Conformational Changes and Free Energies in a Proline Isomerase

Predicting absolute protein folding stability using generative models

While there has been substantial progress in our ability to predict changes in protein stability due to amino acid substitutions, progress has been slower in methods to predict the absolute stability of a protein. Here, we show how a generative model for protein sequence can be leveraged to predict absolute protein stability. We benchmark our predictions across a broad set of proteins and find a mean error of 1.5 kcal/mol and a correlation coefficient of 0.7 for the absolute stability across a range of natural, small- to medium-sized proteins up to ca. 150 amino acid residues. We analyze current limitations and future directions including how such a model may be useful for predicting conformational free energies. Our approach is simple to use and freely available at an online implementation available via https://github.com/KULL-Centre/_2024_cagiada_stability.

Alternate conformations found in protein structures implies biological functions: A case study using cyclophilin A

Protein dynamics linked to numerous biomolecular functions, such as ligand binding, allosteric regulation, and catalysis, must be better understood at the atomic level. Reactive atoms of key residues drive a repertoire of biomolecular functions by flipping between alternate conformations or conformational substates, seldom found in protein structures. Probing such sparsely sampled alternate conformations would provide mechanistic insight into many biological functions. We are therefore interested in evaluating the instance of amino acids adopted alternate conformations, either in backbone or side-chain atoms or in both. Accordingly, over 70000 protein structures appear to contain alternate conformations only 'A' and 'B' for any atom, particularly the instance of amino acids that adopted alternate conformations are more for Arg, Cys, Met, and Ser than others. The resulting protein structure analysis depicts that amino acids with alternate conformations are mainly found in the helical and β-regions and are often seen in high-resolution X-ray crystal structures. Furthermore, a case study on human cyclophilin A (CypA) was performed to explain the pre-existing intrinsic dynamics of catalytically critical residues from the CypA and how such intrinsic dynamics perturbed upon Ser99Thr mutation using molecular dynamics simulations on the ns-μs timescale. Simulation results demonstrated that the Ser99Thr mutation had impaired the alternate conformations or the catalytically productive micro-environment of Phe113, mimicking the experimentally observed perturbation captured by X-ray crystallography. In brief, a deeper comprehension of alternate conformations adopted by the amino acids may shed light on the interplay between protein structure, dynamics, and function.

PyInteraph2 and PyInKnife2 to Analyze Networks in Protein Structural Ensembles

Due to the complex nature of noncovalent interactions and their long-range effects, analyzing protein conformations using network theory can be enlightening. Protein Structure Networks (PSNs) provide a convenient formalism to study protein structures in relation to essential properties such as key residues for structural stability, allosteric communication, and the effects of modifications of the protein. PSNs can be defined according to very different principles, and the available tools have limitations in input formats, supported models, and version control. Other outstanding problems are related to the definition of network cutoffs and the assessment of the stability of the network properties. The protein science community could benefit from a common framework to carry out these analyses and make them easier to reproduce, reuse, and evaluate. We here provide two open-source software packages, PyInteraph2 and PyInKnife2, to implement and analyze PSNs in a reproducible and documented manner. PyInteraph2 interfaces with multiple formats for protein ensembles and incorporates different network models with the possibility of integrating them into a macronetwork and performing various downstream analyses, including hubs, connected components, and several other centrality measures, and visualizes the networks or further analyzes them thanks to compatibility with Cytoscape.PyInKnife2 that supports the network models implemented in PyInteraph2. It employs a jackknife resampling approach to estimate the convergence of network properties and streamline the selection of distance cutoffs. We foresee that the modular structure of the code and the supported version control system will promote the transition to a community-driven effort, boost reproducibility, and establish common protocols in the PSN field. As developers, we will guarantee the introduction of new functionalities and maintenance, assistance, and training of new contributors.

