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Cell cycle transitions result from global changes in protein phosphorylation states triggered by cyclin-dependent kinases (CDKs). To understand how this complexity produces an ordered and rapid cellular reorganisation, we generated a high-resolution map of changing phosphosites throughout unperturbed early cell cycles in single Xenopus embryos, derived the emergent principles through systems biology analysis, and tested them by biophysical modelling and biochemical experiments. We found that most dynamic phosphosites share two key characteristics: they occur on highly disordered proteins that localise to membraneless organelles, and are CDK targets. Furthermore, CDK-mediated multisite phosphorylation can switch homotypic interactions of such proteins between favourable and inhibitory modes for biomolecular condensate formation. These results provide insight into the molecular mechanisms and kinetics of mitotic cellular reorganisation.

Cell cycle transitions result from global changes in protein phosphorylation states triggered by cyclin-dependent kinases (CDKs). To understand how this complexity produces an ordered and rapid cellular reorganisation, we generated a high-resolution map of changing phosphosites throughout unperturbed early cell cycles in single Xenopus embryos, derived the emergent principles through systems biology analysis, and tested them by biophysical modelling and biochemical experiments. We found that most dynamic phosphosites share two key characteristics: they occur on highly disordered proteins that localise to membraneless organelles, and are CDK targets. Furthermore, CDK-mediated multisite phosphorylation can switch homotypic interactions of such proteins between favourable and inhibitory modes for biomolecular condensate formation. These results provide insight into the molecular mechanisms and kinetics of mitotic cellular reorganisation.

The structural investigation of intrinsically disordered proteins (IDPs) requires ensemble models describing the diversity of the conformational states of the molecule. Due to their probabilistic nature, there is a need for new paradigms that understand and treat IDPs from a purely statistical point of view, considering their conformational ensembles as well-defined probability distributions. In this work, we define a conformational ensemble as an ordered set of probability distributions and provide a suitable metric to detect differences between two given ensembles at the residue level, both locally and globally. The underlying geometry of the conformational space is properly integrated, one ensemble being characterized by a set of probability distributions supported on the three-dimensional Euclidean space (for global-scale comparisons) and on the two-dimensional flat torus (for local-scale comparisons). The inherent uncertainty of the data is also taken into account to provide finer estimations of the differences between ensembles. Additionally, an overall distance between ensembles is defined from the differences at the residue level. We illustrate the potential of the approach with several examples of applications for the comparison of conformational ensembles: (i) produced from molecular dynamics (MD) simulations using different force fields, and (ii) before and after refinement with experimental data. We also show the usefulness of the method to assess the convergence of MD simulations, and discuss other potential applications such as in machine-learning-based approaches. The numerical tool has been implemented in Python through easy-to-use Jupyter Notebooks available at https://gitlab.laas.fr/moma/WASCO., The structural investigation of intrinsically disordered proteins (IDPs) requires ensemble models describing the diversity of the conformational states of the molecule. Due to their probabilistic nature, there is a need for new paradigms that understand and treat IDPs from a purely statistical point of view, considering their conformational ensembles as well-defined probability distributions. In this work, we define a conformational ensemble as an ordered set of probability distributions and provide a suitable metric to detect differences between two given ensembles at the residue level, both locally and globally. The underlying geometry of the conformational space is properly integrated, one ensemble being characterized by a set of probability distributions supported on the three-dimensional Euclidean space (for global-scale comparisons) and on the two-dimensional flat torus (for local-scale comparisons). The inherent uncertainty of the data is also taken into account to provide finer estimations of the differences between ensembles. Additionally, an overall distance between ensembles is defined from the differences at the residue level. We illustrate the potential of the approach with several examples of applications for the comparison of conformational ensembles: (i) produced from molecular dynamics (MD) simulations using different force fields, and (ii) before and after refinement with experimental data. We also show the usefulness of the method to assess the convergence of MD simulations, and discuss other potential applications such as in machine-learning-based approaches. The numerical tool has been implemented in Python through easy-to-use Jupyter Notebooks available at https://gitlab.laas.fr/moma/WASCO.

