Replica-exchange Umbrella Sampling Research Articles

Atomic-Level Free Energy Landscape Reveals Cooperative Symport Mechanism of Melibiose Transporter.

The Major Facilitator Superfamily (MFS) transporters are an essential class of secondary active transporters involved in various physiological and pathological processes. The melibiose permease (MelB), which catalyzes the stoichiometric symport of the disaccharide melibiose and monovalent cations (e.g., Na+, H+, or Li+), is a key model for understanding the cation-coupled symport mechanisms. Extensive experimental data has established that positive cooperativity between the cargo melibiose and the coupling cation is central to the symport mechanism. However, the structural and energetic origins of this cooperativity remain unclear at the atomistic level for MelB and most other coupled transporters. Here, leveraging recently resolved structures in inward- and outward-facing conformations, we employed the string method and replica-exchange umbrella sampling simulation techniques to comprehensively map the all-atom free energy landscapes of the Na+-coupled melibiose translocation across the MelB in Salmonella enterica serovar Typhimurium (MelBSt), in comparison with the facilitated melibiose transport in a uniporter mutant. The simulation results unravel asymmetrical free energy profiles of melibiose translocation, which is tightly coupled to protein conformational changes in both the N- and C-terminal domains. Notably, the cytoplasmic release of the melibiose induces the simultaneous opening of an inner gate, resulting in a high-energy state of the system. Periplasmic sugar binding and cytoplasmic melibiose released are dynamically coupled with changes in the internal gating elements along the translocation pathway. The outward-facing sugar-bound state is thermodynamically most stable, while the occluded state is a transient state. The binding of Na+ facilitates melibiose translocation by increasing the melibiose-binding affinity and decreasing the overall free energy barrier and change. The cooperative binding of the two substrates results from the allosteric coupling between their binding sites instead of direct electrostatic interaction. These findings add substantial new atomic-level details into how Na+ binding facilitates melibiose translocation and deepen the fundamental understanding of the molecular basis underlying the symport mechanism of cation-coupled transporters.

Advanced computational approaches to understand protein aggregation.

Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.

Deciphering the free energy landscapes of SARS-CoV-2 wild type and Omicron variant interacting with human ACE2.

The binding of the receptor binding domain (RBD) of the SARS-CoV-2 spike protein to the host cell receptor angiotensin-converting enzyme 2 (ACE2) is the first step in human viral infection. Therefore, understanding the mechanism of interaction between RBD and ACE2 at the molecular level is critical for the prevention of COVID-19, as more variants of concern, such as Omicron, appear. Recently, atomic force microscopy has been applied to characterize the free energy landscape of the RBD-ACE2 complex, including estimation of the distance between the transition state and the bound state, xu. Here, using a coarse-grained model and replica-exchange umbrella sampling, we studied the free energy landscape of both the wild type and Omicron subvariants BA.1 and XBB.1.5 interacting with ACE2. In agreement with experiment, we find that the wild type and Omicron subvariants have similar xu values, but Omicron binds ACE2 more strongly than the wild type, having a lower dissociation constant KD.

Free-energy landscapes of transmembrane homodimers by bias-exchange adaptively biased molecular dynamics

Membrane proteins play essential roles in various biological functions within the cell. One of the most common functional regulations involves the dimerization of two single-pass transmembrane (TM) helices. Glycophorin A (GpA) and amyloid precursor protein (APP) form TM homodimers in the membrane, which have been investigated both experimentally and computationally. The homodimer structures are well characterized using only four collective variables (CVs) when each TM helix is stable. The CVs are the interhelical distance, the crossing angle, and the Crick angles for two TM helices. However, conformational sampling with multi-dimensional replica-exchange umbrella sampling (REUS) requires too many replicas to sample all the CVs for exploring the conformational landscapes. Here, we show that the bias-exchange adaptively biased molecular dynamics (BE-ABMD) with the four CVs effectively explores the free-energy landscapes of the TM helix dimers of GpA, wild-type APP and its mutants in the IMM1 implicit membrane. Compared to the original ABMD, the bias-exchange algorithm in BE-ABMD can provide a more rapidly converged conformational landscape. The BE-ABMD simulations could also reveal TM packing interfaces of the membrane proteins and the dependence of the free-energy landscapes on the membrane thickness. This approach is valuable for numerous other applications, including those involving explicit solvent and a lipid bilayer in all-atom force fields or Martini coarse-grained models, and enhances our understanding of protein-protein interactions in biological membranes.

