Parallel Generalized Born Implicit Solvent Calculations with NAMD

GOLEM: Automated and Robust Cryo-EM-Guided Ligand Docking with Explicit Water Molecules

A detailed understanding of ligand-protein interaction is essential for developing rational drug-design strategies. In recent years, technological advances in cryo-electron microscopy (cryo-EM) brought a new era to the structural determination of biological macromolecules and assemblies at high resolution, marking cryo-EM as a promising tool for studying ligand-protein interactions. However, even in high-resolution cryo-EM results, the densities for the bound small-molecule ligands are often of lower quality due to their relatively dynamic and flexible nature, frustrating their accurate coordinate assignment. To address the challenge of ligand modeling in cryo-EM maps, here we report the development of GOLEM (Genetic Optimization of Ligands in Experimental Maps), an automated and robust ligand docking method that predicts a ligand's pose and conformation in cryo-EM maps. GOLEM employs a Lamarckian genetic algorithm to perform a hybrid global/local search for exploring the ligand's conformational, orientational, and positional space. As an important feature, GOLEM explicitly considers water molecules and places them at optimal positions and orientations. GOLEM takes into account both molecular energetics and the correlation with the cryo-EM maps in its scoring function to optimally place the ligand. We have validated GOLEM against multiple cryo-EM structures with a wide range of map resolutions and ligand types, returning ligand poses in excellent agreement with the densities. As a VMD plugin, GOLEM is free of charge and accessible to the community. With these features, GOLEM will provide a valuable tool for ligand modeling in cryo-EM efforts toward drug discovery.

Multiple Functional Protein-Protein Interaction Interfaces Allosterically Regulate ATP-Binding in Cyclin-Dependent Kinase-1

The ATP-dependent phosphorylation activity of cyclin-dependent kinase 1 (CDK1), an essential enzyme for cell cycle progression, is regulated by interactions with Cyclin-B, substrate, and Cks proteins. We have recently shown that active site acetylation in CDK1 abrogated binding to Cyclin-B which posits an intriguing long-range communication between the catalytic site and the protein-protein interaction (PPI) interface. Now, we demonstrate a general allosteric link between the CDK1 active site and all three of its PPI interfaces through atomistic molecular dynamics (MD) simulations. Specifically, we examined ATP binding free energies to CDK1 in native nonacetylated (K33wt) and acetylated (K33Ac) forms as well as the acetyl-mimic K33Q and the acetyl-null K33R mutant forms, which are accessible in vitro. In agreement with experiments, ATP binding is stronger in K33wt relative to the other three perturbed states. Free energy decomposition reveals, in addition to expected local changes, significant and selective nonlocal entropic responses to ATP binding/perturbation of K33 from theαC $$ \alpha C $$ -helix, activation loop (A-loop), andαG $$ \alpha G $$ -α $$ \alpha $$ H segments in CDK1 which interface with Cyclin-B, substrate, and Cks proteins, respectively. Statistical analysis reveals that while entropic responses of protein segments to active site perturbations are on average correlated with their dynamical changes, such correlations are lost in about 9%-48% of the dataset depending on the segment. Besides proving the bi-directional communication between the active site and the CDK1:Cyclin-B interface, our study uncovers a hitherto unknown mode of ATP binding regulation by multiple PPI interfaces in CDK1.

MDFF_NM: Improved Molecular Dynamics Flexible Fitting into Cryo-EM Density Maps with a Multireplica Normal Mode-Based Search

Molecular Dynamics Flexible Fitting (MDFF) is a widely used tool to refine high-resolution structures into cryo-EM density maps. Despite many successful applications, MDFF is still limited by its high computational cost, overfitting, accuracy, and performance issues due to entrapment within wrong local minima. Modern ensemble-based MDFF tools have generated promising results in the past decade. In line with these studies, we present MDFF_NM, a stochastic hybrid flexible fitting algorithm combining Normal Mode Analysis (NMA) and simulation-based flexible fitting. Initial tests reveal that, besides accelerating the fitting process, MDFF_NM increases the diversity of fitting routes leading to the target, uncovering ensembles of conformations in closer agreement with experimental data. The potential integration of MDFF_NM with other existing methods and integrative modeling pipelines is also discussed.

Interfacial Interactions between Nanoplastics and Biological Systems: toward an Atomic and Molecular Understanding of Plastics-Driven Biological Dyshomeostasis

Micro- and nano-plastics (NPs) are found in human milk, blood, tissues, and organs and associate with aberrant health outcomes including inflammation, genotoxicity, developmental disorders, onset of chronic diseases, and autoimmune disorders. Yet, interfacial interactions between plastics and biomolecular systems remain underexplored. Here, we have examined experimentally, in vitro, in vivo, and by computation, the impact of polystyrene (PS) NPs on a host of biomolecular systems and assemblies. Our results reveal that PS NPs essentially abolished the helix-content of the milk protein β-lactoglobulin (BLG) in a dose-dependent manner. Helix loss is corelated with the near stoichiometric formation of β-sheet elements in the protein. Structural alterations in BLG are also likely responsible for the nanoparticle-dependent attrition in binding affinity and weaker on-rate constant of retinol, its physiological ligand (compromising its nutritional role). PS NP-driven helix-to-sheet conversion was also observed in the amyloid-forming trajectory of hen egg-white lysozyme (accelerated fibril formation and reduced helical content in fibrils). Caenorhabditis elegans exposed to PS NPs exhibited a decrease in the fluorescence of green fluorescent protein-tagged dopaminergic neurons and locomotory deficits (akin to the neurotoxin paraquat exposure). Finally, in silico analyses revealed that the most favorable PS/BLG docking score and binding energies corresponded to a pose near the hydrophobic ligand binding pocket (calyx) of the protein where the NP fragment was found to make nonpolar contacts with side-chain residues via the hydrophobic effect and van der Waals forces, compromising side chain/retinol contacts. Binding energetics indicate that PS/BLG interactions destabilize the binding of retinol to the protein and can potentially displace retinol from the calyx region of BLG, thereby impairing its biological function. Collectively, the experimental and high-resolution in silico data provide new insights into the mechanism(s) by which PS NPs corrupt the bimolecular structure and function, induce amyloidosis and onset neuronal injury, and drive aberrant physiological and behavioral outcomes.

Type 2M/2A von Willebrand disease: a shared phenotype between type 2M and 2A

ABSTRACT

Four variants have been continuously subjected to debate and received different von Willebrand disease (VWD) classifications: p.R1315L, p.R1315C, p.R1374H, and p.R1374C. We chose to comprehensively investigate these variants with full set of VWD tests, protein-modeling predictions and applying structural biology. Patients with p.R1315L, p.R1315C, p.R1374H, and p.R1374C were included. A group with type 2A and 2M was included to better understand similarities and differences. Patients were investigated for phenotypic assays and underlying disease mechanisms. We applied deep protein modeling predictions and structural biology to elucidate the causative effects of variants. Forty-three patients with these variants and 70 with 2A (n = 35) or 2M (n = 35) were studied. Patients with p.R1315L, p.R1374H, or p.R1374C showed a common phenotype between 2M and 2A using von Willebrand factor (VWF):GPIbR/VWF:Ag and VWF:CB/VWF:Ag ratios and VWF multimeric profile, whereas p.R1315C represented a type 2M phenotype. There was an overall reduced VWF synthesis or secretion in 2M and cases with p.R1315L, p.R1374H, and p.R1374C, but not in 2A. Reduced VWF survival was observed in most 2A (77%), 2M (80%), and all 40 cases with p.R1315L, p.R1374H, and p.R1374C. These were the only variants that fall at the interface between the A1-A2 domains. p.R1315L/C mutants induce more compactness and internal mobility, whereas p.R1374H/C display a more extended overall geometry. We propose a new classification of type 2M/2A for p.R1315L, p.R1374H, and p.R1374C because they share a common phenotype with 2M and 2A. Our structural analysis shows the unique location of these variants on the A1-A2 domains and their distinctive effect on VWF.

