androgen-deprivation therapy, a cardiovascular disease risk, and other pathological conditions.Communicated by Ramaswamy H. Sarma.

Theoretical insights into molecular mechanism and energy criteria of PARP-2 enzyme inhibition by benzimidazole analogues

The emergence of poly (ADP-ribose) polymerase (PARP) inhibitors targeting a class of PARP enzymes has gained a great interest in cancer therapy. Majority of the PARP inhibitors are not isoform-selective which may cause unwanted off-target effects. In the present study, we explore the molecular mechanism and energy requirements for PARP-2 inhibition. This involves docking studies, frontier molecular orbital analysis, 500 ns molecular dynamics simulation (MD), binding free energy analysis and principal component analysis. The results clearly suggest the importance of hydrogen bonding (Gly429, Gln332, Ser470, Tyr455) and π-π stacking interactions (His428, Tyr455, Tyr462, Phe463, Tyr473) between residues and the inhibitor. Presence of lowest unoccupied molecular orbitals favors π-π stacking interactions and highest occupied molecular orbital orbital favors hydrogen-bonding interactions in the ligands. The stability of most active/PARP-2 complex is confirmed by hydrogen bonding and π-π stacking interaction parameters. Molecular-mechanics Poisson-Boltzmann surface area energy calculations showed that van der Waals and nonpolar solvation energy terms are crucial components for the stable binding of the ligands. Per residue analysis showed that tyrosine, histidine, and phenyl alanine residues are responsible for hydrophobic interactions with the ligands. Four new inhibitors are designed based on this study and the stability of PARP-2/inhibitor complex is validated by MD, density functional theory studies, and ADME/toxicity properties. Information from the present study can serve as a basis for designing new isoform-selective PARP-2 inhibitors.

Determining the hydration free energies of selected small molecules with MP2 and local MP2 through adaptive force matching

Force fields for seven small solute molecules, ethanol, 2-methyl-1-propanol, 2-butanol, cyclohexene, tetrahydropyran, 1,4-dioxane, and 1,4-butanediol, in dilute aqueous solutions were created with the adaptive force matching (AFM) method using MP2 or local MP2 as reference. The force fields provide a way to predict the hydration free energies (HFEs) of these molecules with only electronic structure calculations as reference. For six of the seven molecules, the predicted HFEs are in very good agreement with experiments. For 1,4-butanediol, the model created by force matching LMP2 provides a HFE that is too positive. Further investigation suggests that LMP2 may not be sufficiently accurate for computing HFEs for alcohols with AFM. Other properties, such as enthalpy of hydration, diffusion constants, and vibrational spectra, are also computed with the force field developed. The force fields developed by AFM provide a bridge for computing ensemble properties of the reference electronic structure method. With MP2 and LMP2 as reference methods, the computed properties of the small molecular solutes are found to be in good agreement with experiments.

A new one-site coarse-grained model for water: Bottom-up many-body projected water (BUMPer). I. General theory and model

Water is undoubtedly one of the most important molecules for a variety of chemical and physical systems, and constructing precise yet effective coarse-grained (CG) water models has been a high priority for computer simulations. To recapitulate important local correlations in the CG water model, explicit higher-order interactions are often included. However, the advantages of coarse-graining may then be offset by the larger computational cost in the model parameterization and simulation execution. To leverage both the computational efficiency of the CG simulation and the inclusion of higher-order interactions, we propose a new statistical mechanical theory that effectively projects many-body interactions onto pairwise basis sets. The many-body projection theory presented in this work shares similar physics from liquid state theory, providing an efficient approach to account for higher-order interactions within the reduced model. We apply this theory to project the widely used Stillinger-Weber three-body interaction onto a pairwise (two-body) interaction for water. Based on the projected interaction with the correct long-range behavior, we denote the new CG water model as the Bottom-Up Many-Body Projected Water (BUMPer) model, where the resultant CG interaction corresponds to a prior model, the iteratively force-matched model. Unlike other pairwise CG models, BUMPer provides high-fidelity recapitulation of pair correlation functions and three-body distributions, as well as N-body correlation functions. BUMPer extensively improves upon the existing bottom-up CG water models by extending the accuracy and applicability of such models while maintaining a reduced computational cost.

