Protein Motions Research Articles

Functional binding dynamics relevant to the evolution of zoonotic spillovers in endemic and emergent Betacoronavirus strains

Comparative functional analysis of the dynamic interactions between various Betacoronavirus mutant strains and broadly utilized target proteins such as ACE2 and CD26, is crucial for a more complete understanding of zoonotic spillovers of viruses that cause diseases such as COVID-19. Here, we employ machine learning to replicated sets of nanosecond scale GPU accelerated molecular dynamics simulations to statistically compare and classify atom motions of these target proteins in both the presence and absence of different endemic and emergent strains of the viral receptor binding domain (RBD) of the S spike glycoprotein. A multi-agent classifier successfully identified functional binding dynamics that are evolutionarily conserved from bat CoV-HKU4 to human endemic/emergent strains. Conserved dynamics regions of ACE2 involve both the N-terminal helices, as well as a region of more transient dynamics encompassing residues K353, Q325 and a novel motif AAQPFLL 386-92 that appears to coordinate their dynamic interactions with the viral RBD at N501. We also demonstrate that the functional evolution of Betacoronavirus zoonotic spillovers involving ACE2 interaction dynamics are likely pre-adapted from two precise and stable binding sites involving the viral bat progenitor strain’s interaction with CD26 at SAMLI 291-5 and SS 333-334. Our analyses further indicate that the human endemic strains hCoV-HKU1 and hCoV-OC43 have evolved more stable N-terminal helix interactions through enhancement of an interfacing loop region on the viral RBD, whereas the highly transmissible SARS-CoV-2 variants (B.1.1.7, B.1.351 and P.1) have evolved more stable viral binding via more focused interactions between the viral N501 and ACE2 K353 alone. Communicated by Ramaswamy H. Sarma

Systematic Structure-Based Search for Ochratoxin-Degrading Enzymes in Proteomes from Filamentous Fungi.

(1) Background: ochratoxins are mycotoxins produced by filamentous fungi with important implications in the food manufacturing industry due to their toxicity. Decontamination by specific ochratoxin-degrading enzymes has become an interesting alternative for the treatment of contaminated food commodities. (2) Methods: using a structure-based approach based on homology modeling, blind molecular docking of substrates and characterization of low-frequency protein motions, we performed a proteome mining in filamentous fungi to characterize new enzymes with potential ochratoxinase activity. (3) Results: the proteome mining results demonstrated the ubiquitous presence of fungal binuclear zinc-dependent amido-hydrolases with a high degree of structural homology to the already characterized ochratoxinase from Aspergillus niger. Ochratoxinase-like enzymes from ochratoxin-producing fungi showed more favorable substrate-binding pockets to accommodate ochratoxins A and B. (4) Conclusions: filamentous fungi are an interesting and rich source of hydrolases potentially capable of degrading ochratoxins, and could be used for the detoxification of diverse food commodities.

Dynamic Connection between Enzymatic Catalysis and Collective Protein Motions.

Enzymes employ a wide range of protein motions to achieve efficient catalysis of chemical reactions. While the role of collective protein motions in substrate binding, product release, and regulation of enzymatic activity is generally understood, their roles in catalytic steps per se remain uncertain. Here, molecular dynamics simulations, enzyme kinetics, X-ray crystallography, and nuclear magnetic resonance spectroscopy are combined to elucidate the catalytic mechanism of adenylate kinase and to delineate the roles of catalytic residues in catalysis and the conformational change in the enzyme. This study reveals that the motions in the active site, which occur on a time scale of picoseconds to nanoseconds, link the catalytic reaction to the slow conformational dynamics of the enzyme by modulating the free energy landscapes of subdomain motions. In particular, substantial conformational rearrangement occurs in the active site following the catalytic reaction. This rearrangement not only affects the reaction barrier but also promotes a more open conformation of the enzyme after the reaction, which then results in an accelerated opening of the enzyme compared to that of the reactant state. The results illustrate a linkage between enzymatic catalysis and collective protein motions, whereby the disparate time scales between the two processes are bridged by a cascade of intermediate-scale motion of catalytic residues modulating the free energy landscapes of the catalytic and conformational change processes.

