Steered molecular dynamics investigations of protein function

Exploring Conformational Landscapes Along Anharmonic Low-Frequency Vibrations

We aim to automatize the identification of collective variables to simplify and speed up enhanced sampling simulations of conformational dynamics in biomolecules. We focus on anharmonic low-frequency vibrations that exhibit fluctuations on time scales faster than conformational transitions but describe a path of least resistance toward structural change. A key challenge is that harmonic approximations are ill-suited to characterize these vibrations, which are observed at far-infrared frequencies and are easily excited by thermal collisions at room temperature. Here, we approached this problem with a frequency-selective anharmonic (FRESEAN) mode analysis that does not rely on harmonic approximations and successfully isolates anharmonic low-frequency vibrations from short molecular dynamics simulation trajectories. We applied FRESEAN mode analysis to simulations of alanine dipeptide, a common test system for enhanced sampling simulation protocols, and compared the performance of isolated low-frequency vibrations to conventional user-defined collective variables (here backbone dihedral angles) in enhanced sampling simulations. The comparison shows that enhanced sampling along anharmonic low-frequency vibrations not only reproduces known conformational dynamics but can even further improve the sampling of slow transitions compared to user-defined collective variables. Notably, free energy surfaces spanned by low-frequency anharmonic vibrational modes exhibit lower barriers associated with conformational transitions relative to representations in backbone dihedral space. We thus conclude that anharmonic low-frequency vibrations provide a promising path for highly effective and fully automated enhanced sampling simulations of conformational dynamics in biomolecules.

In-Silico Analyses of Molecular Force Sensors for Mechanical Characterization of Biological Systems

Mechanical forces play key roles in biological processes such as cell migration and sensory perception. In recent years molecular force sensors have been developed as tools for in situ force measurements. Here we use all-atom steered molecular dynamics simulations to predict and study the relationship between design parameters and mechanical properties for three types of molecular force sensors commonly used in cellular biological research: two peptide- and one DNA-based. The peptide-based sensors consist of a pair of fluorescent proteins, which can undergo Förster resonance energy transfer (FRET), linked by spider silk (GPGGA)n or synthetic (GGSGGS)n disordered regions. The DNA-based sensor consists of two fluorophore-labeled strands of DNA that can be unzipped or sheared upon force application with a FRET signal as readout of dissociation. We simulated nine sensors, three of each kind. After equilibration, flexible peptide linkers of three different lengths were stretched by applying forces to their N- and C-terminal Cα atoms in opposite directions. Similarly, we equilibrated a DNA-based sensor and pulled on the phosphate atom of the terminal guanine of one strand and a selected phosphate atom on the other strand in the opposite direction. These simulations were performed at constant velocity (0.01 nm/ns - 10 nm/ns) and constant force (10 pN - 500 pN) for all versions of the sensors. Our results show how the force response of these sensors depends on their length, sequence, configuration and loading rate. Mechanistic insights gained from simulations analyses indicate that interpretation of experimental results should consider the influence of transient formation of secondary structure in peptide-based sensors and of overstretching in DNA-based sensors. These predictions can guide optimal fluorophore choice and facilitate the rational design of new sensors for use in protein, DNA, hybrid systems, and molecular devices.

Elasticity and Thermal Stability are Key Determinants of Hearing Rescue by Mini-Protocadherin-15 Proteins

Protocadherin-15 is a core protein component of inner-ear hair-cell tip links pulling on transduction channels essential for hearing and balance. Protocadherin-15 defects can result in non-syndromic deafness or Usher syndrome type 1F (USH1F) with hearing loss, balance deficits, and progressive blindness. Three rationally engineered shortened versions of protocadherin-15 (mini-PCDH15s) amenable for gene therapy have been used to rescue function in USH1F mouse models. Two can successfully or partially rescue hearing, while another one fails. Here we show that despite varying levels of hearing rescue, all three mini-PCDH15 versions can rescue hair-cell mechanotransduction. Negative-stain electron microscopy shows that all three versions form dimers like the wild-type protein, while crystal structures of some engineered fragments show that these can properly fold and bind calcium ions essential for function. In contrast, simulations predict distinct elasticities and nano differential scanning fluorimetry shows differences in melting temperature measurements. Our data suggest that elasticity and thermal stability are key determinants of sustained hearing rescue by mini-PCDH15s.

Interactions and Transport of a Bioconjugated Peptide Targeting the Mitomembrane

The Szeto-Schiller (SS) peptides are a subclass of cell-penetrating peptides that can specifically target mitochondria and mediate conditions caused by mitochondrial dysfunction. In this work, we constructed an iron-chelating SS peptide and studied its interaction with a mitochondrial-mimicking membrane using atomistic molecular dynamics (MD) simulations. We report that the peptide/membrane interaction is thermodynamically favorable, and the localization of the peptide to the membrane is driven by electrostatic interactions between the cationic residues and the anionic phospholipid headgroups. The insertion of the peptide into the membrane is driven by hydrophobic interactions between the aromatic side chains in the peptide and the lipid acyl tails. We also probed the translocation of the peptide across the membrane by applying nonequilibrium steered MD simulations and resolved the translocation pathway, free energy profile, and metastable states. We explored four distinct orientations of the peptide along the translocation pathway and found that one orientation was energetically more favorable than the other orientations. We tested a significantly slower pulling velocity on the most thermodynamically favorable system and compared metastable states during peptide translocation. We found that the peptide can optimize hydrophobic interactions with the membrane by having aromatic side chains interacting with the lipid acyl tails instead of forming π-π interactions with each other. The mechanistic insights emerging from our work will potentially facilitate improved peptide design with enhanced activity.

Designing collagens to shed light on the multi-scale structure-function mapping of matrix disorders

Collagens are the most abundant structural proteins in the extracellular matrix of animals and play crucial roles in maintaining the structural integrity and mechanical properties of tissues and organs while mediating important biological processes. Fibrillar collagens have a unique triple helix structure with a characteristic repeating sequence of (Gly-X-Y)n. Variations within the repetitive sequence can cause misfolding of the triple helix, resulting in heritable connective tissue disorders. The most common variations are single-point missense mutations that lead to the substitution of a glycine residue with a bulkier amino acid (Gly → X). In this review, we will first discuss the importance of collagen's triple helix structure and how single Gly substitutions can impact its folding, structure, secretion, assembly into higher-order structures, and biological functions. We will review the role of "designer collagens," i.e., synthetic collagen-mimetic peptides and recombinant bacterial collagen as model systems to include Gly → X substitutions observed in collagen disorders and investigate their impact on structure and function utilizing in vitro studies. Lastly, we will explore how computational modeling of collagen peptides, especially molecular and steered molecular dynamics, has been instrumental in probing the effects of Gly substitutions on structure, receptor binding, and mechanical stability across multiple length scales.

