Disorder transitions and conformational diversity cooperatively modulate biological function in proteins

An inducible amphipathic α-helix mediates subcellular targeting and membrane binding of RPE65

RPE65 retinol isomerase is an indispensable player in the visual cycle between the vertebrate retina and RPE. Although membrane association is critical for RPE65 function, its mechanism is not clear. Residues 107-125 are believed to interact with membranes but are unresolved in all RPE65 crystal structures, whereas palmitoylation at C112 also plays a role. We report the mechanism of membrane recognition and binding by RPE65. Binding of aa107-125 synthetic peptide with membrane-mimicking micellar surfaces induces transition from unstructured loop to amphipathic α-helical (AH) structure but this transition is automatic in the C112-palmitoylated peptide. We demonstrate that the AH significantly affects palmitoylation level, membrane association, and isomerization activity of RPE65. Furthermore, aa107-125 functions as a membrane sensor and the AH as a membrane-targeting motif. Molecular dynamic simulations clearly show AH-membrane insertion, supporting our experimental findings. Collectively, these studies allow us to propose a working model for RPE65-membrane binding, and to provide a novel role for cysteine palmitoylation.

The role of membranes in function and dysfunction of intrinsically disordered amyloidogenic proteins

Membrane-protein interactions play a major role in human physiology as well as in diseases pathology. Interaction of a protein with the membrane was previously thought to be dependent on well-defined three-dimensional structure of the protein. In recent decades, however, it has become evident that a large fraction of the proteome, particularly in eukaryotes, stays disordered in solution and these proteins are termed as intrinsically disordered proteins (IDPs). Also, a vast majority of human proteomes have been reported to contain substantially long disordered regions, called intrinsically disordered regions (IDRs), in addition to the structurally ordered regions. IDPs exist in an ensemble of conformations and the conformational flexibility enables IDPs to achieve functional diversity. IDPs (and IDRs) are found to be important players in cell signaling, where biological membranes act as anchors for signaling cascades. Therefore, IDPs modulate the membrane architectures, at the same time membrane composition also affects the binding of IDPs. Because of intrinsic disorders, misfolding of IDPs often leads to formation of oligomers, protofibrils and mature fibrils through progressive self-association. Accumulation of amyloid-like aggregates of some of the IDPs is a known causative agent for numerous diseases. In this chapter we highlight recent advances in understanding membrane interactions of some of the intrinsically disordered proteins involved in the pathogenesis of human diseases.

Intrinsically disordered proteins and membranes: a marriage of convenience for cell signalling?

The structure-function paradigm has guided investigations into the molecules involved in cellular signalling for decades. The peripheries of this paradigm, however, start to unravel when considering the co-operation between proteins and the membrane in signalling processes. Intrinsically disordered regions hold distinct advantages over folded domains in terms of their binding promiscuity, sensitivity to their particular environment and their ease of modulation through post-translational modifications. Low sequence complexity and bias towards charged residues are also favourable for the multivalent electrostatic interactions that occur at the surfaces of lipid bilayers. This review looks at the principles behind the successful marriage between protein disorder and membranes in addition to the role of this partnership in modifying and regulating signalling in cellular processes. The HVR (hypervariable region) of small GTPases is highlighted as a well-studied example of the nuanced role a short intrinsically disordered region can play in the fine-tuning of signalling pathways.

Intrinsically Disordered Protein Ensembles Shape Evolutionary Rates Revealing Conformational Patterns

Intrinsically disordered proteins (IDPs) lack stable tertiary structure under physiological conditions. The unique composition and complex dynamical behaviour of IDPs make them a challenge for structural biology and molecular evolution studies. Using NMR ensembles, we found that IDPs evolve under a strong site-specific evolutionary rate heterogeneity, mainly originated by different constraints derived from their inter-residue contacts. Evolutionary rate profiles correlate with the experimentally observed conformational diversity of the protein, allowing the description of different conformational patterns possibly related to their structure-function relationships. The correlation between evolutionary rates and contact information improves when structural information is taken not from any individual conformer or the whole ensemble, but from combining a limited number of conformers. Our results suggest that residue contacts in disordered regions constrain evolutionary rates to conserve the dynamic behaviour of the ensemble and that evolutionary rates can be used as a proxy for the conformational diversity of IDPs.