Structure and dynamics of an aqueous solution containing poly-(acrylic acid) and non-ionic surfactant octaethylene glycol n-decyl ether (C10E8) aggregates and their complexes investigated by molecular dynamics simulations

A detailed molecular dynamics simulation study of the self-assembly, intermolecular structure and thermodynamic behavior of an aqueous solution of non-ionic surfactant octa ethylene glycol n-decyl ether (C₁₀E₈) in the presence of a non-ionic polar polymer poly(acrylic acid) PAA is presented. The aggregation number N_agg and concentration of surfactant C_s in the simulation systems were varied in the range 0.01-0.32 M and 5 < N_agg < 101 (dilute to concentrated) with a dilute polymer concentration (C_p = 0.01 M). Lamellar aggregates of non-ionic surfactant in bulk aqueous solution are shown by molecular level computations for the first time. Spherical micellar aggregates and lamellar aggregates are formed at low and high N_agg, respectively. The transition from the spherical micelle phase to the lamellar phase in a binary solution is captured for the first time. A conformational transition from coiled to extended PAA chains adsorbed on the surfactant aggregate occurs at a particular value of N_agg, commensurate with the transition from spherical micelle aggregates to anisotropic lamellar aggregates. Formation of the surfactant aggregate in binary and ternary solutions and the polymer-surfactant complex in a ternary solution is enthalpically favored. Adsorption of PAA on the surfactant aggregate surface is driven by hydrogen bonds (HBs) between carboxylic acid groups of PAA and ethylene oxide groups of C₁₀E₈. A significant number of HBs occur between polar oxygens of C₁₀E₈ and hydroxyl oxygens of PAA. The results are in agreement with the limited available experimental data on this system.

Ligand Affinities within the Open-Boundary Molecular Mechanics/Coarse-Grained Framework (I): Alchemical Transformations within the Hamiltonian Adaptive Resolution Scheme

Our recently developed Open-Boundary Molecular Mechanics/Coarse Grained (OB-MM/CG) framework predicts ligand poses in important pharmaceutical targets, such as G-protein Coupled Receptors, even when experimental structural information is lacking. The approach, which is based on GROMOS and AMBER force fields, allows for grand-canonical simulations of protein-ligand complexes by using the Hamiltonian Adaptive Resolution Scheme (H-AdResS) for the solvent. Here, we present a key step toward the estimation of ligand binding affinities for their targets within this approach. This is the implementation of the H-AdResS in the GROMACS code. The accuracy of our implementation is established by calculating hydration free energies of several molecules in water by means of alchemical transformations. The deviations of the GROMOS- and AMBER-based H-AdResS results from the reference fully atomistic simulations are smaller than the accuracy of the force field and/or they are in the range of the published results. Importantly, our predictions are in good agreement with experimental data. The current implementation paves the way to the use of the OB-MM/CG framework for the study of large biological systems.

Tuning the binding behaviors of a protein YAP65WW domain on graphenic nano-sheets with boron or nitrogen atom doping

In recent years, nanomaterials have attracted considerable research attention for biological and medical related applications due to their well-recognized physical and chemical properties. However, the deep understanding of the binding process at the protein-nanomaterial interface is essential to solve the concern of nano-toxicity. Here, we study the interactions between the recently reported graphenic nano-sheets, BC₃ and C₃N, and a prototypical protein (YAP65WW domain) via atomistic molecular dynamics simulations. Our simulations reveal that elemental doping is an effective way to tune the binding characteristics of YAP65WW with two nanomaterials. While YAP65WW can be attracted by two nanomaterials, the BC₃ sheet is less able to disrupt the protein structure than C₃N. From the energy point of view, this is because protein residues demonstrate a binding preference with the trend from electron rich nitrogen to electron deficient boron. Structural analyses of the bio-nano interface revealed the formation of an ordered water shell on the BC₃ surface, which was compatible to the crystal pattern of BC₃. When a protein binds with BC₃, these interfacial water molecules protect the protein from being disrupted. We suggest that elemental doping is efficient to produce fruitful biological-effects of graphenic nanomaterials, which make it a prospective solution for the future design and fabrication of advanced nanomaterials with desired function.

Leveraging Systematic Functional Analysis to Benchmark an In Silico Framework Distinguishes Driver from Passenger MEK Mutants in Cancer

Despite significant advances in cancer precision medicine, a significant hurdle to its broader adoption remains the multitude of variants of unknown significance identified by clinical tumor sequencing and the lack of biologically validated methods to distinguish between functional and benign variants. Here we used functional data on MAP2K1 and MAP2K2 mutations generated in real-time within a co-clinical trial framework to benchmark the predictive value of a three-part in silico methodology. Our computational approach to variant classification incorporated hotspot analysis, three-dimensional molecular dynamics simulation, and sequence paralogy. In silico prediction accurately distinguished functional from benign MAP2K1 and MAP2K2 mutants, yet drug sensitivity varied widely among activating mutant alleles. These results suggest that multifaceted in silico modeling can inform patient accrual to MEK/ERK inhibitor clinical trials, but computational methods need to be paired with laboratory- and clinic-based efforts designed to unravel variabilities in drug response. SIGNIFICANCE: Leveraging prospective functional characterization of MEK1/2 mutants, it was found that hotspot analysis, molecular dynamics simulation, and sequence paralogy are complementary tools that can robustly prioritize variants for biologic, therapeutic, and clinical validation.See related commentary by Whitehead and Sebolt-Leopold, p. 4042.