Interactions and reactivity in crystalline intermediates of mechanochemical cyclorhodation reactions

There is experimental evidence that solid mixtures of the rhodium dimer [Cp*RhCl2]2 and benzo[h] quinoline (BHQ) produce two different polymorphic molecular cocrystals called 4α and 4β under ball milling conditions. The addition of NaOAc to the mixture leads to the formation of the rhodacycle [Cp*Rh-(BHQ)Cl], where the central Rh atom retains its tetracoordinate character. Isolate 4β reacts with NaOAc leading to the same rhodacycle while isolate 4α does not under the same conditions. We show that the puzzling difference in reactivity between the two cocrystals can be traced back to fundamental aspects of the intermolecular interactions between the BHQ and [Cp*RhCl2]2 fragments in the crystalline environment. To support this view, we report a number of descriptors of the nature and strength of chemical bonds and intermolecular interactions in the extended solids and in a cluster model. We calculate formal quantum mechanical descriptors based on electronic structure, electron density, and binding and interaction energies including an energy decomposition analysis. Without exception, all descriptors point to 4β being a transient structure higher in energy than 4α with larger local and global electrophilic and nucleophilic powers, a more favorable spatial and energetic distribution of the frontier orbitals, and a more fragile crystal structure.

Roles of Accelerated Molecular Dynamics Simulations in Predictions of Binding Kinetic Parameters

Rational predictions on binding kinetics parameters of drugs to targets play significant roles in future drug designs. Full conformational samplings of targets are requisite for accurate predictions of binding kinetic parameters. In this review, we mainly focus on the applications of enhanced sampling technologies in calculations of binding kinetics parameters and residence time of drugs. The methods involved in molecular dynamics simulations are applied to not only probe conformational changes of targets but also reveal calculations of residence time that is significant for drug efficiency. For this review, special attention are paid to accelerated molecular dynamics (aMD) and Gaussian aMD (GaMD) simulations that have been adopted to predict the association or disassociation rate constant. We also expect that this review can provide useful information for future drug design.

Allosteric inhibition of myosin by phenamacril: a synergistic mechanism revealed by computational and experimental approaches

BACKGROUND

Myosin plays a crucial role in cellular processes, while its dysfunction can lead to organismal malfunction. Phenamacril (PHA), a highly species-specific and non-competitive inhibitor of myosin I (FgMyoI) from Fusarium graminearum, has been identified as an effective fungicide for controlling plant diseases caused by partial Fusarium pathogens, such as wheat scab and rice bakanae. However, the molecular basis of its action is still unclear.

RESULTS

This study used multiple computational approaches first to elucidate the allosteric inhibition mechanism of FgMyoI by PHA at the atomistic level. The results indicated the increase of adenosine triphosphate (ATP) binding affinity upon PHA binding, which might impede the release of hydrolysis products. Furthermore, simulations revealed a broadened outer cleft and a significantly more flexible interface for actin binding, accompanied by a decrease in signaling transduction from the catalytic center to the actin-binding interface. These various effects might work together to disrupt the actomyosin cycle and hinder the ability of motor to generate force. Our experimental results further confirmed that PHA reduces the enzymatic activity of myosin and its binding with actin.

CONCLUSION

Therefore, our findings demonstrated that PHA might suppress the function of myosin through a synergistic mechanism, providing new insights into myosin allostery and offering new avenues for drug/fungicide discovery targeting myosin. © 2023 Society of Chemical Industry.

Free Energy Simulations of Receptor-Binding Domain Opening of the SARS-CoV-2 Spike Indicate a Barrierless Transition with Slow Conformational Motions

Infection by sarbecoviruses begins with the attachment of the homotrimeric viral "spike" protein to the angiotensin-converting enzyme 2 receptor on the surface of mammalian cells. This requires one or more receptor-binding domains (RBDs) to be in the open (up) position. Here, we present the results of long molecular dynamics simulations with umbrella sampling (US) to compute a one-dimensional free energy profile of RBD opening/closing and the associated transition times. After ≃3.58μs of simulation time per US window (∼229 μs in total), which was required to approach trajectory decorrelation, the computed free energy profile was found to be without large barriers. This suggests that the RBD diffuses between the open and closed positions without significant energetic hindrance. This interpretation appears consistent with experiments but is at odds with some previous simulations. Modeling the RBD motion as diffusive dynamics along the computed free energy profile, we find that the overall time required for the transition is only about 2 μs, which is 5 orders of magnitude shorter than experimentally measured transition times. We speculate that the most likely reason for the transition time mismatch is our use of very short glycans, which was required to make the simulations performed here feasible. Despite the long simulation times, the final free energy profile is not fully converged with statistical errors of ≃1.16 kcal/mol, which were found to be consistent with the slow time decay in the autocorrelation of the conformational motions of the protein. The simulation lengths that would be required to obtain fully converged results remain unknown, but the present calculations would benefit from at least an order-of-magnitude extension.

Molecular basis of Mg2+ permeation through the human mitochondrial Mrs2 channel

Mitochondrial RNA splicing 2 (Mrs2), a eukaryotic CorA ortholog, enables Mg2+ to permeate the inner mitochondrial membrane and plays an important role in mitochondrial metabolic function. However, the mechanism by which Mrs2 permeates Mg2+ remains unclear. Here, we report four cryo-electron microscopy (cryo-EM) reconstructions of Homo sapiens Mrs2 (hMrs2) under various conditions. All of these hMrs2 structures form symmetrical pentamers with very similar pentamer and protomer conformations. A special structural feature of Cl--bound R-ring, which consists of five Arg332 residues, was found in the hMrs2 structure. Molecular dynamics simulations and mitochondrial Mg2+ uptake assays show that the R-ring may function as a charge repulsion barrier, and Cl- may function as a ferry to jointly gate Mg2+ permeation in hMrs2. In addition, the membrane potential is likely to be the driving force for Mg2+ permeation. Our results provide insights into the channel assembly and Mg2+ permeation of hMrs2.

Molecular basis of conformational changes and mechanics of integrins

Integrin, as a mechanotransducer, establishes the mechanical reciprocity between the extracellular matrix (ECM) and cells at integrin-mediated adhesion sites. This study used steered molecular dynamics (SMD) simulations to investigate the mechanical responses of integrin α_vβ₃ with and without 10th type III fibronectin (FnIII₁₀) binding for tensile, bending and torsional loading conditions. The ligand-binding integrin confirmed the integrin activation during equilibration and altered the integrin dynamics by changing the interface interaction between β-tail, hybrid and epidermal growth factor domains during initial tensile loading. The tensile deformation in integrin molecules indicated that fibronectin ligand binding modulates its mechanical responses in the folded and unfolded conformation states. The bending deformation responses of extended integrin models reveal the change in behaviour of integrin molecules in the presence of Mn²⁺ ion and ligand based on the application of force in the folding and unfolding directions of integrin. Furthermore, these SMD simulation results were used to predict the mechanical properties of integrin underlying the mechanism of integrin-based adhesion. The evaluation of integrin mechanics provides new insights into understanding the mechanotransmission (force transmission) between cells and ECM and contributes to developing an accurate model for integrin-mediated adhesion. This article is part of a discussion meeting issue 'Supercomputing simulations of advanced materials'.

An in silico approach to determine inter-subunit affinities in human septin complexes

The septins are a conserved family of filament-forming guanine nucleotide binding proteins, often named the fourth component of the cytoskeleton. Correctly assembled septin structures are required for essential intracellular processes such as cytokinesis, vesicular transport, polarity establishment, and cellular adhesion. Structurally, septins belong to the P-Loop NTPases but they do not mediate signals to effectors through GTP binding and hydrolysis. GTP binding and hydrolysis are believed to contribute to septin complex integrity, but biochemical approaches addressing this topic are hampered by the stability of septin complexes after recombinant expression and the lack of nucleotide-depleted complexes. To overcome this limitation, we used a molecular dynamics-based approach to determine inter-subunit binding free energies in available human septin dimer structures and in their apo forms, which we generated in silico. The nucleotide in the GTPase active subunits SEPT2 and SEPT7, but not in SEPT6, was identified as a stabilizing element in the G interface. Removal of GDP from SEPT2 and SEPT7 results in flipping of a conserved Arg residue and disruption of an extensive hydrogen bond network in the septin unique element, concomitant with a decreased inter-subunit affinity. Based on these findings we propose a singular "lock-hydrolysis" mechanism stabilizing human septin filaments.

