Explicit Solvent Molecular Dynamics Simulations Research Articles

Effects of cryo-EM cooling on structural ensembles of biomolecules and their solvation shell.

The recent revolution in cryo electron microscopy (cryo-EM) allows the determination of structures of macromolecular complexes at atomic resolution. Cryo-EM also provides information on structural heterogeneity and ensembles of macromolecules. To obtain cryo-EM images of macromolecules, the samples are first rapidly cooled down to liquid nitrogen temperatures. The rapid cooling prevents ice-crystal formation and preserves some information of the room-temperature ensemble. However, to what extent the ensemble of the macromolecues and of the solvation shell is perturbed by the cooling is currently unknown. To quantify the cooling effects, we first estimated the temperature drop rate by solving the heat equation which suggested rapid cooling within microseconds. Then, we started all-atom explicit-solvent molecular dynamics (MD) simulations of the ribosome from 41 snapshots taken from a room-temperature ensemble with linearly decreasing temperatures at 11 different cooling rates (simulation lengths 0.1-128 ns). In the simulations, we observed that cooling markedly decreased the structural heterogeneity of the cooled ensemble. To investigate if and how this effect depends on the cooling rate, we used Bayesian statistics to test three thermodynamic and kinetic models of the cooling process. A kinetic two-state model improves the prediction of the decrease in heterogeneity compared to the cooling-rate independent thermodynamic model suggesting that kinetic effects contribute markedly. The combination of the estimated temperature drop rate with the kinetic model suggests that small barriers between states (<10 kJ/mol) are overcome during cooling and do not contribute to the heterogeneity of the structural ensemble obtained by cryo-EM. In contrast, conformational states separated by larger barriers are expected to be trapped during plunge-freezing. The obtained parameters for the kinetic model will allow one to quantify the heterogeneity of biologically relevant room-temperature ensembles from cryo-EM structures.

Scrutinizing the protein hydration shell from MD simulations against SAXS/SANS data from a worldwide round robin benchmark.

The hydration shell of proteins plays key roles in protein stability, folding, recognition, and enzyme activity. However, it remained unclear whether the hydration shell predicted by explicit-solvent molecular dynamics (MD) simulations matches experimental conditions, while accurate experimental probes of the hydration shell structure remained limited. Small-angle scattering (SAS) in solution using X-rays (SAXS) or neutrons (SANS) in principle provides information on the hydration shell, since both the radius of gyration (Rg) and the zero-angle scattering (I0) depend on the hydration shell contrast relative to bulk solvent. Using MD simulations and explicit-solvent SAXS/SANS calculations, we computed Rg and I0 for five different proteins and a set of 18 different combinations of protein force fields and water models, and we validated the simulation results against consensus data from a recent worldwide round robin benchmark (Trewhella, Vachette et al., doi:10.1107/S2059798322009184). Overall, we find remarkable agreement between MD simulations and consensus SAS data; however the agreement is force field dependent. Certain force field/water model combinations underestimate the hydration layer contrast significantly, while water models with increased dispersion interactions may, for some proteins, overestimate the hydration layer contrast. Our study shows that explicit-solvent SAS calculation and consensus SAS data provide a novel route for scrutinizing the hydration layer of proteins.

Dynamics of the SARS-CoV-2 main protease binding site.

The COVID-19 pandemic has been controlled through quarantines, travel bans, mask mandates, and vaccines. However, due to viral mutations and the unlikelihood of reaching herd immunity, there remains a need for therapeutics. The SARS-CoV-2 main protease (MPro) is necessary for the virus’ replication, thus it is a promising drug target. Additionally, it can be crystallized consistently and its sequence has few changes across virus mutants. MPro crystal structures depict general residue-residue interactions and backbone conformations, but they do not account for the dynamics of flexible regions. Instead, molecular dynamics (MD) simulations are used to identify the flexibility of the binding site, data we hypothesize is essential for successfully designing drugs to bind to MPro using computational drug docking methods. 600 ns of all-atom, explicit solvent MD simulations of the MPro homodimer were conducted, resulting in 1.2 million frames of monomeric data. Principal component analysis (PCA) was conducted on pairwise Cα-Cα distances between selected binding residues within apo and holo PDBs and the MD frames. These distances provide an intuitive set of measurements to characterize the dynamics of the binding site. Contour mapping was used to visualize the presence of clusters in the space defined by a few of the most contributive PC's. Snapshots representative of the most common conformations within the distribution of data were identified through the use of clustering methods and will be used in future drug docking simulations.

