Native contacts determine protein folding mechanisms in atomistic simulations

Structural and functional effects of the L84S mutant in the SARS-COV-2 ORF8 dimer based on microsecond molecular dynamics study

The L84S mutation has been observed frequently in the ORF8 protein of SARS-CoV-2, which is an accessory protein involved in various important functions such as virus propagation, pathogenesis, and evading the immune response. However, the specific effects of this mutation on the dimeric structure of ORF8 and its impacts on interactions with host components and immune responses are not well understood. In this study, we performed one microsecond molecular dynamics (MD) simulation and analyzed the dimeric behavior of the L84S and L84A mutants in comparison to the native protein. The MD simulations revealed that both mutations caused changes in the conformation of the ORF8 dimer, influenced protein folding mechanisms, and affected the overall structural stability. In particular, the 73YIDI76 motif has found to be significantly affected by the L84S mutation, leading to structural flexibility in the region connecting the C-terminal β4 and β5 strands. This flexibility might be responsible for virus immune modulation.  The free energy landscape (FEL) and principle component analysis (PCA) have also supported our investigation. Overall, the L84S and L84A mutations affect the ORF8 dimeric interfaces by reducing the frequency of protein-protein interacting residues (Arg52, Lys53, Arg98, Ile104, Arg115, Val117, Asp119, Phe120, and Ile121) in the ORF8 dimer.  Our findings provide detail insights for further research in designing structure-based therapeutics against the SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Impact of Nonnative Interactions on the Binding Kinetics of Intrinsically Disordered p53 with MDM2: Insights from All-Atom Simulation and Markov State Model Analysis

Intrinsically disordered proteins (IDPs) lack a well-defined tertiary structure but are essential players in various biological processes. Their ability to undergo a disorder-to-order transition upon binding to their partners, known as the folding-upon-binding process, is crucial for their function. One classical example is the intrinsically disordered transactivation domain (TAD) of the tumor suppressor protein p53, which quickly forms a structured α-helix after binding to its partner MDM2, with clinical significance for cancer treatment. However, the contribution of nonnative interactions between the IDP and its partner to the rapid binding kinetics, as well as their interplay with native interactions, is not well understood at the atomic level. Here, we used molecular dynamics simulation and Markov state model (MSM) analysis to study the folding-upon-binding mechanism between p53-TAD and MDM2. Our results suggest that the system progresses from the nascent encounter complex to the well-structured encounter complex and finally reaches the native complex, following an induced-fit mechanism. We found that nonnative hydrophobic and hydrogen bond interactions, combined with native interactions, effectively stabilize the nascent and well-structured encounter complexes. Among the nonnative interactions, Leu25p53-Leu54MDM2 and Leu25p53-Phe55MDM2 are particularly noteworthy, as their interaction strength is close to the optimum. Evidently, strengthening or weakening these interactions could both adversely affect the binding kinetics. Overall, our findings suggest that nonnative interactions are evolutionarily optimized to accelerate the binding kinetics of IDPs in conjunction with native interactions.

Machine Learning Deciphered Molecular Mechanistics with Accurate Kinetic and Thermodynamic Prediction

Time-lagged independent component analysis (tICA) and the Markov state model (MSM) have been extensively employed for extracting conformational dynamics and kinetic community networks from unbiased trajectory ensembles. However, these techniques may not be the optimal choice for elucidating transition mechanisms within low-dimensional representations, especially for intricate biosystems. Unraveling the association mechanism in such complex systems always necessitates permutations of several essential independent components or collective variables, a process that is inherently obscure and may require empirical knowledge for selection. To address these challenges, we have implemented an integrated unsupervised dimension reduction model: uniform manifold approximation and projection (UMAP) with hierarchy density-based spatial clustering of applications with noise (HDBSCAN). This approach effectively generates low-dimensional configurational embeddings. The hierarchical application of this architecture, in conjunction with MSM, reveals global kinetic connectivity while identifying local conformational states. Consequently, our methodology establishes a multiscale mechanistic elucidation framework. Leveraging the benefits of the uniform sample distribution and a denoising approach, our model demonstrates robustness in preserving global and local data structures compared to traditional dimension reduction methods in the field of MD analysis area. The interpretability of hyperparameter selection and compatibility with downstream tasks are cross-validated across various simulation data sets, utilizing both computational evaluation metrics and experimental kinetic observables. Furthermore, the predicted Mcl1-BH3 association kinetics (0.76 s-1) is in close agreement with surface plasmon resonance experiments (0.12 s-1), affirming the plausibility of the identified pathway composed of representative conformations. We anticipate that the devised workflow will serve as a foundational framework for studying recognition patterns in complex biological systems. Its contributions extend to the exploration of protein functional dynamics and rational drug design, offering a potent avenue for advancing research in these domains.

On the role of native contact cooperativity in protein folding

The consistency of energy landscape theory predictions with available experimental data, as well as direct evidence from molecular simulations, have shown that protein folding mechanisms are largely determined by the contacts present in the native structure. As expected, native contacts are generally energetically favorable. However, there are usually at least as many energetically favorable nonnative pairs owing to the greater number of possible nonnative interactions. This apparent frustration must therefore be reduced by the greater cooperativity of native interactions. In this work, we analyze the statistics of contacts in the unbiased all-atom folding trajectories obtained by Shaw and coworkers, focusing on the unfolded state. By computing mutual cooperativities between contacts formed in the unfolded state, we show that native contacts form the most cooperative pairs, while cooperativities among nonnative or between native and nonnative contacts are typically much less favorable or even anticooperative. Furthermore, we show that the largest network of cooperative interactions observed in the unfolded state consists mainly of native contacts, suggesting that this set of mutually reinforcing interactions has evolved to stabilize the native state.

Temperature-Dependent Fold-Switching Mechanism of the Circadian Clock Protein KaiB

The oscillator of the cyanobacterial circadian clock relies on the ability of the KaiB protein to switch reversibly between a stable ground-state fold (gsKaiB) and an unstable fold-switched fold (fsKaiB). Rare fold-switching events by KaiB provide a critical delay in the negative feedback loop of this post-translational oscillator. In this study, we experimentally and computationally investigate the temperature dependence of fold switching and its mechanism. We demonstrate that the stability of gsKaiB increases with temperature compared to fsKaiB and that the Q10 value for the gsKaiB → fsKaiB transition is nearly three times smaller than that for the reverse transition. Simulations and native-state hydrogen-deuterium exchange NMR experiments suggest that fold switching can involve both subglobally and near-globally unfolded intermediates. The simulations predict that the transition state for fold switching coincides with isomerization of conserved prolines in the most rapidly exchanging region, and we confirm experimentally that proline isomerization is a rate-limiting step for fold switching. We explore the implications of our results for temperature compensation, a hallmark of circadian clocks, through a kinetic model.

Molecular mechanisms of Na+-driven bile acid transport in human NTCP

Human Na+ taurocholate co-transporting protein (hNTCP) is a key bile salt transporter to maintain enterohepatic circulation and is responsible for the recognition of hepatitis B and D viruses. Despite landmark cryoelectron microscopy studies revealing open-pore and inward-facing states of hNTCP stabilized by antibodies, the transport mechanism remains largely unknown. To address this knowledge gap, we used molecular dynamics and enhanced sampling metadynamics simulations to elucidate the intrinsic mechanism of hNTCP-mediated taurocholate acid (TCA) transport driven by Na+ binding. We uncovered three TCA-binding modes, including one that closely matched the limited cryoelectron microscopy density observed in the open-pore hNTCP. We also captured several key hNTCP conformations in the substrate transport cycle, particularly including an outward-facing, substrate-bound state. Furthermore, we provided thermodynamic evidence supporting that changes in the Na+-binding state drive the TCA transport by exploiting the amphiphilic nature of the substrate and modulating the protein environment, thereby enabling the TCA molecule to flip through. Understanding these mechanistic details of Na+-driven bile acid transport may aid in the development of hNTCP-targeted therapies for liver diseases.

