Polarizable AMOEBA Model for Simulating Mg2+·Protein·Nucleotide Complexes.

Molecular mechanics (MM) simulations have the potential to provide detailed insights into the mechanisms of enzymes that utilize nucleotides as cofactors. In most cases, the activities of these enzymes also require the binding of divalent cations to catalytic sites. However, modeling divalent cations in MM simulations has been challenging. The inclusion of explicit polarization was considered promising, but despite improvements over nonpolarizable force fields and despite the inclusion of "Nonbonded-fix (NB-fix)" corrections, errors in interaction energies of divalent cations with proteins remain large. Importantly, the application of these models fails to reproduce the experimental structural data on Mg2+·Protein·ATP complexes. Focusing on these complexes, here we provide a systematic assessment of the polarizable AMOEBA model and recommend critical changes that substantially improve its predictive performance. Our key results are as follows. We first show that our recent revision of the AMOEBA protein model (AMOEBABIO18-HFC), which contains high field corrections (HFCs) to induced dipoles, dramatically improves Mg2+-protein interaction energies, reducing the mean absolute error (MAE) from 17 to 10 kcal/mol. This further supports the general applicability of AMOEBABIO18-HFC. The inclusion of many-body NB-fix corrections further reduces MAE to 6 kcal/mol, which amounts to less than 2% error. The errors are estimated with respect to vdW-inclusive density functional theory that we benchmark against CCSD(T) calculations and experiments. We also present a new model of ATP with revised polarization parameters to better capture its high field response, as well as new vdW and dihedral parameters. The ATP model accurately predicts experimental Mg2+-ATP binding free energy in the aqueous phase and provides new insights into how Mg2+ associates with ATP. Finally, we show that molecular dynamics (MD) simulations of Mg2+·Kinase·ATP complexes carried out with these improvements lead to a better agreement in global and local catalytic site structures between MD and X-ray crystallography.

Biochemical properties of naturally occurring human bloom helicase variants.

Bloom syndrome helicase (BLM) is a RecQ-family helicase implicated in a variety of cellular processes, including DNA replication, DNA repair, and telomere maintenance. Mutations in human BLM cause Bloom syndrome (BS), an autosomal recessive disorder that leads to myriad negative health impacts including a predisposition to cancer. BS-causing mutations in BLM often negatively impact BLM ATPase and helicase activity. While BLM mutations that cause BS have been well characterized both in vitro and in vivo, there are other less studied BLM mutations that exist in the human population that do not lead to BS. Two of these non-BS mutations, encoding BLM P868L and BLM G1120R, when homozygous, increase sister chromatid exchanges in human cells. To characterize these naturally occurring BLM mutant proteins in vitro, we purified the BLM catalytic core (BLMcore, residues 636-1298) with either the P868L or G1120R substitution. We also purified a BLMcore K869A K870A mutant protein, which alters a lysine-rich loop proximal to the P868 residue. We found that BLMcore P868L and G1120R proteins were both able to hydrolyze ATP, bind diverse DNA substrates, and unwind G-quadruplex and duplex DNA structures. Molecular dynamics simulations suggest that the P868L substitution weakens the DNA interaction with the winged-helix domain of BLM and alters the orientation of one lobe of the ATPase domain. Because BLMcore P868L and G1120R retain helicase function in vitro, it is likely that the increased genome instability is caused by specific impacts of the mutant proteins in vivo. Interestingly, we found that BLMcore K869A K870A has diminished ATPase activity, weakened binding to duplex DNA structures, and less robust helicase activity compared to wild-type BLMcore. Thus, the lysine-rich loop may have an important role in ATPase activity and specific binding and DNA unwinding functions in BLM.

Biochemical Properties of Naturally Occurring Human Bloom Helicase Variants.

