Protein Motions Research Articles

A protein coupling and molecular simulation analysis of the clinical mutants of androgen receptor revealed a higher binding for Leupaxin, to increase the prostate cancer invasion and motility

Recently a novel coactivator, Leupaxin (LPXN), has been reported to interact with Androgen receptor (AR) and play a significant role in the invasion and progression of prostate cancer. The interaction between AR and LPXN occurs in a ligand-dependent manner and has been reported that the LIM domain in the Leupaxin interacts with the LDB (ligand-binding domain) domain AR. However, no detailed study is available on how the LPXN interacts with AR and increases the (prostate cancer) PCa progression. Considering the importance of the novel co-activator, LPXN, the current study also uses state-of-the-art methods to provide atomic-level insights into the binding of AR and LPXN and the impact of the most frequent clinical mutations H874Y, T877A, and T877S on the binding and function of LPXN. Protein coupling analysis revealed that the three mutants favour the robust binding of LPXN than the wild type by altering the hydrogen bonding network. Further understanding of the binding variations was explored through dissociation constant prediction which demonstrated similar reports as the docking results. A molecular simulation approaches further revealed the dynamic features which reported variations in the dynamics stability, protein packing, hydrogen bonding network, and residues flexibility index. Furthermore, we also assessed the protein motion and free energy landscape which also demonstrated variations in the internal dynamics. The binding free energy calculation revealed -32.95 ± 0.17 kcal/mol for the wild type, for H874Y the total binding energy (BFE) was -36.69 ± 0.11kcal/mol, for T877A the BFE was calculated to be -38.78 ± 0.17 kcal/mol while for T877S the BFE -41.16 ± 0.12 kcal/mol. This shows that the binding of LPXN is increased by these mutations which consequently increase the PCa invasion and motility. In conclusion, the current study helps in understanding the protein networks and particular the coupling of AR-LPXN in prostate cancer and is of great interest in deciphering the molecular mechanism of disease and therapeutics developments.

Study of Protein Dynamics via Neutron Spin Echo Spectroscopy.

Most human body proteins' activity and functionality are related to configurational changes of entire subdomains within the protein crystal structure. The crystal structures build the basis for any calculation that describes the structure or dynamics of a protein, most of the time with strong geometrical restrictions. However, these restrictions from the crystal structure are not present in the solution. The structure of the proteins in the solution may differ from the crystal due to rearrangements of loops or subdomains on the pico to nanosecond time scale (i.e., the internal protein dynamics time regime). The present work describes how slow motions on timescales of several tens of nanoseconds can be accessed using neutron scattering. In particular, the dynamical characterization of two major human proteins, an intrinsically disordered protein that lacks a well-defined secondary structure and a classical antibody protein, is addressed by neutron spin echo spectroscopy (NSE) combined with a wide range of laboratory characterization methods. Further insights into protein domain dynamics were achieved using mathematical modeling to describe the experimental neutron data and determine the crossover between combined diffusive and internal protein motions. The extraction of the internal dynamic contribution to the intermediate scattering function obtained from NSE, including the timescale of the various movements, allows further vision into the mechanical properties of single proteins and the softness of proteins in their nearly natural environment in the crowded protein solution.

Identifying vaccine escape sites via statistical comparisons of short-term molecular dynamics

The identification of viral mutations that confer escape from antibodies is crucial for understanding the interplay between immunity and viral evolution. We describe a molecular dynamics (MD)-based approach that goes beyond contact mapping, scales well to a desktop computer with a modern graphics processor, and enables the user to identify functional protein sites that are prone to vaccine escape in a viral antigen. We first implement our MD pipeline to employ site-wise calculation of Kullback-Leibler divergence in atom fluctuation over replicate sets of short-term MD production runs thus enabling a statistical comparison of the rapid motion of influenza hemagglutinin (HA) in both the presence and absence of three well-known neutralizing antibodies. Using this simple comparative method applied to motions of viral proteins, we successfully identified in silico all previously empirically confirmed sites of escape in influenza HA, predetermined via selection experiments and neutralization assays. Upon the validation of our computational approach, we then surveyed potential hotspot residues in the receptor binding domain of the SARS-CoV-2 virus in the presence of COVOX-222 and S2H97 antibodies. We identified many single sites in the antigen-antibody interface that are similarly prone to potential antibody escape and that match many of the known sites of mutations arising in the SARS-CoV-2 variants of concern. In the Omicron variant, we find only minimal adaptive evolutionary shifts in the functional binding profiles of both antibodies. In summary, we provide an inexpensive and accurate computational method to monitor hotspots of functional evolution in antibody binding footprints.