The role of memory-dependent friction and solvent viscosity in isomerization kinetics in viscogenic media

Molecular isomerization kinetics in liquid solvent depends on a complex interplay between the solvent friction acting on the molecule, internal dissipation effects (also known as internal friction), the viscosity of the solvent, and the dihedral free energy profile. Due to the absence of accurate techniques to directly evaluate isomerization friction, it has not been possible to explore these relationships in full. By combining extensive molecular dynamics simulations with friction memory-kernel extraction techniques we consider a variety of small, isomerising molecules under a range of different viscogenic conditions and directly evaluate the viscosity dependence of the friction acting on a rotating dihedral. We reveal that the influence of different viscogenic media on isomerization kinetics can be dramatically different, even when measured at the same viscosity. This is due to the dynamic solute-solvent coupling, mediated by time-dependent friction memory kernels. We also show that deviations from the linear dependence of isomerization rates on solvent viscosity, which are often simply attributed to internal friction effects, are due to the simultaneous violation of two fundamental relationships: the Stokes-Einstein relation and the overdamped Kramers prediction for the barrier-crossing rate, both of which require explicit knowledge of friction.

Discovery of Novel Anti-Resistance AR Antagonists Guided by Funnel Metadynamics Simulation

Androgen receptor (AR) antagonists are widely used for the treatment of prostate cancer (PCa), but their therapeutic efficacy is usually compromised by the rapid emergence of drug resistance. However, the lack of the detailed interaction between AR and its antagonists poses a major obstacle to the design of novel AR antagonists. Here, funnel metadynamics is employed to elucidate the inherent regulation mechanisms of three AR antagonists (hydroxyflutamide, enzalutamide, and darolutamide) on AR. For the first time it is observed that the binding of antagonists significantly disturbed the C-terminus of AR helix-11, thereby disrupting the specific internal hydrophobic contacts of AR-LBD and correspondingly the communication between AR ligand binding pocket (AR-LBP), activation function 2 (AF2), and binding function 3 (BF3). The subsequent bioassays verified the necessity of the hydrophobic contacts for AR function. Furthermore, it is found that darolutamide, a newly approved AR antagonist capable of fighting almost all reported drug resistant AR mutants, can induce antagonistic binding structure. Subsequently, docking-based virtual screening toward the dominant binding conformation of AR for darolutamide is conducted, and three novel AR antagonists with favorable binding affinity and strong capability to combat drug resistance are identified by in vitro bioassays. This work provides a novel rational strategy for the development of anti-resistant AR antagonists.

Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments

Investigating protein-protein interactions is crucial for understanding cellular biological processes because proteins often function within molecular complexes rather than in isolation. While experimental and computational methods have provided valuable insights into these interactions, they often overlook a critical factor: the crowded cellular environment. This environment significantly impacts protein behavior, including structural stability, diffusion, and ultimately the nature of binding. In this review, we discuss theoretical and computational approaches that allow the modeling of biological systems to guide and complement experiments and can thus significantly advance the investigation, and possibly the predictions, of protein-protein interactions in the crowded environment of cell cytoplasm. We explore topics such as statistical mechanics for lattice simulations, hydrodynamic interactions, diffusion processes in high-viscosity environments, and several methods based on molecular dynamics simulations. By synergistically leveraging methods from biophysics and computational biology, we review the state of the art of computational methods to study the impact of molecular crowding on protein-protein interactions and discuss its potential revolutionizing effects on the characterization of the human interactome.

Enhanced Sampling of Configuration and Path Space in a Generalized Ensemble by Shooting Point Exchange

The computer simulation of many molecular processes is complicated by long timescales caused by rare transitions between long-lived states. Here, we propose a new approach to simulate such rare events, which combines transition path sampling with enhanced exploration of configuration space. The method relies on exchange moves between configuration and trajectory space, carried out based on a generalized ensemble. This scheme substantially enhances the efficiency of the transition path sampling simulations, particularly for systems with multiple transition channels, and yields information on thermodynamics, kinetics and reaction coordinates of molecular processes without distorting their dynamics. The method is illustrated using the isomerization of proline in the KPTP tetrapeptide.

Learning Markovian dynamics with spectral maps

The long-time behavior of many complex molecular systems can often be described by Markovian dynamics in a slow subspace spanned by a few reaction coordinates referred to as collective variables (CVs). However, determining CVs poses a fundamental challenge in chemical physics. Depending on intuition or trial and error to construct CVs can lead to non-Markovian dynamics with long memory effects, hindering analysis. To address this problem, we continue to develop a recently introduced deep-learning technique called spectral map [J. Rydzewski, J. Phys. Chem. Lett. 14, 5216-5220 (2023)]. Spectral map learns slow CVs by maximizing a spectral gap of a Markov transition matrix describing anisotropic diffusion. Here, to represent heterogeneous and multiscale free-energy landscapes with spectral map, we implement an adaptive algorithm to estimate transition probabilities. Through a Markov state model analysis, we validate that spectral map learns slow CVs related to the dominant relaxation timescales and discerns between long-lived metastable states.

Molecular Insights into the Inhibitory Role of α-Crystallin against γD-Crystallin Aggregation

Cataracts, a major cause of global blindness, contribute significantly to the overall prevalence of blindness. The opacification of the lens, resulting in cataract formation, primarily occurs due to the aggregation of crystallin proteins within the eye lens. Despite the high concentration of these crystallins, they remarkably maintain the lens transparency and refractive index. α-Crystallins (α-crys), acting as chaperones, play a crucial role in preventing crystallin aggregation, although the exact molecular mechanism remains uncertain. In this study, we employed a combination of molecular docking, all-atom molecular dynamics simulations, and advanced free energy calculations to investigate the interaction between γD-crystallin (γD-crys), a major structural protein of the eye lens, and α-crystallin proteins. Our findings demonstrate that α-crys exhibits an enhanced affinity for the NTD2 and CTD4 regions of γD-crys. The NTD2 and CTD4 regions form the interface between the N-terminal domain (NTD) and the C-terminal domain (CTD) of the γD-crys protein. By binding to the interface region between the NTD and CTD of the protein, α-crys effectively inhibits the formation of domain-swapped aggregates and mitigates protein aggregation. Analysis of the Markov state models using molecular dynamics trajectories confirms that minimum free energy conformations correspond to the binding of the α-crystallin domain (ACD) of α-crys to NTD2 and CTD4 that form the interdomain interface.

Peripheral Linker Mediates Acyl Carrier Protein's Recognition of Dehydratase and Stabilizes Type-I Mycobacterium tuberculosis Fatty Acid Synthase

Incomplete structural details of Mycobacterium tuberculosis (Mtb) fatty acid synthase-I (FAS-I) at near-atomic resolution have limited our understanding of the shuttling mechanism of its mobile acyl carrier protein (ACP). Here, we have performed atomistic molecular dynamics simulation of Mtb FAS-I with a homology-modeled structure of ACP stalled at dehydratase (DH) and identified key residues that mediate anchoring of the recognition helix of ACP near DH. The observed distance between catalytic residues of ACP and DH agrees with that reported for fungal FAS-I. Further, the conformation of the peripheral linker is found to be crucial in stabilizing ACP near DH. Correlated interdomain motion is observed between DH, enoyl reductase, and malonyl/palmitoyl transferase, consistent with prior experimental reports of fungal and Mtb FAS-I.

