Multiscale Molecular Dynamics Research Articles

Impact of solvation on the photoisomerisation dynamics of a photon-only rotary molecular motor

The optimization of the quantum efficiency of single-molecule light-driven rotary motors typically relies on chemical modifications. While, in isolated conditions, computational methods have been frequently used to design more efficient motors, the role played by the solvent environment has not been satisfactorily investigated. In this study, we used multiscale nonadiabatic molecular dynamics simulations of the working cycle of a 2-stroke photon-only molecular rotary motor. The results, which display dynamics consistent with the available transient spectroscopy measurements, predict a considerable decrease in the isomerisation quantum efficiency in methanol solution with respect to the gas phase. The origin of such a decrease is traced back to the ability of the motor to establish hydrogen bonds with solvent molecules. The analysis suggests that a modified motor with a reduced ability to form hydrogen bonds will display increased quantum efficiency, therefore extending the set of engineering rules available for designing light-driven rotary motors.

Unraveling the Molecular Dance: Insights into TREM2/DAP12 Complex Formation in Alzheimer's Disease through Molecular Dynamics Simulations.

Alzheimer's disease (AD) is a widespread neurodegenerative condition affecting millions globally. Recent research has implicated variants of the triggering receptor expressed in myeloid cells 2 (TREM2) as risk factors for AD. TREM2, an immunomodulatory receptor on microglial surfaces, plays a pivotal role in regulating microglial activation by association with DNAX-activation protein 12 (DAP12). Despite its significance, the mechanism underlying the formation of the complex between the transmembrane domains (TMDs) of TREM2 and DAP12 remains unclear. This study employs multiscale molecular dynamics (MD) simulations to investigate three TMD complex models, including two derived from experiments and one generated by AlphaFold2. Conducted within a lipid membrane consisting of an 80:20 mixture of phosphatidylcholine (POPC) and cholesterol, our analysis reveals hydrogen-bonding interactions between K26 of TREM2 and D16 of DAP12 in all three models, consistent with previous experimental findings. Our results elucidate the different spatial conformations observed in the models and offer insights into the structure of the TREM2/DAP12 TMD complex. Furthermore, we elucidate the role of charged residues in the assembly structure of the complex within the lipid membrane. These findings enhance our understanding of the molecular mechanism governing TREM2/DAP12 complex formation, providing a foundation for designing novel therapeutic strategies to address AD and other neurodegenerative diseases.

In-situ observation of silk nanofibril assembly via graphene plasmonic infrared sensor

Silk nanofibrils (SNFs), the fundamental building blocks of silk fibers, endow them with exceptional properties. However, the intricate mechanism governing SNF assembly, a process involving both protein conformational transitions and protein molecule conjunctions, remains elusive. This lack of understanding has hindered the development of artificial silk spinning techniques. In this study, we address this challenge by employing a graphene plasmonic infrared sensor in conjunction with multi-scale molecular dynamics (MD). This unique approach allows us to probe the secondary structure of nanoscale assembly intermediates (0.8–6.2 nm) and their morphological evolution. It also provides insights into the dynamics of silk fibroin (SF) over extended molecular timeframes. Our novel findings reveal that amorphous SFs undergo a conformational transition towards β-sheet-rich oligomers on graphene. These oligomers then connect to evolve into SNFs. These insights provide a comprehensive picture of SNF assembly, paving the way for advancements in biomimetic silk spinning.

State-dependent binding of cholesterol and an anionic lipid to the muscle-type Torpedo nicotinic acetylcholine receptor

The ability of the Torpedo nicotinic acetylcholine receptor (nAChR) to undergo agonist-induced conformational transitions requires the presence of cholesterol and/or anionic lipids. Here we use recently solved structures along with multiscale molecular dynamics simulations to examine lipid binding to the nAChR in bilayers that have defined effects on nAChR function. We examine how phosphatidic acid and cholesterol, lipids that support conformational transitions, individually compete for binding with phosphatidylcholine, a lipid that does not. We also examine how the two lipids work synergistically to stabilize an agonist-responsive nAChR. We identify rapidly exchanging lipid binding sites, including both phospholipid sites with a high affinity for phosphatidic acid and promiscuous cholesterol binding sites in the grooves between adjacent transmembrane α-helices. A high affinity cholesterol site is confirmed in the inner leaflet framed by a key tryptophan residue on the MX α-helix. Our data provide insight into the dynamic nature of lipid-nAChR interactions and set the stage for a detailed understanding of the mechanisms by which lipids facilitate nAChR function at the neuromuscular junction.