A Study of a Protein-Folding Machine: Transient Rotation of the Polypeptide Backbone Facilitates Rapid Folding of Protein Domains in All-Atom Molecular Dynamics Simulations

Molecular dynamics simulations of protein folding typically consider the polypeptide chain at equilibrium and in isolation from the cellular components. We argue that in order to understand protein folding as it occurs in vivo, it should be modeled as an active, energy-dependent process, in which the cellular protein-folding machine directly manipulates the polypeptide. We conducted all-atom molecular dynamics simulations of four protein domains, whose folding from the extended state was augmented by the application of rotational force to the C-terminal amino acid, while the movement of the N-terminal amino acid was restrained. We have shown earlier that such a simple manipulation of peptide backbone facilitated the formation of native structures in diverse α-helical peptides. In this study, the simulation protocol was modified, to apply the backbone rotation and movement restriction only for a short time at the start of simulation. This transient application of a mechanical force to the peptide is sufficient to accelerate, by at least an order of magnitude, the folding of four protein domains from different structural classes to their native or native-like conformations. Our in silico experiments show that a compact stable fold may be attained more readily when the motions of the polypeptide are biased by external forces and constraints.

The α-Synuclein Monomer May Have Different Misfolding Mechanisms in the Induction of α-Synuclein Fibrils with Different Polymorphs

The aggregation of alpha-synuclein (α-Syn) is closely related to the occurrence of some neurodegenerative diseases such as Parkinson's disease. The misfolding of α-Syn monomer plays a key role in the formation of aggregates and extension of fibril. However, the misfolding mechanism of α-Syn remains elusive. Here, three different α-Syn fibrils (isolated from a diseased human brain, generated by in vitro cofactor-tau induction, and obtained by in vitro cofactor-free induction) were selected for the study. The misfolding mechanisms of α-Syn were uncovered by studying the dissociation of the boundary chains based on the conventional molecular dynamics (MD) and Steered MD simulations. The results showed that the dissociation paths of the boundary chains in the three systems were different. According to the reverse process of dissociation, we concluded that in the human brain system, the binding of the monomer and template starts from the C-terminal and gradually misfolds toward the N-terminal. In the cofactor-tau system, the monomer binding starts from residues 58-66 (contain β3), followed by the C-terminal coil (residues 67-79). Then, the N-terminal coil (residues 36-41) and residues 50-57 (contain β2) bind to the template, followed by residues 42-49 (contain β1). In the cofactor-free system, two misfolding paths were found. One is that the monomer binds to the N/C-terminal (β1/β6) and then binds to the remaining residues. The other one is that the monomer binds sequentially from the C- to N-terminal, similar to the human brain system. Furthermore, in the human brain and cofactor-tau systems, electrostatic interactions (especially from residues 58-66) are the main driving force during the misfolding process, whereas in the cofactor-free system, the contributions of electrostatic and van der Waals interactions are comparable. These results may provide a deeper understanding for the misfolding and aggregation mechanism of α-Syn.

Deep Boosted Molecular Dynamics (DBMD): Accelerating molecular simulations with Gaussian boost potentials generated using probabilistic Bayesian deep neural network

We have developed a new Deep Boosted Molecular Dynamics (DBMD) method. Probabilistic Bayesian neural network models were implemented to construct boost potentials that exhibit Gaussian distribution with minimized anharmonicity, thereby allowing for accurate energetic reweighting and enhanced sampling of molecular simulations. DBMD was demonstrated on model systems of alanine dipeptide and the fast-folding protein and RNA structures. For alanine dipeptide, 30ns DBMD simulations captured up to 83-125 times more backbone dihedral transitions than 1μs conventional molecular dynamics (cMD) simulations and were able to accurately reproduce the original free energy profiles. Moreover, DBMD sampled multiple folding and unfolding events within 300ns simulations of the chignolin model protein and identified low-energy conformational states comparable to previous simulation findings. Finally, DBMD captured a general folding pathway of three hairpin RNAs with the GCAA, GAAA, and UUCG tetraloops. Based on Deep Learning neural network, DBMD provides a powerful and generally applicable approach to boosting biomolecular simulations. DBMD is available with open source in OpenMM at https://github.com/MiaoLab20/DBMD/.

Siloxane Molecules: Nonlinear Elastic Behavior and Fracture Characteristics

Fracture phenomena in soft materials span multiple length and time scales. This poses a major challenge in computational modeling and predictive materials design. To pass quantitatively from molecular to continuum scales, a precise representation of the material response at the molecular level is vital. Here, we derive the nonlinear elastic response and fracture characteristics of individual siloxane molecules using molecular dynamics (MD) studies. For short chains, we find deviations from classical scalings for both the effective stiffness and mean chain rupture times. A simple model of a nonuniform chain of Kuhn segments captures the observed effect and agrees well with MD data. We find that the dominating fracture mechanism depends on the applied force scale in a nonmonotonic fashion. This analysis suggests that common polydimethylsiloxane (PDMS) networks fail at cross-linking points. Our results can be readily lumped into coarse-grained models. Although focusing on PDMS as a model system, our study presents a general procedure to pass beyond the window of accessible rupture times in MD studies employing mean first passage time theory, which can be exploited for arbitrary molecular systems.

Milestoning simulation of ligand dissociation from the glycogen synthase kinase 3β

As drug-binding kinetics has become an important factor to be considered in modern drug discovery, this work evaluated the ability of the Milestoning method in computing the absolute dissociation rate of a ligand from the serine-threonine kinase, glycogen synthase kinase 3β, which is a target for designing drugs to treat diseases such as neurodegenerative disorders and diabetes. We found that the Milestoning method gave good agreement with experiment with modest computational costs. Although the time scale for dissociation lasted tens of seconds, the collective molecular dynamics simulations total less than 1μs. Computing the committor function helped to identify the transition states (TSs), in which the ligand moved substantially away from the binding pocket. The glycine-rich loop with a serine residue attaching to its tips was found to undergo large movement from the bound to the TSs and might play a role in controlling drug-dissociation kinetics.

Free energy and kinetic rate calculation via non-equilibrium molecular simulation: application to biomolecules

Non-equilibrium molecular dynamics (NEMD) simulation has been recognized as a powerful tool for examining biomolecules and provides fruitful insights into not only non-equilibrium but also equilibrium processes. We review recent advances in NEMD simulation and relevant, fundamental results of non-equilibrium statistical mechanics. We first introduce Crooks fluctuation theorem and Jarzynski equality that relate free energy difference to work done on a physical system during a non-equilibrium process. The theorems are beneficial for the analysis of NEMD trajectories. We then describe rate theory, a framework to calculate molecular kinetics from a non-equilibrium process; this theoretical framework enables us to calculate a reaction time-mean-first passage time-from NEMD trajectories. We, in turn, present recent NEMD techniques that apply an external force to a system to enhance molecular dissociation and introduce their application to biomolecules. Lastly, we show the current status of an appropriate selection of reaction coordinates for NEMD simulation.