Conflicting Interfacial Electrostatic Interactions as a Design Principle to Modulate Long-Range Interdomain Communication

The extent and molecular basis of interdomain communication in multidomain proteins, central to understanding allostery and function, is an open question. One simple evolutionary strategy could involve the selection of either conflicting or favorable electrostatic interactions across the interface of two closely spaced domains to tune the magnitude of interdomain connectivity. Here, we study a bilobed domain FF34 from the eukaryotic p190A RhoGAP protein to explore one such design principle that mediates interdomain communication. We find that while the individual structural units in wild-type FF34 are marginally coupled, they exhibit distinct intrinsic stabilities and low cooperativity, manifesting as slow folding. The FF3-FF4 interface harbors a frustrated network of highly conserved electrostatic interactions-a charge troika-that promotes the population of multiple, decoupled, and non-native structural modes on a rugged native landscape. Perturbing this network via a charge-reversal mutation not only enhances stability and cooperativity but also dampens the fluctuations globally and speeds up the folding rate by at least an order of magnitude. Our work highlights how a conserved but nonoptimal network of interfacial electrostatic interactions shapes the native ensemble of a bilobed protein, a feature that could be exploited in designing molecular systems with long-range connectivity and enhanced cooperativity.

Conformational dynamics of α-1 acid glycoprotein (AGP) in cancer: A comparative study of glycosylated and unglycosylated AGP

α-1 acid glycoprotein (AGP) is one of the most abundant plasma proteins. It fulfills two important functions: immunomodulation, and binding to various drugs and receptors. These different functions are closely associated and modulated via changes in glycosylation and cancer missense mutations. From a structural point of view, glycans alter the local biophysical properties of the protein leading to a diverse ligand-binding spectrum. However, glycans can typically not be observed in the resolved X-ray crystallography structure of AGP due to their high flexibility and microheterogeneity, so limiting our understanding of AGP's conformational dynamics 70 years after its discovery. We here investigate how mutations and glycosylation interfere with AGP's conformational dynamics changing its biophysical behavior, by using molecular dynamics (MD) simulations and sequence-based dynamics predictions. The MD trajectories show that glycosylation decreases the local backbone flexibility of AGP and increases the flexibility of distant regions through allosteric effects. We observe that mutations near the glycosylation site affect glycan's conformational preferences. Thus, we conclude that mutations control glycan dynamics which modulates the protein's backbone flexibility directly affecting its accessibility. These findings may assist in the drug design targeting AGP's glycosylation and mutations in cancer.

Significance of the Disulfide Bridge in the Structure and Stability of Metalloprotein Azurin

Metalloproteins make up a class of proteins that incorporate metal ions into their structures, enabling them to perform essential functions in biological systems, such as catalysis and electron transport. Azurin is one such metalloprotein with copper cofactor, having a β-barrel structure with exceptional thermal stability. The copper metal ion is coordinated at one end of the β-barrel structure, and there is a disulfide bond at the opposite end. In this study, we explore the effect of this disulfide bond in the high thermal stability of azurin by analyzing both the native S-S bonded and S-S nonbonded (S-S open) forms using temperature replica exchange molecular dynamics (REMD). Similar to experimental observations, we find a 35 K decrease in denaturation temperature for S-S open azurin compared to that of the native holo form (420 K). As observed in the case of native holo azurin, the unfolding process of the S-S open form also started with disruptions of the α-helix. The free energy surfaces of the unfolding process revealed that the denaturation event of the S-S open form progresses through different sets of conformational ensembles. Subsequently, we compared the stabilities of individual β-sheet strands of both the S-S bonded and the S-S nonbonded forms of azurin. Further, we examined the contacts between individual residues for the central structures from the free energy surfaces of the S-S nonbonded form. The microscopic origin of the lowering in the denaturation temperature is further supplemented by thermodynamic analysis.

Binding Mechanism of Riboswitch to Natural Ligand Elucidated by McMD-Based Dynamic Docking Simulations

Flavin mononucleotide riboswitches are common among many pathogenic bacteria and are therefore considered to be an attractive target for antibiotics development. The riboswitch binds riboflavin (RBF, also known as vitamin B2), and although an experimental structure of their complex has been solved with the ligand bound deep inside the RNA molecule in a seemingly unreachable state, the binding mechanism between these molecules is not yet known. We have therefore used our Multicanonical Molecular Dynamics (McMD)-based dynamic docking protocol to analyze their binding mechanism by simulating the binding process between the riboswitch aptamer domain and the RBF, starting from the apo state of the riboswitch. Here, the refinement stage was crucial to identify the native binding configuration, as several other binding configurations were also found by McMD-based docking simulations. RBF initially binds the interface between P4 and P6 including U61 and G62, which forms a gateway where the ligand lingers until this gateway opens sufficiently to allow the ligand to pass through and slip into the hidden binding site including A48, A49, and A85.

Effects of altered backbone composition on the folding kinetics and mechanism of an ultrafast-folding protein

Sequence-encoded protein folding is a ubiquitous biological process that has been successfully engineered in a range of oligomeric molecules with artificial backbone chemical connectivity. A remarkable aspect of protein folding is the contrast between the rapid rates at which most sequences in nature fold and the vast number of conformational states possible in an unfolded chain with hundreds of rotatable bonds. Research efforts spanning several decades have sought to elucidate the fundamental chemical principles that dictate the speed and mechanism of natural protein folding. In contrast, little is known about how protein mimetic entities transition between an unfolded and folded state. Here, we report effects of altered backbone connectivity on the folding kinetics and mechanism of the B domain of Staphylococcal protein A (BdpA), an ultrafast-folding sequence. A combination of experimental biophysical analysis and atomistic molecular dynamics simulations performed on the prototype protein and several heterogeneous-backbone variants reveal the interplay among backbone flexibility, folding rates, and structural details of the transition state ensemble. Collectively, these findings suggest a significant degree of plasticity in the mechanisms that can give rise to ultrafast folding in the BdpA sequence and provide atomic level insights into how protein mimetic chains adopt an ordered folded state.

Structure-guided design of a trivalent nanobody cluster targeting SARS-CoV-2 spike protein

Nanobodies are natural anti-SARS-CoV-2 drug candidates. Engineering multivalent nanobodies is an effective way to improve the functional binding affinity of natural nanobodies by simultaneously targeting multiple sites on viral proteins. However, multivalent nanobodies have usually been engineered by trial and error, and rational designs are still lacking. Here, we describe a structure-guided design of a self-assembled trivalent nanobody cluster targeting the SARS-CoV-2 spike protein. Using the nanobody Nb6 as a monovalent binder, we first selected a human-derived trimerization scaffold evaluated by molecular dynamics simulations, then selected an optimal linker according to the minimum distance between Nb6 and the trimerization scaffold, and finally successfully engineered a trivalent nanobody cluster called Tribody. Compared with the low-affinity monovalent counterpart (Nb6), Tribody showed much higher target binding affinity (KD < 1 pM) and thus had a 900-fold increase in antiviral neutralization against SARS-CoV-2 pseudovirus. We determined the cryo-EM structure of the Tribody-spike complex and confirmed that all three Nb6 binders of Tribody collectively bind to the three receptor-binding domains (RBDs) of the spike and lock them in a 3-RBD-down conformation, fully consistent with our structure-guided design. This study demonstrates that synthetic nanobody clusters with human-derived self-assembled scaffolds are potential protein drugs against SARS-CoV-2 coronaviruses.

Titin domains with reduced core hydrophobicity cause dilated cardiomyopathy

The underlying genetic defect in most cases of dilated cardiomyopathy (DCM), a common inherited heart disease, remains unknown. Intriguingly, many patients carry single missense variants of uncertain pathogenicity targeting the giant protein titin, a fundamental sarcomere component. To explore the deleterious potential of these variants, we first solved the wild-type and mutant crystal structures of I21, the titin domain targeted by pathogenic variant p.C3575S. Although both structures are remarkably similar, the reduced hydrophobicity of deeply buried position 3575 strongly destabilizes the mutant domain, a scenario supported by molecular dynamics simulations and by biochemical assays that show no disulfide involving C3575. Prompted by these observations, we have found that thousands of similar hydrophobicity-reducing variants associate specifically with DCM. Hence, our results imply that titin domain destabilization causes DCM, a conceptual framework that not only informs pathogenicity assessment of gene variants but also points to therapeutic strategies counterbalancing protein destabilization.

