Intrinsic Protein Dynamics Research Articles

Artificial intelligence-based HDX (AI-HDX) prediction reveals fundamental characteristics to protein dynamics: Mechanisms on SARS-CoV-2 immune escape

Three-dimensional structure and dynamics are essential for protein function. Advancements in hydrogen-deuterium exchange (HDX) techniques enable probing protein dynamic information in physiologically relevant conditions. HDX-coupled mass spectrometry (HDX-MS) has been broadly applied in pharmaceutical industries. However, it is challenging to obtain dynamics information at the single amino acid resolution and time consuming to perform the experiments and process the data. Here, we demonstrate the first deep learning model, artificial intelligence-based HDX (AI-HDX), that predicts intrinsic protein dynamics based on the protein sequence. It uncovers the protein structural dynamics by combining deep learning, experimental HDX, sequence alignment, and protein structure prediction. AI-HDX can be broadly applied to drug discovery, protein engineering, and biomedical studies. As a demonstration, we elucidated receptor-binding domain structural dynamics as a potential mechanism of anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody efficacy and immune escape. AI-HDX fundamentally differs from the current AI tools for protein analysis and may transform protein design for various applications.

Computational and Functional Insights of Protein Misfolding in Neurodegeneration.

Protein folding is the process by which a polypeptide chain self-assembles into the correct three-dimensional structure, so that it ends up in the biologically active, native state. Under conditions of proteotoxic stress, mutations, or cellular aging, proteins can begin to aggregate into non-native structures such as ordered amyloid fibrils and plaques. Many neurodegenerative diseases involve the misfolding and aggregation of specific proteins into abnormal, toxic species. Experimental approaches including crystallography and AFM (atomic force microscopy)-based force spectroscopy are used to exploit the folding and structural characterization of protein molecules. At the same time, computational techniques through molecular dynamics, fold recognition, and structure prediction are widely applied in this direction. Benchmarking analysis for combining and comparing computational methodologies with functional studies can decisively unravel robust interactions between the side groups of the amino acid sequence and monitor alterations in intrinsic protein dynamics with high precision as well as adequately determine potent conformations of the folded patterns formed in the polypeptide structure.

Explicit versus implicit consideration of binding partners in protein-protein complex to elucidate intrinsic dynamics.

The binding of many proteins to their protein partners is tightly regulated via control of their relative intrinsic dynamics during the binding process, a phenomenon which can in turn be modulated. Therefore, investigating the intrinsic dynamics of proteins is necessary to understand function in a comprehensive way. By intrinsic dynamics herein, we principally refer to the vibrational signature of a protein molecule popularly obtained from normal modes or essential modes. For normal modes, one often considers that the molecule under investigation is a collection of springs in a solvent-free or implicit-solvent medium. In the context of a protein-binding partner, the analysis of vibration of the target protein is often complicated due to molecular interaction within the complex. Generally, it is assumed that the isolated bound conformation of the target protein captures the implicit effect of the binding partner on the intrinsic dynamics, therefore suggesting that any influence of the partner molecule is also already integrated. Such an assumption allows large-scale studies of the conservation of protein flexibility. However, in cases where a partner protein directly influences the vibration of the target via critical contacts at the protein-protein interface, the above assumption falls short of providing a detailed view. In this review article, we discuss the implications of considering the dynamics of a protein in a protein-protein complex, as modelled implicitly and explicitly with methods dependent on elastic network models. We further propose how such an explicit consideration can be applied to understand critical protein-protein contacts that can be targeted in future studies.

Conserved conformational dynamics determine enzyme activity.

Homologous enzymes often exhibit different catalytic rates despite a fully conserved active site. The canonical view is that an enzyme sequence defines its structure and function and, more recently, that intrinsic protein dynamics at different time scales enable and/or promote catalytic activity. Here, we show that, using the protein tyrosine phosphatase PTP1B, residues surrounding the PTP1B active site promote dynamically coordinated chemistry necessary for PTP1B function. However, residues distant to the active site also undergo distinct intermediate time scale dynamics and these dynamics are correlated with its catalytic activity and thus allow for different catalytic rates in this enzyme family. We identify these previously undetected motions using coevolutionary coupling analysis and nuclear magnetic resonance spectroscopy. Our findings strongly indicate that conserved dynamics drives the enzymatic activity of the PTP family. Characterization of these conserved dynamics allows for the identification of novel regulatory elements (therapeutic binding pockets) that can be leveraged for the control of enzymes.