A robust computational quest: Discovering potential hits to improve the treatment of pyrazinamide-resistant Mycobacterium tuberculosis.

The rise of pyrazinamide (PZA)-resistant strains of Mycobacterium tuberculosis (MTB) poses a major challenge to conventional tuberculosis (TB) treatments. PZA, a cornerstone of TB therapy, must be activated by the mycobacterial enzyme pyrazinamidase (PZase) to convert its active form, pyrazinoic acid, which targets the ribosomal protein S1. Resistance, often associated with mutations in the RpsA protein, complicates treatment and highlights a critical gap in the understanding of structural dynamics and mechanisms of resistance, particularly in the context of the G97D mutation. This study utilizes a novel integration of computational techniques, including multiscale biomolecular and molecular dynamics simulations, physicochemical and medicinal chemistry predictions, quantum computations and virtual screening from the ZINC and Chembridge databases, to elucidate the resistance mechanism and identify lead compounds that have the potential to improve treatment outcomes for PZA-resistant MTB, namely ZINC15913786, ZINC20735155, Chem10269711, Chem10279789 and Chem10295790. These computational methods offer a cost-effective, rapid alternative to traditional drug trials by bypassing the need for organic subjects while providing highly accurate insight into the binding sites and efficacy of new drug candidates. The need for rapid and appropriate drug development emphasizes the need for robust computational analysis to justify further validation through invitro and invivo experiments.

Mechanistic Insight into the Mechanical Unfolding of the Integral Membrane Diacylglycerol Kinase.

The essential forces stabilizing membrane proteins and governing their folding and unfolding are difficult to decipher. Single-molecule atomic force spectroscopy mechanically unfolds individual membrane proteins and quantifies their dynamics and energetics. However, it remains challenging to structurally assign unfolding intermediates precisely and to deduce dominant interactions between specific residues that facilitate either the localized stabilization of these intermediates or the global assembly of membrane proteins. Here, we performed force spectroscopy experiments and multiscale molecular dynamics simulations to study the unfolding pathway of diacylglycerol kinase (DGK), a small trimeric multispan transmembrane enzyme. The remarkable agreement between experiments and simulations allowed precise structural assignment and interaction analysis of unfolding intermediates, bypassing existing limitations on structural mapping, and thus provided mechanistic explanations for the formation of these states. DGK unfolding was found to proceed with structural segments varying in size that do not correlate with its secondary structure. We identified intermolecular side-chain packing interactions as one of the major contributions to the stability of unfolding intermediates. Mutagenesis creating packing defects induced a dramatic decrease in the mechano-stability of corresponding intermediates and also in the thermo-stability of DGK trimer, in good agreement with predictions from simulations. Hence, the molecular determinants of the mechano- and thermo-stability of a membrane protein can be identified at residue resolution. The accurate structural assignment established and microscopic mechanism revealed in this work may substantially expand the scope of single-molecule studies of membrane proteins.

A binding site for phosphoinositides described by multiscale simulations explains their modulation of voltage-gated sodium channels

Voltage-gated sodium channels (Naᵥ) are membrane proteins which open to facilitate the inward flux of sodium ions into excitable cells. In response to stimuli, Naᵥ channels transition from the resting, closed state to an open, conductive state, before rapidly inactivating. Dysregulation of this functional cycle due to mutations causes diseases including epilepsy, pain conditions, and cardiac disorders, making Naᵥ channels a significant pharmacological target. Phosphoinositides are important lipid cofactors for ion channel function. The phosphoinositide PI(4,5)P2 decreases Naᵥ1.4 activity by increasing the difficulty of channel opening, accelerating fast inactivation and slowing recovery from fast inactivation. Using multiscale molecular dynamics simulations, we show that PI(4,5)P2 binds stably to inactivated Naᵥ at a conserved site within the DIV S4–S5 linker, which couples the voltage-sensing domain (VSD) to the pore. As the Naᵥ C-terminal domain is proposed to also bind here during recovery from inactivation, we hypothesize that PI(4,5)P2 prolongs inactivation by competitively binding to this site. In atomistic simulations, PI(4,5)P2 reduces the mobility of both the DIV S4–S5 linker and the DIII–IV linker, responsible for fast inactivation, slowing the conformational changes required for the channel to recover to the resting state. We further show that in a resting state Naᵥ model, phosphoinositides bind to VSD gating charges, which may anchor them and impede VSD activation. Our results provide a mechanism by which phosphoinositides alter the voltage dependence of activation and the rate of recovery from inactivation, an important step for the development of novel therapies to treat Naᵥ-related diseases.