Molecular Free Energies, Rates, and Mechanisms from Data-Efficient Path Sampling Simulations

Molecular dynamics is a powerful tool for studying the thermodynamics and kinetics of complex molecular events. However, these simulations can rarely sample the required time scales in practice. Transition path sampling overcomes this limitation by collecting unbiased trajectories and capturing the relevant events. Moreover, the integration of machine learning can boost the sampling while simultaneously learning a quantitative representation of the mechanism. Still, the resulting trajectories are by construction non-Boltzmann-distributed, preventing the calculation of free energies and rates. We developed an algorithm to approximate the equilibrium path ensemble from machine-learning-guided path sampling data. At the same time, our algorithm provides efficient sampling, mechanism, free energy, and rates of rare molecular events at a very moderate computational cost. We tested the method on the folding of the mini-protein chignolin. Our algorithm is straightforward and data-efficient, opening the door to applications in many challenging molecular systems.

Staphylococcus aureus functional amyloids catalyze degradation of β-lactam antibiotics

Antibiotic resistance of bacteria is considered one of the most alarming developments in modern medicine. While varied pathways for bacteria acquiring antibiotic resistance have been identified, there still are open questions concerning the mechanisms underlying resistance. Here, we show that alpha phenol-soluble modulins (PSMαs), functional bacterial amyloids secreted by Staphylococcus aureus, catalyze hydrolysis of β-lactams, a prominent class of antibiotic compounds. Specifically, we show that PSMα2 and, particularly, PSMα3 catalyze hydrolysis of the amide-like bond of the four membered β-lactam ring of nitrocefin, an antibiotic β-lactam surrogate. Examination of the catalytic activities of several PSMα3 variants allowed mapping of the active sites on the amyloid fibrils' surface, specifically underscoring the key roles of the cross-α fibril organization, and the combined electrostatic and nucleophilic functions of the lysine arrays. Molecular dynamics simulations further illuminate the structural features of β-lactam association upon the fibril surface. Complementary experimental data underscore the generality of the functional amyloid-mediated catalytic phenomenon, demonstrating hydrolysis of clinically employed β-lactams by PSMα3 fibrils, and illustrating antibiotic degradation in actual S. aureus biofilms and live bacteria environments. Overall, this study unveils functional amyloids as catalytic agents inducing degradation of β-lactam antibiotics, underlying possible antibiotic resistance mechanisms associated with bacterial biofilms.

Design and structural validation of peptide-drug conjugate ligands of the kappa-opioid receptor

Despite the increasing number of GPCR structures and recent advances in peptide design, the development of efficient technologies allowing rational design of high-affinity peptide ligands for single GPCRs remains an unmet challenge. Here, we develop a computational approach for designing conjugates of lariat-shaped macrocyclized peptides and a small molecule opioid ligand. We demonstrate its feasibility by discovering chemical scaffolds for the kappa-opioid receptor (KOR) with desired pharmacological activities. The designed De Novo Cyclic Peptide (DNCP)-β-naloxamine (NalA) exhibit in vitro potent mixed KOR agonism/mu-opioid receptor (MOR) antagonism, nanomolar binding affinity, selectivity, and efficacy bias at KOR. Proof-of-concept in vivo efficacy studies demonstrate that DNCP-β-NalA(1) induces a potent KOR-mediated antinociception in male mice. The high-resolution cryo-EM structure (2.6 Å) of the DNCP-β-NalA-KOR-Gi1 complex and molecular dynamics simulations are harnessed to validate the computational design model. This reveals a network of residues in ECL2/3 and TM6/7 controlling the intrinsic efficacy of KOR. In general, our computational de novo platform overcomes extensive lead optimization encountered in ultra-large library docking and virtual small molecule screening campaigns and offers innovation for GPCR ligand discovery. This may drive the development of next-generation therapeutics for medical applications such as pain conditions.

Activation Loop Plasticity and Active Site Coupling in the MAP Kinase, ERK2

Previous studies of the protein kinase, ERK2, using NMR and hydrogen-exchange measurements have shown changes in dynamics accompanying its activation by phosphorylation. However, knowledge about the conformational motions involved is incomplete. Here, we examined ERK2 using long conventional molecular dynamics (MD) simulations starting from crystal structures of phosphorylated (2P) and unphosphorylated (0P) forms. Individual trajectories were run for (5 to 25) μs, totaling 727 μs. The results show unexpected flexibility of the A-loop, with multiple long-lived (>5 μs) conformational states in both 2P- and 0P-ERK2. Differential contact network and principal component analyses reveal coupling between the A-loop fold and active site dynamics, with evidence for conformational selection in the kinase core of 2P-ERK2 but not 0P-ERK2. Simulations of 2P-ERK2 show A-loop states corresponding to restrained dynamics within the N-lobe, including regions around catalytic residues. One A-loop conformer forms lasting interactions with the L16 segment, leading to reduced RMSF and greater compaction in the active site. By contrast, simulations of 0P-ERK2 reveal excursions of A-loop residues away from the C-lobe, leading to greater active site mobility. Thus, the A-loop in ERK2 switches between distinct conformations that reflect coupling with the active site, possibly via the L16 segment. Crystal packing interactions suggest that lattice contacts with the A-loop may restrain its structural variation in X-ray structures of ERK2. The novel conformational states identified by MD expand our understanding of ERK2 regulation, by linking the activated state of the kinase to reduced dynamics and greater compaction surrounding the catalytic site.

The stability and dynamics of the Aβ40/Aβ42 interlaced mixed fibrils

The accumulation of fibrillar amyloid-β (Aβ) aggregates in the brain, predominantly comprising 40- and 42-residue amyloid-β (Aβ40 and Aβ42), is a major pathological hallmark of Alzheimer's disease (AD). Aβ40 and Aβ42 naturally coexist in the brain under normal physiological conditions, and their interplay is generally considered to be a critical factor in the progression of AD. In addition to forming homogeneous oligomers and fibrils, Aβ40 and Aβ42 are also reported to co-assemble into hetero-oligomers and interlaced mixed fibrils, as evidenced by solid-state nuclear magnetic resonance spectroscopy (NMR), high molecular weight mass spectrometry and cross-seeding experiments. However, the exact molecular mechanisms underlying these processes remain unclear. In this study, we have used a recently resolved structurally uniform 1:1 mixture of Aβ40/Aβ42 interlaced mixed fibril as a prototype to gain insights into the molecular-level interactions between Aβ40 and Aβ42. We employed fully atomistic molecular dynamics simulation and compared the results with a homogeneous U-shaped Aβ40 fibrillar model. Our simulations using two different force fields provide conclusive evidence that the Aβ40/Aβ42 interlaced mixed fibril is energetically more favorable than the homogeneous Aβ40 fibrillar model. Furthermore, we also show that the increase in stability observed in the mixed model stems primarily from the packing interfaces and the stacking interfaces between C-termini. Our simulation results provide valuable mechanistic insights that are not readily accessible in experiment and could have significant implications for both the pathogenesis of AD and the development of current therapeutic strategies.Communicated by Ramaswamy H. Sarma.