Molecular Dynamics Simulations on Spike Protein Mutants Binding with Human β Defensin Type 2

Human β defensin type 2 (hBD-2), a cationic cysteine-rich peptide secreted from the human innate immune system, can bind Spike-RBD at the same site as receptor ACE2, thus blocking viral entry into ACE2-expressing cells. In order to find out the impact of CoV-2 mutations on hBD-2's antiviral activity, it is important to investigate the binding and interaction of hBD-2 with RBD mutants. All-atom molecular dynamics simulations were conducted on typical RBD mutants, including N501Y, E484K, P479S, T478I, S477N, N439K, K417N, and N501Y-E484K-K417N, binding with hBD-2. Starting from the stable binding structure of hBD-2 and wt-RBD and ClusPro and HADDOCK docking-predicted initial structures, the RBD variants bound with hBD-2 simulations were set up, and NAMD simulations were conducted. Based on the structure and dynamics analysis, it was found that most RBD variants can still form a similar number of hydrogen bonds with hBD-2, in addition to having a similar-sized buried surface area (BSA) and a similar binding interface to the RBD wildtype. However, the RBD triple mutant formed a less stable binding structure with hBD-2 than other variants. Additionally, the free energy perturbation (FEP) method was applied to calculate the contribution of key mutant residues to the binding and the free energy change caused by the mutations. The result shows that N439K, K417N, and the trimutation increase the binding free energy of RBD with hBD-2; thus, RBD should bind less stably with hBD-2. E484K decreases the binding free energy, thus it should bind more stably with hBD-2, while N501Y, S477N, T478I, and P479S almost do not change the binding free energy with hBD-2. The MM-GBSA method predicted the binding interaction energy which shows that the trimutant should be able to escape the binding with hBD-2 but N501Y should not. The result can provide insight into understanding the functional mechanism of hBD-2 combating SARS-CoV-2 mutants.

Uncovering the Kinetic Characteristics and Degradation Preference of PROTAC Systems with Advanced Theoretical Analyses

Proteolysis-targeting chimeras (PROTACs), which can selectively induce the degradation of target proteins, represent an attractive technology in drug discovery. A large number of PROTACs have been reported, but due to the complicated structural and kinetic characteristics of the target-PROTAC-E3 ligase ternary interaction process, the rational design of PROTACs is still quite challenging. Here, we characterized and analyzed the kinetic mechanism of MZ1, a PROTAC that targets the bromodomain (BD) of the bromodomain and extra terminal (BET) protein (Brd2, Brd3, or Brd4) and von Hippel-Lindau E3 ligase (VHL), from the kinetic and thermodynamic perspectives of view by using enhanced sampling simulations and free energy calculations. The simulations yielded satisfactory predictions on the relative residence time and standard binding free energy (r_p > 0.9) for MZ1 in different Brd^BD-MZ1-VHL ternary complexes. Interestingly, the simulation of the PROTAC ternary complex disintegration illustrates that MZ1 tends to remain on the surface of VHL with the BD proteins dissociating alone without a specific dissociation direction, indicating that the PROTAC prefers more to bind with E3 ligase at the first step in the formation of the target-PROTAC-E3 ligase ternary complex. Further exploration of the degradation difference of MZ1 in different Brd systems shows that the PROTAC with higher degradation efficiency tends to leave more lysine exposed on the target protein, which is guaranteed by the stability (binding affinity) and durability (residence time) of the target-PROTAC-E3 ligase ternary complex. It is quite possible that the underlying binding characteristics of the Brd^BD-MZ1-VHL systems revealed by this study may be shared by different PROTAC systems as a general rule, which may accelerate rational PROTAC design with higher degradation efficiency.

Structural basis of CMKLR1 signaling induced by chemerin9

Chemokine-like receptor 1 (CMKLR1), also known as chemerin receptor 23 (ChemR23) or chemerin receptor 1, is a chemoattractant G protein-coupled receptor (GPCR) that responds to the adipokine chemerin and is highly expressed in innate immune cells, including macrophages and neutrophils. The signaling pathways of CMKLR1 can lead to both pro- and anti-inflammatory effects depending on the ligands and physiological contexts. To understand the molecular mechanisms of CMKLR1 signaling, we determined a high-resolution cryo-electron microscopy (cryo-EM) structure of the CMKLR1-Gi signaling complex with chemerin9, a nanopeptide agonist derived from chemerin, which induced complex phenotypic changes of macrophages in our assays. The cryo-EM structure, together with molecular dynamics simulations and mutagenesis studies, revealed the molecular basis of CMKLR1 signaling by elucidating the interactions at the ligand-binding pocket and the agonist-induced conformational changes. Our results are expected to facilitate the development of small molecule CMKLR1 agonists that mimic the action of chemerin9 to promote the resolution of inflammation.

Unidirectional rotation of micromotors on water powered by pH-controlled disassembly of chiral molecular crystals

Biological and synthetic molecular motors, fueled by various physical and chemical means, can perform asymmetric linear and rotary motions that are inherently related to their asymmetric shapes. Here, we describe silver-organic micro-complexes of random shapes that exhibit macroscopic unidirectional rotation on water surface through the asymmetric release of cinchonine or cinchonidine chiral molecules from their crystallites asymmetrically adsorbed on the complex surfaces. Computational modeling indicates that the motor rotation is driven by a pH-controlled asymmetric jet-like Coulombic ejection of chiral molecules upon their protonation in water. The motor is capable of towing very large cargo, and its rotation can be accelerated by adding reducing agents to the water.

Molecular Insights into the Improved Bioactivity of Interferon Conjugates Attached to a Helical Polyglutamate

Attaching polymers, especially polyethylene glycol (PEG), to protein drugs has emerged as a successful strategy to prolong circulation time in the bloodstream. The hypothesis is that the flexible chain wobbles on the protein's surface, thus resisting potential nonspecific adsorption. Such a theoretical framework may be challenged when a helical polyglutamate is used to conjugate with target proteins. In this study, we investigated the structure-activity relationships of polyglutamate-interferon conjugates P(EG₃Glu)-IFN using molecular simulations. Our results show that the local crowding effect induced by oligoethylene glycols (i.e., EG₃) is the primary driving force for helix formation in P(EG₃Glu), and its helicity can be effectively increased by reducing the free volume of the two termini. Furthermore, it was found that the steric hindrance induced by IFN is not conductive to the helicity of P(EG₃Glu) but contributes to its dominant orientation relative to interferon. The orientation of IFN relative to the helical P(EG₃Glu) can help to protect the protein drug from neutralizing antibodies while maintaining its bioactivity. These findings suggest that the helical structure and its orientation are critical factors to consider when updating the theoretical framework for protein-polymer conjugates.