Elucidating the dynamics of individual IDPs in a biomolecular condensate using single-molecule FRET and molecular simulation.

A wide range of biomolecules in solution can phase-separate and form membraneless organelles in the cell. These assemblies often have liquid-like properties, and the corresponding dynamics and exchange of molecules with the environment are important for biological function. The dynamics and materials properties of these systems are commonly assessed based on translational diffusion or rheological properties, typically covering timescales of milliseconds and longer. However, information on the structure and dynamics at the molecular level is lacking. We have studied coacervates of two intrinsically disordered highly oppositely charged nuclear proteins as a prototypical example of heterotypic liquid-liquid phase separation of components abundant in the cell nucleus. Using single-molecule fluorescence spectroscopy, we show that the proteins in the condensates remain disordered, and that their chain dynamics occur on timescale surprisingly close to the ∼100-nanosecond dynamics of the 1:1 complex in dilute solution, even though the condensate is almost three orders of magnitude more viscous than the dilute solution and translational diffusion of the same proteins is ∼50 times slower in the dense than in the dilute phase. The experimental results are in good agreement with large-scale all-atom explicit-solvent molecular dynamics simulations consisting of ∼200 proteins and ∼4 million atoms in total, which can thus provide detailed insights into the protein interactions and dynamics within the condensate. The simulations indicate that the rapid protein chain dynamics in the dense phase are linked to the similarity of the local environment experienced by the proteins in the dilute and dense phases and the short lifetime of intermolecular contacts in the dense phase.

Ceftriaxone induces glial EAAT-2 promotor region via NF-kB conformational changes: An interaction analysis using HADDOCK.

Excitotoxicity, depletion of energy metabolites, and ionic imbalance are the major factors involved in neurodegeneration mediated through excitatory amino acid transporter-2 (EAAT-2) dysfunction in ischemic insult. Recent studies have revealed that ceftriaxone expresses EAAT-2 via nuclear transcription factor kappa-B (NF-kB) signaling pathway, stimulation of EAAT-2 expression in the ischemic, and excitotoxic conditions that could provide potential benefits to control neurodegeneration. In this study, we have predicted the in silico model for interaction between NF-kB and EAAT-2 promoter region to rule out the conformational changes for the expression of EAAT-2 protein. Using homology-built model of NF-kB, we identified ceftriaxone-induced conformational changes in gene locus -272 of DNA where NF-kB binding with EAAT-2 promoter region through protein-DNA docking calculation. The interaction profile and conformational dynamics occurred between ceftriaxone predocked and postdocked conformations of NF-kB with DNA employing HADDOCK 2.2 web server followed by 250 ns long all atom explicit solvent molecular dynamics simulations. Both the protein and DNA exhibited modest conformational changes with respect to HADDOCK score, energy terms (desolvation energy [Edesolv ]), van der waal energy (Evdw ), electrostatic energy (Eelec ), restraints energy (Eair ), buried surface area, root mean square deviation, RMSF, radius of gyration, total hydrogen bonds when ceftriaxone pre- and postdocked NF-kB conformations were bound to DNA. Hence, the conformational changes in the C-terminal domain could be the reason for EAAT-2 expression through ceftriaxone specific binding pocket of -272 of DNA.

Machine learning based implicit solvent model for aqueous-solution alanine dipeptide molecular dynamics simulations.