Bloom syndrome helicase (BLM) is a RecQ-family helicase implicated in a variety of cellular processes, including DNA replication, DNA repair, and telomere maintenance. Mutations in human BLM cause Bloom syndrome (BS), an autosomal recessive disorder that leads to myriad negative health impacts including a predisposition to cancer. BS-causing mutations in BLM often negatively impact BLM ATPase and helicase activity. While BLM mutations that cause BS have been well characterized both in vitro and in vivo , there are other less studied BLM mutations that exist in the human population that do not lead to BS. Two of these non-BS mutations, encoding BLM P868L and BLM G1120R, when homozygous, increase sister chromatid exchanges in human cells. To characterize these naturally occurring BLM mutant proteins in vitro , we purified the BLM catalytic core (BLM core , residues 636-1298) with either the P868L or G1120R substitution. We also purified a BLM core K869A K870A mutant protein, which alters a lysine-rich loop proximal to the P868 residue. We found that BLM core P868L and G1120R proteins were both able to hydrolyze ATP, bind diverse DNA substrates, and unwind G-quadruplex and duplex DNA structures. Molecular dynamics simulations suggest that the P868L substitution weakens the DNA interaction with the winged-helix domain of BLM and alters the orientation of one lobe of the ATPase domain. Because BLM core P868L and G1120R retain helicase function in vitro , it is likely that the increased genome instability is caused by specific impacts of the mutant proteins in vivo . Interestingly, we found that BLM core K869A K870A has diminished ATPase activity, weakened binding to duplex DNA structures, and less robust helicase activity compared to wild-type BLM core . Thus, the lysine-rich loop may have an important role in ATPase activity and specific binding and DNA unwinding functions in BLM.

Inclusion of High-Field Target Data in AMOEBA's Calibration Improves Predictions of Protein-Ion Interactions.

The reliability of molecular mechanics simulations to predict effects of ion binding to proteins depends on their ability to simultaneously describe ion-protein, ion-water, and protein-water interactions. Force fields (FFs) to describe protein-water and ion-water interactions have been constructed carefully and have also been refined routinely to improve accuracy. Descriptions for ion-protein interactions have also been refined, although in an a posteriori manner through the use of "nonbonded-fix (NB-fix)" approaches in which parameters from default Lennard-Jones mixing rules are replaced with those optimized against some reference data. However, even after NB-fix corrections, there remains a significant need for improvement. This is also true for polarizable FFs that include self-consistent inducible moments. Our recent studies on the polarizable AMOEBA FF suggested that the problem associated with modeling ion-protein interactions could be alleviated by recalibrating polarization models of cation-coordinating functional groups so that they respond better to the high electric fields present near ions. Here, we present such a recalibration of carbonyls, carboxylates, and hydroxyls in the AMOEBA protein FF and report that it does improve predictions substantially─mean absolute errors in Na+-protein and K+-protein interaction energies decrease from 8.7 to 5.3 and 9.6 to 6.3 kcal/mol, respectively. Errors are computed with respect to estimates from van der Waals-inclusive density functional theory benchmarked against high-level quantum mechanical calculations and experiments. While recalibration does improve ion-protein interaction energies, they still remain underestimated, suggesting that further improvements can be made in a systematic manner through modifications in classical formalism. Nevertheless, we show that by applying our many-body NB-fix correction to Lennard-Jones components, these errors are further reduced to 2.7 and 2.6 kcal/mol, respectively, for Na+ and K+ ions. Finally, we show that the recalibrated AMOEBA protein FF retains its intrinsic reliability in predicting protein structure and dynamics in the condensed phase.

High-Dimensional Parameter Search Method to Determine Force Field Mixing Terms in Molecular Simulations.

