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S Fiori

Publications and source records attributed to S Fiori.

13 recordsLinked to original sources

Probability density function learning by unsupervised neurons.

In a recent work, we introduced the concept of pseudo-polynomial adaptive activation function neuron (FAN) and presented an unsupervised information-theoretic learning theory for such structure. The learning model is based on entropy optimization and provides a way of learning probability distributions from incomplete data. The aim of the present paper is to illustrate some theoretical features of the FAN neuron, to extend its learning theory to asymmetrical density function approximation, and to provide an analytical and numerical comparison with other known density function estimation methods, with special emphasis to the universal approximation ability. The paper also provides a survey of PDF learning from incomplete data, as well as results of several experiments performed on real-world problems and signals.

Algorithms↗

Synthesis and conformational analysis of apamin analogues with natural and non-natural cystine/selenocystine connectivities.

By replacing two cysteine residues in apamin with selenocysteine, the three possible isomers related to the side-chain connectivities of a bis-cystinyl-peptide were synthesized in regioselective manner exploiting the low redox potential of the diselenide bond. Nuclear magnetic resonance conformational analysis of monoselenocystine analogue apamin with the natural diselenide/disulfide network confirmed the highly isomorphous character of the sulfur replacement with selenium despite its slightly larger atomic radius and increased bond lengths. The comparative conformational analysis of the apamin analogues containing the non-natural side-chain links with wild type apamin clearly revealed retention of the main structural fold and thus the high propensity of these small molecules to adopt the secondary structure elements present in natural apamin. These findings offered interesting hints for a better understanding of the oxidative refolding pathway of the bis-cystinyl peptide that leads exclusively to the correct natural isomer.

Amino Acid Sequence↗

Blind signal processing by the adaptive activation function neurons.

The aim of this paper is to study an Information Theory based learning theory for neural units endowed with adaptive activation functions. The learning theory has the target to force the neuron to approximate the input-output transference that makes it flat (uniform) the probability density function of its output or, equivalently, that maximizes the entropy of the neuron response. Then, a network of adaptive activation function neurons is studied, and the effectiveness of the new structure is tested on Independent Component Analysis (ICA) problems. The new ICA neural algorithm is compared with the closely related 'Mixture of Densities' (MOD) technique by Xu et al.. Both simulation results and structural comparison show the new method is effective and more efficient in computational complexity.

Algorithms↗

Preferred conformation of endomorphin-1 in aqueous and membrane-mimetic environments.

The newly discovered endomorphin-1 (Tyr-Pro-Trp-Phe-NH2) and endomorphin-2 (Tyr-Pro-Phe-Phe-NH2) are potent opioid peptides with the highest affinity and selectivity for the mu receptor among all known endogenous ligands. To investigate a possible correlation between these biological properties and the conformational preferences of the small peptides, a comparative structural analysis was performed of endomorphin-1 in aqueous buffer and in membrane-mimicking SDS and AOT normal and reverse micelles by the use of CD, FT-IR, fluorescence and(1)H-NMR spectroscopy. It is well established for opioid peptides that, independently of the receptor selectivity, the Tyr1 residue plays the role of the primary pharmacophore and that the orientation of the second aromatic pharmacophore relative to the tyrosine side-chain dictates the mu or delta-receptor selectivity. By varying the environment of endomorphin-1 from water to the amphipathic SDS micelles and even more efficiently to the AOT reverse micelles, the display of the aromatic side-chains changes from an interaction of the Tyr1 and Phe4 residues to a switch of the Trp3 indole group into close contact with the phenolic moiety to prevent this type of interaction and to force an orientation of the Phe4 side-chain into the opposite direction. This conformational switch is accompanied by a stabilization of the cis -Pro2 isomer and the resulting spatial array of the pharmacophoric groups correlate well with the structural model of mu receptor-bound opioid peptides. The results indicate that AOT reverse micelles with a woof 10, where almost exclusively ordered water is secluded in the cavity, constitute with their electrostatic and hydrophobic potential an excellent mimetic of amphipathic surfaces as present on lipid bilayers and on ligand-recognition and ligand-binding sites of proteins.

Circular Dichroism↗

The disulfide-coupled folding pathway of apamin as derived from diselenide-quenched analogs and intermediates.