Physical Chemistry of the Protein Backbone: Enabling the Mechanisms of Intrinsic Protein Disorder

Over the last two decades it has become clear that well-defined structure is not a requisite for proteins to properly function. Rather, spectra of functionally competent, structurally disordered states have been uncovered requiring canonical paradigms in molecular biology to be revisited or reimagined. It is enticing and oftentimes practical to divide the proteome into structured and unstructured, or disordered, proteins. While function, composition, and structural properties largely differ, these two classes of protein are built upon the same scaffold, namely, the protein backbone. The versatile physicochemical properties of the protein backbone must accommodate structural disorder, order, and transitions between these states. In this review, we survey these properties through the conceptual lenses of solubility and conformational populations and in the context of protein-disorder mediated phenomena (e.g., phase separation, order-disorder transitions, allostery). Particular attention is paid to the results of computational studies, which, through thermodynamic decomposition and dissection of molecular interactions, can provide valuable mechanistic insight and testable hypotheses to guide further solution experiments. Lastly, we discuss changes in the dynamics of side chains and order-disorder transitions of the protein backbone as two modes or realizations of "entropic reservoirs" capable of tuning coupled thermodynamic processes.

Experimentally-driven protein structure modeling

Revolutions in natural and exact sciences started at the dawn of last century have led to the explosion of theoretical, experimental, and computational approaches to determine structures of molecules, complexes, as well as their rich conformational dynamics. Since different experimental methods produce information that is attributed to specific time and length scales, corresponding computational methods have to be tailored to these scales and experiments. These methods can be then combined and integrated in scales, hence producing a fuller picture of molecular structure and motion from the "puzzle pieces" offered by various experiments. Here, we describe a number of computational approaches to utilize experimental data to glance into structure of proteins and understand their dynamics. We will also discuss the limitations and the resolution of the constraints-based modeling approaches. SIGNIFICANCE: Experimentally-driven computational structure modeling and determination is a rapidly evolving alternative to traditional approaches for molecular structure determination. These new hybrid experimental-computational approaches are proving to be a powerful microscope to glance into the structural features of intrinsically or partially disordered proteins, dynamics of molecules and complexes. In this review, we describe various approaches in the field of experimentally-driven computational structure modeling.

Investigation into Early Steps of Actin Recognition by the Intrinsically Disordered N-WASP Domain V

Cellular regulation or signaling processes are mediated by many proteins which often have one or several intrinsically disordered regions (IDRs). These IDRs generally serve as binders to different proteins with high specificity. In many cases, IDRs undergo a disorder-to-order transition upon binding, following a mechanism between two possible pathways, the induced fit or the conformational selection. Since these mechanisms contribute differently to the kinetics of IDR associations, it is important to investigate them in order to gain insight into the physical factors that determine the biomolecular recognition process. The verprolin homology domain (V) of the Neural Wiskott-Aldrich Syndrome Protein (N-WASP), involved in the regulation of actin polymerization, is a typical example of IDR. It is composed of two WH2 motifs, each being able to bind one actin molecule. In this study, we investigated the early steps of the recognition process of actin by the WH2 motifs of N-WASP domain V. Using docking calculations and molecular dynamics simulations, our study shows that actin is first recognized by the N-WASP domain V regions which have the highest propensity to form transient α -helices. The WH2 motif consensus sequences "LKKV" subsequently bind to actin through large conformational changes of the disordered domain V.