Gaussian Accelerated Molecular Dynamics in OpenMM

Gaussian accelerated molecular dynamics (GaMD) is a computational technique that provides both unconstrained enhanced sampling and free energy calculations of biomolecules. Here, we present the implementation of GaMD in the OpenMM simulation package and validate it on model systems of alanine dipeptide and RNA folding. For alanine dipeptide, 30 ns GaMD production simulations reproduced free energy profiles of 1000 ns conventional molecular dynamics (cMD) simulations. In addition, GaMD simulations captured the folding pathways of three hyperstable RNA tetraloops (UUCG, GCAA, and CUUG) and binding of the rbt203 ligand to the HIV-1 Tar RNA, both of which involved critical electrostatic interactions such as hydrogen bonding and base stacking. Together with previous implementations, GaMD in OpenMM will allow for wider applications in simulations of proteins, RNA, and other biomolecules.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

Benchmarking Adaptive Steered Molecular Dynamics (ASMD) on CHARMM Force Fields

The potentials of mean force (PMFs) along the end‐to‐end distance of two different helical peptides have been obtained and benchmarked using the adaptive steered molecular dynamics (ASMD) method. The results depend strongly on the choice of force field driving the underlying all‐atom molecular dynamics, and are reported with respect to the three most popular CHARMM force field versions: c22, c27 and c36. Two small peptides, ALA10 and 1PEF, serve as the particular case studies. The comparisons between the versions of the CHARMM force fields provides both a qualitative and quantitative look at their performance in forced unfolding simulations in which peptides undergo large changes in structural conformations. We find that ASMD with the underlying c36 force field provides the most robust results for the selected benchmark peptides.

A lesson for the maestro of the replication fork: Targeting the protein-binding interface of proliferating cell nuclear antigen for anticancer therapy

The proliferating cell nuclear antigen (PCNA) has emerged as a promising candidate for the development of novel cancer therapeutics. PCNA is a nononcogenic mediator of DNA replication that regulates a diverse range of cellular functions and pathways through a comprehensive list of protein-protein interactions. The hydrophobic binding pocket on PCNA offers an opportunity for the development of inhibitors to target various types of cancers and modulate protein-protein interactions. In the present study, we explored the binding modes and affinity of molecule I1 (standard molecule) with the previously suggested dimer interface pocket and the hydrophobic pocket present on the frontal side of the PCNA monomer. We also identified potential lead molecules from the library of in-house synthesized 3-methylenisoindolin-1-one based molecules to inhibit the protein-protein interactions of PCNA. Our results were based on robust computational methods, including molecular docking, conventional, steered, and umbrella sampling molecular dynamics simulations. Our results suggested that the standard inhibitor I1 interacts with the hydrophobic pocket of PCNA with a higher affinity than the previously suggested binding site. Also, the proposed molecules showed better or comparable binding free energies as calculated by the Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach and further validated by enhanced umbrella sampling simulations. In vitro and in vivo methods could test the computationally suggested molecules for advancement in the drug discovery pipeline.

Extended-ensemble docking to probe dynamic variation of ligand binding sites during large-scale structural changes of proteins

Proteins can sample a broad landscape as they undergo conformational transition between different functional states. At the same time, as key players in almost all cellular processes, proteins are important drug targets. Considering the different conformational states of a protein is therefore central for a successful drug-design strategy. Here we introduce a novel docking protocol, termed extended-ensemble docking, pertaining to proteins that undergo large-scale (global) conformational changes during their function. In its application to multidrug ABC-transporter P-glycoprotein (Pgp), extensive non-equilibrium molecular dynamics simulations employing system-specific collective variables are first used to describe the transition cycle of the transporter. An extended set of conformations (extended ensemble) representing the full transition cycle between the inward- and the outward-facing states is then used to seed high-throughput docking calculations of known substrates, non-substrates, and modulators of the transporter. Large differences are predicted in the binding affinities to different conformations, with compounds showing stronger binding affinities to intermediate conformations compared to the starting crystal structure. Hierarchical clustering of the binding modes shows all ligands preferably bind to the large central cavity of the protein, formed at the apex of the transmembrane domain (TMD), whereas only small binding populations are observed in the previously described R and H sites present within the individual TMD leaflets. Based on the results, the central cavity is further divided into two major subsites, first preferably binding smaller substrates and high-affinity inhibitors, whereas the second one shows preference for larger substrates and low-affinity modulators. These central subsites along with the low-affinity interaction sites present within the individual TMD leaflets may respectively correspond to the proposed high- and low-affinity binding sites in Pgp. We propose further an optimization strategy for developing more potent inhibitors of Pgp, based on increasing its specificity to the extended ensemble of the protein, instead of using a single protein structure, as well as its selectivity for the high-affinity binding site. In contrast to earlier in silico studies using single static structures of Pgp, our results show better agreement with experimental studies, pointing to the importance of incorporating the global conformational flexibility of proteins in future drug-discovery endeavors.

Elastic versus brittle mechanical responses predicted for dimeric cadherin complexes

Cadherins are a superfamily of adhesion proteins involved in a variety of biological processes that include the formation of intercellular contacts, the maintenance of tissue integrity, and the development of neuronal circuits. These transmembrane proteins are characterized by ectodomains composed of a variable number of extracellular cadherin (EC) repeats that are similar but not identical in sequence and fold. E-cadherin, along with desmoglein and desmocollin proteins, are three classical-type cadherins that have slightly curved ectodomains and engage in homophilic and heterophilic interactions through an exchange of conserved tryptophan residues in their N-terminal EC1 repeat. In contrast, clustered protocadherins are straighter than classical cadherins and interact through an antiparallel homophilic binding interface that involves overlapped EC1 to EC4 repeats. Here we present molecular dynamics simulations that model the adhesive domains of these cadherins using available crystal structures, with systems encompassing up to 2.8 million atoms. Simulations of complete classical cadherin ectodomain dimers predict a two-phased elastic response to force in which these complexes first softly unbend and then stiffen to unbind without unfolding. Simulated α, β, and γ clustered protocadherin homodimers lack a two-phased elastic response, are brittle and stiffer than classical cadherins and exhibit complex unbinding pathways that in some cases involve transient intermediates. We propose that these distinct mechanical responses are important for function, with classical cadherin ectodomains acting as molecular shock absorbers and with stiffer clustered protocadherin ectodomains facilitating overlap that favors binding specificity over mechanical resilience. Overall, our simulations provide insights into the molecular mechanics of single cadherin dimers relevant in the formation of cellular junctions essential for tissue function.

GLOW: A Workflow Integrating Gaussian-Accelerated Molecular Dynamics and Deep Learning for Free Energy Profiling

We introduce a Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and free energy profiling workflow (GLOW) to predict molecular determinants and map free energy landscapes of biomolecules. All-atom GaMD-enhanced sampling simulations are first performed on biomolecules of interest. Structural contact maps are then calculated from GaMD simulation frames and transformed into images for building DL models using a convolutional neural network. Important structural contacts are further determined from DL models of attention maps of the structural contact gradients, which allow us to identify the system reaction coordinates. Finally, free energy profiles are calculated for the selected reaction coordinates through energetic reweighting of the GaMD simulations. We have also successfully demonstrated GLOW for the characterization of activation and allosteric modulation of a G protein-coupled receptor, using the adenosine A₁ receptor (A₁AR) as a model system. GLOW findings are highly consistent with previous experimental and computational studies of the A₁AR, while also providing further mechanistic insights into the receptor function. In summary, GLOW provides a systematic approach to mapping free energy landscapes of biomolecules. The GLOW workflow and its user manual can be downloaded at http://miaolab.org/GLOW.