TRAP1 S-nitrosylation as a model of population-shift mechanism to study the effects of nitric oxide on redox-sensitive oncoproteins

S-nitrosylation is a post-translational modification in which nitric oxide (NO) binds to the thiol group of cysteine, generating an S-nitrosothiol (SNO) adduct. S-nitrosylation has different physiological roles, and its alteration has also been linked to a growing list of pathologies, including cancer. SNO can affect the function and stability of different proteins, such as the mitochondrial chaperone TRAP1. Interestingly, the SNO site (C501) of TRAP1 is in the proximity of another cysteine (C527). This feature suggests that the S-nitrosylated C501 could engage in a disulfide bridge with C527 in TRAP1, resembling the well-known ability of S-nitrosylated cysteines to resolve in disulfide bridge with vicinal cysteines. We used enhanced sampling simulations and in-vitro biochemical assays to address the structural mechanisms induced by TRAP1 S-nitrosylation. We showed that the SNO site induces conformational changes in the proximal cysteine and favors conformations suitable for disulfide bridge formation. We explored 4172 known S-nitrosylated proteins using high-throughput structural analyses. Furthermore, we used a coarse-grained model for 44 protein targets to account for protein flexibility. This resulted in the identification of up to 1248 proximal cysteines, which could sense the redox state of the SNO site, opening new perspectives on the biological effects of redox switches. In addition, we devised two bioinformatic workflows ( https://github.com/ELELAB/SNO_investigation_pipelines ) to identify proximal or vicinal cysteines for a SNO site with accompanying structural annotations. Finally, we analyzed mutations in tumor suppressors or oncogenes in connection with the conformational switch induced by S-nitrosylation. We classified the variants as neutral, stabilizing, or destabilizing for the propensity to be S-nitrosylated and undergo the population-shift mechanism. The methods applied here provide a comprehensive toolkit for future high-throughput studies of new protein candidates, variant classification, and a rich data source for the research community in the NO field.

Transient exposure of a buried phosphorylation site in an autoinhibited protein

Autoinhibition is a mechanism used to regulate protein function, often by making functional sites inaccessible through the interaction with a cis-acting inhibitory domain. Such autoinhibitory domains often display a substantial degree of structural disorder when unbound, and only become structured in the inhibited state. These conformational dynamics make it difficult to study the structural origin of regulation, including effects of regulatory post-translational modifications. Here, we study the autoinhibition of the Dbl Homology domain in the protein Vav1 by the so-called acidic inhibitory domain. We use molecular simulations to study the process by which a mostly unstructured inhibitory domain folds upon binding and how transient exposure of a key buried tyrosine residue makes it accessible for phosphorylation. We show that the inhibitory domain, which forms a helix in the bound and inhibited stated, samples helical structures already before binding and that binding occurs via a molten-globule-like intermediate state. Together, our results shed light on key interactions that enable the inhibitory domain to sample a finely tuned equilibrium between an inhibited and a kinase-accessible state.

Investigating Conformational Dynamics and Allostery in the p53 DNA-Binding Domain Using Molecular Simulations

The p53 tumor suppressor is a multifaceted context-dependent protein, which is involved in multiple cellular pathways, with the ability to either keep the cells alive or to kill them through mechanisms such as apoptosis. To complicate this picture, cancer cells that express mutant p53 becomes addicted to the mutant activity, so that the mutant variant features a myriad of gain-of-function activities, opening different venues for therapy. This makes essential to think outside the box and apply new approaches to the study of p53 structure-(mis)function relationship to find new critical components of its pathway or to understand how known parts are interconnected, compete, or cooperate. In this context, I will here illustrate how to integrate different computational methods to the identification of possible allosteric effects transmitted from the DNA binding interface of p53 to regions for cofactor recruitment. The protocol can be extended to any other cases of study. Indeed, it does not necessarily apply only to the study of DNA-induced effects, but more broadly to the investigation of long-range effects induced by a biological partner that binds to a biomolecule of interest.

Protein Dynamics Enables Phosphorylation of Buried Residues in Cdk2/Cyclin-A-Bound p27

Proteins carry out a wide range of functions that are tightly regulated in space and time. Protein phosphorylation is the most common post-translation modification of proteins and plays a key role in the regulation of many biological processes. The finding that many phosphorylated residues are not solvent exposed in the unphosphorylated state opens several questions for understanding the mechanism that underlies phosphorylation and how phosphorylation may affect protein structures. First, because kinases need access to the phosphorylated residue, how do such buried residues become modified? Second, once phosphorylated, what are the structural effects of phosphorylation of buried residues, and do they lead to changed conformational dynamics? We have used the ternary complex between p27^Kip1 (p27), Cdk2, and cyclin A to study these questions using enhanced sampling molecular dynamics simulations. In line with previous NMR and single-molecule fluorescence experiments, we observe transient exposure of Tyr88 in p27, even in its unphosphorylated state. Once Tyr88 is phosphorylated, we observe a coupling to a second site, thus making Tyr74 more easily exposed and thereby the target for a second phosphorylation step. Our observations provide atomic details on how protein dynamics plays a role in modulating multisite phosphorylation in p27, thus supplementing previous experimental observations. More generally, we discuss how the observed phenomenon of transient exposure of buried residues may play a more general role in regulating protein function.

