Structural Basis of Mutation-Dependent p53 Tetramerization Deficiency.

The formation of a tetrameric assembly is essential for the ability of the tumor suppressor protein p53 to act as a transcription factor. Such a quaternary conformation is driven by a specific tetramerization domain, separated from the central DNA-binding domain by a flexible linker. Despite the distance, functional crosstalk between the two domains has been reported. This phenomenon can explain the pathogenicity of some inherited or somatically acquired mutations in the tetramerization domain, including the widespread R337H missense mutation present in the population in south Brazil. In this work, we combined computational predictions through extended all-atom molecular dynamics simulations with functional assays in a genetically defined yeast-based model system to reveal structural features of p53 tetramerization domains and their transactivation capacity and specificity. In addition to the germline and cancer-associated R337H and R337C, other rationally designed missense mutations targeting a significant salt-bridge interaction that stabilizes the p53 tetramerization domain were studied (i.e., R337D, D352R, and the double-mutation R337D plus D352R). The simulations revealed a destabilizing effect of the pathogenic mutations within the p53 tetramerization domain and highlighted the importance of electrostatic interactions between residues 337 and 352. The transactivation assay, performed in yeast by tuning the expression of wild-type and mutant p53 proteins, revealed that p53 tetramerization mutations could decrease the transactivation potential and alter transactivation specificity, in particular by better tolerating negative features in weak DNA-binding sites. These results establish the effect of naturally occurring variations at positions 337 and 352 on p53's conformational stability and function.

Communication pathways bridge local and global conformations in an IgG4 antibody.

The affinity of an antibody for its antigen is primarily determined by the specific sequence and structural arrangement of the complementarity-determining regions (CDRs). Recent evidence, however, points toward a nontrivial relation between the CDR and distal sites: variations in the binding strengths have been observed upon mutating residues separated from the paratope by several nanometers, thus suggesting the existence of a communication network within antibodies, whose extension and relevance might be deeper than insofar expected. In this work, we test this hypothesis by means of molecular dynamics (MD) simulations of the IgG4 monoclonal antibody pembrolizumab, an approved drug that targets the programmed cell death protein 1 (PD-1). The molecule is simulated in both the apo and holo states, totalling 4 µs of MD trajectory. The analysis of these simulations shows that the bound antibody explores a restricted range of conformations with respect to the apo one, and that the global conformation of the molecule correlates with that of the CDR. These results support the hypothesis that pembrolizumab featues a multi-scale hierarchy of intertwined global and local conformational changes. The analysis pipeline developed in this work is general, and it can help shed further light on the mechanistic aspects of antibody function.

From System Modeling to System Analysis: The Impact of Resolution Level and Resolution Distribution in the Computer-Aided Investigation of Biomolecules.

The ever increasing computer power, together with the improved accuracy of atomistic force fields, enables researchers to investigate biological systems at the molecular level with remarkable detail. However, the relevant length and time scales of many processes of interest are still hardly within reach even for state-of-the-art hardware, thus leaving important questions often unanswered. The computer-aided investigation of many biological physics problems thus largely benefits from the usage of coarse-grained models, that is, simplified representations of a molecule at a level of resolution that is lower than atomistic. A plethora of coarse-grained models have been developed, which differ most notably in their granularity; this latter aspect determines one of the crucial open issues in the field, i.e. the identification of an optimal degree of coarsening, which enables the greatest simplification at the expenses of the smallest information loss. In this review, we present the problem of coarse-grained modeling in biophysics from the viewpoint of system representation and information content. In particular, we discuss two distinct yet complementary aspects of protein modeling: on the one hand, the relationship between the resolution of a model and its capacity of accurately reproducing the properties of interest; on the other hand, the possibility of employing a lower resolution description of a detailed model to extract simple, useful, and intelligible information from the latter.

Pharmacological inactivation of the prion protein by targeting a folding intermediate.

Recent computational advancements in the simulation of biochemical processes allow investigating the mechanisms involved in protein regulation with realistic physics-based models, at an atomistic level of resolution. These techniques allowed us to design a drug discovery approach, named Pharmacological Protein Inactivation by Folding Intermediate Targeting (PPI-FIT), based on the rationale of negatively regulating protein levels by targeting folding intermediates. Here, PPI-FIT was tested for the first time on the cellular prion protein (PrP), a cell surface glycoprotein playing a key role in fatal and transmissible neurodegenerative pathologies known as prion diseases. We predicted the all-atom structure of an intermediate appearing along the folding pathway of PrP and identified four different small molecule ligands for this conformer, all capable of selectively lowering the load of the protein by promoting its degradation. Our data support the notion that the level of target proteins could be modulated by acting on their folding pathways, implying a previously unappreciated role for folding intermediates in the biological regulation of protein expression.