Assessing the Stability of Biological Fibrils by Molecular-Scale Simulations

The nanomechanical characterization of several biological fibrils that are the result of protein aggregation via molecular dynamics simulation is nowadays feasible, and together with atomic force microscopy experiments has widened our understanding of the forces in the regime of pN-nN and system sizes of about hundreds of nanometers. Several methodologies have been developed to achieve this target, and they range from the atomistic representation via molecular force fields to coarse-grained strategies that provide comparable results with experiments in a systematic way. In this chapter, we discuss several methodologies for the calculation of mechanical parameters, such as the elastic constants of relevant biological systems. They are presented together with details about parameterization and current limitations. Then, we discuss some of the applications of such methodologies for the description of bacterial filament and β-amyloid systems. Finally, the latest lines of development are discussed.

Shock-Induced Damage Mechanism of Perineuronal Nets

The perineuronal net (PNN) region of the brain’s extracellular matrix (ECM) surrounds the neural networks within the brain tissue. The PNN is a protective net-like structure regulating neuronal activity such as neurotransmission, charge balance, and action potential generation. Shock-induced damage of this essential component may lead to neuronal cell death and neurodegenerations. The shock generated during a vehicle accident, fall, or improvised device explosion may produce sufficient energy to damage the structure of the PNN. The goal is to investigate the mechanics of the PNN in reaction to shock loading and to understand the mechanical properties of different PNN components such as glycan, GAG, and protein. In this study, we evaluated the mechanical strength of PNN molecules and the interfacial strength between the PNN components. Afterward, we assessed the PNN molecules’ damage efficiency under various conditions such as shock speed, preexisting bubble, and boundary conditions. The secondary structure altercation of the protein molecules of the PNN was analyzed to evaluate damage intensity under varying shock speeds. At a higher shock speed, damage intensity is more elevated, and hyaluronan (glycan molecule) is most likely to break at the rigid junction. The primary structure of the protein molecules is least likely to fail. Instead, the molecules’ secondary bonds will be altered. Our study suggests that the number of hydrogen bonds during the shock wave propagation is reduced, which leads to the change in protein conformations and damage within the PNN structure. As such, we found a direct connection between shock wave intensity and PNN damage.

The impact of phosphatidylserine exposure on cancer cell membranes on the activity of the anticancer peptide HB43

HB43 (FAKLLAKLAKKLL) is a synthetic peptide active against cell lines derived from breast, colon, melanoma, lung, prostate, and cervical cancers. Despite its remarkable spectrum of activity, the mechanism of action at the molecular level has never been investigated, preventing further optimization of its selectivity. The alternation of charged and hydrophobic residues suggests amphipathicity, but the formation of alpha-helical structure seems discouraged by its short length and the large number of positively charged residues. Using different biophysical and in silico approaches we show that HB43 is completely unstructured in solution but assumes alpha-helical conformation in the presence of DPC micelles and liposomes exposing phosphatidylserine (PS) used as mimics of cancer cell membranes. Membrane permeabilization assays demonstrate that the interaction leads to the preferential destabilization of PS-containing vesicles with respect to PC-containing ones, here used as noncancerous cell mimics. ssNMR reveals that HB43 is able to fluidify the internal structure of cancer-cell mimicking liposomes while MD simulations show its internalization in such bilayers. This is achieved by the formation of specific interactions between the lysine side chains and the carboxylate group of phosphatidylserine and/or the phosphate oxygen atoms of targeted phospholipids, which could catalyze the formation of the alpha helix required for internalization. With the aim of better understanding the peptide biocompatibility and the additional antibacterial activity, the interaction with noncancerous cell mimicking liposomes exposing phosphatidylcholine (PC) and bacterial mimicking bilayers exposing phosphatidylglycerol (PG) is also described.

Binding of SARS-COV-2 (COVID-19) and SARS-COV to human ACE2: Identifying binding sites and consequences on ACE2 stiffness

The SARS-CoV-2 coronavirus (COVID-19) that is causing the massive global pandemic exhibits similar human cell invasion mechanism as the coronavirus SARS-CoV, which had significantly lower fatalities. The cell membrane protein Angiotensin-converting enzyme 2 (ACE2) is the initiation point for both the coronavirus infections in humans. Here, we model the molecular interactions and mechanical properties of ACE2 with both SARS-CoV and COVID-19 spike protein receptor-binding domains (RBD). We report that the COVID-19 spike RBD interacts with ACE2 more strongly and at only two protein residues, as compared to multi-residue interaction of the SARS-CoV. Although both coronaviruses stiffen the ACE2, the impact of COVID-19 is six times larger, which points towards differences in the severity of the reported respiratory distress. The recognition of specific residues of ACE2 attachments to coronaviruses is important as the residues suggest potential sites of intervention to inhibit attachment and subsequent entry of the COVID-19 into human host cells

The interplay between surface-functionalized gold nanoparticles and negatively charged lipid vesicles

The comprehensive understanding of the interactions between gold nanoparticles (AuNPs) and phospholipid vesicles has important implications in various biomedical applications; however, this is not yet well understood. Here, coarse-grained molecular dynamics (CGMD) simulations were performed to study the interactions between functionalized AuNPs and negatively charged lipid vesicles, and the effects of the surface chemistry and surface charge density (SCD) of AuNPs were analyzed. It is revealed that AuNPs with different surface ligands adhere to the membrane surface (anionic AuNPs) or get into the vesicle bilayer (hydrophobic and cationic AuNPs). Due to the loose arrangement of lipid molecules, AuNPs penetrate curved vesicle membranes more easily than planar lipid bilayers. Cationic AuNPs present three different interaction modes with the vesicle, namely insertion, partial penetration and complete penetration, which are decided by the SCD difference. Both hydrophobic interaction and electrostatic interaction play crucial roles in the interplay between cationic AuNPs and lipid vesicles. For the cationic AuNP with a low SCD, it gets into the lipid bilayer without membrane damage through the hydrophobic interaction, and it is finally stabilized in the hydrophobic interior of the vesicle membrane in a thermodynamically stable "snorkeling" configuration. For the cationic AuNP with a high SCD, it crosses the vesicle membrane and gets into the vesicle core through a membrane pore induced by strong electrostatic interaction. In this process, the membrane structure is destroyed. These findings provide a molecular-level understanding of the interplay between AuNPs and lipid vesicles, which may further expand the application of functional AuNPs in modern biomedicine.

The penetration of human defensin 5 (HD5) through bacterial outer membrane: simulation studies

Human α-defensin 5 (HD5) is one of cationic antimicrobial peptides which plays a crucial role in an innate immune system in human body. HD5 shows the killing activity against a broad spectrum of pathogenic bacteria by making a pore in a bacterial membrane and penetrating into a cytosol. Nonetheless, its pore-forming mechanisms remain unclear. Thus, in this work, the constant-velocity steered molecular dynamics (SMD) simulation was used to simulate the permeation of a dimeric HD5 into a gram-negative lipopolysaccharide (LPS) membrane model. Arginine-rich HD5 is found to strongly interact with a LPS surface. Upon arrival, arginines on HD5 interact with lipid A head groups (a top part of LPS) and then drag these charged moieties down into a hydrophobic core resulting in the formation of water-filled pore. Although all arginines are found to interact with a membrane, Arg13 and Arg32 appear to play a dominant role in the HD5 adsorption on a gram-negative membrane. Furthermore, one chain of a dimeric HD5 is required for HD5 adhesion. The interactions of arginine-lipid A head groups play a major role in adhering a cationic HD5 on a membrane surface and retarding a HD5 passage in the meantime.

