Modeling and simulation of intrinsically disordered proteins

This work is primarily about the development, validation and application of computer simulation models for intrinsically disordered proteins, both in solution and in the presence of uniformly charged, ideal surfaces. The models in question are either coarse-grained or atomistic in nature, and their applications are dependent on the specific purpose of each study. Both, Metropolis Monte Carlo and molecular dynamics simulations were employed to execute them.In regard to the coarse-grained models, it was found that a simple physical model can be used to mimic the properties of flexible proteins, helping to understand how and why these proteins adsorb to surfaces under certain conditions. The same model later shown that two disordered proteins from different sources (saliva and milk) possess similar structural and thermodynamic properties in solution and when adsorbed to surfaces, thus being hypothesized that it may be possible to use one of them as a substitute for the other under a pharmaceutical context.After a first indication that the atomistic models used until recently for the simulation of well-folded proteins may not be applicable to their disordered counterparts, it was then confirmed - by evaluating several such models against experimental evidence - that these models do indeed produce overly collapsed IDP conformational ensembles. New models, favoring protein–water over protein–protein interactions, were then shown to effectively produce more extended conformations, which are in much better agreement with each other and with experimental evidence. One of the new atomistic models was then used to perform the structural characterization of a disordered peptide conjugated to a small molecule, which has been shown to possess promising therapeutical applications. The value of computer simulations is well illustrated in this study, as the insight obtainable from experiment was limited and it was only through the analysis of the simulations that a possible link between the average conjugate structure and its increased antifungal activity is established

Výpočetní studie krátkých peptidů a miniproteinů a vliv prostředí na jejich konformaci.

Apart from biological functions, peptides are of uttermost importance as models for un- folded, denatured or disordered state of the proteins. Similarly, miniproteins such as Trp-cage have proven their role as simple models of both experimental and theoretical studies of protein folding. Molecular dynamics and computer simulations can provide an unique insight on processes at atomic level. However, simulations of peptides and minipro- teins face two cardinal problems-inaccuracy of force fields and inadequate conformation sampling. Both principal issues were tackled in this theses. Firstly, the differences in several force field for peptides and proteins were questioned. We demonstrated the inability of the used force fields to predict consistently intrinsic conformational preferences of individual amino acids in the form of dipeptides and the source of the discrepancies was traced. In order to shed light on the nature of conformational ensembles under various denatur- ing conditions, we studied host-guest AAXAA peptides. The simulations revealed that thermal and chemical denaturation by urea produces qualitatively different ensembles and shift propensities of individual amino acids to particular conformers. The problem of insufficient conformation sampling was dealt by introducing gyration- and...Peptidy, kromě své biologické funkce, představují take důležité modely nesbalených, de- naturovaných nebo nestrukturovaných proteinů. Pobobně důležitými modely pro exper- imentální i teoretické studium sbalování proteinů jsou miniproteiny, jako např. Trp- cage. Chování peptidů i proteinů lze studovat v počítačových simulacích pomocí metod molekulární dynamiky, které umožnují sledovat děje v atomistickém rozlišení. Tyto metody však čelí však dvěma zásadním problémům - přesnosti používaných energetick- ých funkcí a nedostatečnému vzorkování konformačních stavů. V této disertaci jsem se zabýval oběma okruhy problémů. Vliv rozdílných, běžně používných energetických funkcí ("force fields") byl testován na modelu aminokyselinových dipeptidů. Žádná sada parametrů však nedokázala konzis- tentně reprodukovat konformační preference jednotlivých aminokyselin. Výsledky simu- lací byly mezi sebou srovnány a byly hledány příčiny jejich vzájemných odlišností. Abychom odhalili, jakým způsobem různé podmínky ovlivňují konformační stavy peptidů, zkoumali jsme vlastnosti aminokyselin v AAXAA peptidech. Simulace odhalily zásadní rozdíl ve vlivu tepelné a chemické denaturace (močovinou) na charakter a zastoupení konformací peptidů, stejně jako konformačních preferencí jednotlivých aminokyselin. K problematice vzorkování...Department of Physical and Macromolecular ChemistryKatedra fyzikální a makromol. chemieFaculty of SciencePřírodovědecká fakult

