Principles for optimal cooperativity in allosteric materials

Allosteric proteins transmit a mechanical signal induced by binding a ligand. However, understanding the nature of the information transmitted and the architectures optimizing such transmission remains a challenge. Here we show using an {\it in-silico} evolution scheme and theoretical arguments that architectures optimized to be cooperative, which propagate efficiently energy, {qualitatively} differ from previously investigated materials optimized to propagate strain. Although we observe a large diversity of functioning cooperative architectures (including shear, hinge and twist designs), they all obey the same principle {of displaying a {\it mechanism}, i.e. an extended {soft} mode}. We show that its optimal frequency decreases with the spatial extension $L$ of the system as $L^{-d/2}$, where $d$ is the spatial dimension. For these optimal designs, cooperativity decays logarithmically with $L$ for $d=2$ and does not decay for $d=3$. Overall our approach leads to a natural explanation for several observations in allosteric proteins, and { indicates an experimental path to test if allosteric proteins lie close to optimality}.Comment: 11 pages, 9 figures in the main text, 9 pages 9 figures in the supplemental materia

Architecture and Co-Evolution of Allosteric Materials

We introduce a numerical scheme to evolve functional materials that can accomplish a specified mechanical task. In this scheme, the number of solutions, their spatial architectures and the correlations among them can be computed. As an example, we consider an "allosteric" task, which requires the material to respond specifically to a stimulus at a distant active site. We find that functioning materials evolve a less-constrained trumpet-shaped region connecting the stimulus and active sites and that the amplitude of the elastic response varies non-monotonically along the trumpet. As previously shown for some proteins, we find that correlations appearing during evolution alone are sufficient to identify key aspects of this design. Finally, we show that the success of this architecture stems from the emergence of soft edge modes recently found to appear near the surface of marginally connected materials. Overall, our in silico evolution experiment offers a new window to study the relationship between structure, function, and correlations emerging during evolution.Comment: 6 pages, 5 figures, SI: 2 pages, 4 figure

Direct Coupling Analysis of Epistasis in Allosteric Materials

In allosteric proteins, the binding of a ligand modifies function at a distant active site. Such allosteric pathways can be used as target for drug design, generating considerable interest in inferring them from sequence alignment data. Currently, different methods lead to conflicting results, in particular on the existence of long-range evolutionary couplings between distant amino-acids mediating allostery. Here we propose a resolution of this conundrum, by studying epistasis and its inference in models where an allosteric material is evolved in silico to perform a mechanical task. We find in our model the four types of epistasis (Synergistic, Sign, Antagonistic, Saturation), which can be both short or long-range and have a simple mechanical interpretation. We perform a Direct Coupling Analysis (DCA) and find that DCA predicts well the cost of point mutations but is a rather poor generative model. Strikingly, it can predict short-range epistasis but fails to capture long-range epistasis, in consistence with empirical findings. We propose that such failure is generic when function requires subparts to work in concert. We illustrate this idea with a simple model, which suggests that other methods may be better suited to capture long-range effects.Comment: 22 pages, 9 figure

Pattern of care and effectiveness of treatment for glioblastoma patients in the real world: Results from a prospective population-based registry. Could survival differ in a high-volume center?

BACKGROUND: As yet, no population-based prospective studies have been conducted to investigate the incidence and clinical outcome of glioblastoma (GBM) or the diffusion and impact of the current standard therapeutic approach in newly diagnosed patients younger than aged 70 years. METHODS: Data on all new cases of primary brain tumors observed from January 1, 2009, to December 31, 2010, in adults residing within the Emilia-Romagna region were recorded in a prospective registry in the Project of Emilia Romagna on Neuro-Oncology (PERNO). Based on the data from this registry, a prospective evaluation was made of the treatment efficacy and outcome in GBM patients. RESULTS: Two hundred sixty-seven GBM patients (median age, 64 y; range, 29-84 y) were enrolled. The median overall survival (OS) was 10.7 months (95% CI, 9.2-12.4). The 139 patients 64aged 70 years who were given standard temozolomide treatment concomitant with and adjuvant to radiotherapy had a median OS of 16.4 months (95% CI, 14.0-18.5). With multivariate analysis, OS correlated significantly with KPS (HR = 0.458; 95% CI, 0.248-0.847; P = .0127), MGMT methylation status (HR = 0.612; 95% CI, 0.388-0.966; P = .0350), and treatment received in a high versus low-volume center (HR = 0.56; 95% CI, 0.328-0.986; P = .0446). CONCLUSIONS: The median OS following standard temozolomide treatment concurrent with and adjuvant to radiotherapy given to (72.8% of) patients aged 6470 years is consistent with findings reported from randomized phase III trials. The volume and expertise of the treatment center should be further investigated as a prognostic factor