Steered molecular dynamics and stability analysis on PAH dimerisation and condensation on fullerene and soot surfaces

The mechanism of how a soot nucleus is impacted by polycyclic aromatic hydrocarbons (PAHs) and then grows through PAH condensation remains unclear. Using steered molecular dynamics (SMD), the non-bonding interaction between PAHs and soot was quantitatively studied using the free energy distribution during the dimerisation and condensation. The results showed that only two dimers (A₇-A₁₀ and 2 A₁₀) remained stable at 1000 K. The simulations showed that PAH condensation on a fullerene should not be ignored in soot mass growth. For fullerenes with a diameter not less than 1.8 nm (C₅₄₀), even A₄ condenses at temperatures of 1500 K, and A10 condenses stably on the surface of fullerenes even at 2000 K. The effects of multilayers and hydrogenated fullerenes on the free energy of PAH condensation are different. The stability of PAH dimers and PAH condensation pairs was discussed through free energy and chemical equilibrium. The results show that larger dimers are more stable than small ones at flame temperatures. Condensation is far more important than nucleation in mass growth at flame temperatures. Furthermore, the larger the PAH is, the higher the transformation ratio of the PAH in condensation on soot and thus the more stable the condensation product is. Finally, both the stability analysis of an upper temperature limit for condensation and simulation results of ReaxFF-MD cross-confirm that pyrene stably condensates on a simplified nascent soot (C₅₄₀) and a simulated soot (C₆₅₈H₃₁₉O₉), respectively, at 1500 K, but not at higher temperatures over 1800 K.

Nonparametric Analysis of Nonequilibrium Simulations

We extend the nonparametric framework of reaction coordinate optimization to nonequilibrium ensembles of (short) trajectories. For example, we show how, starting from such an ensemble, one can obtain an equilibrium free-energy profile along the committor, which can be used to determine important properties of the dynamics exactly. A new adaptive sampling approach, the transition-state ensemble enrichment, is suggested, which samples the configuration space by "growing" committor segments toward each other starting from the boundary states. This framework is suggested as a general tool, alternative to the Markov state models, for a rigorous and accurate analysis of simulations of large biomolecular systems, as it has the following attractive properties. It is immune to the curse of dimensionality, does not require system-specific information, can approximate arbitrary reaction coordinates with high accuracy, and has sensitive and rigorous criteria to test optimality and convergence. The approaches are illustrated on a 50-dimensional model system and a realistic protein folding trajectory.

Gaussian accelerated molecular dynamics (GaMD): principles and applications

Gaussian accelerated molecular dynamics (GaMD) is a robust computational method for simultaneous unconstrained enhanced sampling and free energy calculations of biomolecules. It works by adding a harmonic boost potential to smooth biomolecular potential energy surface and reduce energy barriers. GaMD greatly accelerates biomolecular simulations by orders of magnitude. Without the need to set predefined reaction coordinates or collective variables, GaMD provides unconstrained enhanced sampling and is advantageous for simulating complex biological processes. The GaMD boost potential exhibits a Gaussian distribution, thereby allowing for energetic reweighting via cumulant expansion to the second order (i.e., "Gaussian approximation"). This leads to accurate reconstruction of free energy landscapes of biomolecules. Hybrid schemes with other enhanced sampling methods, such as the replica exchange GaMD (rex-GaMD) and replica exchange umbrella sampling GaMD (GaREUS), have also been introduced, further improving sampling and free energy calculations. Recently, new "selective GaMD" algorithms including the ligand GaMD (LiGaMD) and peptide GaMD (Pep-GaMD) enabled microsecond simulations to capture repetitive dissociation and binding of small-molecule ligands and highly flexible peptides. The simulations then allowed highly efficient quantitative characterization of the ligand/peptide binding thermodynamics and kinetics. Taken together, GaMD and its innovative variants are applicable to simulate a wide variety of biomolecular dynamics, including protein folding, conformational changes and allostery, ligand binding, peptide binding, protein-protein/nucleic acid/carbohydrate interactions, and carbohydrate/nucleic acid interactions. In this review, we present principles of the GaMD algorithms and recent applications in biomolecular simulations and drug design.

Binding characteristics of staphylococcal protein A and streptococcal protein G for fragment crystallizable portion of human immunoglobulin G

In the wide array of physiological processes, protein-protein interactions and their binding are the most basal activities for achieving adequate biological metabolism. Among the studies on binding proteins, the examination of interactions between immunoglobulin G (IgG) and natural immunoglobulin-binding ligands, such as staphylococcal protein A (spA) and streptococcal protein G (spG), is essential in the development of pharmaceutical science, biotechnology, and affinity chromatography. The widespread utilization of IgG-spA/spG binding characteristics has allowed researchers to investigate these molecular interactions. However, the detailed binding strength of each ligand and the corresponding binding mechanisms have yet to be fully investigated. In this study, the authors analyzed the binding strengths of IgG-spA and IgG-spG complexes and identified the mechanisms enabling these bindings using molecular dynamics simulation, steered molecular dynamics, and advanced Poisson-Boltzmann Solver simulations. Based on the presented data, the binding strength of the spA ligand was found to significantly exceed that of the spG ligand. To find out which non-covalent interactions or amino acid sites have a dominant role in the tight binding of these ligands, further detailed analyses of electrostatic interactions, hydrophobic bonding, and binding free energies have been performed. In investigating their binding affinity, a relatively independent and different unbinding mechanism was found in each ligand. These distinctly different mechanisms were observed to be highly correlated to the protein secondary and tertiary structures of spA and spG ligands, as explicated from the perspective of hydrogen bonding.

Reconstruction of mechanical unfolding and refolding pathways of proteins with atomic force spectroscopy and computer simulations

Most proteins in proteomes are large, typically consist of more than one domain and are structurally complex. This often makes studying their mechanical unfolding pathways challenging. Proteins composed of tandem repeat domains are a subgroup of multi-domain proteins that, when stretched, display a saw-tooth pattern in their mechanical unfolding force extension profiles due to their repetitive structure. However, the assignment of force peaks to specific repeats undergoing mechanical unraveling is complicated because all repeats are similar and they interact with their neighbors and form a contiguous tertiary structure. Here, we describe in detail a combination of experimental and computational single-molecule force spectroscopy methods that proved useful for examining the mechanical unfolding and refolding pathways of ankyrin repeat proteins. Specifically, we explain and delineate the use of atomic force microscope-based single molecule force spectroscopy (SMFS) to record the mechanical unfolding behavior of ankyrin repeat proteins and capture their unusually strong refolding propensity that is responsible for generating impressive refolding force peaks. We also describe Coarse Grain Steered Molecular Dynamic (CG-SMD) simulations which complement the experimental observations and provide insights in understanding the unfolding and refolding of these proteins. In addition, we advocate the use of novel coiled-coils-based mechanical polypeptide probes which we developed to demonstrate the vectorial character of folding and refolding of these repeat proteins. The combination of AFM-based SMFS on native and CC-equipped proteins with CG-SMD simulations is powerful not only for ankyrin repeat polypeptides, but also for other repeat proteins and more generally to various multidomain, non-repetitive proteins with complex topologies.