The compaction of mitochondrial DNA (mtDNA) is regulated by architectural HMG-box proteins whose limited cross-species similarity suggests diverse underlying mechanisms. Viability of Candida albicans, a human antibiotic-resistant mucosal pathogen, is compromised by altering mtDNA regulators. Among them, there is the mtDNA maintenance factor Gcf1p, which differs in sequence and structure from its human and Saccharomyces cerevisiae counterparts, TFAM and Abf2p. Our crystallographic, biophysical, biochemical and computational analysis showed that Gcf1p forms dynamic protein/DNA multimers by a combined action of an N-terminal unstructured tail and a long helix. Furthermore, an HMG-box domain canonically binds the minor groove and dramatically bends the DNA while, unprecedentedly, a second HMG-box binds the major groove without imposing distortions. This architectural protein thus uses its multiple domains to bridge co-aligned DNA segments without altering the DNA topology, revealing a new mechanism of mtDNA condensation.

The structural investigation of intrinsically disordered proteins (IDPs) requires ensemble models describing the diversity of the conformational states of the molecule. Due to their probabilistic nature, there is a need for new paradigms that understand and treat IDPs from a purely statistical point of view, considering their conformational ensembles as well-defined probability distributions. In this work, we define a conformational ensemble as an ordered set of probability distributions and provide a suitable metric to detect differences between two given ensembles at the residue level, both locally and globally. The underlying geometry of the conformational space is properly integrated, one ensemble being characterized by a set of probability distributions supported on the three-dimensional Euclidean space (for global-scale comparisons) and on the two-dimensional flat torus (for local-scale comparisons). The inherent uncertainty of the data is also taken into account to provide finer estimations of the differences between ensembles. Additionally, an overall distance between ensembles is defined from the differences at the residue level. We illustrate the potential of the approach with several examples of applications for the comparison of conformational ensembles: (i) produced from molecular dynamics (MD) simulations using different force fields, and (ii) before and after refinement with experimental data. We also show the usefulness of the method to assess the convergence of MD simulations, and discuss other potential applications such as in machine-learning-based approaches. The numerical tool has been implemented in Python through easy-to-use Jupyter Notebooks available at https://gitlab.laas.fr/moma/WASCO., The structural investigation of intrinsically disordered proteins (IDPs) requires ensemble models describing the diversity of the conformational states of the molecule. Due to their probabilistic nature, there is a need for new paradigms that understand and treat IDPs from a purely statistical point of view, considering their conformational ensembles as well-defined probability distributions. In this work, we define a conformational ensemble as an ordered set of probability distributions and provide a suitable metric to detect differences between two given ensembles at the residue level, both locally and globally. The underlying geometry of the conformational space is properly integrated, one ensemble being characterized by a set of probability distributions supported on the three-dimensional Euclidean space (for global-scale comparisons) and on the two-dimensional flat torus (for local-scale comparisons). The inherent uncertainty of the data is also taken into account to provide finer estimations of the differences between ensembles. Additionally, an overall distance between ensembles is defined from the differences at the residue level. We illustrate the potential of the approach with several examples of applications for the comparison of conformational ensembles: (i) produced from molecular dynamics (MD) simulations using different force fields, and (ii) before and after refinement with experimental data. We also show the usefulness of the method to assess the convergence of MD simulations, and discuss other potential applications such as in machine-learning-based approaches. The numerical tool has been implemented in Python through easy-to-use Jupyter Notebooks available at https://gitlab.laas.fr/moma/WASCO.

Many disordered proteins conserve essential functions in the face of extensive sequence variation, making it challenging to identify the mechanisms responsible for functional selection. Here we identify the molecular mechanism of functional selection for the disordered adenovirus early gene 1A (E1A) protein. E1A competes with host factors to bind the retinoblastoma (Rb) protein, subverting cell cycle regulation. We show that two binding motifs tethered by a hypervariable disordered linker drive picomolar affinity Rb binding and host factor displacement. Compensatory changes in amino acid sequence composition and sequence length lead to conservation of optimal tethering across a large family of E1A linkers. We refer to this compensatory mechanism as conformational buffering. We also detect coevolution of the motifs and linker, which can preserve or eliminate the tethering mechanism. Conformational buffering and motif-linker coevolution explain robust functional encoding within hypervariable disordered linkers and could underlie functional selection of many disordered protein regions.