Understanding the Binding Transition State After the Conformational Selection Step: The Second Half of the Molecular Recognition Process Between NS1 of the 1918 Influenza Virus and Host p85β.

Biomolecular recognition often involves conformational changes as a prerequisite for binding (i.e., conformational selection) or concurrently with binding (i.e., induced-fit). Recent advances in structural and kinetic approaches have enabled the detailed characterization of protein motions at atomic resolution. However, to fully understand the role of the conformational dynamics in molecular recognition, studies on the binding transition state are needed. Here, we investigate the binding transition state between nonstructural protein 1 (NS1) of the pandemic 1918 influenza A virus and the human p85β subunit of PI3K. 1918 NS1 binds to p85β via conformational selection. We present the free-energy mapping of the transition and bound states of the 1918 NS1:p85β interaction using linear free energy relationship and ϕ-value analyses. We find that the binding transition state of 1918 NS1 and p85β is structurally similar to the bound state with well-defined binding orientation and hydrophobic interactions. Our finding provides a detailed view of how protein motion contributes to the development of intermolecular interactions along the binding reaction coordinate.

Probing the small-scale protein motions with a laboratory X-ray

An ordinary laboratory X-ray could be used to characterize the molecular motions of a wide variety of biological molecules.

Remdesivir Strongly Binds to RNA-Dependent RNA Polymerase, Membrane Protein, and Main Protease of SARS-CoV-2: Indication From Molecular Modeling and Simulations.

Development of new drugs is a time-taking and expensive process. Comprehensive efforts are being made globally toward the search of therapeutics against SARS-CoV-2. Several drugs such as remdesivir, favipiravir, ritonavir, and lopinavir have been included in the treatment regimen and shown effective results in several cases. Among the existing broad-spectrum antiviral drugs, remdesivir is found to be more effective against SARS-CoV-2. Remdesivir has broad-spectrum antiviral action against many single-stranded RNA viruses including pathogenic SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). In this study, we proposed that remdesivir strongly binds to membrane protein (Mprotein), RNA-dependent RNA polymerase (RDRP), and main protease (Mprotease) of SARS-CoV-2. It might show antiviral activity by inhibiting more than one target. It has been found that remdesivir binds to Mprotease, Mprotein, and RDRP with −7.8, −7.4, and −7.1 kcal/mol, respectively. The structure dynamics study suggested that binding of remdesivir leads to unfolding of RDRP. It has been found that strong binding of remdesivir to Mprotein leads to decrease in structural deviations and gyrations. Additionally, the average solvent-accessible surface area of Mprotein decreases from 127.17 to 112.12 nm2, respectively. Furthermore, the eigenvalues and the trace of the covariance matrix were found to be low in case of Mprotease–remdesivir, Mprotein–remdesivir, and RDRP–remdesivir. Binding of remdesivir to Mprotease, Mprotein, and RDRP reduces the average motions in protein due to its strong binding. The MMPBSA calculations also suggested that remdesivir has strong binding affinity with Mprotein, Mprotease, and RDRP. The detailed analysis suggested that remdesivir has more than one target of SARS-CoV-2.

Linkage of nanosecond protein motion with enzymatic methyl transfer by nicotinamide N-methyltransferase.

Nicotinamide N-methyltransferase (NNMT), a key cytoplasmic protein in the human body, is accountable to catalyze the nicotinamide (NCA) N1-methylation through S-adenosyl-L-methionine (SAM) as a methyl donor, which has been linked to many diseases. Although extensive studies have concerned about the biological aspect, the detailed mechanism study of the enzyme function, especially in the part of protein dynamics is lacking. Here, wild-type nicotinamide N-methyltransferase together with the mutation at position 20 with Y20F, Y20G, and free tryptophan were carried out to explore the connection between protein dynamics and catalysis using time-resolved fluorescence lifetimes. The results show that wild-type nicotinamide N-methyltransferase prefers to adapt a less flexible protein conformation to achieve enzyme catalysis.

Protons Are Fast and Smart; Proteins Are Slow and Dumb: On the Relationship of Electrospray Ionization Charge States and Conformations.