Conformational gating in ammonia lyases

BACKGROUND

Ammonia lyases are enzymes of industrial and biomedical interest. Knowledge of structure-dynamics-function relationship in ammonia lyases is instrumental for exploiting the potential of these enzymes in industrial or biomedical applications.

METHODS

We investigated the conformational changes in the proximity of the catalytic pocket of a 3-methylaspartate ammonia lyase (MAL) as a model system. At this scope, we used microsecond all-atom molecular dynamics simulations, analyzed with dimensionality reduction techniques, as well as in terms of contact networks and correlated motions.

RESULTS

We identify two regulatory elements in the MAL structure, i.e., the β5-α2 loop and the helix-hairpin-loop subdomain. These regulatory elements undergo conformational changes switching from 'occluded' to 'open' states. The rearrangements are coupled to changes in the accessibility of the active site. The β5-α2 loop and the helix-hairpin-loop subdomain modulate the formation of tunnels from the protein surface to the catalytic site, making the active site more accessible to the substrate when they are in an open state.

CONCLUSIONS

Our work pinpoints a sequential mechanism, in which the helix-hairpin-loop subdomain of MAL needs to break a subset of intramolecular interactions first to favor the displacement of the β5-α2 loop. The coupled conformational changes of these two elements contribute to modulate the accessibility of the catalytic site.

GENERAL SIGNIFICANCE

Similar molecular mechanisms can have broad relevance in other ammonia lyases with similar regulatory loops. Our results also imply that it is important to account for protein dynamics in the design of variants of ammonia lyases for industrial and biomedical applications.

Enhanced sampling and free energy calculations for protein simulations

Molecular dynamics simulation is a powerful computational technique to study biomolecular systems, which complements experiments by providing insights into the structural dynamics relevant to biological functions at atomic scale. It can also be used to calculate the free energy landscapes of the conformational transitions to better understand the functions of the biomolecules. However, the sampling of biomolecular configurations is limited by the free energy barriers that need to be overcome, leading to considerable gaps between the timescales reached by MD simulation and those governing biological processes. To address this issue, many enhanced sampling methodologies have been developed to increase the sampling efficiency of molecular dynamics simulations and free energy calculations. Usually, enhanced sampling algorithms can be classified into methods based on collective variables (CV-based) and approaches which do not require predefined CVs (CV-free). In this chapter, the theoretical basis of free energy estimation is briefly reviewed first, followed by the reviews of the most common CV-based and CV-free methods including the presentation of some examples and recent developments. Finally, the combination of different enhanced sampling methods is discussed.

Dynamic design: manipulation of millisecond timescale motions on the energy landscape of cyclophilin A

Proteins need to interconvert between many conformations in order to function, many of which are formed transiently, and sparsely populated. Particularly when the lifetimes of these states approach the millisecond timescale, identifying the relevant structures and the mechanism by which they interconvert remains a tremendous challenge. Here we introduce a novel combination of accelerated MD (aMD) simulations and Markov state modelling (MSM) to explore these 'excited' conformational states. Applying this to the highly dynamic protein CypA, a protein involved in immune response and associated with HIV infection, we identify five principally populated conformational states and the atomistic mechanism by which they interconvert. A rational design strategy predicted that the mutant D66A should stabilise the minor conformations and substantially alter the dynamics, whereas the similar mutant H70A should leave the landscape broadly unchanged. These predictions are confirmed using CPMG and R1ρ solution state NMR measurements. By efficiently exploring functionally relevant, but sparsely populated conformations with millisecond lifetimes in silico, our aMD/MSM method has tremendous promise for the design of dynamic protein free energy landscapes for both protein engineering and drug discovery.