Molecular dynamics (MD) force fields for lipids and ions are typically developed independently of one another. In simulations consisting of both lipids and ions, lipid-ion interaction energies are estimated using a predefined set of mixing rules for Lennard-Jones (LJ) interactions. This, however, does not guarantee their reliability. In fact, compared to the quantum mechanical reference data, Lorentz-Berthelot mixing rules substantially underestimate the binding energies of Na+ ions with small-molecule analogues of lipid headgroups, yielding errors on the order of 80 and 130 kJ/mol, respectively, for methyl acetate and diethyl phosphate. Previously, errors associated with mixing force fields have been reduced using approaches such as "NB-fix" in which LJ interactions are computed using explicit cross terms rather than those from mixing rules. Building on this idea, we derive explicit lipid-ion cross terms that also may implicitly include many-body cooperativity effects. Additionally, to account for the interdependency between cross terms, we optimize all cross terms simultaneously by performing high-dimensional searches using our ParOpt software. The cross terms we obtain reduce the errors due to mixing rules to below 10 kJ/mol. MD simulation of the lipid bilayer conducted using these optimized cross terms resolves the structural discrepancies between our previous simulations and small-angle X-ray and neutron scattering experiments. These results demonstrate that simulations of lipid bilayers with ions that are accurate up to structural data from scattering experiments can be performed without explicit polarization terms. However, it is worth noting that such NB-fix cross terms are not based on any physical principle; a polarizable lipid model would be more realistic and is still desired. Our approach is generic and can be applied to improve the accuracies of simulations employing mixed force fields.

Cellular Uptake Pathways of Nanoparticles: Process of Endocytosis and Factors Affecting their Fate.

BACKGROUND: Efficient and controlled internalization of NPs into the cells depends on their physicochemical properties and dynamics of the plasma membrane. NPs-cell interaction is a complex process that decides the fate of NPs internalization through different endocytosis pathways. OBJECTIVES: The aim of this review is to highlight the physicochemical properties of synthesized nanoparticles (NPs) and their interaction with the cellular-dynamics and pathways like phagocytosis, pinocytosis, macropinocytosis, clathrin, and caveolae-mediated endocytosis, and the involvement of effector proteins domain such as clathrin, AP2, caveolin, Arf6, Cdc42, dynamin and cell surface receptors in the endocytosis process of NPs. METHODS: An electronic search was performed to explore the focused reviews and research articles on types of endocytosis and physicochemical properties of nanoparticles and their impact on cellular internalizations. The search was limited to peer-reviewed journals in the PubMed database. RESULTS: This article discusses in detail, how different types of NPs and their physicochemical properties such as size, shape, aspect ratio, surface charge, hydrophobicity, elasticity, stiffness, corona formation, and surface functionalization change the pattern of endocytosis in the presence of different pharmacological blockers. Some external forces like a magnetic field, electric field, and ultrasound exploit the cell membrane dynamics to permeabilize them for efficient internalization with respect to fundamental principles of membrane bending and pore formation. CONCLUSION: This review will be useful to attract and guide the audience to understand the endocytosis mechanism and its pattern with respect to physicochemical properties of NPs to improve their efficacy and targeting to achieve the impactful outcome in drug-delivery and theranostic applications.

Contrasting Local and Macroscopic Effects of Collagen Hydroxylation.

Collagen is heavily hydroxylated. Experiments show that proline hydroxylation is important to triple helix (monomer) stability, fibril assembly, and interaction of fibrils with other molecules. Nevertheless, experiments also show that even without hydroxylation, type I collagen does assemble into its native D-banded fibrillar structure. This raises two questions. Firstly, even though hydroxylation removal marginally affects macroscopic structure, how does such an extensive chemical change, which is expected to substantially reduce hydrogen bonding capacity, affect local structure? Secondly, how does such a chemical perturbation, which is expected to substantially decrease electrostatic attraction between monomers, affect collagen's mechanical properties? To address these issues, we conduct a benchmarked molecular dynamics study of rat type I fibrils in the presence and absence of hydroxylation. Our simulations reproduce the experimental observation that hydroxylation removal has a minimal effect on collagen's D-band length. We also find that the gap-overlap ratio, monomer width and monomer length are minimally affected. Surprisingly, we find that de-hydroxylation also has a minor effect on the fibril's Young's modulus, and elastic stress build up is also accompanied by tightening of triple-helix windings. In terms of local structure, de-hydroxylation does result in a substantial drop (23%) in inter-monomer hydrogen bonding. However, at the same time, the local structures and inter-monomer hydrogen bonding networks of non-hydroxylated amino acids are also affected. It seems that it is this intrinsic plasticity in inter-monomer interactions that preclude fibrils from undergoing any large changes in macroscopic properties. Nevertheless, changes in local structure can be expected to directly impact collagen's interaction with extra-cellular matrix proteins. In general, this study highlights a key challenge in tissue engineering and medicine related to mapping collagen chemistry to macroscopic properties but suggests a path forward to address it using molecular dynamics simulations.