Large-Scale Conformational Changes of FhaC Provide Insights Into the Two-Partner Secretion Mechanism.

The Two-Partner secretion pathway mediates protein transport across the outer membrane of Gram-negative bacteria. TpsB transporters belong to the Omp85 superfamily, whose members catalyze protein insertion into, or translocation across membranes without external energy sources. They are composed of a transmembrane β barrel preceded by two periplasmic POTRA domains that bind the incoming protein substrate. Here we used an integrative approach combining in vivo assays, mass spectrometry, nuclear magnetic resonance and electron paramagnetic resonance techniques suitable to detect minor states in heterogeneous populations, to explore transient conformers of the TpsB transporter FhaC. This revealed substantial, spontaneous conformational changes on a slow time scale, with parts of the POTRA2 domain approaching the lipid bilayer and the protein’s surface loops. Specifically, our data indicate that an amphipathic POTRA2 β hairpin can insert into the β barrel. We propose that these motions enlarge the channel and initiate substrate secretion. Our data propose a solution to the conundrum how TpsB transporters mediate protein secretion without the need for cofactors, by utilizing intrinsic protein dynamics.

Detecting Individual Proteins and Their Surface Charge Variations in Solution by the Potentiometric Nanoimpact Method.

Label-free detection and analysis of proteins in their natural form and their dynamic interactions with substrates at the single-molecule level are important for both fundamental studies and various applications. Herein, we demonstrate a simple potentiometric method to achieve this goal by detecting the native charge of protein in solution by utilizing the principle of single-entity electrochemistry techniques. When a charged protein moves near the vicinity of a floating carbon nanoelectrode connected to a high-impedance voltage meter, the distinct local electrostatic potential changes induced by the transient collision event of protein, also called the "nanoimpact" event, can be captured by the nanoelectrode as a potential probe. This potentiometric method is highly sensitive for charged proteins, and low-molecular-weight proteins less than 10 kDa can be detected in low-salt-concentration electrolytes. By analyzing the shape and magnitude of the recorded time-resolved potential change and its time derivative, we can reveal the charge and motion of the protein in the nonspecific protein-surface interaction event. The charge polarity variations of the proteins at different pH values were also successfully probed. Compared with synthetic spherical nanoparticles, the statistical analysis of many single-molecule nanoimpact events revealed a large variation in the recorded transient potential signals, which may be attributed to the intrinsic protein dynamics and surface charge heterogeneity, as suggested by the finite element method and molecular dynamic simulations.

Intrinsic Dynamics of Protein-Peptide Unbinding.

The dynamics of peptide-protein binding and unbinding of a variant of the RNase S system has been investigated. To initiate the process, a photoswitchable azobenzene moiety has been covalently linked to the S-peptide, thereby switching its binding affinity to the S-protein. Transient fluorescence quenching was measured with the help of a time-resolved fluorometer, which has been specifically designed for these experiments and is based on inexpensive light-emitting diodes and laser diodes only. One mutant shows on-off behavior with no specific binding detectable in one of the states of the photoswitch. Unbinding is faster by at least 2 orders of magnitude, compared to that of other variants of the RNase S system. We conclude that unbinding is essentially barrier-less in that case, revealing the intrinsic dynamics of the unbinding event, which occurs on a time scale of a few hundred microseconds in a strongly stretched-exponential manner.

Membrane Environment Modulates Ligand-Binding Propensity of P2Y12 Receptor.

