The association of basic amphipathic peptides to neutral phospholipid membranes is investigated in terms of binding and partition models. The binding of native and modified melittin to egg-yolk phosphatidylcholine vesicles is studied by steady-state fluorescence spectroscopy. The effect of the ionic strength shows an enhancement of the association as the ionic strength increases. After correction for electrostatic effects by the Gouy–Chapman theory, the melittin binding isotherms could be described by a partition model. In terms of conventional binding mechanisms, which do not take into account electrostatic effects, this would correspond to a negative cooperativity. A plausible way in which the interaction occurs is proposed, based on the calculated Hill coefficient.

The synthesis of 2,5,7-triamino[1,2,4]triazolo[1,5-a][1,3,5]triazines was developed. The 3,5-diamino-1,2,4-triazoles were prepared using partial aminolysis of dimethyl N-cyanodithiocarbonimidate followed by cyclization of the obtained N-substituted N’-cyano-S-methylisothioureas with hydrazine. The reaction of 3,5-diamino-1,2,4-triazoles with cyanoguanidine was found to afford 2,5,7-triamino[1,2,4]triazolo[1,5-a][1,3,5]triazines. The structure of the compounds obtained was established using NMR spectroscopy.

A novel approach to bio-macromolecular design from a linear algebra point of view is introduced. Protein’s total (whole-protein) and local (one or more amino-acid) linear indices are a new set of bio-macromolecular descriptors of relevance to protein QSAR/QSPR studies. These amino-acid level biochemical descriptors are based on the calculation of linear maps on ℜⁿ[ƒ_k (x_mi): ℜⁿ→ℜⁿ] in canonical basis. These bio-macromolecular indices are calculated from the k^th power of the macromolecular pseudograph’s α-carbon atom adjacency matrix. Total linear indices are linear functional on ℜⁿ. That is, the k^th total linear indices are a linear maps from ℜⁿ to the scalar ℜ[ƒ_k(x_m):ℜⁿ→ℜ]. Thus, the k^th total linear indices are calculated by summing the amino-acid linear indices of all amino-acids in the protein molecule. A study of the protein stability effects for a complete set of alanine substitutions in Arc repressor illustrates this approach. A quantitative model that discriminates near wild-type stability alanine-mutants from the reduced-stability ones in a training series was obtained. This model permitted the correct classification of 97.56% (40/41) and 91.67% (11/12) of proteins in the training and test set, respectively. It show a high Matthews´ correlation coefficient (MCC = 0.952) for the training set and a MCC = 0.837 for the external prediction set. Additionally, canonical regression analysis corroborated the statistical quality of the classification model (Rcanc = 0.824). This analysis was also used to compute biological stability canonical scores for each Arc alanine-mutant. On the other hand, linear piecewise regression model compared favorably with respect to linear regression one on predicting the melting temperature (t_m) of the Arc alanine-mutants. The linear model explains almost 81% of the variance of the experimental t_m (R = 0.90 and s = 4.29) and the LOO press statistics evidenced its predictive ability (q² = 0.72 and s_cv = 4.79). Moreover, TOMOCOMD-CAMPS method produced a linear piece-wise regression (R = 0.97) between protein backbone descriptors and t_m values for alanine-mutants of Arc repressor. A break-point value of 51.87^oC characterized two mutants’ clusters and coincided perfectly with the experimental scale. For this reason, we can use the linear discriminant analysis and piecewise models in combination to classify and predict the stability of the mutant Arc homodimers. These models also permitted the interpretation of the driving forces of such a folding process, indicating that topologic/topographic protein’s backbone interactions control the stability profile of wild-type Arc and its alanine-mutants.

Motivation: Predicting HIV resistance to drugs is one of many problems for which bioinformaticians have implemented and trained machine learning methods, such as neural networks. Predicting HIV resistance would be much easier if we could directly use the three-dimensional (3D) structure of the targeted protein sequences, but unfortunately we rarely have enough structural information available to train a neural network. Furthermore, prediction of the 3D structure of a protein is not straightforward. However, characteristics related to the 3D structure can be used to train a machine learning algorithm as an alternative to take into account the information of the protein folding in the 3D space. Here, starting from this philosophy, we select the amino acid energies as features to predict HIV drug resistance, using a specific topology of a neural network.
Results: In this paper, we demonstrate that the amino acid energies are good features to represent the HIV genotype. In addition, it was shown that Bidirectional Recurrent Neural Networks can be used as an efficient classification method for this problem. The prediction performance that was obtained was greater than or at least comparable to results obtained previously. The accuracies vary between 81.3% and 94.7%.

Ferroceneamine, H₂N-Fc, has been substituted to the C-terminus of 6 amino acids using the HBTU / HOBt coupling protocol. The synthesized bioconjugates Boc-Aaa-Fc, Aaa = Gly (1), Leu (2), Phe (3), Val (4), Cys(Acm) (5), Tyr(^tBu) (6) (Acm = acetamidomethyl, ^tBu = t-buthyl), have been characterized by ¹H NMR, ¹³C NMR EI-MS, EI-HRMS, UV and CD spectroscopies. In addition, a VT NMR study on 4 and the X-ray structure of 1 are presented.

A series of functionalised 5,9-diaminobenzo[a]phenoxazinium salts, in the free form or linked to L-glycine and L-valine amino acids were evaluated against Saccharomyces cerevisiae, in a microdilution broth assay. The results obtained showed that these compounds exhibited antifungal activity depending on the substituents of the 5,9-diaminobenzo[a]phenoxazine nucleous. The best activities were obtained when substituents at the positions 9 and 10 were NHEt, and Me, respectively, and at the position 5, NH(CH₂)₃Cl or NH(CH₂)₃CO₂Et.

cis-4-(Acetylamino)-N-methylcyclohexane carboxamide has been selected as all carbon ring analogue of the previously described 5-aminopiperidinone-2-carboxylate systems. The potential ß-turn inducing properties of this model compound are evaluated by means of NMR analysis and molecular modeling.

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The telluroether Te[CH₂Si(CH₃)₃]₂ (1) has been prepared in a good yield by the reaction of Na₂Te and ClCH₂SiMe₃ in aqueous solution. The reaction of 1 with I₂ affords TeI₂[CH₂Si(CH₃)₃]₂ (2). The compounds have been characterized by ¹³C{¹H}- and ¹²⁵Te-NMR spectroscopy. The crystal structure of 2 shows the presence of weak Te···I and I···I secondary bonding interactions leading to the formation of a supramolecular assembly.