The Protein Ensemble Database (PED) (https://proteinensemble.org), which holds structural ensembles of intrinsically disordered proteins (IDPs), has been significantly updated and upgraded since its last release in 2016. The new version, PED 4.0, has been completely redesigned and reimplemented with cutting-edge technology and now holds about six times more data (162 versus 24 entries and 242 versus 60 structural ensembles) and a broader representation of state of the art ensemble generation methods than the previous version. The database has a completely renewed graphical interface with an interactive feature viewer for region-based annotations, and provides a series of descriptors of the qualitative and quantitative properties of the ensembles. High quality of the data is guaranteed by a new submission process, which combines both automatic and manual evaluation steps. A team of biocurators integrate structured metadata describing the ensemble generation methodology, experimental constraints and conditions. A new search engine allows the user to build advanced queries and search all entry fields including cross-references to IDP-related resources such as DisProt, MobiDB, BMRB and SASBDB. We expect that the renewed PED will be useful for researchers interested in the atomic-level understanding of IDP function, and promote the rational, structure-based design of IDP-targeting drugs.

The Protein Ensemble Database (PED) (https://proteinensemble.org), which holds structural ensembles of intrinsically disordered proteins (IDPs), has been significantly updated and upgraded since its last release in 2016. The new version, PED 4.0, has been completely redesigned and reimplemented with cutting-edge technology and now holds about six times more data (162 versus 24 entries and 242 versus 60 structural ensembles) and a broader representation of state of the art ensemble generation methods than the previous version. The database has a completely renewed graphical interface with an interactive feature viewer for region-based annotations, and provides a series of descriptors of the qualitative and quantitative properties of the ensembles. High quality of the data is guaranteed by a new submission process, which combines both automatic and manual evaluation steps. A team of biocurators integrate structured metadata describing the ensemble generation methodology, experimental constraints and conditions. A new search engine allows the user to build advanced queries and search all entry fields including cross-references to IDP-related resources such as DisProt, MobiDB, BMRB and SASBDB. We expect that the renewed PED will be useful for researchers interested in the atomic-level understanding of IDP function, and promote the rational, structure-based design of IDP-targeting drugs.

Transient biomolecular interactions play crucial roles in many cellular signaling and regulation processes. However, deciphering the structure of these assemblies is challenging owing to the difficulties in isolating complexes from the individual partners. The additive nature of small-angle X-ray scattering (SAXS) data allows for probing the species present in these mixtures, but decomposition into structural and thermodynamic information is difficult. We present a chemometric approach enabling the decomposition of titration SAXS data into species-specific information. Using extensive synthetic SAXS data, we demonstrate that robust decomposition can be achieved for titrations with a maximum fraction of complex of 0.5 that can be extended to 0.3 when two orthogonal titrations are simultaneously analyzed. The effect of the structural features, titration points, relative concentrations, and noise are thoroughly analyzed. The validation of the strategy with experimental data highlights the power of the approach to provide unique insights into this family of biomolecular assemblies.

Von Willebrand Factor (vWF), a 300-kDa plasma protein key to homeostasis, is cleaved at a single site by multi-domain metallopeptidase ADAMTS-13. vWF is the only known substrate of this peptidase, which circulates in a latent form and becomes allosterically activated by substrate binding. Herein, we characterised the complex formed by a competent peptidase construct (AD13-MDTCS) comprising metallopeptidase (M), disintegrin-like (D), thrombospondin (T), cysteine-rich (C), and spacer (S) domains, with a 73-residue functionally relevant vWF-peptide, using nine complementary techniques. Pull-down assays, gel electrophoresis, and surface plasmon resonance revealed tight binding with sub-micromolar affinity. Cross-linking mass spectrometry with four reagents showed that, within the peptidase, domain D approaches M, C, and S. S is positioned close to M and C, and the peptide contacts all domains. Hydrogen/deuterium exchange mass spectrometry revealed strong and weak protection for C/D and M/S, respectively. Structural analysis by multi-angle laser light scattering and small-angle X-ray scattering in solution revealed that the enzyme adopted highly flexible unbound, latent structures and peptide-bound, active structures that differed from the AD13-MDTCS crystal structure. Moreover, the peptide behaved like a self-avoiding random chain. We integrated the results with computational approaches, derived an ensemble of structures that collectively satisfied all experimental restraints, and discussed the functional implications. The interaction conforms to a ‘fuzzy complex’ that follows a ‘dynamic zipper’ mechanism involving numerous reversible, weak but additive interactions that result in strong binding and cleavage. Our findings contribute to illuminating the biochemistry of the vWF:ADAMTS-13 axis.