In silico protein dynamics in the human cytoplasm: Partial folding, misfolding, fold switching, and non-native interactions

We examine the influence of cellular interactions in all-atom models of a section of the Homo sapiens cytoplasm on the early folding events of the three-helix bundle protein B (PB). While genetically engineered PB is known to fold in dilute water box simulations in three microseconds, the three initially unfolded PB copies in our two cytoplasm models using a similar force field did not reach the native state during 30-microsecond simulations. We did however capture the formation of all three helices in a compact native-like topology. Folding in vivo is delayed because intramolecular contact formation within PB is in direct competition with intermolecular contacts between PB and surrounding macromolecules. In extreme cases, intermolecular beta-sheets are formed. Interactions with other macromolecules are also observed to promote structure formation, for example when a PB helix in our simulations is shielded from solvent by macromolecular crowding. Sticking and crowding in our models initiate sampling of helix/sheet structural plasticity of PB. Relatedly, in past in vitro experiments, similar GA domains were shown to switch between two different folds. Finally, we also observed that stickiness between PB and the cellular environment can be modulated in our simulations through the reduction in protein hydrophobicity when we reversed PB back to the wild-type sequence. This study demonstrates that even fast-folding proteins can get stuck in non-native states in the cell, making them useful models for protein-chaperone interactions and early stages of aggregate formation relevant to cellular disease.

Energy- and evolution-based design of inulosucrase for enhanced thermostability and inulin production

Inulosucrase from Lactobacillus reuteri 121 (LrInu) exhibits promise in the synthesis of prebiotic inulin and fructooligosaccharides. However, for its use in industry, LrInu's thermostability is a crucial consideration. In this study, the computational program FireProt was used to predict the thermostable variants of LrInu. Using rational criteria, nine variants were selected for protein expression and characterization. The G237P variant was determined to be the greatest designed candidate due to its greatly enhanced stability and activity in comparison to the wild-type enzyme. The optimum temperature of G237P increased from 50 to 60°C, with an over 5-fold increase in the half-life. Spectroscopy studies revealed that the G237P mutation could prevent the structural change in LrInu caused by heat or urea treatment. Molecular dynamics (MD) simulations showed that the enhanced thermostability of the G237P variant resulted from an increase in structural rigidity and the number of native contacts within the protein molecule. In addition, G237P variant synthesizes inulin with greater efficiency than WT. KEY POINTS: • Thermostable inulosucrase variant(s) were designed by Fireprot server. • G237P variant showed significantly improved thermostability compared to the wild type. • Inulin is synthesized more efficiently by G237P variant.

Improving Estimation of the Koopman Operator with Kolmogorov-Smirnov Indicator Functions

It has become common to perform kinetic analysis using approximate Koopman operators that transform high-dimensional timeseries of observables into ranked dynamical modes. The key to the practical success of the approach is the identification of a set of observables that form a good basis on which to expand the slow relaxation modes. Good observables are, however, difficult to identify a priori and suboptimal choices can lead to significant underestimations of characteristic time scales. Leveraging the representation of slow dynamics in terms of Hidden Markov Models (HMM), we propose a simple and computationally efficient clustering procedure to infer surrogate observables that form a good basis for slow modes. We apply the approach to an analytically solvable model system as well as on three protein systems of different complexities. We consistently demonstrate that the inferred indicator functions can significantly improve the estimation of the leading eigenvalues of Koopman operators and correctly identify key states and transition time scales of stochastic systems, even when good observables are not known a priori.

Exploring the disruption of SARS-CoV-2 RBD binding to hACE2

The COVID-19 pandemic was declared due to the spread of the novel coronavirus, SARS-CoV-2. Viral infection is caused by the interaction between the SARS-CoV-2 receptor binding domain (RBD) and the human ACE2 receptor (hACE2). Previous computational studies have identified repurposed small molecules that target the RBD, but very few have screened drugs in the RBD-hACE2 interface. When studies focus solely on the binding affinity between the drug and the RBD, they ignore the effect of hACE2, resulting in an incomplete analysis. We screened ACE inhibitors and previously identified SARS-CoV-2 inhibitors for binding to the RBD-hACE2 interface, and then conducted 500 ns of unrestrained molecular dynamics (MD) simulations of fosinopril, fosinoprilat, lisinopril, emodin, diquafosol, and physcion bound to the interface to assess the binding characteristics of these ligands. Based on MM-GBSA analysis, all six ligands bind favorably in the interface and inhibit the RBD-hACE2 interaction. However, when we repeat our simulation by first binding the drug to the RBD before interacting with hACE2, we find that fosinopril, fosinoprilat, and lisinopril result in a strongly interacting trimeric complex (RBD-drug-hACE2). Hydrogen bonding and pairwise decomposition analyses further suggest that fosinopril is the best RBD inhibitor. However, when lisinopril is bound, it stabilizes the trimeric complex and, therefore, is not an ideal potential drug candidate. Overall, these results reveal important atomistic interactions critical to the binding of the RBD to hACE2 and highlight the significance of including all protein partners in the evaluation of a potential drug candidate.

Effect of mutations on the folding and stability of γD-crystallin protein

Interprotein interactions between the partially unfolded states of γD-crystallin (γD-crys) protein are known to cause cataracts. Therefore, understanding the unfolding pathways of native γD-crys is extremely crucial to delineate their aggregation mechanism. In this study, we have performed extensive all-atom Molecular Dynamics simulations with explicit solvent to understand the role of the critical residues that drive the stability of the motifs and domains of γD-crys in its wild type and mutant forms. Our findings show that while the individual motifs of wild type are not stable in the native form, the individual domains remain structurally stable at 425K. This enhanced stability of the domain was attributed to the hydrophobic interactions between the motifs. Single and double point mutations of the domains with negatively charged aspartic and glutamic acid amino acid residues (I3E, W42D, W42E, I3D/W42D, I3E/W42E, and L92D/W157D) decreases the structural stability, leading to unfolding of individual domains of γD-crys. We believe that our study sheds light on the weakest links of γD-crys, along with the role of interactions stabilizing the domains. Further, this study bolsters and provides a better understanding of the domain swapping mechanism of aggregation of γD-crys.Communicated by Ramaswamy H. Sarma.

Coupled Electrostatic and Hydrophobic Destabilisation of the Gelsolin-Actin Complex Enables Facile Detection of Ovarian Cancer Biomarker Lysophosphatidic Acid

Lysophosphatidic acid (LPA) is a promising biomarker candidate to screen for ovarian cancer (OC) and potentially stratify and treat patients according to disease stage. LPA is known to target the actin-binding protein gelsolin which is a key regulator of actin filament assembly. Previous studies have shown that the phosphate headgroup of LPA alone is inadequate to bind to the short chain of amino acids in gelsolin known as the PIP2-binding domain. Thus, the molecular-level detail of the mechanism of LPA binding is poorly understood. Here, we model LPA binding to the PIP2-binding domain of gelsolin in the gelsolin-actin complex through extensive ten-microsecond atomistic molecular dynamics (MD) simulations. We predict that LPA binding causes a local conformational rearrangement due to LPA interactions with both gelsolin and actin residues. These conformational changes are a result of the amphipathic nature of LPA, where the anionic phosphate, polar glycerol and ester groups, and lipophilic aliphatic tail mediate LPA binding via charged electrostatic, hydrogen bonding, and van der Waals interactions. The negatively-charged LPA headgroup binds to the PIP2-binding domain of gelsolin-actin while its hydrophobic tail is inserted into actin, creating a strong LPA-insertion pocket that weakens the gelsolin-actin interface. The computed structure, dynamics, and energetics of the ternary gelsolin-LPA-actin complex confirms that a quantitative OC assay is possible based on LPA-triggered actin release from the gelsolin-actin complex.

Glutaredoxin proteins from E. coli isoforms were compared in terms of energy frustration

Glutaredoxin (GRXs) protein plays a vital role inside the cell, including redox control of transcription to the cell's antioxidant defense, apoptosis, and cellular differentiation regulation. In this study, we have investigated the energy landscape and characterized the pattern of local frustration in different forms and states of the GRX protein ofE. coli.Analysis was done on the conformational alterations, significant changes in the frustration pattern, and different GRXs such as GRX-II, GRX-III, GRX-II-GSH, and GRX-III-GSH complex. We have found the practice of frustration, and structure was quite similar in the same isoform having different states of protein; however, a significant difference was observed between different isoforms. Moreover, oxidation of GRX-I introduced an extra α-helix increasing the destabilizing interactions within the protein. The study of frustrated contacts on oxidized and reduced GRX and with bound and unbound Glutathione indicates its potential application in activating and regulating the behavior of GRXs.