Passive permeability controls synthesis for the allelochemical sorgoleone in sorghum root exudate

Competition for soil nutrients and water with other plants foster competition within the biosphere for access to these limited resources. The roots for the common grain sorghum produce multiple small molecules that are released via root exudates into the soil to compete with other plants. Sorgoleone is one such compound, which suppresses weed growth near sorghum by acting as a quinone analog and interferes with photosynthesis. Since sorghum also grows photosynthetically, and may be susceptible to sorgoleone action if present in tissues above ground, it is essential to exude sorgoleone efficiently. However, since the P450 enzymes that synthesize sorgoleone are intracellular, the release mechanism for sorgoleone remain unclear. In this study, we conducted an in silico assessment for sorgoleone and its precursors to passively permeate biological membranes. To facilitate accurate simulation, CHARMM parameters were newly optimized for sorgoleone and its precursors. These parameters were used to conduct 1 μs of unbiased molecular dynamics simulations to compare the permeability of sorgoleone with its precursors molecules. We find that interleaflet transfer is maximized for sorgoleone, suggesting that the precursor molecules may remain in the same leaflet for access by biosynthetic P450 enzymes. Since no sorgoleone was extracted during unbiased simulations, we compute a permeability coefficient using the inhomogeneous solubility diffusion model. The requisite free energy and diffusivity profiles for sorgoleone through a sorghum membrane model were determined through Replica Exchange Umbrella Sampling (REUS) simulations. The REUS calculations highlight that any soluble sorgoleone would quickly insert into a lipid bilayer, and would readily transit. When sorgoleone forms aggregates in root exudate as indicated by our equilibrium simulations, aggregate formation would lower the effective concentration in aqueous solution, creating a concentration gradient that would facilitate passive transport. This suggests that sorgoleone synthesis occurs within sorghum root cells and that sorgoleone is exuded by permeating through the cell membrane without the need for a transport protein once the extracellular sorgoleone aggregate is formed.

Converging PMF Calculations of Antibiotic Permeation across an Outer Membrane Porin with Subkilocalorie per Mole Accuracy.

The emergence of multidrug-resistant pathogens led to a critical need for new antibiotics. A key property of effective antibiotics against Gram-negative bacteria is their ability to permeate through the bacterial outer membrane via transmembrane porin proteins. Molecular dynamics (MD) simulations are, in principle, capable of modeling antibiotic permeation across outer membrane porins (OMPs). However, owing to sampling problems, it has remained challenging to obtain converged potentials of mean force (PMFs) for antibiotic permeation across OMPs. Here, we investigated the convergence of PMFs along a single collective variable aimed at quantifying the permeation of the antibiotic fosmidomycin across the OprO porin. We compared standard umbrella sampling (US) with three advanced flavors of the US technique: (i) Hamiltonian replica exchange with solute tempering in combination with US, (ii) simulated tempering-enhanced US, and (iii) replica-exchange US. To quantify the PMF convergence and to reveal hysteresis problems, we computed several independent sets of US simulations starting from pulling simulations in the outward and inward permeation directions. We find that replica-exchange US in combination with well-chosen restraints is highly successful for obtaining converged PMFs of fosmidomycin permeation through OprO, reaching PMFs converged to subkilocalorie per mole accuracy.

Origin of the kinetic HDAC2-selectivity of an HDAC inhibitor.

A newly synthesized small molecule, KTT-1, exhibits kinetically selective inhibition of histone deacetylase 2, HDAC2, over its homologous enzyme, HDAC1. KTT-1 is hard to be released from the HDAC2/KTT-1 complex, compared to the HDAC1/KTT-1 complex and the residence time of KTT-1 in HDAC2 is longer than that in HDAC1. To explore the physical origin of this kinetic selectivity, we performed replica-exchange umbrella sampling molecular dynamics simulations for formation of both complexes. The calculated potentials of mean force suggest that KTT-1 is stably bound to HDAC2 and that it is easily disassociated from HDAC1. In the direct vicinity of the KTT-1 binding site in both enzymes, there exists a conserved loop consisting of four consecutive glycine residues (Gly304-307 for HDAC2; Gly299-302 for HDA1). The difference between the two enzymes comes from a single un-conserved residue behind this loop, namely, Ala268 in HDAC2 and Ser263 in HDAC1. The Ala268 contributes to the tight binding of KTT-1 to HDAC2 by the linear orientation of Ala268, Gly306, and one carbon atom in KTT-1. On the other hand, Ser263 cannot stabilize the binding of KTT-1 to HDAC1, because it is relatively further away from the glycine loop and because the directions of the two forces are not in line.