The sequence of apamin, an 18 residue bee venom toxin, encloses all the information required for the correct disulfide-coupled folding into the cystine-stabilized alpha-helical motif. Three apamin analogs, each containing a pair of selenocysteine residues replacing the related cysteines, were synthesized to mimic the three possible apamin isomers with two crossed, parallel, or consecutive disulfides, respectively. Refolding experiments clearly revealed that the redox potential of selenocysteine prevails over the sequence encoded structural information for proper folding of apamin. Thus, selenocysteine can be used as a new device to generate productive and nonproductive folding intermediates of peptides and proteins. In fact, disulfides are selectively reduced in presence of the diselenide and the conformational features derived from these intermediates as well as from the three-dimensional (3D) structures of the selenocysteine-containing analogs with their nonnatural networks of diselenide/disulfide bridges allowed to gain further insight into the subtle driving forces for the correct folding of apamin that mainly derive from local conformational preferences.

Amino Acid Sequence↗

Entropy optimization by the PFANN network: application to blind source separation.

The aim of this paper is to present a study of polynomial functional-link neural units that learn through an information-theoretic-based criterion. First the structure of the neuron is presented and the unsupervised learning theory is explained and discussed, with particular attention being paid to its probability density function and cumulative distribution function approximation capability. Then a neural network formed by such neurons (the polynomial functional-link artificial neural network, or PFANN) is shown to be able to separate out linearly mixed eterokurtic source signals, i.e. signals endowed with either positive or negative kurtoses. In order to compare the performance of the proposed blind separation technique with those exhibited by existing methods, the mixture of densities (MOD) approach of Xu et al, which is closely related to PFANN, is briefly recalled; then comparative numerical simulations performed on both synthetic and real-world signals and a complexity evaluation are illustrated. These results show that the PFANN approach gives similar performance with a noticeable reduction in computational effort.

Artificial Intelligence↗

Isomorphous replacement of cystine with selenocystine in endothelin: oxidative refolding, biological and conformational properties of [Sec3,Sec11,Nle7]-endothelin-1.

Air re-oxidation of fully reduced human endothelin-1 under optimized conditions yields the natural isomer with parallel disulfide bridges and the non-natural isomer with crossed disulfide bridges at a ratio of 3:1. In view of the recently determined highly reducing redox potential of selenocysteine (-381 mV) in peptides, the half-cystine residues Cys3 and Cys11 of the natural isomer of endothelin-1 were replaced by selenocysteine. Taking advantage of the high stability of the diselenide group toward reducing agents for disulfides a regioselective disulfide bridging of the second cysteine pair allowed for straightforward preparation of the [Sec3,Sec11, Nle7]-endothelin-1. NMR structural analysis showed conformational preferences of this endothelin analog that were identical to those of the natural hormone. Similarly, the bioactivity data confirmed that replacement of cysteine residues with selenocysteine was without detectable effect on receptor recognition and signal transduction. Both findings strongly support that the exchange of sulfur against selenium produces a fully isomorphous molecule as recently observed for similar exchanges at the level of methionine residues in proteins. Moreover, oxidative refolding of the fully reduced [Sec3,Sec11,Nle7]-endothelin-1 fulfilled the expectation that the redox potential of the selenocysteines would dictate quantitative formation of the natural isomer. These results suggest that the selenocysteine approach, besides offering an interesting chemical tool for induction of correct oxidative folding of multiple cysteine-containing peptides, should even allow for the preparation of non-natural isomers and thus for studying conformational preferences of folding intermediates in peptides and proteins.

Amino Acid Sequence↗

Conformation of four peptides corresponding to the alpha-helical segments of human GM-CSF.

The conformation of segments corresponding to the four alpha-helical stretches found in human granulocyte-macrophage colony-stimulating factor was studied in water solution in the presence of different amounts of 2,2,2-trifluoroethanol (TFE). The CD spectra reveal the onset of secondary structure upon addition of TFE. The final amount of helical conformation varies among the four peptides. In all cases, the conformational transition is complete before 50% TFE (v/v). 1H-NMR studies were conducted at this solvent composition, leading to the assignment of all the resonances and to the definition of the secondary structure for all four fragments.

Amino Acid Sequence↗