Olanzapine crystal symmetry originates in preformed centrosymmetric solute dimers

The symmetries of a crystal are notoriously uncorrelated to those of its constituent molecules. This symmetry breaking is typically thought to occur during crystallization. Here we demonstrate that one of the two symmetry elements of olanzapine crystals, an inversion centre, emerges in solute dimers extant in solution prior to crystallization. We combine time-resolved in situ scanning probe microscopy to monitor the crystal growth processes with all-atom molecular dynamics simulations. We show that crystals grow non-classically, predominantly by incorporation of centrosymmetric dimers. The growth rate of crystal layers exhibits a quadratic dependence on the solute concentration, characteristic of the second-order kinetics of the incorporation of dimers, which exist in equilibrium with a majority of monomers. We show that growth by dimers is preferred due to overwhelming accumulation of adsorbed dimers on the crystal surface, where it is complemented by dimerization and expedites dimer incorporation into growth sites.

How oncogenic mutations activate human MAP kinase 1 (MEK1): a molecular dynamics simulation study

Approximately 30% of all types of human cancers possess a constitutively activated the mitogen-activated protein kinase (MAPK) signaling pathway while MAP kinase 1 (MEK1) is a critical component of this pathway. It has been reported mutations could improve the activity of MEK1 to result in cell proliferation and transformation, which is a known oncogenic event in various cancer types. In this study, eight molecular dynamics simulations, molecular mechanics Poisson-Boltzmann surface area (MM-PBSA), combined with protein structure network were performed to explore the mechanism that mutations activate MEK1. Protein structure networks and hydrogen bonds analysis demonstrated that active mutations broke the interaction between activation segments (residues 216-222) and C-helix (residues 105-121) in MEK1, leading to it transform inactive form to active form. Moreover, hydrogen bond analysis and MM-PBSA calculation indicated that activating mutations decrease the binding affinity between MEK1 and inhibitor to reduce the inhibitory effect of inhibitors. In addition, some active mutations cause structural changes in the Pro-rich loop (residues 261-268) of MEK1. These changes may stabilize the interaction between the MEK1 mutants and the ligands by increasing the number of exposed hydrophobic residues in the active site of MEK1. Our results may provide useful theoretical evidences for the mechanism underlying the role of human MEK1 in human cancers.Communicated by Ramaswamy H. Sarma.

Theoretical Exploring Selective-Binding Mechanisms of JAK3 by 3D-QSAR, Molecular Dynamics Simulation and Free Energy Calculation

Janus kinase 3 (JAK3) plays a critical role in the JAK/STAT signaling pathway and has become an attractive selective target for the treatment of immune-mediated disorders. Therefore, great efforts have been made for the development of JAK3 inhibitors, but developing selective JAK3 inhibitors remains a great challenge because of the high sequence homology with other kinases. In order to reveal the selective-binding mechanisms of JAK3 and to find the key structural features that refer to specific JAK3 inhibition, a systematic computational method, including 3D-QSAR, molecular dynamics simulation, and free energy calculations, was carried out on a series of JAK3 isoform-selective inhibitors. Necessary pharmacodynamic structures and key residues involved in efficient JAK3-inhibition were then highlighted. Finally, 10 novel JAK3 inhibitors were designed, the satisfactory predicted binding affinity to JAK3 of these analogous demonstrated that this study may facilitate the rational design of novel and selective JAK3 inhibitors.

How Different Substitution Positions of F, Cl Atoms in Benzene Ring of 5-Methylpyrimidine Pyridine Derivatives Affect the Inhibition Ability of EGFRL858R/T790M/C797S Inhibitors: A Molecular Dynamics Simulation Study

Lung cancer is the most frequent cause of cancer-related deaths worldwide, and mutations in the kinase domain of the epidermal growth factor receptor (EGFR) are a common cause of non-small-cell lung cancers, which is a major subtype of lung cancers. Recently, a series of 5-methylpyrimidine-pyridinone derivatives have been designed and synthesized as novel selective inhibitors of EGFR and EGFR mutants. However, the binding-based inhibition mechanism has not yet been determined. In this study, we carried out molecular dynamic simulations and free-energy calculations for EGFR derivatives to fill this gap. Based on the investigation, the three factors that influence the inhibitory effect of inhibitors are as follows: (1) The substitution site of the Cl atom is the main factor influencing the activity through steric effect; (2) The secondary factors are repulsion between the F atom (present in the inhibitor) and Glu762, and the blocking effect of Lys745 on the phenyl ring of the inhibitor. (3) The two factors function synergistically to influence the inhibitory capacity of the inhibitor. The theoretical results of this study can provide further insights that will aid the design of oncogenic EGFR inhibitors with high selectivity.