Scalable Inhibitors of the Nsp3-Nsp4 Coupling in SARS-CoV-2

The human Betacoronavirus SARS-CoV-2 is a novel pathogen claiming millions of lives and causing a global pandemic that has disrupted international healthcare systems, economies, and communities. The virus is fast mutating and presenting more infectious but less lethal versions. Currently, some small-molecule therapeutics have received FDA emergency use authorization for the treatment of COVID-19, including Lagevrio (molnupiravir) and Paxlovid (nirmaltrevir/ritonavir), which target the RNA-dependent RNA polymerase and the 3CLpro main protease, respectively. Proteins downstream in the viral replication process, specifically the nonstructural proteins (Nsps1-16), are potential drug targets due to their crucial functions. Of these Nsps, Nsp4 is a particularly promising drug target due to its involvement in the SARS-CoV viral replication and double-membrane vesicle formation (mediated via interaction with Nsp3). Given the degree of sequence conservation of these two Nsps across the Betacoronavirus clade, their protein-protein interactions and functions are likely to be conserved as well in SARS-CoV-2. Through AlphaFold2 and its recent advancements, protein structures were generated of Nsp3 and 4 lumenal loops of interest. Then, using a combination of molecular docking suites and an existing library of lead-like compounds, we virtually screened 7 million ligands to identify five putative ligand inhibitors of Nsp4, which could present an alternative pharmaceutical approach against SARS-CoV-2. These ligands exhibit promising lead-like properties (ideal molecular weight and log P profiles), maintain fixed-Nsp4-ligand complexes in molecular dynamics (MD) simulations, and tightly associate with Nsp4 via hydrophobic interactions. Additionally, alternative peptide inhibitors based on Nsp3 were designed and shown in MD simulations to provide a highly stable binding to the Nsp4 protein. Finally, these therapeutics were attached to dendrimer structures to promote their multivalent binding with Nsp4, especially its large flexible luminal loop (Nsp4LLL). The therapeutics tested in this study represent many different approaches for targeting large flexible protein structures, especially those localized to the ER. This study is the first work targeting the membrane rearrangement system of viruses and will serve as a potential avenue for treating viruses with similar replicative function.

Identification of a novel adiponectin receptor and opioid receptor dual acting agonist as a potential treatment for diabetic neuropathy

Diabetic neuropathy (DN) is a long-term complication of diabetes mellitus, affecting different periphery nerve systems including sensory and motor neurons. Hyperglycemia is the major cause of DN with symptoms such as weakness of balance or coordination, insensitivity to sensation, weakness of the muscles as well as numbness and pain in limbs Analgesic drug such as opioids can be effective to relief neuropathy pain but there is no effective treatment. Adiponectin is an anti-diabetic adipokine, which possesses insulin-sensitizing and neuroprotective effects. In this project, we aim to identify an agent which is dual acting to opioid and adiponectin receptors. Within a virtual screening repositioning campaign, a large collection of compounds with different structures comprehensive of adipoRon-like piperidine derivatives was screened by docking. Recently developed opioid receptor benzomorphanic agonists finally emerged as good ligands to adiponectin receptors showing some 2D and 3D structural similarities with AdipoRon. Particularly, we have identified (+)-MML1017, which has high affinity to the same binding domain of AdipoR1 and AdipoR2 as AdipoRon. Our western blot results indicate (+)-MML1017 activates AMPK phosphorylation through both adipoR1 and adipoR2 in neuronal cell line. Moreover, pretreatment of (+)-MML1017 can improve the cell viability with motor neurons under hyperglycermic conditions. The (+)-MML1017 also activates μ-opioid receptor cells in a concentration-dependent manner. Our study identified a novel compound having dual activity on opioid receptors and adiponectin receptors that may have analgesic effects and neuroprotective effects to treat diabetic neuropathy.

Dimerization of the Alzheimer's disease pathogenic receptor SORLA regulates its association with retromer

SORL1, the gene encoding the large multidomain SORLA protein, has emerged as only the fourth gene that when mutated can by itself cause Alzheimer's disease (AD), and as a gene reliably linked to both the early- and late-onset forms of the disease. SORLA is known to interact with the endosomal trafficking regulatory complex called retromer in regulating the recycling of endosomal cargo, including the amyloid precursor protein (APP) and the glutamate receptor GluA1. Nevertheless, SORLA's precise structural-functional relationship in endosomal recycling tubules remains unknown. Here, we address these outstanding questions by relying on crystallographic and artificial-intelligence evidence to generate a structural model for how SORLA folds and fits into retromer-positive endosomal tubules, where it is found to dimerize via both SORLA's fibronectin-type-III (3Fn)- and VPS10p-domains. Moreover, we identify a SORLA fragment comprising the 3Fn-, transmembrane, and cytoplasmic domains that has the capacity to form a dimer, and to enhance retromer-dependent recycling of APP by decreasing its amyloidogenic processing. Collectively, these observations generate a model for how SORLA dimer (and possibly polymer) formation can function in stabilizing and enhancing retromer function at endosome tubules. These findings can inform investigation of the many AD-associated SORL1 variants for evidence of pathogenicity and can guide discovery of novel drugs for the disease.

Dendrimer-Peptide Conjugates for Effective Blockade of the Interactions between SARS-CoV-2 Spike Protein and Human ACE2 Receptor

The coronavirus disease 2019 (COVID-19) pandemic has threatened the stability of global healthcare, which is becoming an endemic issue. Despite the development of various treatment strategies to fight COVID-19, the currently available treatment options have shown varied efficacy. Herein, we have developed an avidity-based SARS-CoV-2 antagonist using dendrimer-peptide conjugates (DPCs) for effective COVID-19 treatment. Two different peptide fragments obtained from angiotensin-converting enzyme 2 (ACE2) were integrated into a single sequence, followed by the conjugation to poly(amidoamine) (PAMAM) dendrimers. We hypothesized that the strong multivalent binding avidity endowed by dendrimers would help peptides effectively block the interaction between SARS-CoV-2 and ACE2, and this antagonist effect would be dependent upon the generation (size) of the dendrimers. To assess this, binding kinetics of the DPCs prepared from generation 4 (G4) and G7 PAMAM dendrimers to spike protein of SARS-CoV-2 were quantitatively measured using surface plasmon resonance. The larger dendrimer-based DPCs exhibited significantly enhanced binding strength by 3 orders of magnitude compared to the free peptides, whereas the smaller one showed a 12.8-fold increase only. An in vitro assay using SARS-CoV-2-mimicking microbeads also showed the improved SARS-CoV-2 blockade efficiency of the G7-peptide conjugates compared to G4. In addition, the interaction between the DPCs and SARS-CoV-2 was analyzed using molecular dynamics (MD) simulation, providing an insight into how the dendrimer-mediated multivalent binding effect can enhance the SARS-CoV-2 blockade. Our findings demonstrate that the DPCs having strong binding to SARS-CoV-2 effectively block the interaction between ACE2 and SARS-CoV-2, providing a potential as a high-affinity drug delivery system to direct anti-COVID payloads to the virus.