Inspired by the recent work from Noé and coworkers on the development of machine learning based implicit solvent model for the simulation of solvated peptides [Chen et al., J. Chem. Phys., 2021, 155, 084101], here we report another investigation of the possibility of using machine learning (ML) techniques to "derive" an implicit solvent model directly from explicit solvent molecular dynamics (MD) simulations. For alanine dipeptide, a machine learning potential (MLP) based on the DeepPot-SE representation of the molecule was trained to capture its interactions with its average solvent environment configuration (ASEC). The predicted forces on the solute deviated only by an RMSD of 0.4 kcal mol-1 Å-1 from the reference values, and the MLP-based free energy surface differed from that obtained from explicit solvent MD simulations by an RMSD of less than 0.9 kcal mol-1. Our MLP training protocol could also accurately reproduce combined quantum mechanical molecular mechanical (QM/MM) forces on the quantum mechanical (QM) solute in ASEC environment, thus enabling the development of accurate ML-based implicit solvent models for ab initio-QM MD simulations. Such ML-based implicit solvent models for QM calculations are cost-effective in both the training stage, where the use of ASEC reduces the number of data points to be labelled, and the inference stage, where the MLP can be evaluated at a relatively small additional cost on top of the QM calculation of the solute.

Reversal of the unique Q493R mutation increases the affinity of Omicron S1-RBD for ACE2

The SARS-CoV-2 Omicron variant containing 15 mutations, including the unique Q493R, in the spike protein receptor binding domain (S1-RBD) is highly infectious. While comparison with previously reported mutations provide some insights, the mechanism underlying the increased infections and the impact of the reversal of the unique Q493R mutation seen in BA.4, BA.5, BA.2.75, BQ.1 and XBB lineages is not yet completely understood. Here, using structural modelling and molecular dynamics (MD) simulations, we show that the Omicron mutations increases the affinity of S1-RBD for ACE2, and a reversal of the unique Q493R mutation further increases the ACE2-S1-RBD affinity. Specifically, we performed all atom, explicit solvent MD simulations using a modelled structure of the Omicron S1-RBD-ACE2 and compared the trajectories with the WT complex revealing a substantial reduction in the Cα-atom fluctuation in the Omicron S1-RBD and increased hydrogen bond and other interactions. Residue level analysis revealed an alteration in the interaction between several residues including a switch in the interaction of ACE2 D38 from S1-RBD Y449 in the WT complex to the mutated R residue (Q493R) in Omicron complex. Importantly, simulations with Revertant (Omicron without the Q493R mutation) complex revealed further enhancement of the interaction between S1-RBD and ACE2. Thus, results presented here not only provide insights into the increased infectious potential of the Omicron variant but also a mechanistic basis for the reversal of the Q493R mutation seen in some Omicron lineages and will aid in understanding the impact of mutations in SARS-CoV-2 evolution.

Harmonizing Interstrand Electrostatic Repulsion by Conformational Rigidity in Counterion-Deprived Z-DNA: A Molecular Dynamics Study.

Deoxyribonucleic acid (DNA) is a vital biomacromolecule. Although the right-handed B-DNA type helical structure is the most abundant and extensively studied form of DNA, several noncanonical forms, such as triplex, quadruplex, Z-DNA, A-DNA, and ss-DNA, have been probed from time to time to gain insights into the DNA's function. Z-DNA was recently found to be involved in cancer and several autoimmune diseases. In the present Article, we evaluated the conformational stability of locked-sugar-based Z-DNA via all-atom explicit-solvent molecular dynamics simulations and found that the modified DNA maintained the left-handed conformation even in the absence of counterions, wherein the structural rigidity dominates over the electrostatic repulsion between the complementary strands. The control Z-DNA without counterions, as expected, instantaneously resulted in unfolded states. The remarkable stability of the conformationally locked model system was thoroughly investigated via structural and energetic perspectives and was probably the result of the backbone widening in tandem with enhanced electrostatics between complementary strands. We believe that the design of the proposed modified Z-DNA construct could help understand the otherwise delicate Z-DNA conformation even in salt-deprived conditions. The design could also motivate the medicinal use of short segments of such modified nucleotides and could be utilized in more advanced modeling techniques, such as DNA origami which has gained popularity in recent years.

Interactive Flexible-Receptor Molecular Docking in Virtual Reality Using DockIT.

Interactive docking enables the user to guide and control the docking of two biomolecules into a binding pose. It is of particular use when the binding site is known and is thought to be applicable to structure-based drug design (SBDD) and educating students about biomolecular interactions. For SBDD, it enables expertise and intuition to be brought to bear in the drug design process. In education, it can teach students about the most basic level of biomolecular function. Here, we introduce DockIT for virtual reality (VR) that uses a VR headset and hand-held controllers. Using the method of linear response on explicit solvent molecular dynamics simulations, DockIT can model both global and local conformational changes within the receptor due to forces of interaction with the ligand. It has real-time flexible molecular surface rendering and can show the real-time formation and breaking of hydrogen bonds, both between the ligand and receptor and within the receptor itself as it smoothly changes conformation.