On the Dynamic Mechanism of Long-Flexible Fatty Acid Binding to Fatty Acid Binding Protein: Resolving the Long-Standing Debate

Fatty acids (FAs) are one of the essential energy sources for physiological processes, and they play a vital role in regulating immune and inflammatory responses, promoting cell differentiation and apoptosis, and inhibiting tumor growth. These functions are carried out by FA binding proteins (FABPs) that recognize and transport FAs. Although the crystal structure of the FA-FABPs complex has long been characterized, the mechanism behind FA binding and dissociation from FABP remains unclear. This study employed conventional MD simulations and enhanced sampling technologies to investigate the atomic-scale complexes of heart fatty acid binding proteins and stearic acid (SA). The results revealed two primary pathways for the binding or dissociation of the flexible long-chain ligand, with the orientation of the SA carboxyl head during dissociation determining the chosen path. Conformational changes in the portal region of FABP during the ligand binding/unbinding were found to be trivial, and the overturn of the ″cap″ or the unfolding of the α2 helix was not required. This study resolves the long-standing debate on the binding mechanism of SA with the long-flexible tail to FABP, which significantly improves the understanding of the transport mechanism of FABPs and the development of related therapeutic agents.

Counteraction Effects of Ammonium-Based Ionic Liquids on Urea-Induced Denaturation of α-Lactalbumin: A Comprehensive Molecular Simulation Study

Ionic liquids (ILs) are known to stabilize protein conformations in aqueous medium. Importantly, ILs can also act as refolding additives in urea-driven denaturation of proteins. However, despite the importance of the problem, detailed microscopic understanding of the counteraction effects of ILs on urea-induced protein denaturation remains elusive. In this work, atomistic molecular dynamics (MD) simulations of the protein α-lactalbumin have been carried out in pure aqueous medium, in 8 M binary urea-water solution and in ternary urea-IL-water solutions containing ammonium-based ethyl ammonium acetate (EAA) as the IL at different concentrations (1-4 M). Attempts have been made to quantify detailed molecular-level understanding of the origin behind the counteraction effects of the IL on urea-induced partial unfolding of the protein. The calculations revealed significant conformational changes of the protein with multiple free energy minima due to its partial unfolding in binary urea-water solution. The counteraction effect of the IL was evident from the enhanced structural rigidity of the protein with propensity to transform into a single native free energy minimum state in ternary urea-IL-water solutions. Such an effect has been found to be associated with preferential direct binding of the IL components with the protein and simultaneous expulsion of urea from the interface, thereby providing additional stabilization of the protein in ternary solutions. Most importantly, modified rearrangement of the hydrogen bond network at the interface due to the formation of stronger protein-cation (PC) and protein-anion (PA) hydrogen bonds by breaking relatively weaker protein-urea (PU) and protein-water (PW) hydrogen bonds has been recognized as the microscopic origin behind the counteraction effects of EAA on urea-induced partial unfolding of the protein.

Thermodynamics and kinetics of DNA and RNA dinucleotide hybridization to gaps and overhangs

Hybridization of short nucleic acid segments (<4 nt) to single-strand templates occurs as a critical intermediate in processes such as nonenzymatic nucleic acid replication and toehold-mediated strand displacement. These templates often contain adjacent duplex segments that stabilize base pairing with single-strand gaps or overhangs, but the thermodynamics and kinetics of hybridization in such contexts are poorly understood because of the experimental challenges of probing weak binding and rapid structural dynamics. Here we develop an approach to directly measure the thermodynamics and kinetics of DNA and RNA dinucleotide dehybridization using steady-state and temperature-jump infrared spectroscopy. Our results suggest that dinucleotide binding is stabilized through coaxial stacking interactions with the adjacent duplex segments as well as from potential noncanonical base-pairing configurations and structural dynamics of gap and overhang templates revealed using molecular dynamics simulations. We measure timescales for dissociation ranging from 0.2-40 μs depending on the template and temperature. Dinucleotide hybridization and dehybridization involve a significant free energy barrier with characteristics resembling that of canonical oligonucleotides. Together, our work provides an initial step for predicting the stability and kinetics of hybridization between short nucleic acid segments and various templates.

Computational Peptide Design Cotargeting Glucagon and Glucagon-like Peptide-1 Receptors

Peptides are sustainable alternatives to conventional therapeutics for G protein-coupled receptor (GPCR) linked disorders, promising biocompatible and tailorable next-generation therapeutics for metabolic disorders including type-2 diabetes, as agonists of the glucagon receptor (GCGR) and the glucagon-like peptide-1 receptor (GLP-1R). However, single agonist peptides activating GLP-1R to stimulate insulin secretion also suppress obesity-linked glucagon release. Hence, bioactive peptides cotargeting GCGR and GLP-1R may remediate the blood glucose and fatty acid metabolism imbalance, tackling both diabetes and obesity to supersede current monoagonist therapy. Here, we design and model optimized peptide sequences starting from peptide sequences derived from earlier phage-displayed library screening, identifying those with predicted molecular binding profiles for dual agonism of GCGR and GLP-1R. We derive design rules from extensive molecular dynamics simulations based on peptide-receptor binding. Our newly designed coagonist peptide exhibits improved predicted coupled binding affinity for GCGR and GLP-1R relative to endogenous ligands and could in the future be tested experimentally, which may provide superior glycemic and weight loss control.

PEGylation of Insulin and Lysozyme To Stabilize against Thermal Denaturation: A Molecular Dynamics Simulation Study

Biologic drugs or "biologics" (proteins derived from living organisms) are one of the fastest-growing classes of FDA-approved therapeutics. These compounds are often fragile and require conjugation to polymers for stabilization, with many proteins too ephemeral for therapeutic use. During storage or administration, proteins tend to unravel and lose their secondary structure due to changes in solution temperature, pH, and other external stressors. To enhance their lifetime, protein drugs currently in the market are conjugated with polyethylene glycol (PEG), owing to its ability to increase the stability, solubility, and pharmacokinetics of protein drugs. Here, we perform all-atom molecular dynamics simulations to study the unfolding process of egg-white lysozyme and insulin at elevated temperatures. We test the validity of two force fields─CHARMM36 and Amber ff99SB-ILDN─in the unfolding process. By calculating global and local properties, we capture residues that deteriorate first─these are the "weak links" in the proteins. Next, we conjugate both proteins with PEG and find that PEG preserves the native structure of the proteins at elevated temperatures by blocking water molecules from entering the hydrophobic core, thereby causing the secondary structure to stabilize.

Toward a Benchmark for Markov State Models: The Folding of HP35

Adopting a 300 μs long MD trajectory of the folding of villin headpiece (HP35) by D. E. Shaw Research, we recently constructed a Markov state model (MSM) based on inter-residue contacts. The model reproduces the folding time and predicts that the native basin and unfolded region consist of metastable substates that are structurally well-characterized. Recognizing the need to establish well-defined benchmark problems, we study to what extent and in what sense this MSM can be employed as a reference model. Hence, we test the robustness of the MSM by comparing it to models that use alternative combinations of features, dimensionality reduction methods, and clustering schemes. The study suggests some main characteristics of the folding of HP35 that should be reproduced by other competitive models. Moreover, the discussion reveals which parts of the MSM workflow matter most for the considered problem and illustrates the promises and pitfalls of state-based models for the interpretation of biomolecular simulations.