Mechanics and co-evolution of allosteric materials and proteins

The regulation of several processes inside and outside the cell depends on the action of a particular class of enzymes, called allosteric. In allosteric macromolecules, binding a ligand at one site affects the binding activity at a distal functional site, providing a reliable tool to regulate the corresponding function. The physical mechanisms underpinning allostery and its long-range communication are not yet fully understood, despite a great number of advances were made possible by significant works spanning 60 years, in between biology, bioinformatics and physics. In physics terms, proteins can be viewed as amorphous materials that however underwent billions of years of evolution to be functional as observed today. The framework introduced in this dissertation allows to explore how the structural organisation of an allosteric system is constrained by the function that it has evolved to perform. It allows a classification of allosteric architectures and suggests a physical explanation behind the emergence of such long-range allosteric coupling. Furthermore, it is also apt to build in silico a large amount of allosteric architectures that share the same evolutionary history. The constraints imprinted by evolution on sequences that share a common ancestor motivate the exploration of inference methods that try to predict the fitness of a protein solely from the knowledge of sequences. The strategy used to build this framework is to resort to a coarse-grained model of a protein, on the line of elastic network models resulted successful in the description of the large-scale dynamics of proteins. Ideas on how to pursue these research directions further are discussed throughout the chapters. Firstly, we introduce an in-silico model for the evolution of allosteric behaviour in discrete lattices of harmonic springs. The in-silico evolution is performed for two different allosteric tasks: one optimising for the transmission of strain between the allosteric and active site, while the other maximising the cooperative binding energy between the two. To optimise the transmission of strain, the network develops a lever that amplifies the response at the active site. In such a way, our model proposes a novel allosteric architecture, potentially in use in proteins as well. Cooperative architectures show, among others, hinge and shear motions and rationalise the observation of a low energy mode that describes conformational changes in proteins. Indeed, to achieve proper function, the mode is predicted to get softer as the size of the system increases. This prediction is tested by collecting a database of 34 high resolution structures of allosteric proteins and is proven valid even when elastic nonlinearities are introduced. Secondly, the sequences generated with the in-silico model serve to benchmark existing methods that infer co-evolutionary couplings between amino acids, proven to be successful in predicting local structural constraints, but with unclear performance in the presence of global allosteric constraints. These models do predict local features reflecting structure, but fail in the prediction of long-range functional dependencies and are not able to generate synthetic sequences that function as native ones. Thus, the exploration of new directions is needed

Maximum-energy records in glassy energy landscapes

22 pages, 5 figuresInternational audienceWe study the evolution of the maximum energy E_\max(t) reached between time $0$ and time $t$ in the dynamics of simple models with glassy energy landscapes, in instant quenches from infinite temperature to a target temperature $T$. Through a detailed description of the activated dynamics, we are able to describe the evolution of E_\max(t) from short times, through the aging regime, until after equilibrium is reached, thus providing a detailed description of the long-time dynamics. Finally, we compare our findings with numerical simulations of the $p$-spin glass and show how the maximum energy record can be used to identify the threshold energy in this model

Mechanics of Allostery: Contrasting the Induced Fit and Population Shift Scenarios