Blind Analysis of Molecular Dynamics

We describe a nonparametric approach for accurate determination of the slowest relaxation eigenvectors of molecular dynamics. The approach is blind as it uses no system specific information. In particular, it does not require a functional form with many parameters to closely approximate eigenvectors, e.g., linear combinations of molecular descriptors or a deep neural network, and thus no extensive expertise with the system. We suggest a rigorous and sensitive validation/optimality criterion for an eigenvector. The criterion uses only eigenvector time series and can be used to validate eigenvectors computed by other approaches. The power of the approach is illustrated on long atomistic protein folding trajectories. The determined eigenvectors pass the validation test at a time scale of 0.2 ns, much shorter than alternative approaches.

Antimicrobial Bombinin-like Peptide 3 Selectively Recognizes and Inserts into Bacterial Biomimetic Bilayers in Multiple Steps

Bombinins are a wide family of antimicrobial peptides from Xenopus skin. By sequence clustering, we highlighted at least three families named A, B, and H, which might exert antibacterial activity by different modes of action. In this work, we study bombinin-like peptide 3 (BLP-3) as a nonhemolytic representative of the quite unexplored class A due to its appealing activity toward WHO-priority-list bacteria such as Neisseria, Pseudomonas aeruginosa, and Staphylococcus aureus. A marked preference for cardiolipin and phosphatidylglycerol head groups, typically found in bacteria, is proven with biomimetic membranes studied by liquid and solid NMR and MD simulations. BLP-3 gets structured upon interaction and penetrates deeply into the bilayer in two steps involving a superficial insertion of key side chains and subsequent internalization. All along the pathway, a fundamental role is played by lysine residues in the conserved region 11-19, which act in synergy with other key residues.

Cardiolipin interactions with cytochrome c increase tyrosine nitration yields and site-specificity

The interaction between cytochrome c and cardiolipin is a relevant process in the mitochondrial redox homeostasis, playing roles in the mechanism of electron transfer to cytochrome c oxidase and also modulating cytochrome c conformation, reactivity and function. Peroxynitrite is a widespread nitrating agent formed in mitochondria under oxidative stress conditions, and can result in the formation of tyrosine nitrated cytochrome c. Some of the nitro-cytochrome c species undergo conformational changes at physiological pH and increase its peroxidase activity. In this work we evaluated the influence of cardiolipin on peroxynitrite-mediated cytochrome c nitration yields and site-specificity. Our results show that cardiolipin enhances cytochrome c nitration by peroxynitrite and targets it to heme-adjacent Tyr67. Cytochrome c nitration also modifies the affinity of protein with cardiolipin. Using a combination of experimental techniques and computer modeling, it is concluded that structural modifications in the Tyr67 region are responsible for the observed changes in protein-derived radical and tyrosine nitration levels, distribution of nitrated proteoforms and affinity to cardiolipin. Increased nitration of cytochrome c in presence of cardiolipin within mitochondria and the gain of peroxidatic activity could then impact events such as the onset of apoptosis and other processes related to the disruption of mitochondrial redox homeostasis.

The Interaction of Supramolecular Anticancer Drug Amphiphiles with Phospholipid Membranes

The shape of drug delivery vehicles impacts both the circulation time and the effectiveness of the vehicle. Peptide-based drug amphiphiles (DAs) are promising new candidates as drug delivery vehicles that can self-assemble into shapes such as nanofilament and nanotube (diameter ~ 6-10 nm). The number of conjugated drugs affects the IC50 of these DAs, which is correlated to the effective cellular uptake. Characterizing and optimizing the interaction of these DAs and their assemblies with the cellular membrane is experimentally challenging. Long-time molecular dynamics can determine if the DA molecular structure affects the translocation across and interaction with the cellular membrane. Here, we report long-time atomistic simulation on Anton 2 (up to 25 μs) of these DAs with model cellular membranes. Results indicate that the interaction of these DAs with model cellular membranes is dependent on the number of conjugated drugs. We find that, with increased drug loading, the hydrophobic drug (camptothecin) builds up in the outer hydrophobic core of the membrane, pulling in positively charged peptide groups. Next, we computationally probe the interaction of differing shapes of these model drug delivery vehicles-nanofilament and nanotube-with the same model membranes, finding that the interaction of these nanostructures with the membrane is strongly repulsive. Results suggest that the hydrogen bond density between the nanostructure and the membrane may play a key role in modulating the interaction between the nanostructure and the membrane. Taken together, these results offer important insights for the rational design of peptide-based drug delivery vehicles.

Molecular Basis of the Anticancer and Antibacterial Properties of CecropinXJ Peptide: An In Silico Study

Esophageal cancer is an aggressive lethal malignancy causing thousands of deaths every year. While current treatments have poor outcomes, cecropinXJ (CXJ) is one of the very few peptides with demonstrated in vivo activity. The great interest in CXJ stems from its low toxicity and additional activity against most ESKAPE bacteria and fungi. Here, we present the first study of its mechanism of action based on molecular dynamics (MD) simulations and sequence-property alignment. Although unstructured in solution, predictions highlight the presence of two helices separated by a flexible hinge containing P24 and stabilized by the interaction of W2 with target biomembranes: an amphipathic helix-I and a poorly structured helix-II. Both MD and sequence-property alignment point to the important role of helix I in both the activity and the interaction with biomembranes. MD reveals that CXJ interacts mainly with phosphatidylserine (PS) but also with phosphatidylethanolamine (PE) headgroups, both found in the outer leaflet of cancer cells, while salt bridges with phosphate moieties are prevalent in bacterial biomimetic membranes composed of PE, phosphatidylglycerol (PG) and cardiolipin (CL). The antibacterial activity of CXJ might also explain its interaction with mitochondria, whose phospholipid composition recalls that of bacteria and its capability to induce apoptosis in cancer cells.

Antimicrobial Peptide K11 Selectively Recognizes Bacterial Biomimetic Membranes and Acts by Twisting Their Bilayers

K11 is a synthetic peptide originating from the introduction of a lysine residue in position 11 within the sequence of a rationally designed antibacterial scaffold. Despite its remarkable antibacterial properties towards many ESKAPE bacteria and its optimal therapeutic index (320), a detailed description of its mechanism of action is missing. As most antimicrobial peptides act by destabilizing the membranes of the target organisms, we investigated the interaction of K11 with biomimetic membranes of various phospholipid compositions by liquid and solid-state NMR. Our data show that K11 can selectively destabilize bacterial biomimetic membranes and torque the surface of their bilayers. The same is observed for membranes containing other negatively charged phospholipids which might suggest additional biological activities. Molecular dynamic simulations reveal that K11 can penetrate the membrane in four steps: after binding to phosphate groups by means of the lysine residue at the N-terminus (anchoring), three couples of lysine residues act subsequently to exert a torque in the membrane (twisting) which allows the insertion of aromatic side chains at both termini (insertion) eventually leading to the flip of the amphipathic helix inside the bilayer core (helix flip and internalization).