Conformational Fluctuations in β2-Microglubulin Using Markov State Modeling and Molecular Dynamics

Conformational dynamics in proteins can give rise to aggregation prone states during folding, and these kinetically stable states could form oligomers and aggregates. In this study, we investigate the intermediate states and near-folded states of β2-microglobulin and their physico-chemical properties using molecular dynamics and Markov state modeling. Analysis of hundreds of microseconds simulation show the importance of the edge strands in the misfolded states that give rise to a high exposure of hydrophobic residues in the core of the protein that could initiate oligomerization and aggregate formation. Our study sheds light on the first step of aggregation of β2m monomers and gave a better picture of the landscape of protein misfolding and aggregation.

De Novo Design of a β-Helix Tau Protein Scaffold: An Oligomer-Selective Vaccine Immunogen Candidate for Alzheimer's Disease

Tau pathology is associated with many neurodegenerative disorders, including Alzheimer's disease (AD), where the spatio-temporal pattern of tau neurofibrillary tangles strongly correlates with disease progression, which motivates therapeutics selective for misfolded tau. Here, we introduce a new avidity-enhanced, multi-epitope approach for protein-misfolding immunogen design, which is predicted to mimic the conformational state of an exposed epitope in toxic tau oligomers. A predicted oligomer-selective tau epitope 343KLDFK347 was scaffolded by designing a β-helix structure that incorporated multiple instances of the 16-residue tau fragment 339VKSEKLDFKDRVQSKI354. Large-scale conformational ensemble analyses involving Jensen-Shannon Divergence and the embedding depth D showed that the multi-epitope scaffolding approach, employed in designing the β-helix scaffold, was predicted to better discriminate toxic tau oligomers than other "monovalent" strategies utilizing a single instance of an epitope for vaccine immunogen design. Using Rosetta, 10,000 sequences were designed and screened for the linker portions of the β-helix scaffold, along with a C-terminal stabilizing α-helix that interacts with the linkers, to optimize the folded structure and stability of the scaffold. Structures were ranked by energy, and the lowest 1% (82 unique sequences) were verified using AlphaFold. Several selection criteria involving AlphaFold are implemented to obtain a lead-designed sequence. The structure was further predicted to have free energetic stability by using Hamiltonian replica exchange molecular dynamics (MD) simulations. The synthesized β-helix scaffold showed direct binding in surface plasmon resonance (SPR) experiments to several antibodies that were raised to the structured epitope using a designed cyclic peptide. Moreover, the strength of binding of these antibodies to in vitro tau oligomers correlated with the strength of binding to the β-helix construct, suggesting that the construct presents an oligomer-like conformation and may thus constitute an effective oligomer-selective immunogen.

Dynamic structural analysis-based epitope prediction of Exendin-4 in aqueous solution

The study of epitopes has a broad range of applications in drug discovery, vaccine design, and immunotherapy. In this study, an epitope prediction method was developed based on the dynamic structure of protein antigens. Solvent accessible surface area, charge, and root mean square fluctuation were introduced as the key residue property parameters. The epitope prediction algorithm was established by constructing a three-parameter complex metrics of seven-peptide groups. The method was applied to predict the epitopes of Exendin-4, an effective antidiabetic drug. The epitopes of both the natural and C-terminal amidated forms of Exendin-4 were predicted and compared in their folded and intermediate states. In the folded state, the epitopes of natural Exendin-4 (His1-Phe6 and Asp9-Val19) were found to be nearly identical to the epitopes of C-terminal aminated Exendin-4 (His1-Thr7 and Asp9-Val19). In the intermediate state, however, the epitopes of natural Exendin-4 (His1-Gly4, Phe6 and Lys12-Arg20) covered fewer amino acids than the epitopes of C-terminal aminated Exendin-4 (His1-Gly4, Phe6, Asp9-Val19 and Trp25-Lys27). The comparison with the results from other prediction tools demonstrates the reliability of our predicted epitopes of Exendin-4.

Extreme dynamics in a biomolecular condensate

Proteins and nucleic acids can phase-separate in the cell to form concentrated biomolecular condensates^1-4. The functions of condensates span many length scales: they modulate interactions and chemical reactions at the molecular scale⁵, organize biochemical processes at the mesoscale⁶ and compartmentalize cells⁴. Understanding the underlying mechanisms of these processes will require detailed knowledge of the rich dynamics across these scales⁷. The mesoscopic dynamics of biomolecular condensates have been extensively characterized⁸, but their behaviour at the molecular scale has remained more elusive. Here, as an example of biomolecular phase separation, we study complex coacervates of two highly and oppositely charged disordered human proteins⁹. Their dense phase is 1,000 times more concentrated than the dilute phase, and the resulting percolated interaction network¹⁰ leads to a bulk viscosity 300 times greater than that of water. However, single-molecule spectroscopy optimized for measurements within individual droplets reveals that at the molecular scale, the disordered proteins remain exceedingly dynamic, with their chain configurations interconverting on submicrosecond timescales. Massive all-atom molecular dynamics simulations reproduce the experimental observations and explain this apparent discrepancy: the underlying interactions between individual charged side chains are short-lived and exchange on a pico- to nanosecond timescale. Our results indicate that, despite the high macroscopic viscosity of phase-separated systems, local biomolecular rearrangements required for efficient reactions at the molecular scale can remain rapid.

Protein-Mediated Electroporation in a Cardiac Voltage-Sensing Domain Due to an nsPEF Stimulus

This study takes a step in understanding the physiological implications of the nanosecond pulsed electric field (nsPEF) by integrating molecular dynamics simulations and machine learning techniques. nsPEF, a state-of-the-art technology, uses high-voltage electric field pulses with a nanosecond duration to modulate cellular activity. This investigation reveals a relatively new and underexplored phenomenon: protein-mediated electroporation. Our research focused on the voltage-sensing domain (VSD) of the NaV1.5 sodium cardiac channel in response to nsPEF stimulation. We scrutinized the VSD structures that form pores and thereby contribute to the physical chemistry that governs the defibrillation effect of nsPEF. To do so, we conducted a comprehensive analysis involving the clustering of 142 replicas simulated for 50 ns under nsPEF stimuli. We subsequently pinpointed the representative structures of each cluster and computed the free energy between them. We find that the selected VSD of NaV1.5 forms pores under nsPEF stimulation, but in a way that significant differs from the traditional VSD opening. This study not only extends our understanding of nsPEF and its interaction with protein channels but also adds a new effect to further study.

Structural determinants underlying high-temperature adaptation of thermophilic xylanase from hot-spring microorganisms

Thermophilic xylanases from hot-spring microorganisms play potential biological and industrial applications for renewable and sustainable social development. However, high-temperature adaptation mechanisms of these thermophilic xylanases remain elusive at the molecular and evolutionary levels. Here, two recently reported xylanases, named XynDRTY1 and XynM1, from hot springs were subjected to molecular dynamics (MD) simulations at a series of temperature gradients and comparatively analyzed in comparison with the evolutionary background of the xylanase family. Comparative analysis of MD trajectories revealed that the XynM1 exhibits smaller structural dynamics and greater thermal stability than the XynDRTY1, although both share a similar fold architecture with structural differences in the βα_loops. Local regions whose conformational flexibility and regular secondary structure exhibited differences as temperature increases were closely related to the high-temperature adaptation of xylanase, implying that stabilization of these regions is a feasible strategy to improve the thermal stability of xylanases. Furthermore, coevolutionary information from the xylanase family further specified the structural basis of xylanases. Thanks to these results about the sequence, structure, and dynamics of thermophilic xylanases from hot springs, a series of high-temperature-related structural determinants were resolved to promote understanding of the molecular mechanism of xylanase high-temperature adaptation and to provide direct assistance in the improvement of xylanase thermal stability.