Passive permeability controls synthesis for the allelochemical sorgeoleone in sorghum root exudate.

Competition for soil nutrients and water with other plants foster competition within the biosphere for access to these limited resources. The roots for the common grain sorghum produce exudates that are released into the soil to compete with other plants. Sorgoleone is one such compound, which suppresses weed growth near sorghum by acting as a qunione analog and binding to and inhibiting photosystem II during photosynthesis. Since sorghum also grows photosynthetically, and may be susceptible to sorgoleone action if present in tissues above ground, it is essential for sorgoleone to be excreted efficiently. However, since the P450 enzymes that synthesize sorgoleone are intracellular, the release mechanism for sorgoleone remain unclear. In this study, we conducted an in silico survey for sorgoleone and its precursors to passively permeate biological membranes. To enhance simulation accurate, simulation parameters for sorgoleone and its precursors were optimized using CHARMM methodology. These parameters were used to conduct one microsecond of unbiased molecular dynamics simulations to compare the permeability of sorgoleone with its precursors molecules. We find that interleaflet transfer is maximized for sorgoleone, relative to its precursors. To compute a permeability coefficient using the inhomogeneous solubility diffusion model, we determined the free energy and diffusivity through Replica Exchange Umbrella Sampling simulations. The REUS calculations highlight that sorgleone permeates quickly and may form aggregates in solution that lower the dissolved concentration. This suggests that sorgoleone synthesis occurs within sorghum cells and that sorgoleone is exuded by permeating through the cell membrane without the need for a transport protein.

SARS-CoV-2 spike opening dynamics and energetics reveal the individual roles of glycans and their collective impact.

The trimeric spike (S) glycoprotein, which protrudes from the SARS-CoV-2 viral envelope, binds to human ACE2, initiated by at least one protomer's receptor binding domain (RBD) switching from a “down” (closed) to an “up” (open) state. Here, we used large-scale molecular dynamics simulations and two-dimensional replica exchange umbrella sampling calculations with more than a thousand windows and an aggregate total of 160 μs of simulation to investigate this transition with and without glycans. We find that the glycosylated spike has a higher barrier to opening and also energetically favors the down state over the up state. Analysis of the S-protein opening pathway reveals that glycans at N165 and N122 interfere with hydrogen bonds between the RBD and the N-terminal domain in the up state, while glycans at N165 and N343 can stabilize both the down and up states. Finally, we estimate how epitope exposure for several known antibodies changes along the opening path. We find that the BD-368-2 antibody's epitope is continuously exposed, explaining its high efficacy.

Exploring conformational transitions in membrane proteins with memento.

Despite rapid advances in cryo-EM delivering structures of membrane transport proteins at an unprecedented rate, they are typically solved in one conformational state. Whilst conformational flexibility can be inferred from static end-state structures, the interconversion mechanisms between states are often beyond the scope of direct experimentation. Given the dynamical nature of the processes in question, many studies have attempted to explore conformational transitions using molecular dynamics. However, ensuring proper convergence and reversibility in the predicted transitions is extremely challenging. In this work, we present an approach that we term “MEMENTO” (morphing end states by modelling ensembles with independent Topologies) to generate paths that alleviate starting state dependence (hysteresis) in the construction of conformational free energy profiles. MEMENTO utilises template-based structure modelling to restore physically reasonable protein conformations based on coordinate interpolation (morphing), and we apply it in conjunction with replica-exchange umbrella sampling to sample likely transitions. We demonstrate how the method works via application to well-characterized test cases (deca-alanine and adenylate kinase) before discussing its use in transporter proteins. We also suggest that extended end-state sampling combined with MEMENTO can aid the discovery of collective variables for umbrella sampling on a case-by-case basis.

Plant Terpenoid Permeability through Biological Membranes Explored via Molecular Simulations.

