Assessing the Quality of in Silico Produced Biomolecules: The Discovery of a New Conformer.

The computational procedures for predicting the 3D structure of aptamers interacting with different biological molecules have gained increasing attention in recent years. The information acquired through these methods represents a crucial input for research, especially when relevant crystallographic data are not available. A number of software programs able to perform macromolecular docking are currently accessible, leading to the prediction of the quaternary structure of complexes formed by two or more interacting biological macromolecules. Nevertheless, the scoring protocols employed for ranking the candidate structures do not always produce satisfactory results, making difficult the identification of structures that are most likely to occur in nature. In this paper, we propose a novel procedure to improve the predictive performances of computational scoring protocols, using a maximum likelihood estimate based on topological and electrical properties of interacting biomolecules. The reliability of the new computational approach, enabling the ranking of aptamer-protein configurations produced by an open source docking program, has been assessed by its successful application to a set of antiangiopoietin aptamers, for which experimental data highlighting the sequence-dependent affinity toward the target protein are available. The procedure led to the identification of two main types of aptamer conformers involved in angiopoietin binding. Interestingly, one of these reproduces the arrangement of angiopoietin with its natural target, tyrosine kinase, while the other one is completely unexpected. The possible scenarios related to these results have been discussed. The methodology here described can be used to refine the outcomes of different computational procedures and can be applied to a wide range of biological molecules, thus representing a new tool for guiding the design of bioinspired sensors with enhanced selectivity.

A validation strategy for in silico generated aptamers.

The selection of high-affinity aptamers is of paramount interest for clinical and technological applications. A novel strategy is proposed to validate the reliability of the 3D structures of a group of anti- Angiopoietin-2 aptamers, produced in silico by using free software. In a previous literature these aptamers were processed both in vitro and in silico, by using an approach different from that here presented, and finally tested with a SPS experiment. Computational expectations and experimental outcomes did not agree. The procedure here proposed consists of three steps: a. the production of a large set of conformations for each candidate aptamer; b. the rigid docking upon the receptor; c. the topological and electrical characterization of the products. Steps a. and b. allow a global binding score of the ligand-receptor complexes based on the distribution of the "effective affinity", i.e. the sum of the conformational and the docking energies. Step c. employs a complex network approach (Proteotronics) to characterize the electrical properties of the aptamers and the ligand-receptor complexes. Finally, the results are discussed and compared with the literature on the same aptamers. The computational predictions are in good agreement with the known experimental measurements.

Critical behavior in a stochastic model of vector mediated epidemics.

The extreme vulnerability of humans to new and old pathogens is constantly highlighted by unbound outbreaks of epidemics. This vulnerability is both direct, producing illness in humans (dengue, malaria), and also indirect, affecting its supplies (bird and swine flu, Pierce disease, and olive quick decline syndrome). In most cases, the pathogens responsible for an illness spread through vectors. In general, disease evolution may be an uncontrollable propagation or a transient outbreak with limited diffusion. This depends on the physiological parameters of hosts and vectors (susceptibility to the illness, virulence, chronicity of the disease, lifetime of the vectors, etc.). In this perspective and with these motivations, we analyzed a stochastic lattice model able to capture the critical behavior of such epidemics over a limited time horizon and with a finite amount of resources. The model exhibits a critical line of transition that separates spreading and non-spreading phases. The critical line is studied with new analytical methods and direct simulations. Critical exponents are found to be the same as those of dynamical percolation.

Photoreceptors for a light biotransducer: a comparative study of the electrical responses of two (type-1) opsins.