The binding of natural ligands and synthetic drugs to the P2Y12 receptor is of great interest because of its crucial role in platelets activation and the therapy of arterial thrombosis. Up to now, all computational studies of P2Y12 concentrated on the available crystal structures, while the role of intrinsic protein dynamics and the membrane environment in the functioning of P2Y12 was not clear. In this work, we performed all-atom molecular dynamics simulations of the full-length P2Y12 receptor in three different membrane environments and in two possible conformations derived from available crystal structures. The binding of ticagrelor, its two major metabolites, adenosine diphosphate (ADP) and 2-Methylthioadenosine diphosphate (2MeS-ADP) as agonist, and ethyl 6-[4-(benzylsulfonylcarbamoyl)piperidin-1-yl]-5-cyano-2-methylpyridine-3-carboxylate (AZD1283)as antagonist were assessed systematically by means of ensemble docking. It is shown that the binding of all ligands becomes systematically stronger with the increase of the membrane rigidity. Binding of all ligands to the agonist-bound-like conformations is systematically stronger in comparison to antagonist-bound-likes ones. This is dramatically opposite to the results obtained for static crystal structures. Our results show that accounting for internal protein dynamics, strongly modulated by its lipid environment, is crucial for correct assessment of the ligand binding to P2Y12.

Human LC3 and GABARAP subfamily members achieve functional specificity via specific structural modulations

ABSTRACTAutophagy is a conserved adaptive cellular pathway essential to maintain a variety of physiological functions. Core components of this machinery are the six human Atg8 orthologs that initiate formation of appropriate protein complexes. While these proteins are routinely used as indicators of autophagic flux, it is presently not possible to discern their individual biological functions due to our inability to predict specific binding partners. In our attempts towards determining downstream effector functions, we developed a computational pipeline to define structural determinants of human Atg8 family members that dictate functional diversity. We found a clear evolutionary separation between human LC3 and GABARAP subfamilies and also defined a novel sequence motif responsible for their specificity. By analyzing known protein structures, we observed that functional modules or microclusters reveal a pattern of intramolecular network, including distinct hydrogen bonding of key residues (F52/Y49; a subset of HP2) that may directly modulate their interaction preferences. Multiple molecular dynamics simulations were performed to characterize how these proteins interact with a common protein binding partner, PLEKHM1. Our analysis showed remarkable differences in binding modes via intrinsic protein dynamics, with PLEKHM1-bound GABARAP complexes showing less fluctuations and higher number of contacts. We further mapped 373 genomic variations and demonstrated that distinct cancer-related mutations are likely to lead to significant structural changes. Our findings present a quantitative framework to establish factors underlying exquisite specificity of human Atg8 proteins, and thus facilitate the design of precise modulators.Abbreviations: Atg: autophagy-related; ECs: evolutionary constraints; GABARAP: GABA type A receptor-associated protein; HsAtg8: human Atg8; HP: hydrophobic pocket; KBTBD6: kelch repeat and BTB domain containing 6; LIR: LC3-interacting region; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MD: molecular dynamics; HIV-1 Nef: human immunodeficiency virus type 1 negative regulatory factor; PLEKHM1: pleckstrin homology and RUN domain containing M1; RMSD: root mean square deviation; SQSTM1/p62: sequestosome 1; WDFY3/ALFY: WD repeat and FYVE domain containing 3

Extracting the protein dynamics of bovine serum albumin in the native condition using confocal fluorescent temperature jump

A second-resolved temperature jump (T-jump) system coupled with confocal fluorescent thermometry of 100-μm spatial resolution was employed to unravel the protein dynamics of bovine serum albumin (BSA) at initial temperatures of 25–42 °C. The different evolutions of the tryptophan fluorescence intensity change of the BSA and pure tryptophan upon increasing 5 °C from 25 °C indicated an intrinsic protein dynamics quantified with an apparent rise time of 27 ± 1 s, whereas such a process was not observed at initial temperatures >30 °C. Different heating rates could differentiate the reaction pathways to detour toward reactions possessing different apparent activation energies, successfully explaining the discrepancy of the fluorescence intensity change observed in steady-state and T-jump methods. Moreover, the temperature-dependent steady-state circular dichroism and tryptophan fluorescence spectra were not coincident because they reflected the global and localized structural alterations upon heating, respectively. The combination of the experimental approach and concomitant analysis of the fluorescence evolutions provides a new tool to illustrate the dynamic processes of a big protein upon thermal stimulus.

