Davor Juretić

Secondary structure predictions and medium range interactions

Several authors have proposed that predictions of protein secondary structure derived from statistical information about the known structures can be improved when information about neighboring residues participating in short and medium range interactions is included. A substantial improvement shown here indicates that current methods of including this information are not more successful than methods that do not. Evaluations of the Chou and Fasman method (Adv. Enzymol. 47 (1978) 45-148), that does not include information about interactions (except in averaging), have shown it to be about 49% correct for three states (helix, beta-sheet and undefined). In comparison, the method of Garnier et al. (J. Mol. Biol. 120 (1978) 97-120), that explicitly includes information about neighboring residues, has an accuracy of 57% residues correct for three states. However, we have obtained an 8% improvement for predictions of secondary structure based on the algorithm by Chou and Fasman. The improvements are obtained by eliminating many rules and by choosing the best decision constants for structure assignments. The simplified method described here is 57% correct for three states using preference values calculated in 1978.

Magainin 2 amide and analogues Antimicrobial activity, membrane depolarization and susceptibility to proteolysis

We compared the abilities of synthetic magainin 2 amide and its analogues to inhibit the growth of Escherichia coli and to cause membrane depolarization in E. coli cells and cytochrome oxidase liposomes. The analogue, magainin A, was about 40‐times more active than magainin 2 amide in inhibiting the growth of E. coli and had a much more sustained effect on the membrane potential. In the liposomal system, however, there was only approx. 20% difference between these two peptides in the reduction of membrane potential and uncoupling of respiration. Studies with pronase digestion suggested that the difference in potency may be due to differential susceptibility to proteolysis in the presence of membranes.

DADP: the database of anuran defense peptides

SUMMARY Anuran tissues, and especially skin, are a rich source of bioactive peptides and their precursors. We here present a manually curated database of antimicrobial and other defense peptides with a total of 2571 entries, most of them in the precursor form with demarcated signal peptide (SP), acidic proregion(s) and bioactive moiety(s) corresponding to 1923 non-identical bioactive sequences. Search functions on the corresponding web server facilitate the extraction of six distinct SP classes. The more conserved of these can be used for searching cDNA and UniProtKB databases for potential bioactive peptides, for creating PROSITE search patterns, and for phylogenetic analysis.

Interactions between a new class of eukaryotic antimicrobial agents and isolated rat liver mitochondria.

Members of a newly discovered class of eukaryotic antimicrobial peptides are shown to release respiratory control in isolated rat-liver mitochondria. They also dissipate the membrane potential and inhibit respiration. The uncoupling activity of the peptides decreases with time probably due to the presence of proteases in the mitochondrial preparation. Quinine and Mg2+ reduce the activity of the peptides. The nature of the dependence of the respiratory rate on the concentration of added peptides suggests that they are active in a multimeric form, consistent with the formation of a channel across the inner mitochondrial membrane. The channel allows passage of sucrose.

Photosynthetic models with maximum entropy production in irreversible charge transfer steps

Steady-state bacterial photosynthesis is modelled as cyclic chemical reaction and is examined with respect to overall efficiency, power transfer efficiency, and entropy production. A nonlinear flux-force relationship is assumed. The simplest two-state kinetic model bears complete analogy with the performance of an ideal (zero ohmic resistance of the P-N junction) solar cell. In both cases power transfer to external load is much higher than the 50% allowed by the impedance matching theorem for the linear flux-force relationship. When maximum entropy production is required in the transition with a load, one obtains high optimal photochemical yield of 97% and power transfer efficiency of 91%. In more complex photosynthetic models, entropy production is maximized in all irreversible electron/proton (non-slip) transitions in an iterative procedure. The resulting steady-state is stable with respect to an extremely wide range of initial values for forward rate constants. Optimal proton current increases proportionally to light intensity and decreases with an increase in the proton-motive force (the backpressure effect). Optimal affinity transfer efficiency is very high and nearly perfectly constant for different light absorption rates and for different electrochemical proton gradients. Optimal overall efficiency (of solar into proton-motive power) ranges from 10% (bacteriorhodopsin) to 19% (chlorophyll-based bacterial photosynthesis). Optimal time constants in a photocycle span a wide range from nanoseconds to milliseconds, just as corresponding experimental constants do. We conclude that photosynthetic proton pumps operate close to the maximum entropy production mode, connecting biological to thermodynamic evolution in a coupled self-amplifying process.