Ordered-domain unfolding of thermophilic isolated β subunit ATP synthase

The flexibility of the ATP synthase's β subunit promotes its role in the ATP synthase rotational mechanism, but its domains stability remains unknown. A reversible thermal unfolding of the isolated β subunit (Tβ) of the ATP synthase from Bacillus thermophilus PS3, tracked through circular dichroism and molecular dynamics, indicated that Tβ shape transits from an ellipsoid to a molten globule through an ordered unfolding of its domains, preserving the β-sheet residual structure at high temperature. We determined that part of the stability origin of Tβ is due to a transversal hydrophobic array that crosses the β-barrel formed at the N-terminal domain and the Rossman fold of the nucleotide-binding domain (NBD), while the helix bundle of the C-terminal domain is the less stable due to the lack of hydrophobic residues, and thus the more flexible to trigger the rotational mechanism of the ATP synthase.

Structure Relaxation Approximation (SRA) for Elucidation of Protein Structures from Ion Mobility Measurements (II). Protein Complexes

Characterizing structures of protein complexes and their disease-related aberrations is essential to understanding molecular mechanisms of many biological processes. Electrospray ionization coupled with hybrid ion mobility/mass spectrometry (ESI-IM/MS) methods offer sufficient sensitivity, sample throughput, and dynamic range to enable systematic structural characterization of proteomes. However, because ESI-IM/MS characterizes ionized protein systems in the gas phase, it generally remains unclear to what extent the protein ions characterized by IM/MS have retained their solution structures. Here, we discuss the first application of our computational structure relaxation approximation [Bleiholder, C.; et al. J. Phys. Chem. B 2019, 123 (13), 2756-2769] to assign structures of protein complexes in the range from ∼16 to ∼60 kDa from their "native" IM/MS spectra. Our analysis shows that the computed IM/MS spectra agree with the experimental spectra within the errors of the methods. The structure relaxation approximation (SRA) indicates that native backbone contacts appear largely retained in the absence of solvent for the investigated protein complexes and charge states. Native contacts between polypeptide chains of the protein complex appear to be retained to a comparable extent as contacts within a folded polypeptide chain. Our computations also indicate that the hallmark "compaction" often observed for protein systems in native IM/MS measurements appears to be a poor indicator of the extent to which native residue-residue interactions are lost in the absence of solvent. Further, the SRA indicates that structural reorganization of the protein systems in IM/MS measurements appears driven largely by remodeling of the protein surface that increases its hydrophobic content by approximately 10%. For the systems studied here, this remodeling of the protein surface appears to occur mainly by structural reorganization of surface-associated hydrophilic amino acid residues not associated with β-strand secondary structure elements. Properties related to the internal protein structure, as assessed by void volume or packing density, appear unaffected by remodeling of the surface. Taken together, the structural reorganization of the protein surface appears to be generic in nature and to sufficiently stabilize protein structures to render them metastable on the time scale of IM/MS measurements.

Systematic conformation-to-phenotype mapping via limited deep sequencing of proteins

Non-native conformations drive protein-misfolding diseases, complicate bioengineering efforts, and fuel molecular evolution. No current experimental technique is well suited for elucidating them and their phenotypic effects. Especially intractable are the transient conformations populated by intrinsically disordered proteins. We describe an approach to systematically discover, stabilize, and purify native and non-native conformations, generated in vitro or in vivo, and directly link conformations to molecular, organismal, or evolutionary phenotypes. This approach involves high-throughput disulfide scanning (HTDS) of the entire protein. To reveal which disulfides trap which chromatographically resolvable conformers, we devised a deep-sequencing method for double-Cys variant libraries of proteins that precisely and simultaneously locates both Cys residues within each polypeptide. HTDS of the abundant E. coli periplasmic chaperone HdeA revealed distinct classes of disordered hydrophobic conformers with variable cytotoxicity depending on where the backbone was cross-linked. HTDS can bridge conformational and phenotypic landscapes for many proteins that function in disulfide-permissive environments.

Molecular Dynamics Simulations of HPr Proteins from a Thermophilic and a Mesophilic Organism: A Comparative Thermal Study

The histidine-containing phosphocarrier (HPr) is a monomeric protein conserved in Gram-positive bacteria, which may be of mesophilic or thermophilic nature. In particular, the HPr protein from the thermophilic organism B. stearothermophilus is a good model system for thermostability studies, since experimental data, such as crystal structure and thermal stability curves, are available. However, its unfolding mechanism at higher temperatures is yet unclear at a molecular level. Therefore, in this work, we researched the thermal stability of this protein using molecular dynamics simulations, subjecting it to five different temperatures during a time span of 1 μs. The analyses of the structural parameters and molecular interactions were compared with those of the mesophilic homologue HPr protein from B. subtilis. Each simulation was run in triplicate using identical conditions for both proteins. The results showed that the two proteins lose stability as the temperature increases, but the mesophilic structure is more affected. We found that the salt bridge network formed by the triad of Glu3-Lys62-Glu36 residues and the salt bridge made up of Asp79-Lys83 ion pair are key factors to keep stable the thermophilic protein, maintaining the hydrophobic core protected and the structure packed. In addition, these molecular interactions neutralize the negative surface charge, acting as "natural molecular staples".

Globular Proteins and Where to Find Them within a Polymer Brush-A Case Study

Protein adsorption by polymerized surfaces is an interdisciplinary topic that has been approached in many ways, leading to a plethora of theoretical, numerical and experimental insight. There is a wide variety of models trying to accurately capture the essence of adsorption and its effect on the conformations of proteins and polymers. However, atomistic simulations are case-specific and computationally demanding. Here, we explore universal aspects of the dynamics of protein adsorption through a coarse-grained (CG) model, that allows us to explore the effects of various design parameters. To this end, we adopt the hydrophobic-polar (HP) model for proteins, place them uniformly at the upper bound of a CG polymer brush whose multibead-spring chains are tethered to a solid implicit wall. We find that the most crucial factor affecting the adsorption efficiency appears to be the polymer grafting density, while the size of the protein and its hydrophobicity ratio come also into play. We discuss the roles of ligands and attractive tethering surfaces to the primary adsorption as well as secondary and ternary adsorption in the presence of attractive (towards the hydrophilic part of the protein) beads along varying spots of the backbone of the polymer chains. The percentage and rate of adsorption, density profiles and the shapes of the proteins, alongside with the respective potential of mean force are recorded to compare the various scenarios during protein adsorption.

Comparison of On-the-Fly Probability Enhanced Sampling and Parallel Tempering Combined with Metadynamics for Atomistic Simulations of RNA Tetraloop Folding

Atomistic simulations with reliable models are extremely useful in providing exquisitely detailed pictures of biomolecular phenomena that are not always accessible to experiments. One such biomolecular phenomenon is RNA folding, which often requires exhaustive simulations with combined advanced sampling techniques. In this work, we employed the multithermal-multiumbrella on-the-fly probability enhanced sampling (MM-OPES) technique and compared it against combined parallel tempering and metadynamics simulations. We found that MM-OPES simulations were successful in reproducing the free energy surfaces from combined parallel tempering and metadynamics simulations. Importantly, we also investigated a wide range of temperature sets (minimum and maximum temperatures) for MM-OPES simulations in order to identify some guidelines for deciding the temperature limits for an accurate and efficient exploration of the free energy landscapes. We found that most temperature sets yielded almost the same accuracy in reproducing the free energy surface at the ambient conditions as long as (i) the maximum temperature is reasonably high, (ii) the temperature at which we run the simulation is reasonably high (in our simulations, running temperature is defined as [minimum temperature + maximum temperature]/2), and (iii) the effective sample size at the temperature of interest is statistically reasonable. In terms of the computational cost, all MM-OPES simulations were nearly 4 times less costly than the combined parallel tempering and metadynamics simulations. We concluded that the demanding combined parallel tempering and metadynamics simulations can safely be replaced with approximately 4 times less costly MM-OPES simulations (with carefully selected temperature limits) to obtain the same information.