Modeling PrPSc Generation Through Deformed Templating.

Deformed templating is the process by which self-replicating protein conformations with a given cross-ß folding pattern can seed formation of an alternative self-replicating state with different cross-ß folding pattern. In particular, uninfectious but propagative PrP amyloid can transform into a bona fide infectious conformer, PrPSc through deformed templating. The process can take many rounds of replication (if taking place in vitro) or even several passages of the evolving PrP conformers through successive brains if in vivo, through experimental transmission. In all cases, deformed templating involves a forced conversion in which there is a mismatch between the template and the substrate and/or the templating environment, typically a recombinant PrP amyloid, adept at converting recombinant PrP under denaturing conditions (e.g., presence of chaotropic agents), encountering a glycosylated, GPI-anchored PrPC substrate under physiological conversion conditions. Deformed templating is characterized by emergence of intermediate conformers that exhibit biochemical characteristics that are intermediate between those of the initial PrP amyloid and the final PrPSc conformers. Here, we took advantage of the recent elucidation of the structure of a PrP amyloid by cryo-EM and the availability of a physically plausible atomistic model of PrPSc that we have recently proposed. Using modeling and Molecular Dynamics (MD) approaches, we built a complete molecular modelization of deformed templating, including an atomistic model of a glycosylated intermediate conformer and a modified model of PrPSc. Among other unanticipated outcomes, our results show that fully glycosylated PrP can be stacked in-register, and how 4-rung ß-solenoid (4RßS) PrP architectures can share key structural motifs with parallel-in register intermolecular sheet (PIRIBS) PrP amyloids. Our results shed light on the mechanisms of prion replication.

Full atomistic model of prion structure and conversion.

Prions are unusual protein assemblies that propagate their conformationally-encoded information in absence of nucleic acids. The first prion identified, the scrapie isoform (PrPSc) of the cellular prion protein (PrPC), caused epidemic and epizootic episodes [1]. Most aggregates of other misfolding-prone proteins are amyloids, often arranged in a Parallel-In-Register-ß-Sheet (PIRIBS) [2] or ß-solenoid conformations [3]. Similar folding models have also been proposed for PrPSc, although none of these have been confirmed experimentally. Recent cryo-electron microscopy (cryo-EM) and X-ray fiber-diffraction studies provided evidence that PrPSc is structured as a 4-rung ß-solenoid (4RßS) [4, 5]. Here, we combined different experimental data and computational techniques to build the first physically-plausible, atomic resolution model of mouse PrPSc, based on the 4RßS architecture. The stability of this new PrPSc model, as assessed by Molecular Dynamics (MD) simulations, was found to be comparable to that of the prion forming domain of Het-s, a naturally-occurring ß-solenoid. Importantly, the 4RßS arrangement allowed the first simulation of the sequence of events underlying PrPC conversion into PrPSc. This study provides the most updated, experimentally-driven and physically-coherent model of PrPSc, together with an unprecedented reconstruction of the mechanism underlying the self-catalytic propagation of prions.

Ok Google, how could I design therapeutics against prion diseases?

A number of previous successful attempts in the search for therapeutics for a variety of human pathologies highlight the importance of computational technologies in the drug discovery pipeline. This approach, often referred to as computer-aided drug design, is unfortunately inapplicable when the precise information regarding the three-dimensional structure of disease-associated proteins or the mechanism by which they are altered to generate misfolded isoforms are missing. A typical example is represented by prion diseases, fatal pathologies of the nervous system characterized by the conformational conversion of a physiological protein called PrPC into a misfolded and infectious isoform referred to as PrPSc. Missing information regarding the atomic structure of PrPSc as well as the mechanism of templated conversion of PrPC has severely halted the discovery of effective therapies for prion diseases. In this manuscript, we review emerging opportunities to apply computer-aided techniques to target PrPC, PrPSc or to design inhibitors of prion replication, and discuss how these fast-evolving technologies could lay the groundwork for the application of entirely novel rational drug design schemes for these devastating pathologies.