Importance of the Force Field Choice in Capturing Functionally Relevant Dynamics in the von Willebrand Factor

Whether recent updates and new releases of atomistic force fields can model the structural and dynamical properties of proteins containing both folded and partially disordered domains is still unclear. To address this fundamental question, we tested eight recently released force fields against our set of nuclear magnetic resonance (NMR) observables for a complex and medically relevant system, the major factor VIII binding region on the von Willebrand factor. This biomedically important region comprises both a folded and a partially structured domain. By using an enhanced sampling technique (temperature replica-exchange molecular dynamics simulations), we find that some force fields indeed rise to the challenge and capture the structural and dynamical features of the NMR ensemble and, therefore, are the appropriate choice for simulations of proteins with partially structured domains. What is more, we show that only such force fields can qualitatively capture the effects of a pathogenic mutation on the structural ensemble.

Analyzing Biomolecular Ensembles

Several techniques are available to generate conformational ensembles of proteins and other biomolecules either experimentally or computationally. These methods produce a large amount of data that need to be analyzed to identify structure-dynamics-function relationship. In this chapter, we will cover different tools to unveil the information hidden in conformational ensemble data and to guide toward the rationalization of the data. We included routinely used approaches such as dimensionality reduction, as well as new methods inspired by high-order statistics and graph theory.

Molecular dynamics ensemble refinement of the heterogeneous native state of NCBD using chemical shifts and NOEs

Many proteins display complex dynamical properties that are often intimately linked to their biological functions. As the native state of a protein is best described as an ensemble of conformations, it is important to be able to generate models of native state ensembles with high accuracy. Due to limitations in sampling efficiency and force field accuracy it is, however, challenging to obtain accurate ensembles of protein conformations by the use of molecular simulations alone. Here we show that dynamic ensemble refinement, which combines an accurate atomistic force field with commonly available nuclear magnetic resonance (NMR) chemical shifts and NOEs, can provide a detailed and accurate description of the conformational ensemble of the native state of a highly dynamic protein. As both NOEs and chemical shifts are averaged on timescales up to milliseconds, the resulting ensembles reflect the structural heterogeneity that goes beyond that probed, e.g., by NMR relaxation order parameters. We selected the small protein domain NCBD as object of our study since this protein, which has been characterized experimentally in substantial detail, displays a rich and complex dynamical behaviour. In particular, the protein has been described as having a molten-globule like structure, but with a relatively rigid core. Our approach allowed us to describe the conformational dynamics of NCBD in solution, and to probe the structural heterogeneity resulting from both short- and long-timescale dynamics by the calculation of order parameters on different time scales. These results illustrate the usefulness of our approach since they show that NCBD is rather rigid on the nanosecond timescale, but interconverts within a broader ensemble on longer timescales, thus enabling the derivation of a coherent set of conclusions from various NMR experiments on this protein, which could otherwise appear in contradiction with each other.

Computational modeling highlights the role of the disordered Formin Homology 1 domain in profilin-actin transfer

Formins accelerate actin polymerization, assumed to occur through flexible Formin Homology 1 (FH1) domain-mediated transfer of profilin-actin to the barbed end. To study FH1 properties and address sequence effects, including varying length/distribution of profilin-binding proline-rich motifs, we performed all-atom simulations of a set of representative FH1 domains of formins: mouse mDia1 and mDia2, budding yeast Bni1 and Bnr1, and fission yeast Cdc12, For3, and Fus1. We find FH1 has flexible regions between high-propensity polyproline helix regions. A coarse-grained model retaining sequence specificity, assuming rigid polyproline segments, describes their size. Multiple bound profilins or profilin-actin complexes expand mDia1-FH1, which may be important in cells. Simulations of the barbed end bound to Bni1-FH1-FH2 dimer show that the leading FH1 can better transfer profilin or profilin-actin, with decreasing probability as the distance from FH2 increases.

Rescue of conformational dynamics in enzyme catalysis by directed evolution

Rational design and directed evolution have proved to be successful approaches to increase catalytic efficiencies of both natural and artificial enzymes. Protein dynamics is recognized as important, but due to the inherent flexibility of biological macromolecules it is often difficult to distinguish which conformational changes are directly related to function. Here, we use directed evolution on an impaired mutant of the proline isomerase CypA and identify two second-shell mutations that partially restore its catalytic activity. We show both kinetically, using NMR spectroscopy, and structurally, by room-temperature X-ray crystallography, how local perturbations propagate through a large allosteric network to facilitate conformational dynamics. The increased catalysis selected for in the evolutionary screen is correlated with an accelerated interconversion between the two catalytically essential conformational sub-states, which are both captured in the high-resolution X-ray ensembles. Our data provide a glimpse of an evolutionary trajectory and show how subtle changes can fine-tune enzyme function.