Plants synthesize small molecule diterpenes composed of 20 carbons from precursor isopentenyl diphosphate and dimethylallyl disphosphate, manufacturing diverse compounds used for defense, signaling, and other functions. Industrially, diterpenes are used as natural aromas and flavoring, as pharmaceuticals, and as natural insecticides or repellents. Despite diterpene ubiquity in plant systems, it remains unknown how plants control diterpene localization and transport. For many other small molecules, plant cells maintain transport proteins that control compound compartmentalization. However, for most diterpene compounds, specific transport proteins have not been identified, and so it has been hypothesized that diterpenes may cross biological membranes passively. Through molecular simulation, we study membrane transport for three complex diterpenes from among the many made by members of the Lamiaceae family to determine their permeability coefficient across plasma membrane models. To facilitate accurate simulation, the intermolecular interactions for leubethanol, abietic acid, and sclareol were parametrized through the standard CHARMM methodology for incorporation into molecular simulations. To evaluate the effect of membrane composition on permeability, we simulate the three diterpenes in two membrane models derived from sorghum and yeast lipidomics data. We track permeation events within our unbiased simulations, and compare implied permeation coefficients with those calculated from Replica Exchange Umbrella Sampling calculations using the inhomogeneous solubility diffusion model. The diterpenes are observed to permeate freely through these membranes, indicating that a transport protein may not be needed to export these small molecules from plant cells. Moreover, the permeability is observed to be greater for plant-like membrane compositions when compared against animal-like membrane models. Increased permeability for diterpene molecules in plant membranes suggest that plants have tailored their membranes to facilitate low-energy transport processes for signaling molecules.

SARS-CoV-2 spike opening dynamics and energetics reveal the individual roles of glycans and their collective impact

The trimeric spike (S) glycoprotein, which protrudes from the SARS-CoV-2 viral envelope, binds to human ACE2, initiated by at least one protomer’s receptor binding domain (RBD) switching from a "down” (closed) to an "up” (open) state. Here, we used large-scale molecular dynamics simulations and two-dimensional replica exchange umbrella sampling calculations with more than a thousand windows and an aggregate total of 160 μs of simulation to investigate this transition with and without glycans. We find that the glycosylated spike has a higher barrier to opening and also energetically favors the down state over the up state. Analysis of the S-protein opening pathway reveals that glycans at N165 and N122 interfere with hydrogen bonds between the RBD and the N-terminal domain in the up state, while glycans at N165 and N343 can stabilize both the down and up states. Finally, we estimate how epitope exposure for several known antibodies changes along the opening path. We find that the BD-368-2 antibody’s epitope is continuously exposed, explaining its high efficacy.

The voltage-sensing domain of a hERG1 mutant is a cation-selective channel

A cationic leak current known as an “omega current” may arise from mutations of the first charged residue in the S4 of the voltage sensor domains of sodium and potassium voltage-gated channels. The voltage-sensing domains (VSDs) in these mutated channels act as pores allowing nonspecific passage of cations, such as Li+, K+, Cs+, and guanidinium. Interestingly, no omega currents have been previously detected in the nonswapped voltage-gated potassium channels such as the human-ether-a-go-go-related (hERG1), hyperpolarization-activated cyclic nucleotide-gated, and ether-a-go-go channels. In this work, we discovered a novel omega current by mutating the first charged residue of the S4 of the hERG1, K525 to serine. To characterize this omega current, we used various probes, including the hERG1 pore domain blocker, dofetilide, to show that the omega current does not require cation flux via the canonical pore domain. In addition, the omega flux does not cross the conventional selectivity filter. We also show that the mutated channel (K525S hERG1) conducts guanidinium. These data are indicative of the formation of an omega current channel within the VSD. Using molecular dynamics simulations with replica-exchange umbrella sampling simulations of the wild-type hERG1 and the K525S hERG1, we explored the molecular underpinnings governing the cation flow in the VSD of the mutant. We also show that the wild-type hERG1 may form water crevices supported by the biophysical surface accessibility data. Overall, our multidisciplinary study demonstrates that the VSD of hERG1 may act as a cation-selective channel wherein a mutation of the first charged residue in the S4 generates an omega current. Our simulation uncovers the atomistic underpinning of this mechanism.

CHARMM-GUI Enhanced Sampler for various collective variables and enhanced sampling methods.

Enhanced sampling methodologies modifying underlying Hamiltonians can be used for the systems with a rugged potential energy surface that makes it hard to observe convergence using conventional unbiased molecular dynamics (MD) simulations. We present CHARMM-GUI Enhanced Sampler, a web-based tool to prepare various enhanced sampling simulations inputs with user-selected collective variables (CVs). Enhanced Sampler provides inputs for the following nine methods: accelerated MD, Gaussian accelerated MD, conformational flooding, metadynamics, adaptive biasing force, steered MD, temperature replica exchange MD, replica exchange solute tempering 2, and replica exchange umbrella sampling for the method-implemented MD packages including AMBER, CHARMM, GENESIS, GROMACS, NAMD, and OpenMM. Users only need to select a group of atoms via intuitive web-implementation in order to define commonly used nine CVs of interest: center of mass based distance, angle, dihedral, root-mean-square-distance, radius of gyration, distance projected on axis, two types of angles projected on axis, and coordination numbers. The enhanced sampling methods are tested with several biological systems to illustrate their efficiency over conventional MD. Enhanced Sampler with carefully optimized system-dependent parameters will help users to get meaningful results from their enhanced sampling simulations.