Pin1 is a peptidyl-prolyl cis/trans isomerase (PPIase) essential for cell cycle regulation. Pin1-catalyzed peptidyl-prolyl isomerization provides a key conformational switch to activate phosphorylation sites with the common phospho-Ser/Thr-Pro sequence motif. This motif is ubiquitously exploited in cellular response to a variety of signals. Pin1 is able to bind phospho-Ser/Thr-Pro-containing sequences at two different sites that compete for the same substrate. One binding site is located within the N-terminal WW domain, which is essential for protein targeting and localization. The other binding site is located in the C-terminal catalytic domain, which is structural homologous to the FK506-binding protein (FKBP) class of PPIases. A flexible linker of 12 residues connects the WW and catalytic domain. To characterize the structure and dynamics of full-length Pin1 in solution, high resolution NMR methods have been used to map the nature of interactions between the two domains of Pin1. In addition, the influence of target peptides on domain interactions has been investigated. The studies reveal a dynamic picture of the domain interactions. 15N spin relaxation data, differential chemical shift mapping, and residual dipolar coupling data indicate that Pin1 can either behave as two independent domains connected by the flexible linker or as a single intact domain with some amount of hinge bending motion depending on the sequence of the bound peptide. The functional importance of the modulation of relative domain flexibility in light of the multitude of interaction partners of Pin1 is discussed.

Polypeptide GalNAc-transferase T3 (GalNAc-T3) regulates fibroblast growth factor 23 (FGF23) by O-glycosylating Thr178 in a furin proprotein processing motif RHT178R↓S. FGF23 regulates phosphate homeostasis and deficiency in GALNT3 or FGF23 results in hyperphosphatemia and familial tumoral calcinosis. We explored the molecular mechanism for GalNAc-T3 glycosylation of FGF23 using engineered cell models and biophysical studies including kinetics, molecular dynamics and X-ray crystallography of GalNAc-T3 complexed to glycopeptide substrates. GalNAc-T3 uses a lectin domain mediated mechanism to glycosylate Thr178 requiring previous glycosylation at Thr171. Notably, Thr178 is a poor substrate site with limiting glycosylation due to substrate clashes leading to destabilization of the catalytic domain flexible loop. We suggest GalNAc-T3 specificity for FGF23 and its ability to control circulating levels of intact FGF23 is achieved by FGF23 being a poor substrate. GalNAc-T3’s structure further reveals the molecular bases for reported disease-causing mutations. Our findings provide an insight into how GalNAc-T isoenzymes achieve isoenzyme-specific nonredundant functions.

Proline is found in a cis conformation in proteins more often than other proteinogenic amino acids, where it influences structure and modulates function, being the focus of several high-resolution structural studies. However, until now, technical and methodological limitations have hampered the site-specific investigation of the conformational preferences of prolines present in poly proline (poly-P) homorepeats in their protein context. Here, we apply site-specific isotopic labeling to obtain high-resolution NMR data on the cis/trans equilibrium of prolines within the poly-P repeats of huntingtin exon 1, the causative agent of Huntington’s disease. Screening prolines in different positions in long (poly-P11) and short (poly-P3) poly-P tracts, we found that, while the first proline of poly-P tracts adopts similar levels of cis conformation as isolated prolines, a length-dependent reduced abundance of cis conformers is observed for terminal prolines. Interestingly, the cis isomer could not be detected in inner prolines, in line with percentages derived from a large database of proline-centered tripeptides extracted from crystallographic structures. These results suggest a strong cooperative effect within poly-Ps that enhances their stiffness by diminishing the stability of the cis conformation. This rigidity is key to rationalizing the protection toward aggregation that the poly-P tract confers to huntingtin. Furthermore, the study provides new avenues to probe the structural properties of poly-P tracts in protein design as scaffolds or nanoscale rulers.