Probing terahertz dynamics of multidomain protein in cell-like confinement

The development of meaningful descriptions of multidomain proteins exhibiting complex inter-domain dynamics modes is a key challenge for understanding their roles in molecular recognition and signalling processes. Here we developed a generally applicable approach for probing the low frequency collective hydration dynamics of multidomain proteins that uses terahertz spectroscopy of a protein molecule confined in a phospholipid reverse micelles environment (named Droplet THz). With the combination of normal mode analysis, we demonstrated the binding of calcium ions modulates the local inter-domain motion of the human coagulant factor VIII protein in a concentration-dependent manner. These findings highlight the Droplet THz as a valuable tool for dissecting the ultrafast dynamics of domain motion in the multidomain proteins and suggest a modulating mechanism of calcium ions on the structural flexibility and function of human coagulant proteins.

Site-selective dynamics of ligand-free and ligand-bound azidolysozyme.

Azido-modified alanine residues (AlaN3) are environment-sensitive, minimally invasive infrared probes for the site-specific investigation of protein structure and dynamics. Here, the capability of the label is investigated to query whether or not a ligand is bound to the active site of lysozyme and how the spectroscopy and dynamics change upon ligand binding. The results demonstrate specific differences for center frequencies of the asymmetric azide stretch vibration, the longtime decay, and the static offset of the frequency fluctuation correlation function (FFCF)-all of which are experimental observables-between the ligand-free and the ligand-bound N3-labeled protein. The center-frequency shifts range from 1 to 8 cm-1, which is detectable from state-of-the art experiments. Similarly, the nonvanishing static component Δ0 of the FFCF between ligand-free and ligand-bound protein can differ by up to a factor of 2.5. This makes the azide label a versatile and structurally sensitive probe to report on the dynamics of proteins in a variety of environments and for a range of different applications. Ligand-induced differences in the dynamics are also mapped onto changes in the local and through-space coupling between residues by virtue of dynamical cross correlation maps. This demonstrates that the position where the label is placed also influences the local and global protein motions.

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion.

One-dimensional (1-D) sliding of transcription factor (TF) protein along DNA is essential for facilitated diffusion of the TF to locate target DNA site for genetic regulation. Detecting base-pair (bp) resolution of the TF sliding or stepping on the DNA is still experimentally challenging. We have recently performed all-atom molecular dynamics (MD) simulations capturing spontaneous 1-bp stepping of a small WRKY domain TF protein along DNA. Based on the 10 µs WRKY stepping path obtained from such simulations, the protocol here shows how to conduct more extensive conformational samplings of the TF-DNA systems, by constructing the Markov state model (MSM) for the 1-bp protein stepping, with various numbers of micro- and macro-states tested for the MSM construction. In order to examine processive 1-D diffusional search of the TF protein along DNA with structural basis, the protocol further shows how to conduct coarse-grained (CG) MD simulations to sample long-time scale dynamics of the system. Such CG modeling and simulations are particularly useful to reveal the protein-DNA electrostatic impacts on the processive diffusional motions of the TF protein above tens of microseconds, in comparison with sub-microseconds to microseconds protein stepping motions revealed from the all-atom simulations.

Label-Free Optical Analysis of Biomolecules in Solid-State Nanopores: Toward Single-Molecule Protein Sequencing.