We present simple considerations of how differences in time scales of motions of protons, the lightest and fastest chemical moiety, and the much longer time scales associated with the dynamics of proteins, among the heaviest and slowest analytes, may allow many protein conformations from solution to be kinetically trapped during the process of electrospraying protein solutions into the gas phase. In solution, the quantum nature of protons leads them to change locations by tunneling, an instantaneous process; moreover, the Grotthuss mechanism suggests that these small particles can respond nearly instantaneously to the dynamic motions of proteins that occur on much longer time scales. A conformational change is accompanied by favorable or unfavorable variations in the free energy of the system, providing the impetus for solvent ↔ protein proton exchange. Thus, as thermal distributions of protein conformations interconvert, protonation states rapidly respond, as specific acidic and basic sites are exposed or protected. In the vacuum of the mass spectrometer, protons become immobilized in locations that are specific to the protein conformations from which they were incorporated. In this way, conformational states from solution are preserved upon electrospraying them into the gas phase. These ideas are consistent with the exquisite sensitivity of electrospray mass spectra to small changes of the local environment that alter protein structure in solution. We might remember this approximation for the protonation of proteins in solution with the colloquial expression-protons are fast and smart; proteins are slow and dumb.

Efforts to Generate a Male Contraception Just by Prevention of Sperm Motility Acquirement in Epididymis Without Influencing the Physiology of Spermatogenesis: Yet Still a Little Far Goal

In view of the world population escalating at an alarming rate anticipated population will reach 9.8 billion by 2050. In contrast to female contraceptive measures male contraceptive methods are relatively negligible. Maximum researchers have concentrated on generation of male contraceptive methods by trying to modulate hormones but had to abandon this strategy as the pharmaceutical companies were not happy in view of marked adverse actions. Maximum nonhormonal strategies in research concentrate on spermatogenesis repression or reversible physical barriers. Sperm motility represents one of the maximum significant markers of semen quality as it is necessary for sperm motion appropriately in the female reproductive tract for it to arrive intricately towards the egg as well as fertilize it. The group of Vijayraghavan S, et al. have been concentrating on generation of a male contraceptive by utilization of targeting sperm motility at epididymal level by extensively studying the regulation of flaggelar protein motion by various subunits like Protein Phosphatase 1 (PP1), Protein Phosphatase Inhibitor-2 (PPPIR2), its phosphorylation by Glycogen Synthase Kinase-3 (GSK3), A kinase anchor protein 4(AKAP4). Recently they attempted to generate a bioportide that could simulate binding of the anchor protein AKAP4 that had been earlier revealed as a PPγ2 interactor in human sperm,that are implicated in sperm motility .Unfortunately that did not abolish sperm motility completely .This seemed to be surprising as PP1/ PPPIR2crosstalk seems to be central in regulation of sperm motility. Thus Silva et al., pointed that evaluation of the probable part of PPPIR7 as well as PPPIR11 in the manipulation of sperm motility in men might be the aim of future studies that needs to be continued to get more insight in this field.

Finding Druggable Sites in Proteins Using TACTICS.

Structure-based drug discovery efforts require knowledge of where drug-binding sites are located on target proteins. To address the challenge of finding druggable sites, we developed a machine-learning algorithm called TACTICS (trajectory-based analysis of conformations to identify cryptic sites), which uses an ensemble of molecular structures (such as molecular dynamics simulation data) as input. First, TACTICS uses k-means clustering to select a small number of conformations that represent the overall conformational heterogeneity of the data. Then, TACTICS uses a random forest model to identify potentially bindable residues in each selected conformation, based on protein motion and geometry. Lastly, residues in possible binding pockets are scored using fragment docking. As proof-of-principle, TACTICS was applied to the analysis of simulations of the SARS-CoV-2 main protease and methyltransferase and the Yersinia pestis aryl carrier protein. Our approach recapitulates known small-molecule binding sites and predicts the locations of sites not previously observed in experimentally determined structures. The TACTICS code is available at https://github.com/Albert-Lau-Lab/tactics_protein_analysis.

Does Electric Friction Matter in Living Cells?