A single cysteine post-translational oxidation suffices to compromise globular proteins kinetic stability and promote amyloid formation

Oxidatively modified forms of proteins accumulate during aging. Oxidized protein conformers might act as intermediates in the formation of amyloids in age-related disorders. However, it is not known whether this amyloidogenic conversion requires an extensive protein oxidative damage or it can be promoted just by a discrete, localized post-translational modification of certain residues. Here, we demonstrate that the irreversible oxidation of a single free Cys suffices to severely perturb the folding energy landscape of a stable globular protein, compromise its kinetic stability, and lead to the formation of amyloids under physiological conditions. Experiments and simulations converge to indicate that this specific oxidation-promoted protein aggregation requires only local unfolding. Indeed, a large scale analysis indicates that many cellular proteins are at risk of undergoing this kind of deleterious transition; explaining how oxidative stress can impact cell proteostasis and subsequently lead to the onset of pathological states.

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The population of aggregation-prone states by natural proteins does not require their extensive oxidation.

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A single residue irreversible oxidation suffices to promote the formation of amyloid fibrils.

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Under oxidative stress, many cellular proteins are at risk of aggregating into toxic species.

An optimal distance cutoff for contact-based Protein Structure Networks using side-chain centers of mass

Proteins are highly dynamic entities attaining a myriad of different conformations. Protein side chains change their states during dynamics, causing clashes that are propagated at distal sites. A convenient formalism to analyze protein dynamics is based on network theory using Protein Structure Networks (PSNs). Despite their broad applicability, few efforts have been devoted to benchmarking PSN methods and to provide the community with best practices. In many applications, it is convenient to use the centers of mass of the side chains as nodes. It becomes thus critical to evaluate the minimal distance cutoff between the centers of mass which will provide stable network properties. Moreover, when the PSN is derived from a structural ensemble collected by molecular dynamics (MD), the impact of the MD force field has to be evaluated. We selected a dataset of proteins with different fold and size and assessed the two fundamental properties of the PSN, i.e. hubs and connected components. We identified an optimal cutoff of 5 Å that is robust to changes in the force field and the proteins. Our study builds solid foundations for the harmonization and standardization of the PSN approach.

Changes in the free-energy landscape of p38α MAP kinase through its canonical activation and binding events as studied by enhanced molecular dynamics simulations

p38α is a Ser/Thr protein kinase involved in a variety of cellular processes and pathological conditions, which makes it a promising pharmacological target. Although the activity of the enzyme is highly regulated, its molecular mechanism of activation remains largely unexplained, even after decades of research. By using state-of-the-art molecular dynamics simulations, we decipher the key elements of the complex molecular mechanism refined by evolution to allow for a fine tuning of p38α kinase activity. Our study describes for the first time the molecular effects of different regulators of the enzymatic activity, and provides an integrative picture of the activation mechanism that explains the seemingly contradictory X-ray and NMR data.

DOI:http://dx.doi.org/10.7554/eLife.22175.001

Molecular motions and free-energy landscape of serine proteinase K in relation to its cold-adaptation: a comparative molecular dynamics simulation study and the underlying mechanisms

The physicochemical bases for enzyme cold-adaptation remain elusive.

The Mutational Landscape of the Oncogenic MZF1 SCAN Domain in Cancer

SCAN domains in zinc-finger transcription factors are crucial mediators of protein-protein interactions. Up to 240 SCAN-domain encoding genes have been identified throughout the human genome. These include cancer-related genes, such as the myeloid zinc finger 1 (MZF1), an oncogenic transcription factor involved in the progression of many solid cancers. The mechanisms by which SCAN homo- and heterodimers assemble and how they alter the transcriptional activity of zinc-finger transcription factors in cancer and other diseases remain to be investigated. Here, we provide the first description of the conformational ensemble of the MZF1 SCAN domain cross-validated against NMR experimental data, which are probes of structure and dynamics on different timescales. We investigated the protein-protein interaction network of MZF1 and how it is perturbed in different cancer types by the analyses of high-throughput proteomics and RNASeq data. Collectively, we integrated many computational approaches, ranging from simple empirical energy functions to all-atom microsecond molecular dynamics simulations and network analyses to unravel the effects of cancer-related substitutions in relation to MZF1 structure and interactions.