Sequence identification of peptides and proteins is central to proteomics. Protein sequencing is mainly conducted by insensitive mass spectroscopy because proteins cannot be amplified, which hampers applications such as single-cell proteomics and precision medicine. The commercial success of portable nanopore sequencers for single DNA molecules has inspired extensive research and development of single-molecule techniques for protein sequencing. Among them, three challenges remain: (1) discrimination of the 20 amino acids as building blocks of proteins; (2) unfolding proteins; and (3) controlling the motion of proteins with nonuniformly charged sequences. In this context, the emergence of label-free optical analysis techniques for single amino acids and peptides by solid-state nanopores shows promise for addressing the first challenge. In this Perspective, we first discuss the current challenges of single-molecule fluorescence detection and nanopore resistive pulse sensing in a protein sequencing. Then, label-free optical methods are described to show how they address the single-amino-acid identification within single peptides. They include localized surface plasmon resonance detection and surface-enhanced Raman spectroscopy on plasmonic nanopores. Notably, we report new data to show the ability of plasmon-enhanced Raman scattering to record and discriminate the 20 amino acids at a single-molecule level. In addition, we discuss briefly the manipulation of molecule translocation and liquid flow in plasmonic nanopores for controlling molecule movement to allow high-resolution reading of protein sequences. We envision that a combination of Raman spectroscopy with plasmonic nanopores can succeed in single-molecule protein sequencing in a label-free way.

Protein Fluctuations in Response to Random External Forces

Elastic network models (ENMs) have been widely used in the last decades to investigate protein motions and dynamics. There the intrinsic fluctuations based on the isolated structures are obtained from the normal modes of these elastic networks, and they generally show good agreement with the B-factors extracted from X-ray crystallographic experiments, which are commonly considered to be indicators of protein flexibility. In this paper, we propose a new approach to analyze protein fluctuations and flexibility, which has a more appropriate physical basis. It is based on the application of random forces to the protein ENM to simulate the effects of collisions of solvent on a protein structure. For this purpose, we consider both the Cα-atom coarse-grained anisotropic network model (ANM) and an elastic network augmented with points included for the crystallized waters. We apply random forces to these protein networks everywhere, as well as only on the protein surface alone. Despite the randomness of the directions of the applied perturbations, the computed average displacements of the protein network show a remarkably good agreement with the experimental B-factors. In particular, for our set of 919 protein structures, we find that the highest correlation with the B-factors is obtained when applying forces to the external surface of the water-augmented ANM (an overall gain of 3% in the Pearson’s coefficient for the entire dataset, with improvements up to 30% for individual proteins), rather than when evaluating the fluctuations obtained from the normal modes of a standard Cα-atom coarse-grained ANM. It follows that protein fluctuations should be considered not just as the intrinsic fluctuations of the internal dynamics, but also equally well as responses to external solvent forces, or as a combination of both.

New Horizons in Structural Biology of Membrane Proteins: Experimental Evaluation of the Role of Conformational Dynamics and Intrinsic Flexibility.

A plethora of membrane proteins are found along the cell surface and on the convoluted labyrinth of membranes surrounding organelles. Since the advent of various structural biology techniques, a sub-population of these proteins has become accessible to investigation at near-atomic resolutions. The predominant bona fide methods for structure solution, X-ray crystallography and cryo-EM, provide high resolution in three-dimensional space at the cost of neglecting protein motions through time. Though structures provide various rigid snapshots, only an amorphous mechanistic understanding can be inferred from interpolations between these different static states. In this review, we discuss various techniques that have been utilized in observing dynamic conformational intermediaries that remain elusive from rigid structures. More specifically we discuss the application of structural techniques such as NMR, cryo-EM and X-ray crystallography in studying protein dynamics along with complementation by conformational trapping by specific binders such as antibodies. We finally showcase the strength of various biophysical techniques including FRET, EPR and computational approaches using a multitude of succinct examples from GPCRs, transporters and ion channels.