Methyl-Induced Polarization Destabilizes the Noncovalent Interactions of N-Methylated Lysines.

Lysine methylation can modify noncovalent interactions by altering lysine's hydrophobicity as well as its electronic structure. Although the ramifications of the former are documented, the effects of the latter remain largely unknown. Understanding the electronic structure is important for determining how biological methylation modulates protein-protein binding, and the impact of artificial methylation experiments in which methylated lysines are used as spectroscopic probes and protein crystallization facilitators. The benchmarked first-principles calculations undertaken here reveal that methyl-induced polarization weakens the electrostatic attraction of amines with protein functional groups - salt bridges, hydrogen bonds and cation-π interactions weaken by as much as 10.3, 7.9 and 3.5 kT, respectively. Multipole analysis shows that weakened electrostatics is due to the altered inductive effects, which overcome increased attraction from methyl-enhanced polarizability and dispersion. Due to their fundamental nature, these effects are expected to be present in many cases. A survey of methylated lysines in protein structures reveals several cases in which methyl-induced polarization is the primary driver of altered noncovalent interactions; in these cases, destabilizations are found to be in the 0.6-4.7 kT range. The clearest case of where methyl-induced polarization plays a dominant role in regulating biological function is that of the PHD1-PHD2 domain, which recognizes lysine-methylated states on histones. These results broaden our understanding of how methylation modulates noncovalent interactions.

Site-specific identification and validation of hepatic histone nitration in vivo: Implications for alcohol-induced liver injury.

Oxidative and nitrative stress have been implicated in the molecular mechanisms underlying a variety of biological processes and disease states including cancer, aging, cardiovascular disease, neurological disorders, diabetes, and alcohol-induced liver injury. One marker of nitrative stress is the formation of 3-nitrotyrosine, or protein tyrosine nitration (PTN), which has been observed during inflammation and tissue injury; however, the role of PTN in the progression or possibly the pathogenesis of disease is still unclear. We show in a model of alcohol-induced liver injury that an increase in PTN occurs in hepatocyte nuclei within the liver of wild-type male C57BL/6J mice following chronic ethanol exposure (28 days). High-resolution mass spectrometric analysis of isolated hepatic nuclei revealed several novel sites of tyrosine nitration on histone proteins. Histone nitration sites were validated by tandem mass spectrometry (MS/MS) analysis of representative synthetic nitropeptides equivalent in sequence to the respective nitrotyrosine sites identified in vivo. We further investigated the potential structural impact of the novel histone H3 Tyr41 (H3Y41) nitration site identified using molecular dynamics (MD) simulations. MD simulations of the nitrated and non-nitrated forms of histone H3Y41 showed significant structural changes at the DNA interface upon H3Y41 nitration. The results from this study suggest that, in addition to other known post-translational modifications that occur on histone proteins (e.g., acetylation and methylation), PTN could induce chromatin structural changes, possibly affecting gene transcription processes associated with the development of alcohol-induced liver injury.