A binding site for phosphoinositides described by multiscale simulations explains their modulation of voltage-gated sodium channels.

Voltage-gated sodium channels (Naᵥ) are membrane proteins which open to facilitate the inward flux of sodium ions into excitable cells. In response to stimuli, Naᵥ channels transition from the resting, closed state to an open, conductive state, before rapidly inactivating. Dysregulation of this functional cycle due to mutations causes diseases including epilepsy, pain conditions, and cardiac disorders, making Naᵥ channels a significant pharmacological target. Phosphoinositides are important lipid cofactors for ion channel function. The phosphoinositide PI(4,5)P2 decreases Naᵥ1.4 activity by increasing the difficulty of channel opening, accelerating fast inactivation and slowing recovery from fast inactivation. Using multiscale molecular dynamics simulations, we show that PI(4,5)P2 binds stably to inactivated Naᵥ at a conserved site within the DIV S4-S5 linker, which couples the voltage-sensing domain (VSD) to the pore. As the Naᵥ C-terminal domain is proposed to also bind here during recovery from inactivation, we hypothesize that PI(4,5)P2 prolongs inactivation by competitively binding to this site. In atomistic simulations, PI(4,5)P2 reduces the mobility of both the DIV S4-S5 linker and the DIII-IV linker, responsible for fast inactivation, slowing the conformational changes required for the channel to recover to the resting state. We further show that in a resting state Naᵥ model, phosphoinositides bind to VSD gating charges, which may anchor them and impede VSD activation. Our results provide a mechanism by which phosphoinositides alter the voltage dependence of activation and the rate of recovery from inactivation, an important step for the development of novel therapies to treat Naᵥ-related diseases.

Understanding Self-Assembly and Molecular Packing in Methylcellulose Aqueous Solutions Using Multiscale Modeling and Simulations.

We present a multiscale molecular dynamics (MD) simulation study on self-assembly in methylcellulose (MC) aqueous solutions. First, using MD simulations with a new coarse-grained (CG) model of MC chains in implicit water, we establish how the MC chains self-assemble to form fibrils and fibrillar networks and elucidate the MC chains' packing within the assembled fibrils. The CG model for MC is extended from a previously developed model for unsubstituted cellulose and captures the directionality of H-bonding interactions between the -OH groups. The choice and placement of the CG beads within each monomer facilitates explicit modeling of the exact degree and position of methoxy substitutions in the monomers along the MC chain. CG MD simulations show that with increasing hydrophobic effect and/or increasing H-bonding strength, the commercial MC chains (with degree of methoxy substitution, DS, ∼1.8) assemble from a random dispersed configuration into fibrils. The assembled fibrils exhibit consistent fibril diameters regardless of the molecular weight and concentration of MC chains, in agreement with past experiments. Most MC chains' axes are aligned with the fibril axis, and some MC chains exhibit twisted conformations in the fibril. To understand the molecular driving force for the twist, we conduct atomistic simulations of MC chains preassembled in fibrils (without any chain twists) in explicit water at 300 and 348 K. These atomistic simulations also show that at DS = 1.8, MC chains adopt twisted conformations, with these twists being more prominent at higher temperatures, likely as a result of shielding of hydrophobic methyl groups from water. For MC chains with varying DS, at 348 K, atomistic simulations show a nonmonotonic effect of DS on water-monomer contacts. For 0.0 < DS < 0.6, the MC monomers have more water contacts than at DS = 0.0 or DS > 0.6, suggesting that with few methoxy substitutions, the MC chains are effectively hydrophilic, letting the water molecules diffuse into the fibril to participate in H-bonds with the MC chains' remaining -OH groups. At DS > 0.6, the MC monomers become increasingly hydrophobic, as seen by decreasing water contacts around each monomer. We conclude based on the atomistic observations that MC chains with lower degrees of substitutions (DS ≤ 0.6) should exhibit solubility in water over broader temperature ranges than DS ∼ 1.8 chains.

Lipid Landscapes: Vibrational Spectroscopy for Decoding Membrane Complexity.