Hydration Thermodynamics of a Powdered G-Protein-Coupled Receptor

Membrane proteins such as G protein-coupled receptors (GPCRs) are prominent targets for novel pharmaceutical drugs. Preparation and storage of fully functional GPCRs is crucial to the processes of drug delivery and discovery. Here we describe a novel method of preparing powdered GPCRs using rhodopsin as the prototype. Our new method for generating powdered samples, notable for exceptionally high protein content while retaining photochemical functionality, paves the way for conducting functional and biophysical experiments on the dynamic process of receptor activation. As an illustrative application, powdered rhodopsin is prepared with and without the cofactor 11-cis retinal enabling the partial hydration of the protein with 2H2O in a controlled manner [1]. These samples were used to study the changes in hydrogen-atom dynamics using the quasi-elastic neutron scattering (QENS) technique. Evaluation of QENS data using the interpretations of both spatial motion and energy landscape models offer key insights into the thermodynamics of GPCR activation. The QENS studies reveal a broadly distributed relaxation of the hydrogen atom dynamics of rhodopsin on a picosecond-nanosecond time scale, essential for protein function, previously observed for only globular proteins [2]. Interestingly, the results suggest significant differences in the intrinsic protein dynamics of the dark-state rhodopsin versus the ligand-free apoprotein, opsin. These differences can be attributed to the influence of the covalently bound retinal ligand. Furthermore, preparation of powdered samples from photoilluminated rhodopsin effectively captures the state of the excited protein while undergoing the conformational changes leading to activation. These discoveries create new avenues towards understanding the central role of water in GPCR activation and unlocking the mechanisms of the biologically important signaling process of rhodopsin. [1] S.M.D.C. Perera et al. (2016) J. Phys. Chem. Lett.7, 4239-4235. [2] U.R. Shresta et al. (2016) J. Phys. Chem. Lett. 7, 4130-4136.

Integration of Molecular Dynamics Based Predictions into the Optimization of De Novo Protein Designs: Limitations and Benefits.

Recent advances in de novo protein design have gained considerable insight from the intrinsic dynamics of proteins, based on the integration of molecular dynamics simulations protocols on the state-of-the-art de novo protein design protocols used nowadays. With this protocol we illustrate how to set up and run a molecular dynamics simulation followed by a functional protein dynamics analysis. New users will be introduced to some useful open-source computational tools, including the GROMACS molecular dynamics simulation software package and ProDy for protein structural dynamics analysis.

Quasi-elastic Neutron Scattering Reveals Ligand-Induced Protein Dynamics of a G-Protein-Coupled Receptor.

Light activation of the visual G-protein-coupled receptor (GPCR) rhodopsin leads to significant structural fluctuations of the protein embedded within the membrane yielding the activation of cognate G-protein (transducin), which initiates biological signaling. Here, we report a quasi-elastic neutron scattering study of the activation of rhodopsin as a GPCR prototype. Our results reveal a broadly distributed relaxation of hydrogen atom dynamics of rhodopsin on a picosecond-nanosecond time scale, crucial for protein function, as only observed for globular proteins previously. Interestingly, the results suggest significant differences in the intrinsic protein dynamics of the dark-state rhodopsin versus the ligand-free apoprotein, opsin. These differences can be attributed to the influence of the covalently bound retinal ligand. Furthermore, an idea of the generic free-energy landscape is used to explain the GPCR dynamics of ligand-binding and ligand-free protein conformations, which can be further applied to other GPCR systems.

Similarity in Shape Dictates Signature Intrinsic Dynamics Despite No Functional Conservation in TIM Barrel Enzymes.