Sequence Control of the Self-Assembly of Elastin-Like Polypeptides into Hydrogels with Bespoke Viscoelastic and Structural Properties

The biofabrication of structural proteins with controllable properties via amino acid sequence design is interesting for biomedicine and biotechnology, yet a complete framework that connects amino acid sequence to material properties is unavailable, despite great progress to establish design rules for synthesizing peptides and proteins with specific conformations (e.g., unfolded, helical, β-sheets, or β-turns) and intermolecular interactions (e.g., amphipathic peptides or hydrophobic domains). Molecular dynamics (MD) simulations can help in developing such a framework, but the lack of a standardized way of interpreting the outcome of these simulations hinders their predictive value for the design of de novo structural proteins. To address this, we developed a model that unambiguously classifies a library of de novo elastin-like polypeptides (ELPs) with varying numbers and locations of hydrophobic/hydrophilic and physical/chemical-cross-linking blocks according to their thermoresponsiveness at physiological temperature. Our approach does not require long simulation times or advanced sampling methods. Instead, we apply (un)supervised data analysis methods to a data set of molecular properties from relatively short MD simulations (150 ns). We also experimentally investigate hydrogels of those ELPs from the library predicted to be thermoresponsive, revealing several handles to tune their mechanical and structural properties: chain hydrophilicity/hydrophobicity or block distribution control the viscoelasticity and thermoresponsiveness, whereas ELP concentration defines the network permeability. Our findings provide an avenue to accelerate the design of de novo ELPs with bespoke phase behavior and material properties.

Computer-Assisted Design and Characterization of RNA Nanostructures

Molecular dynamics (MD) simulations can aid in the design and characterization of RNA nanomaterials, providing details about structural and dynamical properties as a function of sequence and environment. Here, we describe how to perform explicit and implicit solvent all-atom MD simulations for RNA nanoring systems.

Effect of pH on stability of dimer structure of the main protease of coronavirus-2

The viral main protease (M^pro) from a novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a key enzyme essential for viral replication and has become an attractive target for antiviral drug development. The M^pro forms a functional dimer and exhibits a pH-dependent enzyme activity and dimerization. Here, we report a molecular dynamics (MD) investigation to gain insights into the structural stability of the enzyme dimer at neutral and acidic pH. Our data shows larger changes in structure of the protein with the acidic pH than that with the neutral pH. Structural analysis of MD trajectories reveals a substantial increase in intersubunit separation, the loss of domain contacts, binding free energy and interaction energy of the dimer which implies the protein instability and tendency of dimer dissociation at acidic pH. The loss in the interaction energy is mainly driven by electrostatic interactions. We have identified the intersubunit hydrogen-bonding residues involved in the decreased dimer stability. These findings may be helpful for rational drug design and target evaluation against COVID-19.

Design of Peptides that Fold and Self-Assemble on Graphite

The graphite-water interface provides a unique environment for polypeptides that generally favors ordered structures more than in solution. Therefore, systems consisting of designed peptides and graphitic carbon might serve as a convenient medium for controlled self-assembly of functional materials. Here, we computationally designed cyclic peptides that spontaneously fold into a β-sheet-like conformation at the graphite-water interface and self-assemble, and we subsequently observed evidence of such assembly by atomic force microscopy. Using a novel protocol, we screened nearly 2000 sequences, optimizing for formation of a unique folded conformation while discouraging unfolded or misfolded conformations. A head-to-tail cyclic peptide with the sequence GTGSGTGGPGGGCGTGTGSGPG showed the greatest apparent propensity to fold spontaneously, and this optimized sequence was selected for larger scale molecular dynamics simulations, rigorous free-energy calculations, and experimental validation. In simulations ranging from hundreds of nanoseconds to a few microseconds, we observed spontaneous folding of this peptide at the graphite-water interface under many different conditions, including multiple temperatures (295 and 370 K), with different initial orientations relative to the graphite surface, and using different molecular dynamics force fields (CHARMM and Amber). The thermodynamic stability of the folded conformation on graphite over a range of temperatures was verified by replica-exchange simulations and free-energy calculations. On the other hand, in free solution, the folded conformation was found to be unstable, unfolding in tens of picoseconds. Intermolecular hydrogen bonds promoted self-assembly of the folded peptides into linear arrangements where the peptide backbone exhibited a tendency to align along one of the six zigzag directions of the graphite basal plane. For the optimized peptide, atomic force microscopy revealed growth of single-molecule-thick linear patterns of 6-fold symmetry, consistent with the simulations, while no such patterns were observed for a control peptide with the same amino acid composition but a scrambled sequence.

Cellulose Hollow Annular Nanoparticles Prepared from High-Intensity Ultrasonic Treatment

Cellulose nanomaterials, such as cellulose nanocrystals (CNCs), have received enormous attention in various material research fields due to their unique properties and green/sustainable nature, among other qualities. Herein, we report hollow-type annular cellulose nanocrystals (HTA-CNCs), which are generated by following a high-intensity ultrasonic treatment. The advanced aberration-corrected transmission electron microscopy results reveal that HTA-CNCs exhibit ring structures with a typical diameter of 10.0-30.0 nm, a width of 3.0-4.0 nm, and a thickness of 2.0-5.0 nm, similar to those of elementary crystallites. The X-ray diffraction measurements show that the as-prepared HTA-CNCs maintain the cellulose I structure. The changes in structure and hydrogen-bonding characteristics of HTA-CNCs are further determined based on the FT-IR results after deconvolution fitting, showing that three types of hydrogen bonds decrease and the content of free OH increases in HTA-CNCs compared with those in the original CNCs. Furthermore, molecular dynamics simulation is carried out to support the experimental study. The formation of HTA-CNCs might be attributed to the structural change and entropy increase. The hollow-type annular CNCs may have broad value-added applications as cellulose nanomaterials in different fields.

Global Fold Switching of the RafH Protein: Diverse Structures with a Conserved Pathway

It is generally believed that a protein's sequence uniquely determines its structure, the basis for a protein to perform biological functions. However, as a representative metamorphic protein, RfaH can be encoded by a single amino acid sequence into two distinct native state structures. Its C-terminal domain (CTD) either takes an all-α-helical configuration to pack tightly with its N-terminal domain (NTD), or the CTD disassociates from the NTD, transforms into an all-β-barrel fold, and further attaches to the ribosome, leaving the NTD exposed to bind RNA polymerases. Therefore, the RfaH protein couples transcription and translation processes. Although previous studies have provided a preliminary understanding of its function, the full course of the conformational change of RfaH-CTD at the atomic level is elusive. We used teDA2, a feature space-based enhanced sampling protocol, to explore the transformation of RfaH-CTD. We found that it undergoes a large-scale structural rearrangement, with characteristic spectra as the fingerprint, and a global unfolding transition with a tighter and energetically moderate molten globule-like nucleus formed in between. The formation of this nucleus limits the possible intermediate conformations, facilitates the formation of secondary and tertiary structures, and thus ensures the efficiency of transformation. The key features along the transition path disclosed from this work are likely associated with the evolution of RfaH, such that encoding a single sequence into multiple folds with distinct biological functions is energetically unhindered.

HBD-2 binds SARS-CoV-2 RBD and blocks viral entry: Strategy to combat COVID-19

New approaches to complement vaccination are needed to combat the spread of SARS-CoV-2 and stop COVID-19-related deaths and medical complications. Human beta defensin 2 (hBD-2) is a naturally occurring epithelial cell-derived host defense peptide that has anti-viral properties. Our comprehensive in-silico studies demonstrate that hBD-2 binds the site on the CoV-2-RBD that docks with the ACE2 receptor. Biophysical measurements confirm that hBD-2 indeed binds to the CoV-2-receptor-binding domain (RBD) (K_D ∼ 2μM by surface plasmon resonance), preventing it from binding to ACE2-expressing cells. Importantly, hBD-2 shows specificity by blocking CoV-2/spike pseudoviral infection, but not VSVG-mediated infection, of ACE2-expressing human cells with an IC₅₀ of 2.8 ± 0.4 μM. These promising findings offer opportunities to develop hBD-2 and/or its derivatives and mimetics to safely and effectively use as agents to prevent SARS-CoV-2 infection.