Quantification of Conformational Heterogeneity and its Role in Protein Aggregation and Unfolding

Proteins can exhibit significant conformational heterogeneity either under denaturing conditions or in aqueous solutions. The latter is true for a class of proteins whose sequences predispose them to form heterogeneous ensembles of conformations. Characterization of conformational heterogeneity in a protein ensemble requires the quantification of the amplitudes of spontaneous fluctuations in conjunction with information regarding coarse grain measures that report on the average sizes, shapes, and densities. This often demands multiplexed experimental approaches whose readouts are interpreted or annotated using ensembles drawn from atomistic or coarse grain computational simulations. Efforts to characterize conformational heterogeneity contribute directly to our understanding of disorder-to-order transitions in protein folding and self-assembly. These efforts are also crucial to our understanding of the heterotypic interactions involving intrinsically disordered proteins and non-native states of well-folded proteins. These heterotypic interactions are important in signal transduction and the regulation of protein homeostasis. The onset and progression of several systemic and neurodegenerative conformational diseases are linked to the nature and degree of conformational heterogeneity in specific proteins or proteolytic products of proteins. This thesis work focuses on the quantitative characterization of conformational heterogeneity in simulated ensembles of inducibly unfolded and intrinsically disordered proteins. Advances in nuclear magnetic resonance spectroscopy afford the possibility of detailed measurements of inter-residue distances and modulations to the relaxation dynamics of paramagnetic spins that are inserted as probes into a protein. These state-of-the-art measurements show interesting features within denatured state ensembles that cannot be explained using canonical random coil models. Here, we use computer simulations to generate plausible facsimiles of denatured state ensembles that reproduce experimental data and demonstrate that the ensembles that are consistent with the data are characterized by the presence of low-likelihood, long-range intra-chain contacts between hydrophobic groups. When placed in the context of sequence conservation information, it appears that these contacts act as gatekeepers that protect proteins from the deleterious consequences of protein aggregation by sequestering hydrophobic groups in an assortment of intra-chain long-range contacts. We also characterize the nature and degree of conformational heterogeneity in glutamine- and asparagine-rich containing systems. These efforts lead to insights regarding the role of conformational heterogeneity in mediating intermolecular associations that are implicated in aggregation and self-assembly of these systems. Analysis of results from atomistic simulations leads to a phenomenological model for the modulation of conformational heterogeneity and degeneracies of intermolecular interactions by naturally occurring sequences that flank polyglutamine domains. Finally, we develop a formal order parameter to quantify the conformational heterogeneity in simulated ensembles of proteins. When combined with measures of density and fluctuations thereof, it can be used to provide a complete description of the degree and nature of conformational heterogeneity in different ensembles, thus affording the ability to compare different ensembles to each other while also providing a way to categorize conformational transitions