The thermal motion of charged proteins causes randomly fluctuating electric fields inside cells. According to the fluctuation–dissipation theorem, there is an additional friction force associated with such fluctuations. However, the impact of these fluctuations on the diffusion and dynamics of proteins in the cytoplasm is unclear. Here, we provide an order-of-magnitude estimate of this effect by treating electric field fluctuations within a generalized Langevin equation model with a time-dependent friction memory kernel. We find that electric friction is generally negligible compared to solvent friction. However, a significant slowdown of protein diffusion and dynamics is expected for biomolecules with high net charges such as intrinsically disordered proteins and RNA. The results show that direct contacts between biomolecules in a cell are not necessarily required to alter their dynamics.

Cryo-kinetics Reveal Dynamic Effects on the Chemistry of Human Dihydrofolate Reductase.

Effects of isotopic substitution on the rate constants of human dihydrofolate reductase (HsDHFR), an important target for anti‐cancer drugs, have not previously been characterized due to its complex fast kinetics. Here, we report the results of cryo‐measurements of the kinetics of the HsDHFR catalyzed reaction and the effects of protein motion on catalysis. Isotopic enzyme labeling revealed an enzyme KIE (k H LE/k H HE) close to unity above 0 °C; however, the enzyme KIE was increased to 1.72±0.15 at −20 °C, indicating that the coupling of protein motions to the chemical step is minimized under optimal conditions but enhanced at non‐physiological temperatures. The presented cryogenic approach provides an opportunity to probe the kinetics of mammalian DHFRs, thereby laying the foundation for characterizing their transition state structure.

Glutarate Hydroxylation by the Carbon Starvation-Induced Protein D: A Computational Study into the Stereo- and Regioselectivities of the Reaction.

The carbon starvation-induced protein D (CsiD) is a recently characterized iron(II)/α-ketoglutarate-dependent oxygenase that activates a glutarate molecule as substrate at the C2 position to exclusively produce (S)-2-hydroxyglutarate products. This selective hydroxylation reaction by CsiD is an important component of the lysine biodegradation pathway in Escherichia coli; however, little is known on the details and the origin of the selectivity of the reaction. So far, experimental studies failed to trap and characterize any short-lived catalytic cycle intermediates. As no computational studies have been reported on this enzyme either, we decided to investigate the chemical reaction mechanism of glutarate activation by an iron(IV)-oxo model of the CsiD enzyme. In this work, we present a density functional theory study on a large active site cluster model of CsiD and investigate the glutarate hydroxylation pathways by a high-valent iron(IV)-oxo species leading to (S)-2-hydroxyglutarate, (R)-2-hydroxyglutarate, and 3-hydroxyglutarate. In agreement with experimental observation, the favorable product channel leads to pro-S C2-H hydrogen atom abstraction to form (S)-2-hydroxyglutarate. The reaction is stepwise with a hydrogen atom abstraction by an iron(IV)-oxo species followed by OH rebound from a radical intermediate. The work presented in this paper shows that despite the fact that the C-H bond strengths at the C2 and C3 positions of glutarate are similar in the gas phase, substrate binding and positioning guide the reaction to an enantioselective reaction process by destabilizing the hydrogen atom abstraction pathways for the pro-R C2-H and C3-H positions. Our studies predict the chemical properties of the iron(IV)-oxo species and its rate constants with glutarate and deuterated-glutarate. Moreover, the work shows little protein motions during the catalytic process, while the substrate entrance into the substrate binding pocket appears to be guided by three active site arginine residues that position the substrate for pro-S C2-H hydrogen atom abstraction. Finally, the calculations show that irrespective of the position of the substrate and what C-H bond is closest to the metal center, the lowest energy pathway is for a selective pro-S C2-H hydrogen atom abstraction.

Comparison between slow anisotropic LE4PD fluctuations and the principal component analysis modes of ubiquitin.

The biological function and folding mechanisms of proteins are often guided by large-scale slow motions, which involve crossing high energy barriers. In a simulation trajectory, these slow fluctuations are commonly identified using a principal component analysis (PCA). Despite the popularity of this method, a complete analysis of its predictions based on the physics of protein motion has been so far limited. This study formally connects the PCA to a Langevin model of protein dynamics and analyzes the contributions of energy barriers and hydrodynamic interactions to the slow PCA modes of motion. To do so, we introduce an anisotropic extension of the Langevin equation for protein dynamics, called the LE4PD-XYZ, which formally connects to the PCA "essential dynamics." The LE4PD-XYZ is an accurate coarse-grained diffusive method to model protein motion, which describes anisotropic fluctuations in the alpha carbons of the protein. The LE4PD accounts for hydrodynamic effects and mode-dependent free-energy barriers. This study compares large-scale anisotropic fluctuations identified by the LE4PD-XYZ to the mode-dependent PCA predictions, starting from a microsecond-long alpha carbon molecular dynamics atomistic trajectory of the protein ubiquitin. We observe that the inclusion of free-energy barriers and hydrodynamic interactions has important effects on the identification and timescales of ubiquitin's slow modes.