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HBD-2 binds spike-RBD at the ACE2 interaction site in silico

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Biophysical and biological assays confirm hBD-2 binding to spike-RBD

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HBD-2 blocks spike-RBD:ACE2 binding

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HBD-2 prevents CoV-2/spike pseudovirions from infecting ACE2-expressing human cells

Impact of new variants on SARS-CoV-2 infectivity and neutralization: A molecular assessment of the alterations in the spike-host protein interactions

The emergence of SARS-CoV-2 variants necessitates rational assessment of their impact on the recognition and neutralization of the virus by the host cell. We present a comparative analysis of the interactions of Alpha, Beta, Gamma, and Delta variants with cognate molecules (ACE2 and/or furin), neutralizing nanobodies (Nbs), and monoclonal antibodies (mAbs) using in silico methods, in addition to Nb-binding assays. Our study elucidates the molecular origin of the ability of Beta and Delta variants to evade selected antibodies, such as REGN10933, LY-CoV555, B38, C105, or H11-H4, while being insensitive to others including REGN10987. Experiments confirm that nanobody Nb20 retains neutralizing activity against the Delta variant. The substitutions T478K and L452R in the Delta variant enhance associations with ACE2, whereas P681R promotes recognition by proteases, thus facilitating viral entry. The Ab-specific responses of variants highlight how full-atomic structure and dynamics analyses are required for assessing the response to newly emerging variants.

Contact-Based Analysis of Aggregation of Intrinsically Disordered Proteins

We review the contact-based description of aggregation of intrinsically disordered proteins in coarse-grained and all-atom models. We consider polyglutamines and polyalanines at various concentrations of the peptides. We also study associations of two chains of α-synuclein and up to 20 chains of a 12-residue-long segment of protein tau. We demonstrate that the total number of two-chain association events (in an aggregate that comprises at least two chains) provides a useful measure of the propensity to aggregate. This measure is consistent, for instance, with the previously reported mass spectroscopy data. The distribution of the number of association events is given essentially by a power law as a function of the duration of these events. The corresponding exponent depends on the protein and the temperature but not on the concentration of the proteins.

Molecular Dynamics Simulations of Human Beta-Defensin Type 3 Crossing Different Lipid Bilayers

Human β defensin type 3 (hBD-3) is a small cationic cysteine-rich peptide. It has a broad spectrum of antimicrobial activities. However, at high concentrations, it also shows hemolytic activity by interrupting red blood cells. To understand the selectivity of hBD-3 disrupting cell membranes, investigating the capability of hBD-3 translocating through different membranes is important. Since hBD-3 in the analogue form in which all three pairs of disulfide bonds are broken has similar antibacterial activities to the wild-type, this project investigates the structure and dynamics of an hBD-3 analogue in monomer, dimer, and tetramer forms through both zwitterionic and negatively charged lipid bilayers using molecular dynamics (MD) simulations. One tetramer structure of hBD-3 was predicted by running all-atom MD simulations on hBD-3 in water at a high concentration, which was found to be stable in water during 400 ns all-atom simulations based on root-mean-squared deviation, root-mean-squared fluctuation, buried surface area, and binding interaction energy calculations. After that, hBD-3 in different forms was placed inside different membranes, and then steered MD simulation was conducted to pull the hBD-3 out of the membrane along the z-direction to generate different configurational windows to set up umbrella-sampling (US) simulations. Because extensive sampling is important to obtain accurate free energy barriers, coarse-grained US MD simulations were performed in each window. Based on the long-term simulation result, membrane thinning was found near hBD-3 in different lipid bilayers and in different hBD-3 oligomer systems. By calculating the root-mean-squared deviation of the z-coordinate of hBD-3 molecules, rotation of the oligomer inside the bilayer and stretching of the oligomer structure along the z-direction were observed. Although reorientation of lipid heads toward the hBD-3 tetramer was observed based on the density profile calculation, the order parameter calculation shows that hBD-3 disrupts 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-l-serine (POPS) lipids more significantly and makes it less ordered than on 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipids. Calculating the free energy of hBD-3 through different lipid bilayers, it was found that generally hBD-3 encounters a lower energy barrier through negatively charged lipid membranes than the zwitterionic membrane. hBD-3 in different forms needs to overcome a lower energy barrier crossing the combined POPC+POPS bilayer through the POPS leaflet than through the POPC leaflet. Besides that, the potential of mean force result suggests that hBD-3 forms an oligomer translocating negatively charged lipid membranes at a low concentration. This study supplied new insight into the antibacterial mechanism of hBD-3 through different membranes.

Modeling the Mechanical Response of Microtubule Lattices to Pressure

Microtubules, the largest and stiffest filaments of the cytoskeleton, have to be well adapted to the high levels of crowdedness in cells to perform their multitude of functions. Furthermore, fundamental processes that involve microtubules, such as the maintenance of the cellular shape and cellular motion, are known to be highly dependent on external pressure. In light of the importance of pressure for the functioning of microtubules, numerous studies interrogated the response of these cytoskeletal filaments to osmotic pressure, resulting from crowding by osmolytes, such as poly(ethylene glycol)/poly(ethylene oxide) (PEG/PEO) molecules, or to direct applied pressure. The interpretation of experiments is usually based on the assumptions that PEG molecules have unfavorable interactions with the microtubule lattices and that the behavior of microtubules under pressure can be described by using continuous models. We probed directly these two assumptions. First, we characterized the interaction between the main interfaces in a microtubule filament and PEG molecules of various sizes using a combination of docking and molecular dynamics simulations. Second, we studied the response of a microtubule filament to compression using a coarse-grained model that allows for the breaking of lattice interfaces. Our results show that medium length PEG molecules do not alter the energetics of the lateral interfaces in microtubules but rather target and can penetrate into the voids between tubulin monomers at these interfaces, which can lead to a rapid loss of lateral interfaces under pressure. Compression of a microtubule under conditions corresponding to high osmotic pressure results in the formation of the deformed phase found in experiments. Our simulations show that the breaking of lateral interfaces, rather than the buckling of the filament inferred from the continuous models, accounts for the deformation.

Retrained Generic Antibodies Can Recognize SARS-CoV-2

The dramatic impact novel viruses can have on humans could be more quickly mitigated if generic antibodies already present in one's system are temporarily retrained to recognize these viruses. This type of intervention can be administered during the early stages of infection, while a specific immune response is being developed. With this idea in mind, double-faced peptide-based boosters were computationally designed to allow recognition of SARS-CoV-2 by Hepatitis B antibodies. One booster face is made of ACE2-mimic peptides that can bind to the receptor binding domain (RBD) of SARS-CoV-2. The other booster face is composed of a Hepatitis B core-antigen, targeting the Hepatitis B antibody fragment. Molecular dynamics simulations revealed that the designed boosters have a highly specific and stable binding to both the RBD and the antibody fragment (AF). This approach can provide a cheap and efficient neutralization of emerging pathogens.

Retrained Generic Antibodies Can Recognize SARS-CoV-2

The dramatic impact novel viruses can have on humans could be more quickly mitigated if generic antibodies already present in one's system are temporarily retrained to recognize these viruses. This type of intervention can be administered during the early stages of infection, while a specific immune response is being developed. With this idea in mind, double-faced peptide-based boosters were computationally designed to allow recognition of SARS-CoV-2 by Hepatitis B antibodies. One booster face is made of ACE2-mimic peptides that can bind to the receptor binding domain (RBD) of SARS-CoV-2. The other booster face is composed of a Hepatitis B core-antigen, targeting the Hepatitis B antibody fragment. Molecular dynamics simulations revealed that the designed boosters have a highly specific and stable binding to both the RBD and the antibody fragment (AF). This approach can provide a cheap and efficient neutralization of emerging pathogens.