Atomic-Resolution Experimental Structural Biology and Molecular Dynamics Simulations of Hyaluronan and Its Complexes.

This review summarizes the atomic-resolution structural biology of hyaluronan and its complexes available in the Protein Data Bank, as well as published studies of atomic-resolution explicit-solvent molecular dynamics simulations on these and other hyaluronan and hyaluronan-containing systems. Advances in accurate molecular mechanics force fields, simulation methods and software, and computer hardware have supported a recent flourish in such simulations, such that the simulation publications now outnumber the structural biology publications by an order of magnitude. In addition to supplementing the experimental structural biology with computed dynamic and thermodynamic information, the molecular dynamics studies provide a wealth of atomic-resolution information on hyaluronan-containing systems for which there is no atomic-resolution structural biology either available or possible. Examples of these summarized in this review include hyaluronan pairing with other hyaluronan molecules and glycosaminoglycans, with ions, with proteins and peptides, with lipids, and with drugs and drug-like molecules. Despite limitations imposed by present-day computing resources on system size and simulation timescale, atomic-resolution explicit-solvent molecular dynamics simulations have been able to contribute significant insight into hyaluronan's flexibility and capacity for intra- and intermolecular non-covalent interactions.

Exploring the Binding Process of Cognate Ligand to Add Adenine Riboswitch Aptamer by Using Explicit Solvent Molecular Dynamics (MD) Simulation.

Riboswitches are RNA-structured elements that modulate gene expression by changing their conformation in response to specific metabolite ligand binding. Therefore, the biological functions of riboswitches mainly depend on the switching of secondary and three-dimensional structures in the presence and absence of the metabolite ligands. However, the binding mechanisms of cognate ligands to riboswitches are still not well understood. Here, we have introduced how to use explicit solvent molecular dynamics (MD) simulation to observe the binding process of cognate ligand to add adenine riboswitch aptamer at the atomic level. In addition, we have analyzed the driving factors of the binding process and calculated the binding free energy based on the Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) method.

Explicit-solute implicit-solvent molecular simulation with binary level-set, adaptive-mobility, and GPU

Coarse-grained modeling and efficient computer simulations are critical to the study of complex molecular processes with many degrees of freedom and multiple spatiotemporal scales. Variational implicit-solvent model (VISM) for biomolecular solvation is such a modeling framework, and its initial success has been demonstrated consistently. In VISM, an effective free-energy functional of solute-solvent interfaces is minimized, and the surface energy is a key component of the free energy. In this work, we extend VISM to include the solute mechanical interactions, and develop fast algorithms and GPU implementation for the extended variational explicit-solute implicit-solvent (VESIS) molecular simulations to determine the underlying molecular equilibrium conformations. We employ a fast binary level-set method for minimizing the solvation free energy of solute-solvent interfaces and construct an adaptive–mobility gradient descent method for solute atomic optimization. We also implement our methods on the integrated GPU. Numerical tests and applications to several molecular systems verify the accuracy, stability, and efficiency of our methods and algorithms. It is found that our new methods and GPU implementation improve the efficiency of the molecular simulation significantly over the CPU implementation. Our fast computational techniques may enable us to simulate very large systems such as protein-protein interactions and membrane dynamics for which explicit-solvent all-atom molecular dynamics simulations can be very expensive.

Atomistic Insights into A315E Mutation-Enhanced Pathogenicity of TDP-43 Core Fibrils.