Molecular basis for higher affinity of SARS-CoV-2 spike RBD for human ACE2 receptor.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused substantially more infections, deaths, and economic disruptions than the 2002-2003 SARS-CoV. The key to understanding SARS-CoV-2's higher infectivity lies partly in its host receptor recognition mechanism. Experiments show that the human angiotensin converting enzyme 2 (ACE2) protein, which serves as the primary receptor for both CoVs, binds to the receptor binding domain (RBD) of CoV-2's spike protein stronger than SARS-CoV's spike RBD. The molecular basis for this difference in binding affinity, however, remains unexplained from X-ray structures. To go beyond insights gained from X-ray structures and investigate the role of thermal fluctuations in structure, we employ all-atom molecular dynamics simulations. Microseconds-long simulations reveal that while CoV and CoV-2 spike-ACE2 interfaces have similar conformational binding modes, CoV-2 spike interacts with ACE2 via a larger combinatorics of polar contacts, and on average, makes 45% more polar contacts. Correlation analysis and thermodynamic calculations indicate that these differences in the density and dynamics of polar contacts arise from differences in spatial arrangements of interfacial residues, and dynamical coupling between interfacial and non-interfacial residues. These results recommend that ongoing efforts to design spike-ACE2 peptide blockers will benefit from incorporating dynamical information as well as allosteric coupling effects.

Predictive QM/MM Modeling of Modulations in Protein-Protein Binding by Lysine Methylation.

Lysine methylation is a key regulator of protein-protein binding. The amine group of lysine can accept up to three methyl groups, and experiments show that protein-protein binding free energies are sensitive to the extent of methylation. These sensitivities have been rationalized in terms of chemical and structural features present in the binding pockets of methyllysine binding domains. However, understanding their specific roles requires an energetic analysis. Here we propose a theoretical framework to combine quantum and molecular mechanics methods, and compute the effect of methylation on protein-protein binding free energies. The advantages of this approach are that it derives contributions from all local non-trivial effects of methylation on induction, polarizability and dispersion directly from self-consistent electron densities, and at the same time determines contributions from well-characterized hydration effects using a computationally efficient classical mean field method. Limitations of the approach are discussed, and we note that predicted free energies of fourteen out of the sixteen cases agree with experiment. Critical assessment of these cases leads to the following overarching principles that drive methylation-state recognition by protein domains. Methylation typically reduces the pairwise interaction between proteins. This biases binding toward lower methylated states. Simultaneously, however, methylation also makes it easier to partially dehydrate proteins and place them in protein-protein complexes. This latter effect biases binding in favor of higher methylated states. The overall effect of methylation on protein-protein binding depends ultimately on the balance between these two effects, which is observed to be tuned via several combinations of local features.

Improved description of ligand polarization enhances transferability of ion-ligand interactions.

The reliability of molecular mechanics (MM) simulations in describing biomolecular ion-driven processes depends on their ability to accurately model interactions of ions simultaneously with water and other biochemical groups. In these models, ion descriptors are calibrated against reference data on ion-water interactions, and it is then assumed that these descriptors will also satisfactorily describe interactions of ions with other biochemical ligands. The comparison against the experiment and high-level quantum mechanical data show that this transferability assumption can break down severely. One approach to improve transferability is to assign cross terms or separate sets of non-bonded descriptors for every distinct pair of ion type and its coordinating ligand. Here, we propose an alternative solution that targets an error-source directly and corrects misrepresented physics. In standard model development, ligand descriptors are never calibrated or benchmarked in the high electric fields present near ions. We demonstrate for a representative MM model that when the polarization descriptors of its ligands are improved to respond to both low and high fields, ligand interactions with ions also improve, and transferability errors reduce substantially. In our case, the overall transferability error reduces from 3.3 kcal/mol to 1.8 kcal/mol. These improvements are observed without compromising on the accuracy of low-field interactions of ligands in gas and condensed phases. Reference data for calibration and performance evaluation are taken from the experiment and also obtained systematically from "gold-standard" CCSD(T) in the complete basis set limit, followed by benchmarked vdW-inclusive density functional theory.

Transferable interactions of Li+ and Mg2+ ions in polarizable models.