Molecular dynamics simulations and functional studies reveal that hBD-2 binds SARS-CoV-2 spike RBD and blocks viral entry into ACE2 expressing cells

New approaches to complement vaccination are needed to combat the spread of SARS-CoV-2 and stop COVID-19 related deaths and long-term medical complications. Human beta defensin 2 (hBD-2) is a naturally occurring epithelial cell derived host defense peptide that has antiviral properties. Our comprehensive in-silico studies demonstrate that hBD-2 binds the site on the CoV-2-RBD that docks with the ACE2 receptor. Biophysical and biochemical assays confirm that hBD-2 indeed binds to the CoV-2-receptor binding domain (RBD) (KD ~ 300 nM), preventing it from binding to ACE2 expressing cells. Importantly, hBD-2 shows specificity by blocking CoV-2/spike pseudoviral infection, but not VSV-G mediated infection, of ACE2 expressing human cells with an IC50 of 2.4± 0.1 μM. These promising findings offer opportunities to develop hBD-2 and/or its derivatives and mimetics to safely and effectively use as novel agents to prevent SARS-CoV-2 infection.

Adaptive Evolution of Peptide Inhibitors for Mutating SARS-CoV-2

The SARS-CoV-2 virus is currently causing a worldwide pandemic with dramatic societal consequences for the humankind. In the past decades, disease outbreaks due to such zoonotic pathogens have appeared with an accelerated rate, which calls for an urgent development of adaptive (smart) therapeutics. Here, a computational strategy is developed to adaptively evolve peptides that could selectively inhibit mutating S protein receptor binding domains (RBDs) of different SARS-CoV-2 viral strains from binding to their human host receptor, angiotensin-converting enzyme 2 (ACE2). Starting from suitable peptide templates, based on selected ACE2 segments (natural RBD binder), the templates are gradually modified by random mutations, while retaining those mutations that maximize their RBD-binding free energies. In this adaptive evolution, atomistic molecular dynamics simulations of the template-RBD complexes are iteratively perturbed by the peptide mutations, which are retained under favorable Monte Carlo decisions. The computational search will provide libraries of optimized therapeutics capable of reducing the SARS-CoV-2 infection on a global scale.

In Situ Tracking of Colloidally Stable and Ordered Assemblies of Gold Nanorods

Solution-phase self-assembly of anisotropic nanoparticles into complex 2D and 3D assemblies is one of the most promising strategies toward obtaining nanoparticle-based materials and devices with unique optical properties at the macroscale. However, controlling this process with single-particle precision is highly demanding, mostly due to insufficient understanding of the self-assembly process at the nanoscale. We report the use of in situ environmental scanning transmission electron microscopy (WetSTEM), combined with UV/vis spectroscopy, small-angle X-ray diffraction (SAXRD) and multiscale modeling, to draw a detailed picture of the dynamics of vertically aligned assemblies of gold nanorods. Detailed understanding of the self-assembly/disassembly mechanisms is obtained from real-time observations, which provide direct evidence of the colloidal stability of side-to-side nanorod clusters. Structural details and the forces governing the disassembly process are revealed with single particle resolution as well as in bulk samples, by combined experimental and theoretical modeling. In particular, this study provides unique information on the evolution of the orientational order of nanorods within side-to-side 2D assemblies and shows that both electrostatic (at the nanoscale) and thermal (in bulk) stimuli can be used to drive the process. These results not only give insight into the interactions between nanorods and the stability of their assemblies, thereby assisting the design of ordered, anisotropic nanomaterials but also broaden the available toolbox for in situ tracking of nanoparticle behavior at the single-particle level.

Tethering of the IgG1 Antibody to Amorphous Silica for Immunosensor Development: A Molecular Dynamics Study

A key factor for improving the sensitivity and performance of immunosensors based on mechanical-plasmonic methods is the orientation of the antibody proteins immobilized on the inorganic surface. Although experimental techniques fail to determine surface phenomena at the molecular level, modern simulations open the possibility for improving our understanding of protein-surface interactions. In this work, replica exchange molecular dynamics (REMD) simulations have been used to model the IgG1 protein tethered onto the amorphous silica surface by considering a united-atom model and a relatively large system (2500 nm² surface). Additional molecular dynamics (MD) simulations have been conducted to derive an atomistic model for the amorphous silica surface using the cristobalite crystal structure as a starting point and to examine the structure of the free IgG1 antibody in the solution for comparison when immobilized. Analyses of the trajectories obtained for the tethered IgG1, which was sampled considering 32 different temperatures, have been used to define the geometry of the protein with respect to the inorganic surface. The tilt angle of the protein with respect to the surface plane increases with temperature, the most populated values being 24, 66, and 87° at the lowest (250 K), room (298 K), and the highest (380 K) temperatures. This variation indicates that the importance of protein-surface interactions decreases with increasing temperature. The influence of the surface on the structure of the antibody is very significant in the constant region, which is directly involved in the tethering process, while it is relatively unimportant for the antigen-binding fragments, which are farthest from the surface. These results are expected to contribute to the development of improved mechanical-plasmonic sensor microarrays in the near future.

Identification of an α-MoRF in the Intrinsically Disordered Region of the Escargot Transcription Factor

Molecular recognition features (MoRFs) are common in intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs). MoRFs are in constant order-disorder structural transitions and adopt well-defined structures once they are bound to their targets. Here, we study Escargot (Esg), a transcription factor in Drosophila melanogaster that regulates multiple cellular functions, and consists of a disordered N-terminal domain and a group of zinc fingers at its C-terminal domain. We analyzed the N-terminal domain of Esg with disorder predictors and identified a region of 45 amino acids with high probability to form ordered structures, which we named S2. Through 54 μs of molecular dynamics (MD) simulations using CHARMM36 and implicit solvent (generalized Born/surface area (GBSA)), we characterized the conformational landscape of S2 and found an α-MoRF of ∼16 amino acids stabilized by key contacts within the helix. To test the importance of these contacts in the stability of the α-MoRF, we evaluated the effect of point mutations that would impair these interactions, running 24 μs of MD for each mutation. The mutations had mild effects on the MoRF, and in some cases, led to gain of residual structure through long-range contacts of the α-MoRF and the rest of the S2 region. As this could be an effect of the force field and solvent model we used, we benchmarked our simulation protocol by carrying out 32 μs of MD for the (AAQAA)₃ peptide. The results of the benchmark indicate that the global amount of helix in shorter peptides like (AAQAA)₃ is reasonably predicted. Careful analysis of the runs of S2 and its mutants suggests that the mutation to hydrophobic residues may have nucleated long-range hydrophobic and aromatic interactions that stabilize the MoRF. Finally, we have identified a set of residues that stabilize an α-MoRF in a region still without functional annotations in Esg.

Scalable molecular dynamics on CPU and GPU architectures with NAMD

NAMDis a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.