Molecular simulation of lignin-related aromatic compound permeation through gram-negative bacterial outer membranes

Lignin, an abundant aromatic heteropolymer in secondary plant cell walls, is the single largest source of renewable aromatics in the biosphere. Leveraging this resource for renewable bioproducts through targeted microbial action depends on lignin fragment uptake by microbial hosts and subsequent enzymatic action to obtain the desired product. Recent computational work has emphasized that bacterial inner membranes are permeable to many aromatic compounds expected from lignin depolymerization processes. In this study, we expand on these findings through simulations for 42 lignin-related compounds across a gram-negative bacterial outer membrane model. Unbiased simulation trajectories indicate that spontaneous crossing for the full outer membrane is relatively rare at molecular simulation timescales, primarily due to preferential membrane partitioning and slow diffusion within the lipopolysaccharide layer within the outer membrane. Membrane partitioning and permeability coefficients were determined through replica exchange umbrella sampling simulations to overcome sampling limitations. We find that the glycosylated lipopolysaccharides found in the outer membrane increase the permeation barrier to many lignin-related compounds, particularly the most hydrophobic compounds. However, the effect is relatively modest; at industrially relevant concentrations, uncharged lignin-related compounds will readily diffuse across the outer membrane without the need for specific porins. Together, our results provide insight into the permeability of the bacterial outer membrane for assessing lignin fragment uptake and the future production of renewable bioproducts.

Practical Protocols for Efficient Sampling of Kinase-Inhibitor Binding Pathways Using Two-Dimensional Replica-Exchange Molecular Dynamics.

Molecular dynamics (MD) simulations are increasingly used to study various biological processes such as protein folding, conformational changes, and ligand binding. These processes generally involve slow dynamics that occur on the millisecond or longer timescale, which are difficult to simulate by conventional atomistic MD. Recently, we applied a two-dimensional (2D) replica-exchange MD (REMD) method, which combines the generalized replica exchange with solute tempering (gREST) with the replica-exchange umbrella sampling (REUS) in kinase-inhibitor binding simulations, and successfully observed multiple ligand binding/unbinding events. To efficiently apply the gREST/REUS method to other kinase-inhibitor systems, we establish modified, practical protocols with non-trivial simulation parameter tuning. The current gREST/REUS simulation protocols are tested for three kinase-inhibitor systems: c-Src kinase with PP1, c-Src kinase with Dasatinib, and c-Abl kinase with Imatinib. We optimized the definition of kinase-ligand distance as a collective variable (CV), the solute temperatures in gREST, and replica distributions and umbrella forces in the REUS simulations. Also, the initial structures of each replica in the 2D replica space were prepared carefully by pulling each ligand from and toward the protein binding sites for keeping stable kinase conformations. These optimizations were carried out individually in multiple short MD simulations. The current gREST/REUS simulation protocol ensures good random walks in 2D replica spaces, which are required for enhanced sampling of inhibitor dynamics around a target kinase.

NMMD: Efficient Cryo-EM Flexible Fitting Based on Simultaneous Normal Mode and Molecular Dynamics atomic displacements

Atomic models of cryo electron microscopy (cryo-EM) maps of biomolecular conformations are often obtained by flexible fitting of the maps with available atomic structures of other conformations (e.g., obtained by X-ray crystallography). This article presents a new flexible fitting method, NMMD, which combines normal mode analysis (NMA) and molecular dynamics simulation (MD). Given an atomic structure and a cryo-EM map to fit, NMMD simultaneously estimates global atomic displacements based on NMA and local displacements based on MD. NMMD was implemented by modifying EMfit, a flexible fitting method using MD only, in GENESIS 1.4. As EMfit, NMMD can be run with replica exchange umbrella sampling procedure. The new method was tested using a variety of EM maps (synthetic and experimental, with different noise levels and resolutions). The results of the tests show that adding normal modes to MD-based fitting makes the fitting faster (40% in average) and, in the majority of cases, more accurate.