Identification of key residues in protein functional movements by using molecular dynamics simulations combined with a perturbation-response scanning method

The realization of protein functional movement is usually accompanied by specific conformational changes, and there exist some key residues that mediate and control the functional motions of proteins in the allosteric process. In the present work, the perturbation-response scanning method developed by our group was combined with the molecular dynamics (MD) simulation to identify the key residues controlling the functional movement of proteins. In our method, a physical quantity that is directly related to protein specific function was introduced, and then based on the MD simulation trajectories, the perturbation-response scanning method was used to identify the key residues for functional motions, in which the residues that highly correlated with the fluctuation of the function-related quantity were identified as the key residues controlling the specific functional motions of the protein. Two protein systems, i.e., the heat shock protein 70 and glutamine binding protein, were selected as case studies to validate the effectiveness of our method. Our calculated results are in good agreement with the experimental results. The location of the key residues in the two proteins are similar, indicating the similar mechanisms behind the performance of their biological functions.

The Role of Rigid Residues in Modulating TEM-1 β-Lactamase Function and Thermostability.

The relationship between protein motions (i.e., dynamics) and enzymatic function has begun to be explored in β-lactamases as a way to advance our understanding of these proteins. In a recent study, we analyzed the dynamic profiles of TEM-1 (a ubiquitous class A β-lactamase) and several ancestrally reconstructed homologues. A chief finding of this work was that rigid residues that were allosterically coupled to the active site appeared to have profound effects on enzyme function, even when separated from the active site by many angstroms. In the present work, our aim was to further explore the implications of protein dynamics on β-lactamase function by altering the dynamic profile of TEM-1 using computational protein design methods. The Rosetta software suite was used to mutate amino acids surrounding either rigid residues that are highly coupled to the active site or to flexible residues with no apparent communication with the active site. Experimental characterization of ten designed proteins indicated that alteration of residues surrounding rigid, highly coupled residues, substantially affected both enzymatic activity and stability; in contrast, native-like activities and stabilities were maintained when flexible, uncoupled residues, were targeted. Our results provide additional insight into the structure-function relationship present in the TEM family of β-lactamases. Furthermore, the integration of computational protein design methods with analyses of protein dynamics represents a general approach that could be used to extend our understanding of the relationship between dynamics and function in other enzyme classes.

Rotational dynamics of proteins in nanochannels: role of solvent’s local viscosity

Viscosity variation of solvent in local regions near a solid surface, be it a biological surface of a protein or an engineered surface of a nanoconfinement, is a direct consequence of intermolecular interactions between the solid body and the solvent. The current coarse-grained molecular dynamics study takes advantage of this phenomenon to investigate the anomaly in a solvated protein’s rotational dynamics confined using a representative solid matrix. The concept of persistence time, the characteristic time of structural reordering in liquids, is used to compute the solvent’s local viscosity. With an increase in the degree of confinement, the confining matrix significantly influences the solvent molecule’s local viscosity present in the protein hydration layer through intermolecular interactions. This effect contributes to the enhanced drag force on protein motion, causing a reduction in the rotational diffusion coefficient. Simulation results suggest that the direct matrix-protein non-bonded interaction is responsible for the occasional jump and discontinuity in orientational motion when the protein is in very tight confinement.

Intermediate scattering functions of a rigid body monoclonal antibody protein in solution studied by dissipative particle dynamic simulation.