Structural characterization of protein–protein interactions can provide essential details to understand biological functions at the molecular level and to facilitate their manipulation for biotechnological and biomedical purposes. Unfortunately, the 3D structure is available for only a small fraction of all possible protein–protein interactions, due to the technical limitations of high-resolution structural determination methods. In this context, low-resolution structural techniques, such as small-angle X-ray scattering (SAXS), can be combined with computational docking to provide structural models of protein–protein interactions at large scale. In this chapter, we describe the pyDockSAXS web server (https://life.bsc.es/pid/pydocksaxs), which uses pyDock docking and scoring to provide structural models that optimally satisfy the input SAXS data. This server, which is freely available to the scientific community, provides an automatic pipeline to model the structure of a protein–protein complex from SAXS data.

Structural characterization of protein–protein interactions can provide essential details to understand biological functions at the molecular level and to facilitate their manipulation for biotechnological and biomedical purposes. Unfortunately, the 3D structure is available for only a small fraction of all possible protein–protein interactions, due to the technical limitations of high-resolution structural determination methods. In this context, low-resolution structural techniques, such as small-angle X-ray scattering (SAXS), can be combined with computational docking to provide structural models of protein–protein interactions at large scale. In this chapter, we describe the pyDockSAXS web server (https://life.bsc.es/pid/pydocksaxs), which uses pyDock docking and scoring to provide structural models that optimally satisfy the input SAXS data. This server, which is freely available to the scientific community, provides an automatic pipeline to model the structure of a protein–protein complex from SAXS data, This work was supported by the Spanish Ministry of Science (grant BIO2016-79930-R), the European Union H2020 programme (grant MuG 676566), and the Labex EpiGenMed, an "Investissements d’avenir" program (ANR-10-LABX-12-01). The CBS is a member of France-BioImaging (FBI) and the French Infrastructure for Integrated Structural Biology (FRISBI), two national infrastructures supported by the French National Research Agency (ANR-10-INSB-04-01 and ANR-10-INSB-05, respectively)., Peer Reviewed, Postprint (author's final draft)

Epidermal growth factor receptor (EGFR) signaling is initiated by a large ligand-favored conformational change of the extracellular domain (ECD) from a closed, self-inhibited tethered monomer, to an open untethered state, which exposes a loop required for strong dimerization and activation. In glioblastomas (GBMs), structurally heterogeneous missense and deletion mutations concentrate at the ECD for unclear reasons. We explore the conformational impact of GBM missense mutations, combining elastic network models (ENMs) with multiple molecular dynamics (MD) trajectories. Our simulations reveal that the main missense class, located at the I-II interface away from the self-inhibitory tether, can unexpectedly favor spontaneous untethering to a compact intermediate state, here validated by small-angle X-ray scattering (SAXS). Significantly, such intermediate is characterized by the rotation of a large ECD fragment (N-TR1), deleted in the most common GBM mutation, EGFRvIII, and that makes accessible a cryptic epitope characteristic of cancer cells. This observation suggested potential structural equivalence of missense and deletion ECD changes in GBMs. Corroborating this hypothesis, our FACS, in vitro, and in vivo data demonstrate that entirely different ECD variants all converge to remove N-TR1 steric hindrance from the 806-epitope, which we show is allosterically coupled to an intermediate kinase and hallmarks increased oncogenicity. Finally, the detected extraintracellular coupling allows for synergistic cotargeting of the intermediate with mAb806 and inhibitors, which is proved herein.

Human mitochondrial transcription factor A (TFAM) distorts DNA into a U-turn, as shown by crystallographic studies. The relevance of this U-turn is associated with transcription initiation at the mitochondrial light strand promoter (LSP). However, it has not been yet discerned whether a tight U-turn or an alternative conformation, such as a V-shape, is formed in solution. Here, single-molecule FRET experiments on freely diffusing TFAM/LSP complexes containing different DNA lengths show that a DNA U-turn is induced by progressive and cooperative binding of the two TFAM HMG-box domains and the linker between them. SAXS studies further show compaction of the protein upon complex formation. Finally, molecular dynamics simulations reveal that TFAM/LSP complexes are dynamic entities, and the HMG boxes induce the U-turn against the tendency of the DNA to adopt a straighter conformation. This tension is resolved by reversible unfolding of the linker, which is a singular mechanism that allows a flexible protein to stabilize a tight bending of DNA.