Cell membranes are incredibly complex environments containing hundreds of components. Despite substantial advances in the past decade, fundamental questions related to lipid-lipid interactions and heterogeneity persist. This review explores the complexity of lipid membranes, showcasing recent advances in vibrational spectroscopy to characterize the structure, dynamics, and interactions at the membrane interface. We include an overview of modern techniques such as surface-enhanced infrared spectroscopy as a steady-state technique with single-bilayer sensitivity, two-dimensional sum-frequency generation spectroscopy, and two-dimensional infrared spectroscopy to measure time-evolving structures and dynamics with femtosecond time resolution. Furthermore, we discuss the potential of multiscale molecular dynamics (MD) simulations, focusing on recently developed simulation algorithms, which have emerged as a powerful approach to interpret complex spectra. We highlight the ongoing challenges in studying heterogeneous environments in multicomponent membranes via current vibrational spectroscopic techniques and MD simulations. Overall, this review provides an up-to-date comprehensive overview of the powerful combination of vibrational spectroscopy and simulations, which has great potential to illuminate lipid-lipid, lipid-protein, and lipid-water interactions in the intricate conformational landscape of cell membranes. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 75 is April 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Reconciling ASPP-p53 binding mode discrepancies through an ensemble binding framework that bridges crystallography and NMR data.

ASPP2 and iASPP bind to p53 through their conserved ANK-SH3 domains to respectively promote and inhibit p53-dependent cell apoptosis. While crystallography has indicated that these two proteins employ distinct surfaces of their ANK-SH3 domains to bind to p53, solution NMR data has suggested similar surfaces. In this study, we employed multi-scale molecular dynamics (MD) simulations combined with free energy calculations to reconcile the discrepancy in the binding modes. We demonstrated that the binding mode based solely on a single crystal structure does not enable iASPP's RT loop to engage with p53's C-terminal linker-a verified interaction. Instead, an ensemble of simulated iASPP-p53 complexes facilitates this interaction. We showed that the ensemble-average inter-protein contacting residues and NMR-detected interfacial residues qualitatively overlap on ASPP proteins, and the ensemble-average binding free energies better match experimental KD values compared to single crystallgarphy-determined binding mode. For iASPP, the sampled ensemble complexes can be grouped into two classes, resembling the binding modes determined by crystallography and solution NMR. We thus propose that crystal packing shifts the equilibrium of binding modes towards the crystallography-determined one. Lastly, we showed that the ensemble binding complexes are sensitive to p53's intrinsically disordered regions (IDRs), attesting to experimental observations that these IDRs contribute to biological functions. Our results provide a dynamic and ensemble perspective for scrutinizing these important cancer-related protein-protein interactions (PPIs).

Multiscale Molecular Dynamics Simulations of an Active Self-Assembling Material.

Inspired by the adaptability observed in biological materials, self-assembly processes have attracted significant interest for their potential to yield novel materials with unique properties. However, experimental methods have often fallen short in capturing the molecular details of the assembly process. In this study, we employ a multiscale molecular dynamics simulation approach, complemented by NMR quantification, to investigate the mechanism of self-assembly in a redox-fueled bioinspired system. Contrary to conventional assumptions, we have uncovered a significant role played by the monomer precursor in the assembly process, with its presence varying with concentration and the extent of conversion of the monomer to the dimer. Experimental confirmation through NMR quantification underscores the concentration-dependent incorporation of monomers into the fibrous structures. Furthermore, our simulations also shed light on the diverse intermolecular interactions, including T-shaped and parallel π stacking, as well as hydrogen bonds, in stabilizing the aggregates. Overall, the open conformation of the dimer is preferred within these aggregates. However, inside the aggregates, the distribution of conformations shifts slightly to the closed conformation compared to on the surface. These findings contribute to the growing field of bioinspired materials science by providing valuable mechanistic and structural insights to guide the design and development of self-assembling materials with biomimetic functionalities.

The role of cryptic ancestral symmetry in histone folding mechanisms across Eukarya and Archaea.

Histones compact and store DNA in both Eukarya and Archaea, forming heterodimers in Eukarya and homodimers in Archaea. Despite this, the folding mechanism of histones across species remains unclear. Our study addresses this gap by investigating 11 types of histone and histone-like proteins across humans, Drosophila, and Archaea through multiscale molecular dynamics (MD) simulations, complemented by NMR and circular dichroism experiments. We confirm and elaborate on the widely applied "folding upon binding" mechanism of histone dimeric proteins and report a new alternative conformation, namely, the inverted non-native dimer, which may be a thermodynamically metastable configuration. Protein sequence analysis indicated that the inverted conformation arises from the hidden ancestral head-tail sequence symmetry underlying all histone proteins, which is congruent with the previously proposed histone evolution hypotheses. Finally, to explore the potential formations of homodimers in Eukarya, we utilized MD-based AWSEM and AI-based AlphaFold-Multimer models to predict their structures and conducted extensive all-atom MD simulations to examine their respective structural stabilities. Our results suggest that eukaryotic histones may also form stable homodimers, whereas their disordered tails bring significant structural asymmetry and tip the balance towards the formation of commonly observed heterotypic dimers.