The aggregation of TAR DNA-binding protein of 43 kDa (TDP-43) into fibrillary deposits is implicated in amyotrophic lateral sclerosis (ALS), and some hereditary mutations localized in the low complexity domain (LCD) facilitate the formation of pathogenic TDP-43 fibrils. A recent cryo-EM study reported the atomic-level structures of the A315E TDP-43 LCD (residues 288-319, TDP-43288-319) core fibril in which the protofilaments have R-shaped structures and hypothesized that A315E U-shaped protofilaments can readily convert to R-shaped protofilaments compared to the wild-type (WT) ones. There are no atomic structures of WT protofilaments available yet. Herein, we performed extensive all-atom explicit-solvent molecular dynamics simulations on A315E and WT protofilaments starting from both the cryo-EM-determined R-shaped and our constructed U-shaped structures. Our simulations show that WT protofilaments also adopt the R-shaped structures but are less stable than their A315E counterparts. Except for R293-E315 salt bridges, N312-F316 hydrophobic interactions and F316-F316 π-π stacking interactions are also crucial for the stabilization of the neck region of the R-shaped A315E protofilaments. The loss of R293-E315 salt bridges and the weakened interactions of N312-F316 and F316-F316 result in the reduced stability of the R-shaped WT protofilaments. Simulations starting from U-shaped folds reveal that A315E protofilaments can spontaneously convert to the cryo-EM-derived R-shaped protofilaments, whereas WT protofilaments convert to R-shape-like structures with remodeled neck regions. The R-shape-like WT protofilaments could act as intermediate states slowing down the U-to-R transition. This study reveals that A315E mutation can not only enhance the structural stability of the R-shaped TDP-43288-319 protofilaments but also promote the U-to-R transition, which provides atomistic insights into the A315E mutation-enhanced TDP-43 pathogenicity in ALS.

Solvation Thermodynamics of Solutes in Water and Ionic Liquids Using the Multiscale Solvation-Layer Interface Condition Continuum Model.

Molecular assembly processes are generally driven by thermodynamic properties in solutions. Atomistic modeling can be very helpful in designing and understanding complex systems, except that bulk solvent is very inefficient to treat explicitly as discrete molecules. In this work, we develop and assess two multiscale solvation models for computing solvation thermodynamic properties. The new SLIC/CDC model combines continuum solvent electrostatics based on the solvent layer interface condition (SLIC) with new statistical thermodynamic models for hydrogen bonding and nonpolar modes: cavity formation, dispersion interactions, combinatorial mixing (CDC). Given the structures of 500 solutes, the SLIC/CDC model predicts Gibbs energies of solvation in water with an average accuracy better than 1 kcal/mol, when compared to experimental measurements, and better than 0.8 kcal/mol, when compared to explicit-solvent molecular dynamics simulations. The individual SLIC/CDC energy mode values agree quantitatively with those computed from explicit-solvent molecular dynamics. The previously published SLIC/SASA multiscale model combines the SLIC continuum electrostatic model with the solvent-accessible surface area (SASA) nonpolar energy mode. With our new, improved parametrization method, the SLIC/SASA model now predicts Gibbs energies of solvation with better than 1.4 kcal/mol average accuracy in aqueous systems, compared to experimental and explicit-solvent molecular dynamics, and better than 1.6 kcal/mol average accuracy in ionic liquids, compared to explicit-solvent molecular dynamics. Both models predict solvation entropies, and are the first implicit-solvation models capable of predicting solvation heat capacities.

Pharmacophore-Model-Based Drug Repurposing for the Identification of the Potential Inhibitors Targeting the Allosteric Site in Dengue Virus NS5 RNA-Dependent RNA Polymerase.

Dengue virus (DENV) is the causative agent of DENV infection. To tackle DENV infection, the development of therapeutic molecules as direct-acting antivirals (DAAs) has been demonstrated as a truly effective approach. Among various DENV drug targets, non-structural protein 5 (NS5)—a highly conserved protein among the family Flaviviridae—carries the RNA-dependent RNA polymerase (DENVRdRp) domain at the C-terminal, and its “N-pocket” allosteric site is widely considered for anti-DENV drug development. Therefore, in this study, we developed a pharmacophore model by utilising 41 known inhibitors of the DENVRdRp domain, and performed model screening against the FDA’s approved drug database for drug repurposing against DENVRdRp. Herein, drugs complying with the pharmacophore hypothesis were further processed through standard-precision (SP) and extra-precision (XP) docking scores (DSs) and binding pose refinement based on MM/GBSA binding energy (BE) calculations. This resulted in the identification of four potential potent drugs: (i) desmopressin (DS: −10.52, BE: −69.77 kcal/mol), (ii) rutin (DS: −13.43, BE: −67.06 kcal/mol), (iii) lypressin (DS: −9.84, BE: −67.65 kcal/mol), and (iv) lanreotide (DS: −8.72, BE: −64.7 kcal/mol). The selected drugs exhibited relevant interactions with the allosteric N-pocket of DENVRdRp, including priming-loop and entry-point residues (i.e., R729, R737, K800, and E802). Furthermore, 100 ns explicit-solvent molecular dynamics simulations and end-point binding free energy assessments support the considerable stability and free energy of the selected drugs in the targeted allosteric pocket of DENVRdRp. Hence, these four drugs, repurposed as potent inhibitors of the allosteric site of DENVRdRp, are recommended for further validation using experimental assays.