Primary Structure and Solution Conditions Determine Conformational Ensemble Properties of Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) are a class of proteins that do not exhibit well-defined three-dimensional structures. The absence of structure is intrinsic to their amino acid sequences, which are characterized by low hydrophobicity and high net charge per residue compared to folded proteins. Contradicting the classic structure-function paradigm, IDPs are capable of interacting with high specificity and affinity, often acquiring order in complex with protein and nucleic acid binding partners. This phenomenon is evident during cellular activities involving IDPs, which include transcriptional and translational regulation, cell cycle control, signal transduction, molecular assembly, and molecular recognition. Although approximately 30% of eukaryotic proteomes are intrinsically disordered, the nature of IDP conformational ensembles remains unclear. In this dissertation, we describe relationships connecting characteristics of IDP conformational ensembles to their primary structures and solution conditions. Using molecular simulations and fluorescence experiments on a set of base-rich IDPs, we find that net charge per residue segregates conformational ensembles along a globule-to-coil transition. Speculatively generalizing this result, we propose a phase diagram that predicts an IDP\u27s average size and shape based on sequence composition and use it to generate hypotheses for a broad set of intrinsically disordered regions (IDRs). Simulations reveal that acid-rich IDRs, unlike their oppositely charged base-rich counterparts, exhibit disordered globular ensembles despite intra-chain repulsive electrostatic interactions. This apparent asymmetry is sensitive to simulation parameters for representing alkali and halide salt ions, suggesting that solution conditions modulate IDP conformational ensembles. We refine the ion parameters using a calibration procedure that relies exclusively on crystal lattice properties. Simulations with these parameters recover swollen coil behavior for acid-rich IDRs, but also uncover a dependence on sequence patterning for polyampholytic IDPs. These contributions initiate an endeavor to elucidate general principles that enable prediction of an IDP\u27s conformational ensemble based on primary structure and solution conditions, a goal analogous to structure prediction for folded proteins. Such principles would provide a molecular basis for understanding the roles of IDPs in physiology and pathophysiology, guide development of agents that modulate their behavior, and enable their rational design from chosen specifications

In-silico Investigation of Ion-Pumping Rotary A- and V-type ATPases: Structural and Dynamical Aspects

Advances in Molecular Biosciences have revolutionised the way we perceive and pursue current biological research. Dynamic, complex biomacromolecules constitute the essential components of Cells. Particularly proteins have been characterised as the workhorse molecules of life. Either as single chains or complexes of associated units, proteins participate in every biological process with a specific structural and/or functional role. Ion-pumping rotary ATPases is a large family of important membrane-bound protein nanomachines. In the current work we investigate structural and dynamical aspects of the A- and V-type rotary ATPases, related to functional dynamics, and propose a multiscale computational framework for their in-silico biophysical characterisation and the interpretation of low-resolution experimental data from electron microscopy in Chapter 3. For the first time we present results from explicit-solvent atomistic molecular dynamics simulations of the prokaryotic A-type peripheral stator stalk and central rotor axle, both being critical subunits involved in the mechanical coupling of the rotary ATPases in Chapter 4. Our simulation data reveal the presence of flexibility heterogeneity and demonstrate the dynamic nature of the peripheral stator stalk as a source of intact ATPase particle conformational variability. In Chapter 5 we show the presence of structural plasticity in the eukaryotic peripheral stator stalk of the V-ATPase and discuss possible implications for V-ATPase regulation. Overall, the wealth of information accessed with molecular-dynamics simulations allows the exploitation of atomistic information within the multiscale framework of Chapter 3 to be applied for the mechanical characterisation of rotary ATPases in future studies. In particular, atomistic data could serve as high-resolution information for future parameterisation of simplified coarse-grain models for all ATPase subunits and the construction of molecular models for the intact ATPases. We anticipate that our approach will contribute to elucidating the molecular origin of rotary ATPases’ conformational flexibility and its implications for the holoenzyme’s function and kinetic efficiency

Development of novel computational methods suitable for modelling intrinsically disordered proteins