Thermodynamics of Conformational Transitions in a Disordered Protein Backbone Model

Conformational entropy is expected to contribute significantly to the thermodynamics of structural transitions in intrinsically disordered proteins or regions in response to protein/ligand binding, posttranslational modifications, and environmental changes. We calculated the backbone (dihedral) conformational entropy of oligoglycine (Gly_N), a protein backbone mimic and model intrinsically disordered region, as a function of chain length (N=3, 4, 5, 10, and 15) from simulations using three different approaches. The backbone conformational entropy scales linearly with chain length with a slope consistent with the entropy of folding of well-structured proteins. The entropic contributions of second-order dihedral correlations are predominantly through intraresidue ϕ-ψ pairs, suggesting that oligoglycine may be thermodynamically modeled as a system of independent glycine residues. We find the backbone conformational entropy to be largely independent of global structural parameters, like the end-to-end distance and radius of gyration. We introduce a framework referred to herein as "ensemble confinement" to estimate the loss (gain) of conformational free energy and its entropic component when individual residues are constrained to (released from) particular regions of the ϕ-ψ map. Quantitatively, we show that our protein backbone model resists ordering/folding with a significant, unfavorable ensemble confinement free energy because of the loss of a substantial portion of the absolute backbone entropy. Proteins can couple this free-energy reservoir to distal binding events as a regulatory mechanism to promote or suppress binding.

Bioinformatics in Latin America and SoIBio impact, a tale of spin-off and expansion around genomes and protein structures

Owing to the emerging impact of bioinformatics and computational biology, in this article, we present an overview of the history and current state of the research on this field in Latin America (LA). It will be difficult to cover without inequality all the efforts, initiatives and works that have happened for the past two decades in this vast region (that includes >19 million km² and >600 million people). Despite the difficulty, we have done an analytical search looking for publications in the field made by researchers from 19 LA countries in the past 25 years. In this way, we find that research in bioinformatics in this region should develop twice to approach the average world scientific production in the field. We also found some of the pioneering scientists who initiated and led bioinformatics in the region and were promoters of this new scientific field. Our analysis also reveals that spin-off began around some specific areas within the biomolecular sciences: studies on genomes (anchored in the new generation of deep sequencing technologies, followed by developments in proteomics) and studies on protein structures (supported by three-dimensional structural determination technologies and their computational advancement). Finally, we show that the contribution to this endeavour of the Iberoamerican Society for Bioinformatics, founded in Mexico in 2009, has been significant, as it is a leading forum to join efforts of many scientists from LA interested in promoting research, training and education in bioinformatics.

Structural Characterization of N-WASP Domain V Using MD Simulations with NMR and SAXS Data

Because of their large conformational heterogeneity, structural characterization of intrinsically disordered proteins (IDPs) is very challenging using classical experimental methods alone. In this study, we use NMR and small-angle x-ray scattering (SAXS) data with multiple molecular dynamics (MD) simulations to describe the conformational ensemble of the fully disordered verprolin homology domain of the neural Aldrich syndrome protein involved in the regulation of actin polymerization. First, we studied several back-calculation software of SAXS scattering intensity and optimized the adjustable parameters to accurately calculate the SAXS intensity from an atomic structure. We also identified the most appropriate force fields for MD simulations of this IDP. Then, we analyzed four conformational ensembles of neural Aldrich syndrome protein verprolin homology domain, two generated with the program flexible-meccano with or without NMR-derived information as input and two others generated by MD simulations with two different force fields. These four conformational ensembles were compared to available NMR and SAXS data for validation. We found that MD simulations with the AMBER-03w force field and the TIP4P/2005s water model are able to correctly describe the conformational ensemble of this 67-residue IDP at both local and global level.

Exploring Protein Conformational Diversity

The native state of proteins is composed of conformers in dynamical equilibrium. In this chapter, different issues related to conformational diversity are explored using a curated and experimentally based database called CoDNaS (Conformational Diversity in the Native State). This database is a collection of redundant structures for the same sequence. CoDNaS estimates the degree of conformational diversity using different global and local structural similarity measures. It allows the user to explore how structural differences among conformers change as a function of several structural features providing further biological information. This chapter explores the measurement of conformational diversity and its relationship with sequence divergence. Also, it discusses how proteins with high conformational diversity could affect homology modeling techniques.