Ab-initio binding of barnase–barstar with DelPhiForce steered Molecular Dynamics (DFMD) approach

Receptor–ligand interactions are involved in various biological processes, therefore understanding the binding mechanism and ability to predict the binding mode are essential for many biological investigations. While many computational methods exist to predict the 3D structure of the corresponding complex provided the knowledge of the monomers, here we use the newly developed DelPhiForce steered Molecular Dynamics (DFMD) approach to model the binding of barstar to barnase to demonstrate that first-principles methods are also capable of modeling the binding. Essential component of DFMD approach is enhancing the role of long-range electrostatic interactions to provide guiding force of the monomers toward their correct binding orientation and position. Thus, it is demonstrated that the DFMD can successfully dock barstar to barnase even if the initial positions and orientations of both are completely different from the correct ones. Thus, the electrostatics provides orientational guidance along with pulling force to deliver the ligand in close proximity to the receptor.

Adaptive Evolution of Peptide Inhibitors for Mutating SARS-CoV-2

The SARS-CoV-2 virus is currently causing a worldwide pandemic with dramatic societal consequences for the humankind. In the last decades, disease outbreaks due to such zoonotic pathogens have appeared with an accelerated rate, which calls for an urgent development of
adaptive (smart) therapeutics. Here, we develop a computational strategy to adaptively evolve peptides that could selectively inhibit mutating S protein receptor binding domains (RBDs) of different SARS-CoV-2 viral strains from binding to their human host receptor, angiotensin-converting enzyme 2 (ACE2). Starting from suitable peptide templates, based on selected ACE2 segments (natural RBD binder), we gradually modify the templates by random mutations, while retaining those mutations that maximize their RBD-binding free energies. In this adaptive evolution, atomistic molecular dynamics simulations of the template-RBD complexes are iteratively perturbed by the peptide mutations, which are retained under favorable Monte Carlo decisions. The computational search will provide libraries
of optimized therapeutics capable of reducing the SARS-CoV-2 infection on a global scale.
.

The transition between active and inactive conformations of Abl kinase studied by rock climbing and Milestoning

BACKGROUND

Kinases are a family of enzymes that catalyze the transfer of the ɤ-phosphate group from ATP to a protein's residue. Malfunctioning kinases are involved in many health problems such as cardiovascular diseases, diabetes, and cancer. Kinases transitions between multiple conformations of inactive to active forms attracted considerable interest.

METHOD

A reaction coordinate is computed for the transition between the active to inactive conformation in Abl kinase with a focus on the DFG-in to DFG-out flip. The method of Rock Climbing is used to construct a path locally, which is subsequently optimized using a functional of the entire path. The discrete coordinate sets along the reaction path are used in a Milestoning calculation of the free energy landscape and the rate of the transition.

RESULTS

The estimated transition times are between a few milliseconds and seconds, consistent with simulations of the kinetics and with indirect experimental data. The activation requires the transient dissociation of the salt bridge between Lys271 and Glu286. The salt bridge reforms once the DFG motif is stabilized by a locked conformation of Phe382. About ten residues are identified that contribute significantly to the process and are included as part of the reaction space.

CONCLUSIONS

The transition from DFG-in to DFG-out in Abl kinase was simulated using atomic resolution of a fully solvated protein yielding detailed description of the kinetics and the mechanism of the DFG flip. The results are consistent with other computational methods that simulate the kinetics and with some indirect experimental measurements.

GENERAL SIGNIFICANCE

The activation of kinases includes a conformational transition of the DFG motif that is important for enzyme activity but is not accessible to conventional Molecular Dynamics. We propose a detailed mechanism for the transition, at a timescale longer than conventional MD, using a combination of reaction path and Milestoning algorithms. The mechanism includes local structural adjustments near the binding site as well as collective interactions with more remote residues.

Elastic continuum stiffness of contractile tail sheaths from molecular dynamics simulations

Contractile tails are key components of the biological nanomachinery involved in cell membrane puncturing, where they provide a means to deliver molecules and ions inside cells. Two intriguing examples of contractile tails are those from bacteriophage T4 and R2-pyocin. Although the two systems are different in terms of biological activity, they share a fascinatingly similar injection mechanism, during which the tail sheaths of both systems contract from a so-called extended state to around half of their length (the contracted state), accompanied by release of elastic energy originally stored in the sheath. Despite the great prevalence and biomedical importance of contractile delivery systems, many fundamental details of their injection machinery and dynamics are still unknown. In this work, we calculate the bending and torsional stiffness constants of a helical tail sheath strand of bacteriophage T4 and R2-pyocin, in both extended and contracted states, using molecular dynamics simulations of about one-sixth of the entire sheath. Differences in stiffness constants between the two systems are rationalized by comparing their all-atom monomer structures, changes in sheath architecture on contraction, and differences in interstrand interactions. The calculated coefficients indicate that the T4 strand is stiffer for both bending and torsion than the corresponding R2-pyocin strands in both extended and contracted conformations. The sheath strands also have greater stiffness in the contracted state for both systems. As the main application of this study, we describe how the stiffness constants can be incorporated in a model to simulate the dynamics of contractile nanoinjection machineries.

Modeling Electrostatic Force in Protein-Protein Recognition

Electrostatic interactions are important for understanding molecular interactions, since they are long-range interactions and can guide binding partners to their correct binding positions. To investigate the role of electrostatic forces in molecular recognition, we calculated electrostatic forces between binding partners separated at various distances. The investigation was done on a large set of 275 protein complexes using recently developed DelPhiForce tool and in parallel, evaluating the total electrostatic force via electrostatic association energy. To accomplish the goal, we developed a method to find an appropriate direction to move one chain of protein complex away from its bound position and then calculate the corresponding electrostatic force as a function of separation distance. It is demonstrated that at large distances between the partners, the electrostatic force (magnitude and direction) is consistent among the protocols used and the main factors contributing to it are the net charge of the partners and their interfaces. However, at short distances, where partners form specific pair-wise interactions or de-solvation penalty becomes significant, the outcome depends on the precise balance of these factors. Based on the electrostatic force profile (force as a function of distance), we group the cases into four distinctive categories, among which the most intriguing is the case termed "soft landing." In this case, the electrostatic force at large distances is favorable assisting the partners to come together, while at short distance it opposes binding, and thus slows down the approach of the partners toward their physical binding.

Phosphorylation of Fibronectin Influences the Structural Stability of the Predicted Interchain Domain

As a key player in cell adhesion, the glycoprotein fibronectin is involved in the complex mechanobiology of the extracellular matrix. Although the function of many modules in the fibronectin molecule has already been understood, the structure and biological relevance of the C-terminal cross-linked region (CTXL) still remains unclear. It is known that fibronectin is only phosphorylated in the CTXL domain, but no results have been presented to date, which indicate a biological function based on this phosphorylation. For the first time, we introduce a structural model of the CTXL region in fibronectin, which we obtained by exhaustive replica exchange molecular dynamics simulations (TIGER2hs). The sampling revealed a conformational landscape of the dimerization module, and the global minimum state showed an umbrella-like module body and conspicuous structural region with two feet. We observed that the CTXL foot region exhibits a structural stability in its physiological state, which disappears upon changes in the phosphorylation state. Thus, our in silico studies enabled us to show that the flexibility of the CTXL region is guided by phosphorylation. These results indicate an in vivo function of the CTXL domain in protein binding and cell adhesion, which is controlled by phosphorylation.