Therapeutic implications of Li+, in many cases, stem from its ability to inhibit certain Mg2+-dependent enzymes, where it interacts with or substitutes for Mg2+. The underlying details of its action are, however, unknown. Molecular simulations can provide insights, but their reliability depends on how well they describe relative interactions of Li+ and Mg2+ with water and other biochemical groups. Here, we explore, benchmark, and recommend improvements to two simulation approaches: the one that employs an all-atom polarizable molecular mechanics (MM) model and the other that uses a hybrid quantum and MM implementation of the quasi-chemical theory (QCT). The strength of the former is that it describes thermal motions explicitly and that of the latter is that it derives local contributions from electron densities. Reference data are taken from the experiment, and also obtained systematically from CCSD(T) theory, followed by a benchmarked vdW-inclusive density functional theory. We find that the QCT model predicts relative hydration energies and structures in agreement with the experiment and without the need for additional parameterization. This implies that accurate descriptions of local interactions are essential. Consistent with this observation, recalibration of local interactions in the MM model, which reduces errors from 10.0 kcal/mol to 1.4 kcal/mol, also fixes aqueous phase properties. Finally, we show that ion-ligand transferability errors in the MM model can be reduced significantly from 10.3 kcal/mol to 1.2 kcal/mol by correcting the ligand's polarization term and by introducing Lennard-Jones cross-terms. In general, this work sets up systematic approaches to evaluate and improve molecular models of ions binding to proteins.

Role of Structural Fluctuations in Allosteric Stimulation of Paramyxovirus Hemagglutinin-Neuraminidase.

Complexity in understanding allosteric stimulation of the hemagglutinin-neuraminidase (HN) protein of paramyxoviruses by host sialic acids (SIAs) stems from (1) unavailability of structure in its SIA-bound state and (2) the observation that this process is temperature sensitive. To consider simultaneously SIA's effect on structure and thermal fluctuations, we use molecular dynamics and simulate the dimeric form of the Newcastle disease virus HN. We find that SIA induces only minor structural changes in individual monomers, yet it reorients dimer interface by 10°. Interface reorientation is accompanied by constriction of SIA binding groove and enhanced fluctuations of interfacial residues that disrupt hydrophobic interactions and favor creation of new salt bridges. Supervised machine learning analysis of non-equilibrium data reveals that the allosteric signal is not formed from a directed sequence of these events. Altogether, we propose a detailed model of the initial events of allosteric stimulation, consistent with experiments on engineered mutations.

Interactions of Monovalent and Divalent Cations at Palmitoyl-Oleoyl-Phosphatidylcholine Interface.

Li+ is a biologically active and medically important cation. Experiments show that Li+ modulates some phospholipid bilayer properties in a manner similar to divalent cations, rather than other monovalent cations. We previously performed a comparative simulation study of the interaction of several monovalent cations with palmitoyl-oleoyl-phosphatidylcholine bilayers and reported that Li+ exhibited the highest association with lipids and formed a unique tetrahedral coordinated structure with lipid head groups. Here we extend these studies to two biologically important divalent cations, Mg2+ and Ca2+, and observe that, just like monovalent cations, Mg2+ and Ca2+ reduce bilayer areas and increase chain order. Bilayer area changes induced by cations are strongly correlated with the amount of charge inside the headgroup region; however, Mg2+ and Li+ are clear outliers. At the same time though, Mg2+ adsorption in the bilayer is the smallest among all cations, which is in contrast to Li+ that binds strongly to lipids. In fact, in contrast to all other cations, Mg2+ remains fully hydrated in the lipid headgroup region. However, Li+ and Mg2+ share high overlap between their inner-shell coordination topologies. This suggests that Li+ can structurally replace Mg2+, which is bound to other biomolecules with up to fourfold coordination, provided such replacement is energetically feasible. We compute structural topologies and compare them quantitatively using a new weighted-graphs-based method. Finally, we find that the specificity of cation interaction with lipid head groups exhibit consistent trend with the solvation shell energetics of ions in lipid headgroup and bulk water regions.

Ion-Hydroxyl Interactions: From High-Level Quantum Benchmarks to Transferable Polarizable Force Fields.