Vectorial insertion of a β-helical peptide into membrane: a theoretical study on polytheonamide B

Spontaneous unidirectional, or vectorial, insertion of transmembrane peptides is a fundamental biophysical process for toxin and viral actions. Polytheonamide B (pTB) is a potent cytotoxic peptide with a β6.3-helical structure. Previous experimental studies revealed that the pTB inserts into the membrane in a vectorial fashion and forms a channel with its single molecular length long enough to span the membrane. Also, molecular dynamics simulation studies demonstrated that the pTB is prefolded in aqueous solution. These are unique features of pTB because most of the peptide toxins form channels through oligomerization of transmembrane helices. Here, we performed all-atom molecular dynamics simulations to examine the dynamic mechanism of the vectorial insertion of pTB, providing underlying elementary processes of the membrane insertion of a prefolded single transmembrane peptide. We find that the insertion of pTB proceeds with only the local lateral compression of the membrane in three successive phases: “landing,” “penetration,” and “equilibration” phases. The free energy calculations using the replica-exchange umbrella sampling simulations present an energy cost of 4.3 kcal/mol at the membrane surface for the membrane insertion of pTB from bulk water. The trajectories of membrane insertion revealed that the insertion process can occur in two possible pathways, namely “trapped” and “untrapped” insertions; in some cases, pTB is trapped in the upper leaflet during the penetration phase. Our simulations demonstrated the importance of membrane anchoring by the hydrophobic N-terminal blocking group in the landing phase, leading to subsequent vectorial insertion.

Large-Scale Membrane Permeability Prediction of Cyclic Peptides Crossing a Lipid Bilayer Based on Enhanced Sampling Molecular Dynamics Simulations.

Membrane permeability is a significant obstacle facing the development of cyclic peptide drugs. However, membrane permeation mechanisms are poorly understood. To investigate common features of permeable (and nonpermeable) designs, it is necessary to reproduce the membrane permeation process of cyclic peptides through the lipid bilayer. We simulated the membrane permeation process of 100 six-residue cyclic peptides across the lipid bilayer based on steered molecular dynamics (MD) and replica-exchange umbrella sampling simulations and predicted membrane permeability using the inhomogeneous solubility-diffusion model and a modified version of it. Furthermore, we confirmed the effectiveness of this protocol by predicting the membrane permeability of 56 eight-residue cyclic peptides with diverse chemical structures, including some confidential designs from a pharmaceutical company. As a result, a reasonable correlation between experimentally assessed and calculated membrane permeability of cyclic peptides was observed for the peptide libraries, except for strongly hydrophobic peptides. Our analysis of the MD trajectory demonstrated that most peptides were stabilized in the boundary region between bulk water and membrane and that for most peptides, the process of crossing the center of the membrane is the main obstacle to membrane permeation. The height of this barrier is well correlated with the electrostatic interaction between the peptide and the surrounding media. The structural and energetic features of the representative peptide at each vertical position within the membrane were also analyzed, revealing that peptides permeate the membrane by changing their orientation and conformation according to the surrounding environment.

A replica exchange umbrella sampling (REUS) approach to predict host\u2013guest binding free energies in SAMPL8 challenge

In this study, we report binding free energy calculations of various drugs-of-abuse to Cucurbit-[8]-uril as part of the SAMPL8 blind challenge. Force-field parameters were obtained from force-matching with different quantum mechanical levels of theory. The Replica Exchange Umbrella Sampling (REUS) approach was used with a cylindrical restraint to enhance the sampling of host–guest binding. Binding free energy was calculated by pulling the guest molecule from one side of the symmetric and cylindrical host, then into and through the host, and out the other side (bidirectional) as compared to pulling only to the bound pose inside the cylindrical host (unidirectional). The initial results with force-matched MP2 parameter set led to RMSE of 4.68 {text{kcal}}/{text{mol}} from experimental values. However, the follow-up study with CHARMM generalized force field parameters and force-matched PM6-D3H4 parameters resulted in RMSEs from experiment of 2.65 and 1.72 {text{kcal}}/{text{mol}}, respectively, which demonstrates the potential of REUS for accurate binding free energy calculation given a more suitable description of energetics. Moreover, we compared the free energies for the so called bidirectional and unidirectional free energy approach and found that the binding free energies were highly similar. However, one issue in the bidirectional approach is the asymmetry of profile on the two sides of the host. This is mainly due to the insufficient sampling for these larger systems and can be avoided by longer sampling simulations. Overall REUS shows great promise for binding free energy calculations.