D3PM: a comprehensive database for protein motions ranging from residue to domain

BackgroundKnowledge of protein motions is significant to understand its functions. While currently available databases for protein motions are mostly focused on overall domain motions, little attention is paid on local residue motions. Albeit with relatively small scale, the local residue motions, especially those residues in binding pockets, may play crucial roles in protein functioning and ligands binding.ResultsA comprehensive protein motion database, namely D3PM, was constructed in this study to facilitate the analysis of protein motions. The protein motions in the D3PM range from overall structural changes of macromolecule to local flip motions of binding pocket residues. Currently, the D3PM has collected 7679 proteins with overall motions and 3513 proteins with pocket residue motions. The motion patterns are classified into 4 types of overall structural changes and 5 types of pocket residue motions. Impressively, we found that less than 15% of protein pairs have obvious overall conformational adaptations induced by ligand binding, while more than 50% of protein pairs have significant structural changes in ligand binding sites, indicating that ligand-induced conformational changes are drastic and mainly confined around ligand binding sites. Based on the residue preference in binding pocket, we classified amino acids into “pocketphilic” and “pocketphobic” residues, which should be helpful for pocket prediction and drug design.ConclusionD3PM is a comprehensive database about protein motions ranging from residue to domain, which should be useful for exploring diverse protein motions and for understanding protein function and drug design. The D3PM is available on www.d3pharma.com/D3PM/index.php.

A Comparative Evaluation of the Structural and Dynamic Properties of Insect Odorant Binding Proteins.

Insects devote a major part of their metabolic resources to the production of odorant binding proteins (OBPs). Although initially, these proteins were implicated in the solubilisation, binding and transport of semiochemicals to olfactory receptors, it is now recognised that they may play diverse, as yet uncharacterised, roles in insect physiology. The structures of these OBPs, the majority of which are known as “classical” OBPs, have shed some light on their potential functional roles. However, the dynamic properties of these proteins have received little attention despite their functional importance. Structural dynamics are encoded in the native protein fold and enable the adaptation of proteins to substrate binding. This paper provides a comparative review of the structural and dynamic properties of OBPs, making use of sequence/structure analysis, statistical and theoretical physics-based methods. It provides a new layer of information and additional methodological tools useful in unravelling the relationship between structure, dynamics and function of insect OBPs. The dynamic properties of OBPs, studied by means of elastic network models, reflect the similarities/dissimilarities observed in their respective structures and provides insights regarding protein motions that may have important implications for ligand recognition and binding. Furthermore, it was shown that the OBPs studied in this paper share conserved structural ‘core’ that may be of evolutionary and functional importance.

Dynamic motions of ice-binding proteins in living Caenorhabditis elegans using diffracted X-ray blinking and tracking

The dynamic properties of protein molecules are involved in the relationship between their structure and function. Time-resolved X-ray observation enables capturing the structures of biomolecules with picometre-scale precision. However, this technique has yet to be implemented in living animals. Here, we examined diffracted X-ray blinking (DXB) and diffracted X-ray tracking (DXT) to observe the dynamics of a protein located on intestinal cells in adult Caenorhabditis elegans. This in vivo tissue-specific DXB was examined at temperatures from 20 °C to −10 °C for a recombinant ice-binding protein from Antarctomyces psychrotrophicus (AnpIBP) connected with the cells through a transmembrane CD4 protein equipped with a glycine-serine linker. AnpIBP inhibits ice growth at subzero temperatures by binding to ice crystals. We found that the rotational motion of AnpIBP decreases at −10 °C. In contrast, the motion of the AnpIBP mutant, which has a defective ice-binding ability, did not decrease at −10 °C. The twisting and tilting motional speeds of AnpIBPs measured above 5 °C by DXT were always higher than those of the defective AnpIBP mutant. These results suggest that wild-type AnpIBP is highly mobile in solution, and it is halted at subzero temperatures through ice binding. DXB and DXT allow for exploring protein behaviour in live animals with subnano resolution precision.

The functional evolution of ACE2 receptor binding of Betacoronaviruses in the past, present, and uncertain future

Comparative functional analysis of the dynamic interactions between various Betacoronavirus mutant strains and broadly utilized target proteins, is crucial for a more complete understanding of zoonotic spillovers of viruses that cause COVID-19. Here, we employ machine learning to replicate 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 of the S spike glycoprotein.

Interrogating conformational dynamics of single-proteins in a plasmonic hotspot

A full understanding of the function of many proteins can only be obtained if different conformations and transitions between them can be monitored in aqueous solution, with adequate temporal resolution. Despite the importance of conformational dynamics, monitoring domain motions of single proteins remains challenging experimentally. Established techniques to determine these conformational changes typically require site-directed chemical modification. The work presented here introduces an approach that traps single unmodified proteins in solution in a plasmonic hotspot and makes it possible to follow changes in protein conformation by concomitant changes in refractive index that can be detected and monitored for minutes to hours with a temporal resolution in the microsecond range.