Impact of Polydopamine Nanoparticle Surface Pattern and Roughness on Interactions with Poly(ethylene glycol) in Aqueous Solution: A Multiscale Modeling and Simulation Study.

A significant research effort in the past few years has been devoted to engineering synthetic mimics of naturally occurring eumelanin. One such effort has involved the assembly of oligomers of 5,6-dihydroxyindole (DHI), a synthetic precursor of polydopamine (PDA), into melanin-mimicking nanoparticles for use in a variety of applications with desired optical, photonic, thermal, and electrical properties. In many of these applications, the PDA nanoparticles are mixed with other polymers or oligomers, thus motivating this specific study to understand how the surface characteristics of the assembled PDA-nanoparticles affect their interaction with poly(ethylene glycol) (PEG) chains in aqueous solution. We use molecular dynamics (MD) simulations to study the interaction of linear 20-mer PEG chains with different PDA-nanoparticles assembled using four types of oligomers of 5,6-DHI: two isomers of 5,6-DHI 2-mers with the monomers bonding either at the 2-2' position (A-type isomer) or 7-7' position (B-type isomer), denoted as A:2-mer and B:2-mer, respectively, and a 4-mer and an 8-mer of B-type chemistry denoted as B:4-mer and B:8-mer, respectively. Using explicit-solvent atomistic MD simulations, we find that PDA-nanoparticle surfaces assembled from B:8-mer exhibit smaller density fluctuations of water molecules and, as a result, are relatively more hydrophilic than the PDA-nanoparticle surfaces assembled from A:2-mer, B:2-mer, and B:4-mer. The surface composition of PDA-nanoparticles assembled from A:2-mer contains relatively fewer hydroxyl (-OH) groups compared to PDA-nanoparticles assembled from a B:2-mer, B:4-mer, or B:8-mer, yet the sample of PEG chains show more collapsed and adsorbed conformations on A:2-mer nanoparticles' surface. To explain the atomistically observed behavior of PEG chains on the nanoparticles' surfaces, we use coarse-grained (CG) MD simulations and explain the roles of the pattern formed by the attractive sites (e.g.,-OH groups) exposed on the surface and the roughness of the surface on interactions with a genric PEG-like copolymer chain. By comparing atomistic and CG MD simulation results, we confirm that the -OH groups' pattern on the surface of the PDA-nanoparticle assembled from A:2-mer is patchier than the random or string-like patterns on the PDA-nanoparticle assembled from B:2-mer, B:4-mer, or B:8-mer, and it is this -OH groups' surface pattern that dictates the PEG chain conformations and adsorption on the PDA-nanoparticle surface. Overall, these results guide the design of chemically and physically heterogeneous nanoparticle surfaces for the desired polymer interaction and conformations.

Impact of Inert Crowders on Host-Guest Recognition Process.

Biological environments typically contain high concentrations (300-400 mg/mL) of different macromolecules at volume fractions as large as 30%-40%. Biomolecular recognition processes, a ubiquitous biological phenomena, occurring in such crowded heterogeneous media would differ significantly compared to the dilute buffer solutions. Here we quantify the potential impact of inert crowders on prototypical host-guest recognition process by explicit-solvent molecular dynamics (MD) simulations in atomic resolution. We demonstrate that the crowders, when smaller in size, would facilitate the binding process of the guest molecule by decreasing the free energy barrier for binding via excluded volume effect and desolvation of the host receptor. However, the extent of crowder-induced stabilization of a host-guest complex is found to be significantly higher when the guest molecule is sterically constricted to approach the host along a centrosymmetric direction, compared to its unrestricted, freely diffusive movement. A kinetic analysis of the recognition process reveals that the origin of a relatively stronger crowder impact during constricted movement of guest molecule lies in the relatively enhanced residence time of the guest inside the host by crowders. Together, our results suggest that the extent of impact of crowding on recognition processes would be contingent upon the presence or absence of constriction on ligand movement.