Deformation mechanisms based on the multiscale molecular dynamics of a gradient TA1 titanium alloy.

The heterogeneous gradient TA1 titanium alloy holds great potential for a wide range of industrial applications. Considering the influence of the gradient structure on the plastic deformation behavior of the material, the TA1 gradient polycrystalline model under uniaxial compression is established. The deformation behavior of TA1 gradient polycrystals under uniaxial compression is investigated by molecular dynamics simulation. The simulation shows that there is significant transmission during the plastic deformation of TA1 gradient polycrystals. The transmissibility of plastic deformation is specified by the alternating appearance of twinning and grain refinement. Besides, the uniaxial compression process is accompanied by active dislocation motions. Moreover, the movement of dislocations is a dynamic cyclic process. In the same uniaxial compression environment, the triggering of the plasticity mechanism in the gradient polycrystalline model is closely related to grain size. The smaller grain size crystals hardly produce plastic deformation. Grain boundary migration of medium grain size crystals dominates in plastic deformation. The proliferation of dislocations under compressive stress is the primary trigger mechanism in larger grain size crystals. In addition, the stress concentration phenomenon in regions with medium grain sizes is more significant than that in regions with larger and small grain sizes.

Relation between Double Layer Structure, Capacitance, and Surface Tension in Electrowetting of Graphene and Aqueous Electrolytes.

Deciphering the mechanisms of charge storage on carbon-based materials is pivotal for the development of next-generation electrochemical energy storage systems. Graphene, the building block of graphitic electrodes, is an ideal model for probing such processes on a fundamental level. Herein, we investigate the thermodynamics of the graphene/aqueous electrolyte interface by utilizing a multiscale quantum mechanics-classical molecular dynamics (QM/MD) approach to provide insights into the effect of alkali metal ion (Li+) concentration on the interfacial tension (γSL) of the charged graphene/electrolyte interface. We demonstrate that the dependence of γSL on the applied surface charge exhibits an asymmetric behavior relative to the neutral surface. At the positively charged graphene sheet, the electrowetting response is amplified by electrolyte concentration, resulting in a strongly hydrophilic surface. On the contrary, at negative potential bias, γSL shows a weaker response to the charging of the electrode. Changes in γSL greatly affect the total areal capacitance predicted by the Young-Lippmann equation but have a negligible impact on the simulated total areal capacitance, indicating that the EDL structure is not directly correlated with the wettability of the surface and different interfacial mechanisms drive the two phenomena. The proposed model is validated experimentally by studying the electrowetting response of highly oriented pyrolytic graphite over a wide range of electrolyte concentrations. Our work presents the first combined theoretical and experimental study on electrowetting using carbon surfaces, introducing new conceptual routes for the investigation of wetting phenomena under potential bias.

Multiscale Molecular Dynamics Simulations of the Homodimer Accessory Protein ORF7b of SARS-CoV-2.

The SARS-CoV-2 ORF7b protein has drawn attention for its potential role in viral pathogenesis, but its structural details and lateral membrane associations remain elusive. In this study, we conducted multiscale molecular dynamics simulations to provide detailed molecular insights of the protein's dimerization, which is crucial for unraveling its structural model of protein-protein interface important to regulating cellular immune response. To gain a deeper understanding of homodimer configurations, we employed a machine learning algorithm for structural-based clustering. Clusters were categorized into three distinct groups for both parallel and antiparallel orientations, highlighting the influence of the initial monomer conformation on dimer configurations. Analysis of hydrogen bonding and π-π and π-cation stacking interactions within clusters revealed variations in interactions between clusters. In parallel dimers, weak stacking interactions in the transmembrane (TM) region were observed. In contrast, antiparallel dimers exhibited strong hydrogen bonding and stacking interactions contributing to tight dimeric packing, both within and outside the TM domain. Overall, our study provides a comprehensive view of the structural dynamics of ORF7b homodimerization in both parallel and antiparallel orientations. These findings shed light on the molecular interactions involved in ORF7b dimerization, which are crucial for understanding its potential roles in SARS-CoV-2 pathogenesis. This knowledge could inform future research and therapeutic strategies targeting this viral protein.