High-resolution imaging of the interplay of replicative proteins on DNA using correlative tweezers fluorescence microscopy

DNA is synthesized by an orchestrated multi-protein machinery in a highly coordinated and dynamic fashion. Current single-molecule strategies provide us great details in kinetic motion of replicative proteins and dynamic DNA-protein interaction. However, many of these studies lack the possibility for direct observing multi-molecules interacting with DNA. Here we present a Correlative Tweezers Fluorescence Microscopy (CTFM) strategy to observe, with high-temporal-resolution, multiple replicative protein interacting on single DNA molecules.

Uncertainty in Markov state models for small macromolecules

Markov state models (MSMs) are a tool to describe and analyse protein dynamics. They are useful in particular to determine characteristic timescales of protein motion. For larger biomolecules such as proteins it is challenging to obtain sufficient sampling for the timescales to converge, which is thus a frequent concern. There are, however, also several other sources of uncertainty, such as choice of lag time and the number of dimensions in the dimension reduction preprocessing step (e.g. time-lagged independent component analysis), the number of Markov states, or choice of the MSM lag time.

Fast, simple molecular entropy calculations from Voronoi diagrams of a single structure

Protein entropy is not as well developed as the many different protein energy calculation techniques. However, it is a crucial metric for the free energy calculations along with the energy. Since molecular dynamics (MD) simulations, one of the most commonly relied upon simulation methods, requires free energy to accurately model protein motions, there is a significant need for improved efficient, reliable entropies. Although there are several previous ways to estimate protein entropy, most of these approaches are directly or indirectly derived from MD.

Single-molecule characterization of the iLID system in live bacterial cells

The development of single-molecule tracking (SMT) microscopy has enabled high resolution, live-cell imaging of protein motion in real time. The diffusion rate of the tracked protein can be used to deduce protein-protein interactions at specific subcellular locations, because diffusion is dependent on the size of the protein complex. However, the assignment and validation of diffusive states to specific oligomeric species relies on statistical parameter estimation and, in many cases, deletion or mutation of binding partners that disrupt the protein-protein interaction in question.

Whole virion simulations unveiling the hemagglutinin-neuraminidase interplay

Despite decades of research, the mechanism of how influenza virions release from a cell is still murky. We know the membrane protein neuraminidase must cleave a bond, releasing another membrane protein, hemagglutinin, from the cell surface. We examine this interplay between hemagglutinin and neuraminidase through simulations. We created an influenza virion and ran all-atom molecular dynamics. We analyzed the ensuing protein motions through Markov state models and protein contacts to determine how these two membrane proteins interact to free influenza virions from host cells.

Use of Site-Directed Spin Labeling EPR Spectroscopy to Study Protein-LPS Interactions.

Site-directed spin labeling EPR (electron paramagnetic resonance) spectroscopy is a technique used to identify the local conformational changes at a specific residue of interest within a purified protein in response to a ligand. Here, we describe the site-directed spin labeling EPR spectroscopy methodology to monitor changes in the side-chain motion in soluble lipopolysaccharide transport proteins upon the addition of lipopolysaccharide (LPS). A comparison of the spectral overlays of the spin-labeled protein in the absence and presence of LPS provides a qualitative visualization of how LPS binding affects the motion of each spin-labeled site tested within the protein. No change in the spectral lineshapes of a spin-labeled protein in the absence and presence of LPS indicates that the site is not affected by LPS binding, while differences in the spectral lineshapes indicate that LPS does affect the mobility of the spin label side chain within the protein structure. This is a powerful readout of conformational changes at specific residues of interest that can be used to identify a specific site as a reporter of changes induced by ligand binding and to map out the effects of ligand binding through an array of reporter sites within a protein. With the use of AquaStar tubing, protein concentrations as low as 2μM allow for up to a 100-fold excess of LPS. This methodology may also be applied to other protein-ligand or protein-protein interactions with minor adaptations.