Large scale analysis of protein conformational transitions from aqueous to non-aqueous media

Background

Biocatalysis in organic solvents is nowadays a common practice with a large potential in Biotechnology. Several studies report that proteins which are co-crystallized or soaked in organic solvents preserve their fold integrity showing almost identical arrangements when compared to their aqueous forms. However, it is well established that the catalytic activity of proteins in organic solvents is much lower than in water. In order to explain this diminished activity and to further characterize the behaviour of proteins in non-aqueous environments, we performed a large-scale analysis (1737 proteins) of the conformational diversity of proteins crystallized in aqueous and co-crystallized or soaked in non-aqueous media.

Results

Using proteins’ experimentally determined conformational diversity taken from CoDNaS database, we found that proteins in non-aqueous media display much lower conformational diversity when compared to the corresponding conformers obtained in water. When conformational diversity is compared between conformers obtained in different non-aqueous media, their structural differences are larger and mostly independent of the presence of cognate ligands. We also found that conformers corresponding to non-aqueous media have larger but less flexible cavities, lower number of disordered regions and lower active-site residue mobility.

Conclusions

Our results show that non-aqueous media conformers have specific structural features and that they do not adopt extreme conformations found in aqueous media. This makes them clearly different from their corresponding aqueous conformers.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2044-2) contains supplementary material, which is available to authorized users.

Homology modeling in a dynamical world

A key concept in template-based modeling (TBM) is the high correlation between sequence and structural divergence, with the practical consequence that homologous proteins that are similar at the sequence level will also be similar at the structural level. However, conformational diversity of the native state will reduce the correlation between structural and sequence divergence, because structural variation can appear without sequence diversity. In this work, we explore the impact that conformational diversity has on the relationship between structural and sequence divergence. We find that the extent of conformational diversity can be as high as the maximum structural divergence among families. Also, as expected, conformational diversity impairs the well-established correlation between sequence and structural divergence, which is nosier than previously suggested. However, we found that this noise can be resolved using a priori information coming from the structure-function relationship. We show that protein families with low conformational diversity show a well-correlated relationship between sequence and structural divergence, which is severely reduced in proteins with larger conformational diversity. This lack of correlation could impair TBM results in highly dynamical proteins. Finally, we also find that the presence of order/disorder can provide useful beforehand information for better TBM performance.

Conformational diversity analysis reveals three functional mechanisms in proteins

Protein motions are a key feature to understand biological function. Recently, a large-scale analysis of protein conformational diversity showed a positively skewed distribution with a peak at 0.5 Å C-alpha root-mean-square-deviation (RMSD). To understand this distribution in terms of structure-function relationships, we studied a well curated and large dataset of ~5,000 proteins with experimentally determined conformational diversity. We searched for global behaviour patterns studying how structure-based features change among the available conformer population for each protein. This procedure allowed us to describe the RMSD distribution in terms of three main protein classes sharing given properties. The largest of these protein subsets (~60%), which we call "rigid" (average RMSD = 0.83 Å), has no disordered regions, shows low conformational diversity, the largest tunnels and smaller and buried cavities. The two additional subsets contain disordered regions, but with differential sequence composition and behaviour. Partially disordered proteins have on average 67% of their conformers with disordered regions, average RMSD = 1.1 Å, the highest number of hinges and the longest disordered regions. In contrast, malleable proteins have on average only 25% of disordered conformers and average RMSD = 1.3 Å, flexible cavities affected in size by the presence of disordered regions and show the highest diversity of cognate ligands. Proteins in each set are mostly non-homologous to each other, share no given fold class, nor functional similarity but do share features derived from their conformer population. These shared features could represent conformational mechanisms related with biological functions.