DNA-binding protects p53 from interactions with cofactors involved in transcription-independent functions

Binding-induced conformational changes of a protein at regions distant from the binding site may play crucial roles in protein function and regulation. The p53 tumour suppressor is an example of such an allosterically regulated protein. Little is known, however, about how DNA binding can affect distal sites for transcription factors. Furthermore, the molecular details of how a local perturbation is transmitted through a protein structure are generally elusive and occur on timescales hard to explore by simulations. Thus, we employed state-of-the-art enhanced sampling atomistic simulations to unveil DNA-induced effects on p53 structure and dynamics that modulate the recruitment of cofactors and the impact of phosphorylation at Ser215. We show that DNA interaction promotes a conformational change in a region 3 nm away from the DNA binding site. Specifically, binding to DNA increases the population of an occluded minor state at this distal site by more than 4-fold, whereas phosphorylation traps the protein in its major state. In the minor conformation, the interface of p53 that binds biological partners related to p53 transcription-independent functions is not accessible. Significantly, our study reveals a mechanism of DNA-mediated protection of p53 from interactions with partners involved in the p53 transcription-independent signalling. This also suggests that conformational dynamics is tightly related to p53 signalling.

Mapping transiently formed and sparsely populated conformations on a complex energy landscape

Determining the structures, kinetics, thermodynamics and mechanisms that underlie conformational exchange processes in proteins remains extremely difficult. Only in favourable cases is it possible to provide atomic-level descriptions of sparsely populated and transiently formed alternative conformations. Here we benchmark the ability of enhanced-sampling molecular dynamics simulations to determine the free energy landscape of the L99A cavity mutant of T4 lysozyme. We find that the simulations capture key properties previously measured by NMR relaxation dispersion methods including the structure of a minor conformation, the kinetics and thermodynamics of conformational exchange, and the effect of mutations. We discover a new tunnel that involves the transient exposure towards the solvent of an internal cavity, and show it to be relevant for ligand escape. Together, our results provide a comprehensive view of the structural landscape of a protein, and point forward to studies of conformational exchange in systems that are less characterized experimentally.

DOI:http://dx.doi.org/10.7554/eLife.17505.001

Proteins are the workhorses of cells, where they perform a wide range of roles. To do so, they adopt specific three-dimensional structures that enable them to interact with other molecules as necessary. Often a protein needs to be able to shift between different states with distinct structures as it goes about its job. To fully understand how a protein works, it is important to be able to characterize these different structures and how the protein changes between them.

Many of the experimental techniques used to study protein structure rely on isolating the individual structural forms of a protein. Since many structures only exist briefly, this can be very difficult. To complement experimental results, computer simulations allow researchers to model how atoms behave within a molecule. However, a number of factors limit how well these models represent what happens experimentally, such as the accuracy of the physical description used for the modeling.

Wang et al. set out to test and benchmark how well computer simulations could model changes in structure for a protein called T4 lysozyme, which has been studied extensively using experimental techniques. T4 lysozyme exists in two different states that have distinct structures. By comparing existing detailed experimental measurements with the results of their simulations, Wang et al. found that the simulations could capture key aspects of how T4 lysozyme changes its shape.

The simulations described the structure of the protein in both states and accurately determined the relative proportion of molecules that are found in each state. They could also determine how long it takes for a molecule to change its shape from one state to the other. The findings allowed Wang et al. to describe in fine detail – down to the level of individual atoms – how the protein changes its shape and how mutations in the protein affect its ability to do so. A key question for future studies is whether these insights can be extended to other proteins that are less well characterized experimentally than T4 lysozyme.

DOI:http://dx.doi.org/10.7554/eLife.17505.002

Free energy surface of an intrinsically disordered protein: comparison between temperature replica exchange molecular dynamics and bias-exchange metadynamics

Intrinsically disordered proteins (IDPs), which are expected to be largely unstructured under physiological conditions, make up a large fraction of eukaryotic proteins. Molecular dynamics simulations have been utilized to probe structural characteristics of these proteins, which are not always easily accessible to experiments. However, exploration of the conformational space by brute force molecular dynamics simulations is often limited by short time scales. Present literature provides a number of enhanced sampling methods to explore protein conformational space in molecular simulations more efficiently. In this work, we present a comparison of two enhanced sampling methods: temperature replica exchange molecular dynamics and bias exchange metadynamics. By investigating both the free energy landscape as a function of pertinent order parameters and the per-residue secondary structures of an IDP, namely, human islet amyloid polypeptide, we found that the two methods yield similar results as expected. We also highlight the practical difference between the two methods by describing the path that we followed to obtain both sets of data.