PhD ThesisProteins without a stable tertiary structure are known as intrinsically disordered or metamorphic. These proteins denoted as IDPs – or protein domains denoted as IDRs – exert crucial roles in cellular signalling, growth and molecular recognition events. Due to their high plasticity, IDPs and IDRs are very challenging for experimental and computational structural studies. To enable these, all-atom molecular dynamics (MD) simulations are used, as they provide insight into structure and dynamics at the atomistic level of detail. However, the current generalist physical models (protein force fields and solvent models) used in MD simulations are unable to generate satisfactory ensembles for IDPs/IDRs when compared to existing experimental data. This work aimed to improve on the state-of-the-art accuracy for simulations of IDPs/IDRs without sacrificing accuracy for folded domains. Herein, the accuracy of several different force fields frequently used for simulations of proteins was compared, in simulations of both ordered and disordered systems. The results showed that each force field has strengths and limitations. Given the fact that interactions with the solvent are pivotal for accurate simulations of intrinsically disordered proteins, a novel solvation model was developed, denoted as Charge-Augmented 3 Point water model for Intrinsically disordered Proteins (CAIPi3P). CAIPi3P model was generated through systematic scanning of the dipole moment values calculated for the popular TIP3P three-point water model. By increasing the dipole magnitude, the agreement between experimental and calculated small-angle X-ray scattering (SAXS) curves was massively improved for a series of model IDRs. To further improve the simulations of proteins containing IDRs, a novel method to assemble force field parameters has been developed. Denoted as Hybrid_FF, it merges parameters from different established force-fields, performing well for structured and disordered regions (AMBER99SB-ILDN and AMBER03ws, respectively), parametrising each secondary structure differently. Testing these joint parameters for a series of IDR-containing proteins showed that such an approach improved the accuracy of the sampled configurations for long disordered regions. Finally, a software to estimate and analyse the transition dynamics of intrinsically disordered regions has been developed in this work. Named structural quantifier of entropy (SQuE), it uses a first-order approximation to the probability distribution to assess the structural entropy for protein transitions barriers. It is expected that tools developed in this study will generate more accurate IDP/IDR ensembles, broadening the range of biologically relevant systems amenable to atomistic molecular dynamics simulations

Disordered Proteins: Connecting Sequences to Emergent Properties

Many IDPs participate in coupled folding and binding reactions and form alpha helical structures in their bound complexes. Alanine, glycine, or proline scanning mutagenesis approaches are often used to dissect the contributions of intrinsic helicities to coupled folding and binding. These experiments can yield confounding results because the mutagenesis strategy changes the amino acid compositions of IDPs. Therefore, an important next step in mutagenesis-based approaches to mechanistic studies of coupled folding and binding is the design of sequences that satisfy three major constraints. These are (i) achieving a target intrinsic alpha helicity profile; (ii) fixing the positions of residues corresponding to the binding interface; and (iii) maintaining the native amino acid composition. Here, we report the development of a Genetic Algorithm for Design of Intrinsic secondary Structure (GADIS) for designing sequences that satisfy the specified constraints. We describe the algorithm and present results to demonstrate the applicability of GADIS by designing sequence variants of the intrinsically disordered PUMA system that undergoes coupled folding and binding to Mcl-1. Our sequence designs span a range of intrinsic helicity profiles. The predicted variations in sequence-encoded mean helicities are tested against experimental measurements.There is a significant collection of proteins with repeating blocks of oppositely charged residues where the consensus sequence is a block of four Glu residues followed by a block of four Lys or Arg residues, (Glu4(Lys/Arg)4)n. These proteins have been experimentally shown to form long single alpha helices (SAHs) under biologically relevant conditions. However, these results are confounding to disorder predictors and to certain atomistic simulations in that both predict these sequences to be strongly disordered. The current working hypothesis is that SAHs are stabilized by i:i+4 salt bridges between opposite charges in consecutive helical turns. We test the merits of this hypothesis to understand the sequence-encoded preference for SAHs and the logic behind the failure of certain atomistic simulations in anticipating the preference for stable SAHs.In simulations with fixed charges the favorable free energy of solvation of charged residues and the associated loss of sidechain entropy hinders the formation of SAHs. We proposed that alterations to charge states induced by sequence context might play an important role in stabilizing SAHs. We tested this hypothesis using a (Glu4Lys4)n repeat protein and a simulation strategy that permits the substitution of charged residues with neutralized protonated or deprotonated variants of Glu / Lys. Our results predict that stable SAH structures derive from the neutralization of approximately half the Glu residues. These findings explain experimental observations and also provide a coherent rationale for the failure of simulations based on fixed charge models. Large-scale sequence analysis reveals that naturally occurring sequences often include defects in charge patterns such as Gln or Ala substitutions. This sequence-encoded incorporation of uncharged residues combined with neutralization of charged residues might tilt the balance toward alpha helical conformations.Micron-sized, non-membrane bound cellular bodies can form as the result of collective interactions between modules of distinct multidomain proteins. Li et al. have examined the phase diagrams that result for polymers of SH3 domains and proline-rich modules (PRMs) while varying the number of interacting domains. It is noteworthy that flexible, intrinsically disordered linkers connect the interacting units within each polymer. Conventional wisdom holds that linkers play a passive role in determining the phase behavior of multidomain proteins that undergo phase separations. Here, we ask if this view is accurate. The motivation for our work comes from recent studies that have uncovered a rich diversity of composition-to-conformation and sequence-to-conformation relationships for intrinsically disordered proteins. The central finding is that disordered regions of proteins have distinct sequence-encoded conformational preferences. Accordingly, we reasoned that the conformational properties of linkers might be a contributing factor, in addition to polyvalency, to the phase behavior of multidomain proteins.We have developed and deployed a three-dimensional lattice model to arrive at a predictive framework to query the effects of linkers on the phase diagrams of polyvalent systems. We find that the critical concentration for phase transition can be influenced by the conformational properties of linkers. Specifically, our results show that linkers modulate the cooperative binding between domains of polymers that are already bound together. Depending on their conformational properties, linkers can also block access to the binding domains via excluded volume effects. Additionally, we find that the properties of the linkers can lead to controls over the mixing of proteins in these bodies. Specifically, we find that there are large ranges of parameters for three protein systems where the bodies isolate specific proteins to different regions of the bodies instead of uniformly mixing them. This result is validated by recent findings of organization inside some observed bodies