In allosteric proteins, binding a ligand can affect function at a distant location, for example, by changing the binding affinity of a substrate at the active site. The induced fit and population shift models, which differ by the assumed number of stable configurations, explain such cooperative binding from a thermodynamic viewpoint. Yet, understanding what mechanical principles constrain these models remains a challenge. Here, we provide an empirical study on 34 proteins supporting the idea that allosteric conformational change generally occurs along a soft elastic mode presenting extended regions of high shear. We argue, based on a detailed analysis of how the energy profile along such a mode depends on binding, that in the induced fit scenario, there is an optimal stiffness k*(a) similar to 1/N for cooperative binding, where N is the number of residues. We find that the population shift scenario is more robust to mutations affecting stiffness because binding becomes more and more cooperative with stiffness up to the same characteristic value k*(a), beyond which cooperativity saturates instead of decaying. We numerically confirm these findings in a nonlinear mechanical model. Dynamical considerations suggest that a stiffness of order k*(a) is favorable in that scenario as well, supporting that for proper function, proteins must evolve a functional elastic mode that is softer as their size increases. In consistency with this view, we find a fair anticorrelation between the stiffness of the allosteric response and protein size in our data set

Candida Infective Endocarditis Report of 15 Cases From a Prospective Multicenter Study

Candida species are an uncommon cause of infective endocarditis (IE). Given the rarity of this infection, the epidemiology, prognosis, and optimal therapy of Candida IE are poorly defined. We conducted a prospective, observational study at 18 medical centers in Italy, including all consecutive patients with a definite diagnosis of IE admitted front January 2004 through December 2007. A Candida species was the causative organism in 8 cases of prosthetic valve endocarditis (PVE), 5 cases of native valve endocarditis (NVE), I case of pacemaker endocarditis, and I case of left ventricular patch infection. Candida species accounted for 1.8% of total cases, and for 3.4% of PVE cases. Most patients (86.6%) had a health care-associated infection. PVE associated with a health care contact occurred after a median of 225 days from valve implantation. Ten patients (66.6%) were treated with caspofungin alone or in combination with other antifungal drugs. The overall mortality rate was 46.6%. Mortality was higher in patients with PVE (5 of 8 cases, 62.5%) than in patients with NVE (2 of 5 patients, 40%). A better outcome was observed in patients treated with a combined medical and surgical therapy. Candida IE should be classified as an emerging infectious disease, usually involving patients with intravascular prosthetic devices, and associated with substantial related morbidity and mortality. Candida PVE usually is a late-onset disease, which becomes clinically evident even several months after an initial episode of transient candidemia. (Medicine 2009;88: 160-168

Current features of infective endocarditis in persons on hemodialysis: a prevalence study with case control design from the prospective multicenter SEI cohort

Purpose: Persons on hemodialysis (HD) are at high risk of infective endocarditis (IE). In non-comparative retrospective studies, a higher rate of mortality was reported in IE on HD. We assessed risk factors, clinical characteristics, and outcomes of IE in HD. Methods: This was a prevalence study with a case control methodology on a set of data from the prospectively followed cohort of the Studio Endocarditi Italiano (SEI), conducted between 2004 and 2011. Included were 42 consecutive cases of IE HD subjects and 126 controls not on HD, matched for age, sex, type of IE, and heart side involved. Clinical, echocardiographic, microbiological features, and disease complications and therapeutic modalities were assessed. Results: HD patients were more often diabetics (42.9 vs 18.2 % in no-HD; p = 0.007) and immune-suppressed (16.7 vs 3.2 %; p = 0.02), and had a higher rate of predisposing cardiac conditions (45 vs 25 %; p = 0.031). A higher prevalence of health care-related acquisition and a shorter diagnostic delay was observed in IE on HD, that was more likely to be caused by staphylococci and less by streptococci (p < 0.002). Cardiac surgery was performed in 38 % of HD patients and 36.5 % of no-HD patients (p = 0.856). Complications were similar and in-hospital mortality did not differ significantly (26.2 % in HD vs 15.9 % in no-HD; p = 0.168). Conclusions: IE in persons on HD is characterized by distinctive clinical features, including a higher prevalence of some important comorbidities. Inconsistent with prior studies, we could not confirm a higher rate of complications and mortality in HD patients with IE