The conservation of the intrinsic dynamics of proteins emerges as we attempt to understand the relationship between sequence, structure and functional conservation. We characterise the conservation of such dynamics in a case where the structure is conserved but function differs greatly. The triosephosphate isomerase barrel fold (TBF), renowned for its 8 β-strand-α-helix repeats that close to form a barrel, is one of the most diverse and abundant folds found in known protein structures. Proteins with this fold have diverse enzymatic functions spanning five of six Enzyme Commission classes, and we have picked five different superfamily candidates for our analysis using elastic network models. We find that the overall shape is a large determinant in the similarity of the intrinsic dynamics, regardless of function. In particular, the β-barrel core is highly rigid, while the α-helices that flank the β-strands have greater relative mobility, allowing for the many possibilities for placement of catalytic residues. We find that these elements correlate with each other via the loops that link them, as opposed to being directly correlated. We are also able to analyse the types of motions encoded by the normal mode vectors of the α-helices. We suggest that the global conservation of the intrinsic dynamics in the TBF contributes greatly to its success as an enzymatic scaffold both through evolution and enzyme design.

A Pipeline To Enhance Ligand Virtual Screening: Integrating Molecular Dynamics and Fingerprints for Ligand and Proteins.

The importance of taking into account protein flexibility in drug design and virtual ligand screening (VS) has been widely debated in the literature, and molecular dynamics (MD) has been recognized as one of the most powerful tools for investigating intrinsic protein dynamics. Nevertheless, deciphering the amount of information hidden in MD simulations and recognizing a significant minimal set of states to be used in virtual screening experiments can be quite complicated. Here we present an integrated MD-FLAP (molecular dynamics-fingerprints for ligand and proteins) approach, comprising a pipeline of molecular dynamics, clustering and linear discriminant analysis, for enhancing accuracy and efficacy in VS campaigns. We first extracted a limited number of representative structures from tens of nanoseconds of MD trajectories by means of the k-medoids clustering algorithm as implemented in the BiKi Life Science Suite ( http://www.bikitech.com [accessed July 21, 2015]). Then, instead of applying arbitrary selection criteria, that is, RMSD, pharmacophore properties, or enrichment performances, we allowed the linear discriminant analysis algorithm implemented in FLAP ( http://www.moldiscovery.com [accessed July 21, 2015]) to automatically choose the best performing conformational states among medoids and X-ray structures. Retrospective virtual screenings confirmed that ensemble receptor protocols outperform single rigid receptor approaches, proved that computationally generated conformations comprise the same quantity/quality of information included in X-ray structures, and pointed to the MD-FLAP approach as a valuable tool for improving VS performances.

Controlling the state of dynamic proteins

Protein Evolution Small molecules that change the oligomeric state of proteins by binding to a site distant from the interface are called allosteric. They often act by taking advantage of intrinsic protein dynamics and stabilizing a particular conformation of the protein. Perica et al. show that

Real-time monitoring of protein conformational changes using a nano-mechanical sensor.

Proteins can switch between different conformations in response to stimuli, such as pH or temperature variations, or to the binding of ligands. Such plasticity and its kinetics can have a crucial functional role, and their characterization has taken center stage in protein research. As an example, Topoisomerases are particularly interesting enzymes capable of managing tangled and supercoiled double-stranded DNA, thus facilitating many physiological processes. In this work, we describe the use of a cantilever-based nanomotion sensor to characterize the dynamics of human topoisomerase II (Topo II) enzymes and their response to different kinds of ligands, such as ATP, which enhance the conformational dynamics. The sensitivity and time resolution of this sensor allow determining quantitatively the correlation between the ATP concentration and the rate of Topo II conformational changes. Furthermore, we show how to rationalize the experimental results in a comprehensive model that takes into account both the physics of the cantilever and the dynamics of the ATPase cycle of the enzyme, shedding light on the kinetics of the process. Finally, we study the effect of aclarubicin, an anticancer drug, demonstrating that it affects directly the Topo II molecule inhibiting its conformational changes. These results pave the way to a new way of studying the intrinsic dynamics of proteins and of protein complexes allowing new applications ranging from fundamental proteomics to drug discovery and development and possibly to clinical practice.