Sequence Determinants of the Individual and Collective Behaviour of Intrinsically Disordered Proteins

Intrinsically disordered proteins and protein regions (IDPs) represent around thirty percent of the eukaryotic proteome. IDPs do not fold into a set three dimensional structure, but instead exist in an ensemble of inter-converting states. Despite being disordered, IDPs are decidedly not random; well-defined - albeit transient - local and long-range interactions give rise to an ensemble with distinct statistical biases over many length-scales. Among a variety of cellular roles, IDPs drive and modulate the formation of phase separated intracellular condensates, non-stoichiometric assemblies of protein and nucleic acid that serve many functions. In this work, we have explored how the amino acid sequence of IDPs determines their conformational behaviour, and how sequence and single chain behaviour influence their collective behaviour in the context of phase separation. In part I, in a series of studies, we used simulation, theory, and statistical analysis coupled with a wide range of experimental approaches to uncover novel rules that further explore how primary sequence and local structure influence the global and local behaviour of disordered proteins, with direct implications for protein function and evolution. We found that amino acid sidechains counteract the intrinsic collapse of the peptide backbone, priming the backbone for interaction and providing a fully reconciliatory explanation for the mechanism of action associated with the denaturants urea and GdmCl. We discovered that proline can engender a conformational buffering effect in IDPs to counteract standard electrostatic effects, and that the patterning those proline residues can be a crucial determinant of the conformational ensemble. We developed a series of tools for analysing primary sequences on a proteome wide scale and used them to discover that different organisms can have substantially different average sequence properties. Finally, we determined that for the normally folded protein NTL9, the unfolded state under folding conditions is relatively expanded but has well defined native and non-native structural preferences. In part II, we identified a novel mode of phase separation in biology, and explored how this could be tuned through sequence design. We discovered that phase separated liquids can be many orders of magnitude more dilute than simple mean-field theories would predict, and developed an analytic framework to explain and understand this phenomenon. Finally, we designed, developed and implemented a novel lattice-based simulation engine (PIMMS) to provide sequence-specific insight into the determinants of conformational behaviour and phase separation. PIMMS allows us to accurately and rapidly generate sequence-specific conformational ensembles and run simulations of hundreds of polymers with the goal of allowing us to systematically elucidate the link between primary sequence of phase separation