Molecular dynamics simulations of the secondary-binding site in disaccharide-modified glycopeptide antibiotics

Oritavancin is a semisynthetic glycopeptide antibiotic used to treat severe infections by multidrug-resistant Gram-positive pathogens. Oritavancin is known to be a thousand times more potent than vancomycin against Gram-positive bacteria due to the additional interactions with bacterial peptidoglycan (PG) facilitated by a secondary-binding site. The presence of this secondary-binding site is evident in desleucyl-oritavancin, an Edman degradation product of oritavancin, still retaining its potency against Gram-positive bacteria, whereas desleucyl-vancomycin is devoid of any antimicrobial activities. Herein, using explicit solvent molecular dynamics (MD) simulations, steered MD simulations, and umbrella sampling, we show evidence of a secondary-binding site mediated by the disaccharide-modified hydrophobic sidechain of oritavancin interactions with the pentaglycyl-bridge segment of the PG. The interactions were characterized through comparison to the interaction of PG with chloroeremomycin, vancomycin, and the desleucyl analogs of the glycopeptides. Our results show that the enhanced binding of oritavancin to PG over the binding of the other complexes studied is due to an increase in the hydrophobic effect, electrostatic and van der Waals interactions, and not the average number of hydrogen bonds. Our ranking of the binding interactions of the biomolecular complexes directly correlates with the order based on their experimental minimum inhibitory concentrations. The results of our simulations provide insight into the modification of glycopeptides to increase their antimicrobial activities or the design of novel antibiotics against pathogenic Gram-positive bacteria.

Multiple-Allele MHC Class II Epitope Engineering by a Molecular Dynamics-Based Evolution Protocol.

Epitopes that bind simultaneously to all human alleles of Major Histocompatibility Complex class II (MHC II) are considered one of the key factors for the development of improved vaccines and cancer immunotherapies. To engineer MHC II multiple-allele binders, we developed a protocol called PanMHC-PARCE, based on the unsupervised optimization of the epitope sequence by single-point mutations, parallel explicit-solvent molecular dynamics simulations and scoring of the MHC II-epitope complexes. The key idea is accepting mutations that not only improve the affinity but also reduce the affinity gap between the alleles. We applied this methodology to enhance a Plasmodium vivax epitope for multiple-allele binding. In vitro rate-binding assays showed that four engineered peptides were able to bind with improved affinity toward multiple human MHC II alleles. Moreover, we demonstrated that mice immunized with the peptides exhibited interferon-gamma cellular immune response. Overall, the method enables the engineering of peptides with improved binding properties that can be used for the generation of new immunotherapies.

Bicyclo-DNA mimics with enhanced protein binding affinities: insights from molecular dynamics simulations

DNA-protein interactions occur at all levels of DNA expression and replication and are crucial determinants for the survival of a cell. Several modified nucleotides have been utilized to manipulate these interactions and have implications in drug discovery. In the present article, we evaluated the binding of bicyclo-nucleotides (generated by forming a methylene bridge between C1’ and C5’ in sugar, leading to a bicyclo system with C2’ axis of symmetry at the nucleotide level) to proteins. We utilized four ssDNA-protein complexes with experimentally known binding free energies and investigated the binding of modified nucleotides to proteins via all-atom explicit solvent molecular dynamics (MD) simulations (200 ns), and compared the binding with control ssDNA-protein systems. The modified ssDNA displayed enhanced binding to proteins as compared to the control ssDNA, as seen by means of MD simulations followed by MM-PBSA calculations. Further, the Delphi-based electrostatic estimation revealed that the high binding of modified ssDNA to protein might be related to the enhanced electrostatic complementarity displayed by the modified ssDNA molecules in all the four systems considered for the study. The improved binding achieved with modified nucleotides can be utilized to design and develop anticancer/antisense molecules capable of targeting proteins or ssRNAs. Communicated by Ramaswamy H. Sarma