Investigation on penetration of saffron components through lipid bilayer bound to spike protein of SARS-CoV-2 using steered molecular dynamics simulation

A coronavirus identified as COVID-19 is the reason for an infection outbreak which is started in December 2019. NO completely effective drugs and treatments are not recognized for this virus. Recently, saffron and its compounds were used to treat different viral diseases. Saffron extract and its major ingredients have shown antiviral effects. In this study, the steered molecular dynamics simulation was used for investigating the effect of four main components of saffron that include: crocin, crocetin, safranal, and picrocrocin as candidate for drug molecules, on COVID-19. The binding energies between drug molecules and spike protein and the main protease of the virus were evaluated. The obtained results based on Lennard-Jones and electrostatic potentials demonstrated that crocetin has a high affinity towards spike protein and also the main protease of the virus. Also, the quantum mechanics calculations elucidated that the crocetin could overcome energy barrier of lipid bilayer with strong dipole moment and polarizability. The pharmacokinetic and ADMET properties proved that crocetin could be a suitable drug candidate. So, crocetin could be a promising drug for treatment of COVID-19.

Structural and Computational Insights into a Blebbistatin-Bound Myosin•ADP Complex with Characteristics of an ADP-Release Conformation along the Two-Step Myosin Power Stoke

The motor protein myosin drives a wide range of cellular and muscular functions by generating directed movement and force, fueled through adenosine triphosphate (ATP) hydrolysis. Release of the hydrolysis product adenosine diphosphate (ADP) is a fundamental and regulatory process during force production. However, details about the molecular mechanism accompanying ADP release are scarce due to the lack of representative structures. Here we solved a novel blebbistatin-bound myosin conformation with critical structural elements in positions between the myosin pre-power stroke and rigor states. ADP in this structure is repositioned towards the surface by the phosphate-sensing P-loop, and stabilized in a partially unbound conformation via a salt-bridge between Arg131 and Glu187. A 5 Å rotation separates the mechanical converter in this conformation from the rigor position. The crystallized myosin structure thus resembles a conformation towards the end of the two-step power stroke, associated with ADP release. Computationally reconstructing ADP release from myosin by means of molecular dynamics simulations further supported the existence of an equivalent conformation along the power stroke that shows the same major characteristics in the myosin motor domain as the resolved blebbistatin-bound myosin-II·ADP crystal structure, and identified a communication hub centered on Arg232 that mediates chemomechanical energy transduction.

Efficient Conformational Sampling of Collective Motions of Proteins with Principal Component Analysis-Based Parallel Cascade Selection Molecular Dynamics

Molecular dynamics (MD) simulation has become a powerful tool because it provides a time series of protein dynamics at high temporal-spatial resolution. However, the accessible timescales of MD simulation are shorter than those of the biologically rare events. Generally, long-time MD simulations over microseconds are required to detect the rare events. Therefore, it is desirable to develop rare-event-sampling methods. For a rare-event-sampling method, we have developed parallel cascade selection MD (PaCS-MD). PaCS-MD generates transition pathways from a given source structure to a target structure by repeating short-time MD simulations. The key point in PaCS-MD is how to select reasonable candidates (protein configurations) with high potentials to make transitions toward the target structure. In the present study, based on principal component analysis (PCA), we propose PCA-based PaCS-MD to detect rare events of collective motions of a given protein. Here, the PCA-based PaCS-MD is composed of the following two steps. At first, as a preliminary run, PCA is performed using an MD trajectory from the target structure to define a principal coordinate (PC) subspace for describing the collective motions of interest. PCA provides principal modes as eigenvectors to project a protein configuration onto the PC subspace. Then, as a production run, all the snapshots of short-time MD simulations are ranked by inner products (IPs), where an IP is defined between a snapshot and the target structure. Then, snapshots with higher values of the IP are selected as reasonable candidates, and short-time MD simulations are independently restarted from them. By referring to the values of the IP, the PCA-based PaCS-MD repeats the short-time MD simulations from the reasonable candidates that are highly correlated with the target structure. As a demonstration, we applied the PCA-based PaCS-MD to adenylate kinase and detected its large-amplitude (open-closed) transition with a nanosecond-order computational cost.

Unveiling the activation dynamics of a fold-switch bacterial glycosyltransferase by 19F NMR

Fold-switch pathways remodel the secondary structure topology of proteins in response to the cellular environment. It is a major challenge to understand the dynamics of these folding processes. Here, we conducted an in-depth analysis of the α-helix–to–β-strand and β-strand–to–α-helix transitions and domain motions displayed by the essential mannosyltransferase PimA from mycobacteria. Using ¹⁹F NMR, we identified four functionally relevant states of PimA that coexist in dynamic equilibria on millisecond-to-second timescales in solution. We discovered that fold-switching is a slow process, on the order of seconds, whereas domain motions occur simultaneously but are substantially faster, on the order of milliseconds. Strikingly, the addition of substrate accelerated the fold-switching dynamics of PimA. We propose a model in which the fold-switching dynamics constitute a mechanism for PimA activation.

Interaction of Camptothecin with Model Cellular Membranes

Accurate and efficient prediction of drug partitioning in model membranes is of significant interest to the pharmaceutical industry. Herein, we utilize advanced sampling methods, specifically, the adaptive biasing force methodology to calculate the potential of mean force for a model hydrophobic anticancer drug, camptothecin (CPT), across three model interfaces. We consider an octanol bilayer, a thick octanol/water interface, and a model 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC)/water interface. We characterize the enthalpic and entropic contributions of the drug to the potential of mean force. We show that the rotational entropy of the drug is inversely related to the probability of hydrogen bond formation of the drug with the POPC membrane. In addition, in long-time microsecond simulations of a high concentration of CPT above the POPC membrane, we show that strong drug-drug aromatic interactions shift the spatial orientation of the drug with the membrane. Stacks of hydrophobic drugs form, allowing penetration of the drug just under the POPC head groups. These results imply that inhomogeneous membrane models need to take into account the effect of drug aggregation on the membrane environment.

Microscopic Characterization of GRP1 PH Domain Interaction with Anionic Membranes

The pleckstrin homology (PH) domain of general receptor for phosphoionositides 1 (GRP1-PHD) binds specifically to phosphatidylinositol (3,4,5)-triphosphate (PIP3 ), and acts as a second messenger. Using an extensive array of molecular dynamics (MD) simulations employing highly mobile membrane mimetic (HMMM) model as well as complementary full membrane simulations, we capture differentiable binding and dynamics of GRP1-PHD in the presence of membranes containing PC, PS, and PIP3 lipids in varying compositions. While GRP1-PHD forms only transient interactions with pure PC membranes, incorporation of anionic lipids resulted in stable membrane-bound configurations. We report the first observation of two distinct PIP3 binding modes on GRP1-PHD, involving PIP3 interactions at a "canonical" and at an "alternate" site, suggesting the possibility of simultaneous binding of multiple anionic lipids. The full membrane simulations confirmed the stability of the membrane bound pose of GRP1-PHD as captured from our HMMM membrane binding simulations. By performing additional steered membrane unbinding simulations and calculating nonequilibrium work associated with the process, as well as metadynamics simulations, on the protein bound to full membranes, allowing for more quantitative examination of the binding strength of the GRP1-PHD to the membrane, we demonstrate that along with the bound PIP3 , surrounding anionic PS lipids increase the energetic cost of unbinding of GRP1-PHD from the canonical mode, causing them to dissociate more slowly than the alternate mode. Our results demonstrate that concurrent binding of multiple anionic lipids by GRP1-PHD contributes to its membrane affinity, which in turn control its signaling activity. © 2019 Wiley Periodicals, Inc.