Towards a Molecular Understanding of the Link between Imatinib Resistance and Kinase Conformational Dynamics

Due to its inhibition of the Abl kinase domain in the BCR-ABL fusion protein, imatinib is strikingly effective in the initial stage of chronic myeloid leukemia with more than 90% of the patients showing complete remission. However, as in the case of most targeted anti-cancer therapies, the emergence of drug resistance is a serious concern. Several drug-resistant mutations affecting the catalytic domain of Abl and other tyrosine kinases are now known. But, despite their importance and the adverse effect that they have on the prognosis of the cancer patients harboring them, the molecular mechanism of these mutations is still debated. Here by using long molecular dynamics simulations and large-scale free energy calculations complemented by in vitro mutagenesis and microcalorimetry experiments, we model the effect of several widespread drug-resistant mutations of Abl. By comparing the conformational free energy landscape of the mutants with those of the wild-type tyrosine kinases we clarify their mode of action. It involves significant and complex changes in the inactive-to-active dynamics and entropy/enthalpy balance of two functional elements: the activation-loop and the conserved DFG motif. What is more the T315I gatekeeper mutant has a significant impact on the binding mechanism itself and on the binding kinetics.

Integrating atomistic molecular dynamics simulations, experiments, and network analysis to study protein dynamics: strength in unity

In the last years, we have been observing remarkable improvements in the field of protein dynamics. Indeed, we can now study protein dynamics in atomistic details over several timescales with a rich portfolio of experimental and computational techniques. On one side, this provides us with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome their own limitations. Moreover, now that we have the means to study protein dynamics in great details, we need new tools to understand the information embedded in the protein ensembles and in their dynamic signature. With this aim in mind, we should enrich the current tools for analysis of biomolecular simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations.

New Insights into the Molecular Mechanism of E-Cadherin-Mediated Cell Adhesion by Free Energy Calculations

Three-dimensional domain swapping is an important mode of protein association leading to the formation of stable dimers. Monomers associating via this mechanism mutually exchange a domain to form a homodimer. Classical cadherins, an increasingly important target for anticancer therapy, use domain swapping to mediate cell adhesion. However, despite its importance, the molecular mechanism of domain swapping is still debated. Here, we study the conformational changes that lead to activation and dimerization via domain swapping of E-cadherin. Using state-of-the-art enhanced sampling atomistic simulations, we reconstruct its conformational free energy landscape, obtaining the free energy profile connecting the inactive and active form. Our simulations predict that the E-cadherin monomer populates the open and closed forms almost equally, which is in agreement with the proposed "selected fit" mechanism in which monomers in an active conformational state bind to form a homodimer, analogous to the conformational selection mechanism often observed in ligand-target binding. Moreover, we find that the open state population is increased in the presence of calcium ions at the extracellular boundary, suggesting their possible role as allosteric activators of the conformational change.

Comparing molecular dynamics force fields in the essential subspace

The continued development and utility of molecular dynamics simulations requires improvements in both the physical models used (force fields) and in our ability to sample the Boltzmann distribution of these models. Recent developments in both areas have made available multi-microsecond simulations of two proteins, ubiquitin and Protein G, using a number of different force fields. Although these force fields mostly share a common mathematical form, they differ in their parameters and in the philosophy by which these were derived, and previous analyses showed varying levels of agreement with experimental NMR data. To complement the comparison to experiments, we have performed a structural analysis of and comparison between these simulations, thereby providing insight into the relationship between force-field parameterization, the resulting ensemble of conformations and the agreement with experiments. In particular, our results show that, at a coarse level, many of the motional properties are preserved across several, though not all, force fields. At a finer level of detail, however, there are distinct differences in both the structure and dynamics of the two proteins, which can, together with comparison with experimental data, help to select force fields for simulations of proteins. A noteworthy observation is that force fields that have been reparameterized and improved to provide a more accurate energetic description of the balance between helical and coil structures are difficult to distinguish from their "unbalanced" counterparts in these simulations. This observation implies that simulations of stable, folded proteins, even those reaching 10 microseconds in length, may provide relatively little information that can be used to modify torsion parameters to achieve an accurate balance between different secondary structural elements.