Computational design of highly selective antimicrobial peptides.

We have created a structure-selectivity database (AMPad) of frog-derived, helical antimicrobial peptides (AMPs), in which the selectivity was determined as a therapeutic index (TI), and then used the novel concept of sequence moments to study the lengthwise asymmetry of physicochemical peptide properties. We found that the cosine of the angle between two sequence moments obtained with different hydrophobicity scales, defined as the D-descriptor, identifies highly selective peptide antibiotics. We could then use this descriptor to predict TI changes after point mutations in known AMPs, and to aid the prediction of TI for de novo designed AMPs. In combination with an amino acid selectivity index, a motif regularity index and other statistical rules extracted from AMPad, the D-descriptor enabled construction of the AMP-Designer algorithm. A 23 residue, glycine-rich, peptide suggested by the algorithm was synthesized and the activity and selectivity tested. This peptide, adepantin 1, is less than 50% identical to any other AMP, has a potent antibacterial activity against the reference organism, E. coli, and has a significantly greater selectivity (TI > 200) than the best AMP present in the AMPad database (TI = 125).

Kirchhoff's loop law and the maximum entropy production principle.

In contrast to the standard derivation of Kirchhoffs loop law, which invokes electric potential, we show, for the linear planar electric network in a stationary state at the fixed temperature, that loop law can be derived from the maximum entropy production principle. This means that the currents in network branches are distributed in such a way as to achieve the state of maximum entropy production.

Knowledge-based computational methods for identifying or designing novel, non-homologous antimicrobial peptides

We describe computational approaches for identifying promising lead candidates for the development of peptide antibiotics, in the context of quantitative structure–activity relationships (QSAR) studies for this type of molecule. A first approach deals with predicting the selectivity properties of generated antimicrobial peptide sequences in terms of measured therapeutic indices (TI) for known antimicrobial peptides (AMPs). Based on a training set of anuran AMPs, the concept of sequence moments was used to construct algorithms that could predict TIs for a second test set of natural AMPs and could also predict the effect of point mutations on TI values. This approach was then used to design peptide antibiotics (adepantins) not homologous to known natural or synthetic AMPs. In a second approach, many novel putative AMPs were identified from DNA sequences in EST databases, using the observation that, as a rule, specific subclasses of highly conserved signal peptides are associated exclusively with AMPs. Both anuran and teleost sequences were used to elucidate this observation and its implications. The predicted therapeutic indices of identified sequences could then be used to identify new types of selective putative AMPs for future experimental verification.

Preference functions for prediction of membrane-buried helices in integral membrane proteins

The preference functions method is described for prediction of membrane-buried helices in membrane proteins. Preference for the alpha-helix conformation of amino acid residue in a sequence is a non-linear function of average hydrophobicity of its sequence neighbors. Kyte-Doolittle hydropathy values are used to extract preference functions from a training data set of integral membrane proteins of partially known secondary structure. Preference functions for beta-sheet, turn and undefined conformation are also extracted by including beta-class soluble proteins of known structure in the training data set. Conformational preferences are compared in tested sequence for each residue and predicted secondary structure is associated with the highest preference. This procedure is incorporated in an algorithm that performs accurate prediction of transmembrane helical segments. Correct sequence location and secondary structure of transmembrane segments is predicted for 20 of 21 reference membrane polypeptides with known crystal structure that were not included in the training data set. Comparison with hydrophobicity plots revealed that our preference profiles are more accurate and exhibit higher resolution and less noise. Shorter unstable or movable membrane-buried alpha-helices are also predicted to exist in different membrane proteins with transport function. For instance, in the sequence of voltage-gated ion channels and glutamate receptors, N-terminal parts of known P-segments can be located as characteristic alpha-helix preference peaks. Our e-mail server: predict@drava.etfos.hr, returns a preference profile and secondary structure prediction for a suspected or known membrane protein when its sequence is submitted.

Myelin basic protein ability to organize lipid bilayers: Structural transition in bilayers of lisophosphatidylcholine micelles

Abstract Myelin basic protein isolated by a single step with the cationic detergent cethyltrimethylammonium bromide in a lipid-bound form is able to induce structural transition of lysophosphatydilcholine micelles into multilaminar vesicles. This finding, observed through electron microscopy, is discussed in the light of the assumed ability of the basic protein to organize myelin lipids.