The increasing interest in photoactivated proteins as natural replacements for standard inorganic materials in photocells leads to the comparison analysis of bacteriorhodopsin and proteorhodopsin, two widely diffused proteins belonging to the family of type-1 opsins. These proteins share similar behaviors but exhibit relevant differences in the sequential chain of the amino acids constituting their tertiary structure. The use of an impedance network analog to model the protein main features provides a microscopic interpretation of a set of experiments on their photo-conductance properties. In particular, this model links the protein electrical responses to the tertiary structure and to the interactions between neighboring amino acids. The same model is also used to predict the small-signal response in terms of the Nyquist plot. Interestingly, these rhodopsins are found to behave like a wide-gap semiconductor with intrinsic conductivities of the order of 10⁻7 S cm⁻¹.

Evidence of Gumbel distributions of conductance fluctuations in bacteriorhodopsin thin films.

By considering a set of experiments carried out on bacteriorhodopsin in vitro by Casuso et al (2007 Phys. Rev. E 76 041919), we extract the conductance as function of the applied voltage. The microscopic interpretation of experiments shows that charge transfer is ruled by a direct tunneling (DT) mechanism at low bias and by a Fowler­Nordheim (FN) tunneling mechanism at high bias. A nucleation region at the cross-over between the DT and FN regimes can be identified. A theoretical analysis of conductance fluctuations is performed by calculating the corresponding variance and the probability density functions (PDFs): these constitute a powerful indicator in order to understand the internal dynamics of the system. Conductance fluctuations are non-Gaussian and follow well the standard generalized Gumbel distributions G(a). In particular, at low bias, the PDFs are bimodal and can be resolved in at least a couple of G(a) functions with different values of the shape parameter a. The nucleation region is characterized by a single Gumbel distribution, G(1). At increasing bias, the G(1) distribution turns in a bimodal distribution. We discuss possible correlations between the voltage dependence of the G(a) and the microscopic mechanisms that determine the electrical response of the system.

Charge transport in purple membrane monolayers: a sequential tunneling approach.

Current-voltage (I-V) characteristics in proteins are sensitive to conformational changes induced by an external stimulus (photons, chemical, etc.). This sensitivity can be used in medical and industrial applications as well as shedding new light on the microscopic structure of biological materials. Here, we show that a sequential tunneling model of carrier transfer between neighboring amino acids in a single protein is the basic mechanism responsible for the electrical properties measured over a wide range of applied potentials. We also show that such a strict correlation between the protein structure and the electrical response can lead to a new generation of nanobiosensors that mimic the sensorial activity of living species. To demonstrate the potential usefulness of protein electrical properties, we provide a microscopic interpretation of recent I-V experiments carried out in bacteriorhodopsin at a nanoscale length.

Role of topology in electrical properties of bacterio-rhodopsin and rat olfactory receptor I7.

We report on electrical properties of the two sensing proteins: bacteriorhodopsin and rat olfactory receptor OR-I7. As relevant transport parameters we consider the small-signal impedance spectrum and the static current-voltage characteristics. Calculations are compared with available experimental results and the model predictability is tested for future perspectives.

Resistance and resistance fluctuations in random resistor networks under biased percolation.

We consider a two-dimensional random resistor network (RRN) in the presence of two competing biased processes consisting of the breaking and recovering of elementary resistors. These two processes are driven by the joint effects of an electrical bias and of the heat exchange with a thermal bath. The electrical bias is set up by applying a constant voltage or, alternatively, a constant current. Monte Carlo simulations are performed to analyze the network evolution in the full range of bias values. Depending on the bias strength, electrical failure or steady state are achieved. Here we investigate the steady state of the RRN focusing on the properties of the non-Ohmic regime. In constant-voltage conditions, a scaling relation is found between /(0) and V/V(0), where is the average network resistance, (0) the linear regime resistance, and V0 the threshold value for the onset of nonlinearity. A similar relation is found in constant-current conditions. The relative variance of resistance fluctuations also exhibits a strong nonlinearity whose properties are investigated. The power spectral density of resistance fluctuations presents a Lorentzian spectrum and the amplitude of fluctuations shows a significant non-Gaussian behavior in the prebreakdown region. These results compare well with electrical breakdown measurements in thin films of composites and of other conducting materials.