In the past decade, there was increased research interest in studying internal motions of flexible proteins in solution using Neutron Spin Echo (NSE) as NSE can simultaneously probe the dynamics at the length and time scales comparable to protein domain motions. However, the collective intermediate scattering function (ISF) measured by NSE has the contributions from translational, rotational, and internal motions, which are rather complicated to be separated. Widely used NSE theories to interpret experimental data usually assume that the translational and rotational motions of a rigid particle are decoupled and independent to each other. To evaluate the accuracy of this approximation for monoclonal antibody (mAb) proteins in solution, dissipative particle dynamic computer simulation is used here to simulate a rigid-body mAb for up to about 200 ns. The total ISF together with the ISFs due to only the translational and rotational motions as well as their corresponding effective diffusion coefficients is calculated. The aforementioned approximation introduces appreciable errors to the calculated effective diffusion coefficients and the ISFs. For the effective diffusion coefficient, the error introduced by this approximation can be as large as about 10% even though the overall agreement is considered reasonable. Thus, we need to be cautious when interpreting the data with a small signal change. In addition, the accuracy of the calculated ISFs due to the finite computer simulation time is also discussed.

Mathematical Modeling in Biology: Part 2. Models of Protein Interaction Processes in a Photosynthetic Membrane

The second part of the article concerns agent-based, multiparticle, Brownian and molecular dynamic models. In these models, the motion and interaction of individual proteins—electron carriers (Brownian multiparticle models) and individual atoms in molecules—electron carriers and their complexes (molecular dynamics) are described based on the apparatus of Brownian and molecular modeling. Direct multiparticle models explicitly simulate the Brownian diffusion of mobile protein carriers and their electrostatic interactions with multienzyme complexes, both in solution and in the interior of a biomembrane. Analysis of these models reveals the role of diffusion and electrostatic factors in the regulation of electron transport, the effect of the of reaction volume geometry, and ionic strength and pH of the cell medium on the rate of electron transport reactions between protein carriers. Through joint application methods of kinetic and Brownian multiparticle modeling make it possible to study the regulation mechanisms of electron transport processes at the subcellular and molecular levels and also mechanisms of electron-flow switching in plant and algae cells and to evaluate the optimal conditions for the obtainment of target products in microalgae cells, e.g., hydrogen as an alternative fuel. The prospects for various methods of mathematical modeling used to study subcellular systems are discussed in the conclusion. The paper is based on the results obtained at the Department of Biophysics, Biological Faculty, Moscow State University.

Quantifying steric hindrance and topological obstruction to protein structure superposition

BackgroundIn computational structural biology, structure comparison is fundamental for our understanding of proteins. Structure comparison is, e.g., algorithmically the starting point for computational studies of structural evolution and it guides our efforts to predict protein structures from their amino acid sequences. Most methods for structural alignment of protein structures optimize the distances between aligned and superimposed residue pairs, i.e., the distances traveled by the aligned and superimposed residues during linear interpolation. Considering such a linear interpolation, these methods do not differentiate if there is room for the interpolation, if it causes steric clashes, or more severely, if it changes the topology of the compared protein backbone curves.ResultsTo distinguish such cases, we analyze the linear interpolation between two aligned and superimposed backbones. We quantify the amount of steric clashes and find all self-intersections in a linear backbone interpolation. To determine if the self-intersections alter the protein’s backbone curve significantly or not, we present a path-finding algorithm that checks if there exists a self-avoiding path in a neighborhood of the linear interpolation. A new path is constructed by altering the linear interpolation using a novel interpretation of Reidemeister moves from knot theory working on three-dimensional curves rather than on knot diagrams. Either the algorithm finds a self-avoiding path or it returns a smallest set of essential self-intersections. Each of these indicates a significant difference between the folds of the aligned protein structures. As expected, we find at least one essential self-intersection separating most unknotted structures from a knotted structure, and we find even larger motions in proteins connected by obstruction free linear interpolations. We also find examples of homologous proteins that are differently threaded, and we find many distinct folds connected by longer but simple deformations. TM-align is one of the most restrictive alignment programs. With standard parameters, it only aligns residues superimposed within 5 Ångström distance. We find 42165 topological obstructions between aligned parts in 142068 TM-alignments. Thus, this restrictive alignment procedure still allows topological dissimilarity of the aligned parts.ConclusionsBased on the data we conclude that our program ProteinAlignmentObstruction provides significant additional information to alignment scores based solely on distances between aligned and superimposed residue pairs.