PyInteraph: A Framework for the Analysis of Interaction Networks in Structural Ensembles of Proteins

In the last years, a growing interest has been gathering around the ability of Molecular Dynamics (MD) to provide insight into the paths of long-range structural communication in biomolecules. The knowledge of the mechanisms related to structural communication helps in the rationalization in atomistic details of the effects induced by mutations, ligand binding, and the intrinsic dynamics of proteins. We here present PyInteraph, a tool for the analysis of structural ensembles inspired by graph theory. PyInteraph is a software suite designed to analyze MD and structural ensembles with attention to binary interactions between residues, such as hydrogen bonds, salt bridges, and hydrophobic interactions. PyInteraph also allows the different classes of intra- and intermolecular interactions to be represented, combined or alone, in the form of interaction graphs, along with performing network analysis on the resulting interaction graphs. The program also integrates the network description with a knowledge-based force field to estimate the interaction energies between side chains in the protein. It can be used alone or together with the recently developed xPyder PyMOL plugin through an xPyder-compatible format. The software capabilities and associated protocols are here illustrated by biologically relevant cases of study. The program is available free of charge as Open Source software via the GPL v3 license at http://linux.btbs.unimib.it/pyinteraph/.

Gsatools: Analysis of Allosteric Communication and Functional Local Motions using a Structural Alphabet

BackgroundBiomolecular motions play a key role in several biological functions: enzymatic activity, protein-protein interactions, ligand binding and allosteric regulation. Computational approaches, such as Molecular Dynamics (MD), are now routinely used to reproduce the intrinsic dynamics of proteins, but effective tools are still required to gain functional insight from the simulated data.Methods and ResultsWe previously suggested a method aimed at recovering the role of local conformational changes in functional motions. To this purpose we developed a Structural Alphabet (SA): a set of 25 canonical states of 4-residue protein fragments (Cα atoms only) describing the most probable local conformations in high-resolution protein structures [1]. The SA provides a mean for the coarse-grained annotation and processing of local conformations in a string format, which lends itself to a range of efficient sequence analysis algorithms. The SA has been successfully used in analysing local changes and allosteric signal transmission [2].Here we present GSATools [3], a set of SA-related tools interfacing with GROMACS for the analysis of conformational ensembles. GSATools is designed for the investigation of the conformational dynamics of local structures, the functional correlations between local and global motions, and the mechanisms of allosteric communication.ConclusionsGSATools is a free, easy-to-use and fully documented software for the analysis of conformational ensembles of proteins. The GSATools complement the GROMACS toolkit with a powerful set of analyses to detect, annotate and interpret local motions of functional relevance.1. Pandini A., Fornili A. & Kleinjung J. BMC Bioinformatics 11, 97 (2010).2. Pandini A., Fornili A., Fraternali F. & Kleinjung J., FASEB J., 26, 868 (2012).3. Pandini A., Fornili A., Fraternali F. & Kleinjung J., Bioinformatics, 29, 2053 (2013).

A Mechanism for Localized Dynamics-driven Affinity Regulation of the Binding of von Willebrand Factor to Platelet Glycoprotein Ibα

Binding of the A1 domain of von Willebrand factor (vWF) to glycoprotein Ibα (GPIbα) results in platelet adhesion, activation, and aggregation that initiates primary hemostasis. Both the elevated shear stress and the mutations associated with type 2B von Willebrand disease enhance the interaction between A1 and GPIbα. Through molecular dynamics simulations for wild-type vWF-A1 and its eight gain of function mutants (R543Q, I546V, ΔSS, etc.), we found that the gain of function mutations destabilize the N-terminal arm, increase a clock pendulum-like movement of the α2-helix, and turn a closed A1 conformation into a partially open one favoring binding to GPIbα. The residue Arg(578) at the α2-helix behaves as a pivot in the destabilization of the N-terminal arm and a consequent dynamic change of the α2-helix. These results suggest a localized dynamics-driven affinity regulation mechanism for vWF-GPIbα interaction. Allosteric drugs controlling this intrinsic protein dynamics may be effective in blocking the GPIb-vWF interaction.