The metabolic regulator Lamtor5 suppresses inflammatory signaling via regulating mTOR-mediated TLR4 degradation

Comprehensive immune responses are essential for eliminating pathogens but must be tightly controlled to avoid sustained immune activation and potential tissue damage. The engagement of TLR4, a canonical pattern recognition receptor, has been proposed to trigger inflammatory responses with different magnitudes and durations depending on TLR4 cellular compartmentalization. In the present study, we identify an unexpected role of Lamtor5, a newly identified component of the amino acid-sensing machinery, in modulating TLR4 signaling and controlling inflammation. Specifically, Lamtor5 associated with TLR4 via their LZ/TIR domains and facilitated their colocalization at autolysosomes, preventing lysosomal tethering and the activation of mTORC1 upon LPS stimulation and thereby derepressing TFEB to promote autophagic degradation of TLR4. The loss of Lamtor5 was unable to trigger the TFEB-driven autolysosomal pathway and delay degradation of TLR4, leading to sustained inflammation and hence increased mortality among Lamtor5 haploinsufficient mice during endotoxic shock. Intriguingly, nutrient deprivation, particularly leucine deprivation, blunted inflammatory signaling and conferred protection to endotoxic mice. This effect, however, was largely abrogated upon Lamtor5 deletion. We thus propose a homeostatic function of Lamtor5 that couples pathogenic insults and nutrient availability to optimize the inflammatory response; this function may have implications for TLR4-associated inflammatory and metabolic disorders.

Structural underpinnings of Ric8A function as a G-protein α-subunit chaperone and guanine-nucleotide exchange factor

Resistance to inhibitors of cholinesterase 8A (Ric8A) is an essential regulator of G protein α-subunits (Gα), acting as a guanine nucleotide exchange factor and a chaperone. We report two crystal structures of Ric8A, one in the apo form and the other in complex with a tagged C-terminal fragment of Gα. These structures reveal two principal domains of Ric8A: an armadillo-fold core and a flexible C-terminal tail. Additionally, they show that the Gα C-terminus binds to a highly-conserved patch on the concave surface of the Ric8A armadillo-domain, with selectivity determinants residing in the Gα sequence. Biochemical analysis shows that the Ric8A C-terminal tail is critical for its stability and function. A model of the Ric8A/Gα complex derived from crosslinking mass spectrometry and molecular dynamics simulations suggests that the Ric8A C-terminal tail helps organize the GTP-binding site of Gα. This study lays the groundwork for understanding Ric8A function at the molecular level.

Ric8A regulates G protein α-subunits (Gα) by acting as a guanine nucleotide exchange factor (GEF) and a Gα chaperone. Here, the authors solve the crystal structures of free and Gα fragment bound Ric8A, and provide insights into the structural basis for Ric8A’s GEF and chaperone functions.

Replica-Based Protein Structure Sampling Methods II: Advanced Hybrid Solvent TIGER2hs

In many cases, native states of proteins may be predicted with sufficient accuracy by molecular dynamics simulations (MDSs) with modern force fields. Enhanced sampling methods based on MDS are applied for exploring the phase space of a protein sequence and to overcome barriers on rough conformational energy landscapes. The minimum free energy state is obtained with sampling algorithms providing sufficient convergence and accuracy. A reliable but computationally very expensive method is replica exchange molecular dynamics, with many modifications to this approach presented in the past. Recently, we demonstrated how our temperature intervals with global exchange of replicas hybrid (TIGER2h) solvent sampling algorithm made a good compromise between efficiency and accuracy. There, all states are sampled under full explicit solvent conditions with a freely chosen number of replicas, whereas an implicit solvent is used during the swap decisions. This hybrid method yielded a much better approximation to the agreement with calculations in an explicit solvent than fully implicit solvent simulations. Here, we present an extension of TIGER2h and add a few layers of explicit water molecules around the peptide for the energy calculations, whereas the dynamics in fully explicit water is maintained. We claim that these water layers better reproduce steric effects, the polarization of the solvent, and the resulting reaction field energy than typical implicit solvent models. By investigating the protein-solvent interactions across comprehensive thermodynamic state ensembles, we found a strong conformational dependence of this reaction field energy. All simulations were performed with nanoscale molecular dynamics on two peptides, the α-helical peptide (AAQAA)₃ and the β-hairpin peptide HP7. A production-ready TIGER2hs implementation is supplied, approaching the accuracy of full explicit solvent sampling at a fraction of computational resources.

Namdinator - automatic molecular dynamics flexible fitting of structural models into cryo-EM and crystallography experimental maps

Model building into experimental maps is a key element of structural biology, but can be both time consuming and error prone for low-resolution maps. Here we present Namdinator, an easy-to-use tool that enables the user to run a molecular dynamics flexible fitting simulation followed by real-space refinement in an automated manner through a pipeline system. Namdinator will modify an atomic model to fit within cryo-EM or crystallography density maps, and can be used advantageously for both the initial fitting of models, and for a geometrical optimization step to correct outliers, clashes and other model problems. We have benchmarked Namdinator against 39 deposited cryo-EM models and maps, and observe model improvements in 34 of these cases (87%). Clashes between atoms were reduced, and the model-to-map fit and overall model geometry were improved, in several cases substantially. We show that Namdinator is able to model large-scale conformational changes compared to the starting model. Namdinator is a fast and easy tool for structural model builders at all skill levels. Namdinator is available as a web service (https://namdinator.au.dk), or it can be run locally as a command-line tool.

Polymyxins interaction to the human serum albumin: A thermodynamic and computational study

Polymyxin B and E (colistin), are a group of cationic charged cyclic antibiotic lipopeptides that are frequently used in the clinics to treat infections caused by the multidrug-resistant gram-negative bacteria. Since the interactions with the blood plasma drug-transport proteins may play a critical role in determining their pharmacological and pharmacokinetic profiles, we studied the binding properties of polymyxins to the human serum albumin (HSA) under simulated physiological conditions by the combination of biophysical approaches, such as isothermal titration calorimetry (ITC), fluorescence anisotropy, circular dichroism (CD) buttressed by computational studies. The HSA binding to the polymyxins was relatively strong (K_a ≈ 1.0 × 10⁷ M^-1). Molecular docking indicated that polymyxins bind to the cleft of HSA between domains I and III via the electrostatic interactions. This evidence was further confirmed by the entropy-driven interaction for the polymyxins bound HSA. Far UV-CD experiments showed that the secondary structure of HSA doesn't alter and its stable structure is preserved. Collectively, these investigations revealed that the polymyxins bind preferentially to the partially unfolded intermediate forms of the protein structure; however, HSA molecule does not undergo any significant conformational changes upon binding. This is promising as it may limit the unfavorable side effects of the medicine. On the whole, the results provide quantitative and qualitative insight of the binding interaction between HSA and polymyxins, which is important in understanding their effect as therapeutic agents.

From quantum to subcellular scales: multi-scale simulation approaches and the SIRAH force field

Modern molecular and cellular biology profits from astonishing resolution structural methods, currently even reaching the whole cell level. This is encompassed by the development of computational methods providing a deep view into the structure and dynamics of molecular processes happening at very different scales in time and space. Linking such scales is of paramount importance when aiming at far-reaching biological questions. Computational methods at the interface between classical and coarse-grained resolutions are gaining momentum with several research groups dedicating important efforts to their development and tuning. An overview of such methods is addressed herein, with special emphasis on the SIRAH force field for coarse-grained and multi-scale simulations. Moreover, we provide proof of concept calculations on the implementation of a multi-scale simulation scheme including quantum calculations on a classical fine-grained/coarse-grained representation of double-stranded DNA. This opens the possibility to include the effect of large conformational fluctuations in chromatin segments on, for instance, the reactivity of particular base pairs within the same simulation framework.