Intrinsically Disordered Proteins (IDPs) perform a broad range of biological functions. Their relevance has motivated intense research activity seeking to characterize their sequence/structure/function relationships. However, the conformational plasticity of these molecules hampers the application of traditional structural approaches, and new tools and concepts are being developed to address the challenges they pose. Small-Angle Scattering (SAS) is a structural biology technique that probes the size and shape of disordered proteins and their complexes with other biomolecules. The low-resolution nature of SAS can be compensated with specially designed computational tools and its combined interpretation with complementary structural information. In this review, we describe recent advances in the application of SAS to disordered proteins and highly flexible complexes and discuss current challenges.

Deciphering conformational dynamics is crucial for understanding the biological functions of proteins and for designing compounds targeting them. In particular, providing an accurate description of microsecond–millisecond motions opens the opportunity for regulating protein–protein interactions (PPIs) by modulating the dynamics of one interacting partner. Here we analyzed the conformational dynamics of prolyl oligopeptidase (POP) and the effects of active-site-directed inhibitors on the dynamics. We used an integrated structural biology approach based on NMR spectroscopy and SAXS experiments complemented by MD simulations. We found that POP is in a slow equilibrium in solution between open and closed conformations, and that inhibitors effectively abolished this equilibrium by stabilizing the enzyme in the closed conformation., This work was supported by the Institute for Research in Biomedicine, MINECO-FEDER (Bio2013-40716-R, CTQ2013-48287 and CTQ2012-32183/BQU), and the Generalitat de Catalunya (XRB and Grup Consolidat 2014SGR521). AL has received funding from the Instituto de Salud Carlos III. PB acknowledges the Agence Nationale de la Recherche (SPINHD-ANR-CHEX-2011) and the ATIP-Avenir program for financial support. FHT’s fellowship is co-funded by the INSERM and the University of Copenhagen. Technical assistance from staff at the P12 beam line (EMBL/DESY) is acknowledged., Peer Reviewed, Postprint (author's final draft)

The intrinsically disordered p15PAF regulates DNA replication and repair when interacting with the Proliferating Cell Nuclear Antigen (PCNA) sliding clamp. As many interactions between disordered proteins and globular partners involved in signaling and regulation, the complex between p15PAF and trimeric PCNA is of low affinity, forming a transient complex that is difficult to characterize at a structural level due to its inherent polydispersity. We have determined the structure, conformational fluctuations, and relative population of the five species that coexist in solution by combining small-angle X-ray scattering (SAXS) with molecular modelling. By using explicit ensemble descriptions for the individual species, built using integrative approaches and molecular dynamics (MD) simulations, we collectively interpreted multiple SAXS profiles as population-weighted thermodynamic mixtures. The analysis demonstrates that the N-terminus of p15PAF penetrates the PCNA ring and emerges on the back face. This observation substantiates the role of p15PAF as a drag regulating PCNA processivity during DNA repair. Our study reveals the power of ensemble-based approaches to decode structural, dynamic, and thermodynamic information from SAXS data. This strategy paves the way for deciphering the structural bases of flexible, transient and multivalent macromolecular assemblies involved in pivotal biological processes.