Ion descriptors in molecular mechanics models are calibrated against reference data on ion-water interactions. It is then typically assumed that these descriptors will also satisfactorily describe interactions of ions with other functional groups, such as those present in biomolecules. However, several studies now demonstrate that this transferability assumption produces, in many different cases, large errors. Here we address this issue in a representative polarizable model and focus on transferability of cationic interactions from water to a series of alcohols. Both water and alcohols use hydroxyls for ion-coordination, and, therefore, this set of molecules constitutes the simplest possible case of transferability. We obtain gas phase reference data systematically from "gold-standard" quantum Monte Carlo and CCSD(T) methods, followed by benchmarked vdW-corrected DFT. We learn that the original polarizable model yields large gas phase water → alcohol transferability errors - the RMS and maximum errors are 2.3 and 5.1 kcal/mol, respectively. These errors are, nevertheless, systematic in that ion-alcohol interactions are overstabilized, and systematic errors typically imply that some essential physics is either missing or misrepresented. A comprehensive analysis shows that when both low- and high-field responses of ligand dipole polarization are described accurately, then transferability improves significantly - the RMS and maximum errors in the gas phase reduce, respectively, to 0.9 and 2.5 kcal/mol. Additionally, predictions of condensed phase transfer free energies also improve. Nevertheless, within the limits of the extrathermodynamic assumptions necessary to separate experimental estimates of salt dissolution into constituent cationic and anionic contributions, we note that the error in the condensed phase is systematic, which we attribute, at least, partially to the parametrization in long-range electrostatics. Overall, this work demonstrates a rational approach to boosting transferability of ionic interactions that will be applicable broadly to improving other polarizable and nonpolarizable models.

Interaction of salt with ether- and ester-linked phospholipid bilayers.

A distinguishing feature of Archaeal plasma membranes is that their phospholipids contain ether-links, as opposed to bacterial and eukaryotic plasma membranes where phospholipids primarily contain ester-links. Experiments show that this chemical difference in headgroup-tail linkage does produce distinct differences in model bilayer properties. Here we examine the effects of salt on bilayer structure in the case of an ether-linked lipid bilayer. We use molecular dynamics simulations and compare equilibrium properties of two model lipid bilayers in NaCl salt solution - POPC and its ether-linked analog that we refer to as HOPC. We make the following key observations. The headgroup region of HOPC "adsorbs" fewer ions compared to the headgroup region of POPC. Consistent with this, we note that the Debye screening length in the HOPC system is ∼ 10% shorter than that in the POPC system. Herein, we introduce a protocol to identify the lipid-water interfacial boundary that reproduces the bulk salt distribution consistent with Gouy-Chapman theory. We also note that the HOPC bilayer has excess solvent in the headgroup region when compared to POPC, coinciding with a trough in the electrostatic potential. Waters in this region have longer autocorrelation times and smaller lateral diffusion rates compared to the corresponding region in the POPC bilayer, suggesting that the waters in HOPC are more strongly coordinated to the lipid headgroups. Furthermore, we note that it is this region of tightly coordinated waters in the HOPC system that has a lower density of Na+ ions. Based on these observations we conclude that an ether-linked lipid bilayer has a lower binding affinity for Na+ compared to an ester-linked lipid bilayer.

Machine learning approaches to evaluate correlation patterns in allosteric signaling: A case study of the PDZ2 domain.

Many proteins are regulated by dynamic allostery wherein regulator-induced changes in structure are comparable with thermal fluctuations. Consequently, understanding their mechanisms requires assessment of relationships between and within conformational ensembles of different states. Here we show how machine learning based approaches can be used to simplify this high-dimensional data mining task and also obtain mechanistic insight. In particular, we use these approaches to investigate two fundamental questions in dynamic allostery. First, how do regulators modify inter-site correlations in conformational fluctuations (Cij)? Second, how are regulator-induced shifts in conformational ensembles at two different sites in a protein related to each other? We address these questions in the context of the human protein tyrosine phosphatase 1E's PDZ2 domain, which is a model protein for studying dynamic allostery. We use molecular dynamics to generate conformational ensembles of the PDZ2 domain in both the regulator-bound and regulator-free states. The employed protocol reproduces methyl deuterium order parameters from NMR. Results from unsupervised clustering of Cij combined with flow analyses of weighted graphs of Cij show that regulator binding significantly alters the global signaling network in the protein; however, not by altering the spatial arrangement of strongly interacting amino acid clusters but by modifying the connectivity between clusters. Additionally, we find that regulator-induced shifts in conformational ensembles, which we evaluate by repartitioning ensembles using supervised learning, are, in fact, correlated. This correlation Δij is less extensive compared to Cij, but in contrast to Cij, Δij depends inversely on the distance from the regulator binding site. Assuming that Δij is an indicator of the transduction of the regulatory signal leads to the conclusion that the regulatory signal weakens with distance from the regulatory site. Overall, this work provides new approaches to analyze high-dimensional molecular simulation data and also presents applications that yield new insight into dynamic allostery.