LipIDens: simulation assisted interpretation of lipid densities in cryo-EM structures of membrane proteins

Cryo-electron microscopy (cryo-EM) enables the determination of membrane protein structures in native-like environments. Characterising how membrane proteins interact with the surrounding membrane lipid environment is assisted by resolution of lipid-like densities visible in cryo-EM maps. Nevertheless, establishing the molecular identity of putative lipid and/or detergent densities remains challenging. Here we present LipIDens, a pipeline for molecular dynamics (MD) simulation-assisted interpretation of lipid and lipid-like densities in cryo-EM structures. The pipeline integrates the implementation and analysis of multi-scale MD simulations for identification, ranking and refinement of lipid binding poses which superpose onto cryo-EM map densities. Thus, LipIDens enables direct integration of experimental and computational structural approaches to facilitate the interpretation of lipid-like cryo-EM densities and to reveal the molecular identities of protein-lipid interactions within a bilayer environment. We demonstrate this by application of our open-source LipIDens code to ten diverse membrane protein structures which exhibit lipid-like densities.

Multi-scale molecular dynamics simulations of enhanced energy transfer in organic molecules under strong coupling

Exciton transport can be enhanced in the strong coupling regime where excitons hybridize with confined light modes to form polaritons. Because polaritons have group velocity, their propagation should be ballistic and long-ranged. However, experiments indicate that organic polaritons propagate in a diffusive manner and more slowly than their group velocity. Here, we resolve this controversy by means of molecular dynamics simulations of Rhodamine molecules in a Fabry-Pérot cavity. Our results suggest that polariton propagation is limited by the cavity lifetime and appears diffusive due to reversible population transfers between polaritonic states that propagate ballistically at their group velocity, and dark states that are stationary. Furthermore, because long-lived dark states transiently trap the excitation, propagation is observed on timescales beyond the intrinsic polariton lifetime. These insights not only help to better understand and interpret experimental observations, but also pave the way towards rational design of molecule-cavity systems for coherent exciton transport.

Learning coarse-grained force fields for fibrogenesis modeling

Fine-grained molecular dynamics (FGMD) can examine the dynamical and structural details of many complex systems including those found in biology, and can mitigate the many deficiencies of in vitro experiments. However these advantages come at the cost of prohibitive computing expense. Coarsening molecular structure and dynamics can dramatically diminish the computing complexity of simulations, while retaining modeling accuracies, and have become the state-of-the-art alternative to FGMD studies. Here we formulate the coarsening operator for application to fine-grained coordinates and develop the corresponding coarsening operator for forces to mathematically facilitate the transformation. In an exemplary application to studying the formation of fibrin networks of a few hundreds of soluble protein fibrinogens, we leverage multiscale molecular dynamics and machine learning to develop a physics-informed parameter learning (PIPL) framework with the learnable force parameters in physics priors as the learning target. While its adaptivity or performance on more general macromolecules remains untested, we show its performances, measured in terms of speed and accuracy, and demonstrate that simulations with the learned CGMD force field achieve higher accuracies and higher speeds than with existing methods. The resulting predictions of our model, additionally, are validated by in vitro observations.

Deciphering the Catalytic Mechanism of Virginiamycin B Lyase with Multiscale Methods and Molecular Dynamics Simulations.

Due to the emergence of antibiotic resistance, the need to explore novel antibiotics and/or novel strategies to counter antibiotic resistance is of utmost importance. In this work, we explored the molecular and mechanistic details of the degradation of a streptogramin B antibiotic by virginiamycin B (Vgb) lyase of Staphylococcus aureus using classical molecular dynamics simulations and multiscale quantum mechanics/molecular mechanics methods. Our results were in line with available experimental kinetic information. Although we were able to identify a stepwise mechanism, in the wild-type enzyme, the intermediate is short-lived, showing a small barrier to decay to the product state. The impact of point mutations on the reaction was also assessed, showing not only the importance of active site residues to the reaction catalyzed by Vgb lyase but also of near positive and negative residues surrounding the active site. Using molecular dynamics simulations, we also predicted the most likely protonation state of the 3-hydroxypicolinic moiety of the antibiotic and the impact of mutants on antibiotic binding. All this information will expand our understanding of linearization reactions of cyclic antibiotics, which are crucial for the development of novel strategies that aim to tackle antibiotic resistance.