Structural characterization of protein–protein interactions at molecular level is essential to understand biological processes and identify new therapeutic opportunities. However, atomic resolution structural techniques cannot keep pace with current advances in interactomics. Low-resolution structural techniques, such as small-angle X-ray scattering (SAXS), can be applied at larger scale, but they miss atomic details. For efficient application to protein–protein complexes, low-resolution information can be combined with theoretical methods that provide energetic description and atomic details of the interactions. Here we present the pyDockSAXS web server (http://life.bsc.es/pid/pydocksaxs) that provides an automatic pipeline for modeling the structure of a protein–protein complex from SAXS data. The method uses FTDOCK to generate rigid-body docking models that are subsequently evaluated by a combination of pyDock energy-based scoring function and their capacity to describe SAXS data. The only required input files are structural models for the interacting partners and a SAXS curve. The server automatically provides a series of structural models for the complex, sorted by the pyDockSAXS scoring function. The user can also upload a previously computed set of docking poses, which opens the possibility to filter the docking solutions by potential interface residues or symmetry restraints. The server is freely available to all users without restriction., Programa Estatal I+D+i, the SpanishMinistry of Economy andCompetitiveness [BIO2013-48213-R to J.F.-R.]; Agence Nationale de la Recherche [SPIN-HD-ANR-CHEX-2011 and ATIP-Avenir Program to P.B.]; FPU Fellowship, the Spanish Ministry of Science and Innovation [BES-2011-045634 to B.J.G.]. Funding for open access charge: Spanish Ministry of Economy and Competitiveness [BIO2013-48213-R]; Agence Nationale de la Recherche [SPIN-HDANR- CHEX-2011]., Postprint (published version)

The intrinsically disordered protein p15(PAF) regulates DNA replication and repair by binding to the proliferating cell nuclear antigen (PCNA) sliding clamp. We present the structure of the human p15(PAF)-PCNA complex. Crystallography and NMR show the central PCNA-interacting protein motif (PIP-box) of p15(PAF) tightly bound to the front-face of PCNA. In contrast to other PCNA-interacting proteins, p15(PAF) also contacts the inside of, and passes through, the PCNA ring. The disordered p15(PAF) termini emerge at opposite faces of the ring, but remain protected from 20S proteasomal degradation. Both free and PCNA-bound p15(PAF) binds DNA mainly through its histone-like N-terminal tail, while PCNA does not, and a model of the ternary complex with DNA inside the PCNA ring is consistent with electron micrographs. We propose that p15(PAF) acts as a flexible drag that regulates PCNA sliding along the DNA and facilitates the switch from replicative to translesion synthesis polymerase binding.

Protein O-glycosylation is controlled by polypeptide GalNAc-transferases (GalNAc-Ts) that uniquely feature both a catalytic and lectin domain. The underlying molecular basis of how the lectin domains of GalNAc-Ts contribute to glycopeptide specificity and catalysis remains unclear. Here we present the first crystal structures of complexes of GalNAc-T2 with glycopeptides that together with enhanced sampling molecular dynamics simulations demonstrate a cooperative mechanism by which the lectin domain enables free acceptor sites binding of glycopeptides into the catalytic domain. Atomic force microscopy and small-angle X-ray scattering experiments further reveal a dynamic conformational landscape of GalNAc-T2 and a prominent role of compact structures that are both required for efficient catalysis. Our model indicates that the activity profile of GalNAc-T2 is dictated by conformational heterogeneity and relies on a flexible linker located between the catalytic and the lectin domains. Our results also shed light on how GalNAc-Ts generate dense decoration of proteins with O-glycans.

© The Author(s) 2015. The mitochondrial replicative helicase Twinkle is involved in strand separation at the replication fork of mitochondrial DNA (mtDNA). Twinkle malfunction is associated with rare diseases that include late onset mitochondrial myopathies, neuromuscular disorders and fatal infantile mtDNA depletion syndrome. We examined its 3D structure by electron microscopy (EM) and small angle X-ray scattering (SAXS) and built the corresponding atomic models, which gave insight into the first molecular architecture of a full-length SF4 helicase that includes an N-terminal zinc-binding domain (ZBD), an intermediate RNA polymerase domain (RPD) and a RecA-like hexamerization C-terminal domain (CTD). The EM model of Twinkle reveals a hexameric two-layered ring comprising the ZBDs and RPDs in one layer and the CTDs in another. In the hexamer, contacts in trans with adjacent subunits occur between ZBDs and RPDs, and between RPDs and CTDs. The ZBDs show important structural heterogeneity. In solution, the scattering data are compatible with a mixture of extended hexa- and heptameric models in variable conformations. Overall, our structural data show a complex network of dynamic interactions that reconciles with the structural flexibility required for helicase activity.

© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Molecular plasticity controls enzymatic activity: the native fold of a protein in a given environment is normally unique and at a global free-energy minimum. Some proteins, however, spontaneously undergo substantial fold switching to reversibly transit between defined conformers, the >metamorphic> proteins. Here, we present a minimal metamorphic, selective, and specific caseinolytic metallopeptidase, selecase, which reversibly transits between several different states of defined three-dimensional structure, which are associated with loss of enzymatic activity due to autoinhibition. The latter is triggered by sequestering the competent conformation in incompetent but structured dimers, tetramers, and octamers. This system, which is compatible with a discrete multifunnel energy landscape, affords a switch that provides a reversible mechanism of control of catalytic activity unique in nature. Shape shifting: A minimal metamorphic, selective, and specific caseinolytic metallopeptidase, selecase, reversibly transits between several different states of defined three-dimensional structure (monomer and tetramer represented in picture). The competent conformation is sequestered in incompetent but structured dimers, tetramers, and octamers, which are associated with loss of enzymatic activity due to autoinhibition.

The early stages of the thermal unfolding of apoflavodoxin have been determined by using atomistic multi microsecondscale molecular dynamics (MD) simulations complemented with a variety of experimental techniques. Results strongly suggest that the intermediate is reached very early in the thermal unfolding process and that it has the properties of an ‘‘activated’’ form of the native state, where thermal fluctuations in the loops break loop-loop contacts. The unrestrained loops gain then kinetic energy corrupting short secondary structure elements without corrupting the core of the protein. The MD-derived ensembles agree with experimental observables and draw a picture of the intermediate state inconsistent with a well-defined structure and characteristic of a typical partially disordered protein. Our results allow us to speculate that proteins with a well packed core connected by long loops might behave as partially disordered proteins under native conditions, or alternatively behave as three state folders. Small details in the sequence, easily tunable by evolution, can yield to one or the other type of proteins

The early stages of the thermal unfolding of apoflavodoxin have been determined by using atomistic multi microsecond-scale molecular dynamics (MD) simulations complemented with a variety of experimental techniques. Results strongly suggest that the intermediate is reached very early in the thermal unfolding process and that it has the properties of an "activated" form of the native state, where thermal fluctuations in the loops break loop-loop contacts. The unrestrained loops gain then kinetic energy corrupting short secondary structure elements without corrupting the core of the protein. The MD-derived ensembles agree with experimental observables and draw a picture of the intermediate state inconsistent with a well-defined structure and characteristic of a typical partially disordered protein. Our results allow us to speculate that proteins with a well packed core connected by long loops might behave as partially disordered proteins under native conditions, or alternatively behave as three state folders. Small details in the sequence, easily tunable by evolution, can yield to one or the other type of proteins. © 2012 García-Fandino et al.

Small Angle X-ray Scattering (SAXS) of macromolecules in solution is a technique that allows lowresolution structural analysis of proteins and their complexes, including protein-DNA complexes. The number of SAXS studies on macromolecular particles has increased significantly in the last years, due to improvement of algorithms and beamtime availability in synchrotron facilities. One advantage of this technique is that is no limited by factors like particle size or flexibility; on the contrary, it is possible to assess these or other features, like the coexistence of particles of different sizes in the same preparation. The experimental SAXS curve allows to fit against it a theoretical curve calculated using a crystallographic atomic model or an electron microscopy shape, which might be modified to optimise the curve fitting. Fitting optimisation can be attempted by exploring the conformational space of the particle on the basis of the available model, using techniques like simple manual displacement of domains or more sophisticated ones like normal mode analysis, and select those models that altogether yield a curve that fits best; such a methodology can be useful in determining the degree of flexibility of domains or interdomain segments. Macromolecular complexes are reconstructed using static threedimensional models of the complexes or by docking the individual components; by playing with the proportion of non-interacting vs interacting partners, is possible to establish the dynamics of the complex. Furthermore, by introducing the conformational-space analysis algorithms within macromolecular complexes is possible to explore the conformational changes induced by ligands, substrates or interacting partners. We are going to present a SAXS analysis of three phylogenetically-related proteins whose structure is based on homology models, and in one case involving a protein/DNA complex. The strategies applied will be analysed and the results discussed