An effective treatment approach of DPP-IV inhibitor encapsulated polymeric nanoparticles conjugated with anti-CD-4 mAb for type 1 diabetes.

Nanotechnology based biomedical approaches and surface modification techniques made it easier for targeting specific site and improving the treatment efficacy. The present study reports on targeted polymeric nanoparticles conjugated with antibody as a site-specific carrier system for effective treatment of type 1 diabetes. Sitagliptin (SP)-loaded Poly (lactic-co-glycolic acid) (PLGA) nanoparticles (NP) were prepared by nanoprecipitation cum solvent evaporation method and were characterized in terms of morphology, size, surface charge, and entrapment efficiency. Optimized batch demonstrated a particle size of 105.24 nm, with significant entrapment efficacy. In vitro release studies exhibited a controlled release pattern of 67.76 ± 1.30% in 24 h, and a maximum of 96.59 ± 1.26% at the end of 48 h. Thiol groups were introduced on the surface of SP-NPs whose concentration on SP-NPs was 27 ± 2.6 mmol/mol PLGA-NPs, anti-CD4 antibody clone Q4120 was conjugated to the thiolated SP-NPs via a sulfo-MBS cross-linker, ∼70% conjugation was observed. The in vitro cytotoxicity studies performed on RIN-5 F cells for mAb-SP-NPs presented an IC50 of 76 µg/mL, and the insulin release assay had revealed an increased release at 5.15 ± 0.16 IU/mL. The results indicate that mAb-SP-NPs allowed a controlled release of SP and thereby produced insulin levels comparable with control. Therefore, mAb-SP-NPs system appears to be effective in the treatment of auto immune diabetes, subject to further analysis.

Stimulation of Nipah Fusion: Small Intradomain Changes Trigger Extensive Interdomain Rearrangements.

Nipah is an emerging paramyxovirus that is of serious concern to human health. It invades host cells using two of its membrane proteins-G and F. G binds to host ephrins and this stimulates G to activate F. Upon activation, F mediates virus-host membrane fusion. Here we focus on mechanisms that underlie the stimulation of G by ephrins. Experiments show that G interacts with ephrin and F through separate sites located on two different domains, the receptor binding domain (RBD) and the F activation domain (FAD). No models explain this allosteric coupling. In fact, the analogous mechanisms in other paramyxoviruses also remain undetermined. The structural organization of G is such that allosteric coupling must involve at least one of the two interfaces-the RBD-FAD interface and/or the RBD-RBD interface. Here we examine using molecular dynamics the effect of ephrin binding on the RBD-RBD interface. We find that despite inducing small changes in individual RBDs, ephrin reorients the RBD-RBD interface extensively, and in a manner that will enhance solvent exposure of the FAD. While this finding supports a proposed model of G stimulation, we also find from additional simulations that ephrin induces a similar RBD-RBD reorientation in a stimulation-deficient G mutant, V209 VG → AAA. Together, our simulations suggest that while inter-RBD reorientation may be important, it is not, by itself, a sufficient condition for G stimulation. Additionally, we find that the mutation affects the conformational ensemble of RBD globally, including the RBD-FAD interface, suggesting the latter's role in G stimulation. Because ephrin induces small changes in individual RBDs, a proper analysis of conformational ensembles required that they are compared directly-we employ a method we developed recently, which we now release at SimTK, and show that it also performs excellently for non-Gaussian distributions.