On the optimality of the genetic code, with the consideration of coevolution theory by comparison of prominent cost measure matrices

Statistical and biochemical studies have revealed non-random patterns in codon assignments. The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslation errors and point mutations, since it is known that when an amino acid is converted to another due to error, the biochemical properties of the resulted amino acid are usually very similar to those of the original one. In this study, using altered forms of the fitness functions used in the prior studies, we have optimized the parameters involved in the calculation of the error minimizing property of the genetic code so that the genetic code outscores the random codes as much as possible. This work also compares two prominent matrices, the Mutation Matrix and Point Accepted Mutations 74-100 (PAM(74-100)). It has been resulted that the hypothetical properties of the coevolution theory of the genetic code are already considered in PAM(74-100), giving more evidence on the existence of bias towards the genetic code in this matrix. Furthermore, our results indicate that PAM(74-100) is biased towards the single base mistranslation occurrences in second codon position as well as the frequency of amino acids. Thus PAM(74-100) is not a suitable substitution matrix for the studies conducted on the evolution of the genetic code.     

Identification and characterization of allophenylnorstatine-based inhibitors of plasmepsin II, an antimalarial target

Plasmepsin II is a key enzyme in the life cycle of the Plasmodium parasites responsible for malaria, a disease that afflicts more than 300 million individuals annually. Since plasmepsin II inhibition leads to starvation of the parasite, it has been acknowledged as an important target for the development of new antimalarials. In this paper, we identify and characterize high-affinity inhibitors of plasmepsin II based upon the allophenylnorstatine scaffold. The best compound, KNI-727, inhibits plasmepsin II with a K(i) of 70 nM and a 22-fold selectivity with respect to the highly homologous human enzyme cathepsin D. KNI-727 binds to plasmepsin II in a process favored both enthalpically and entropically. At 25 degrees C, the binding enthalpy (DeltaH) is -4.4 kcal/mol and the entropic contribution (-TDeltaS) to the Gibbs energy is -5.56 kcal/mol. Structural stability measurements of plasmepsin II were also utilized to characterize inhibitor binding. High-sensitivity differential scanning calorimetry experiments performed in the absence of inhibitors indicate that, at pH 4.0, plasmepsin II undergoes thermal denaturation at 63.3 degrees C. The structural stability of the enzyme increases with inhibitor concentration in a manner for which the binding energetics of the inhibitor can quantitatively account. The effectiveness of the best compounds in killing the malaria parasite was validated by performing cytotoxicity assays in red blood cells infected with Plasmodium falciparum. EC50s ranging between 6 and 10 microM (3-6 microg/mL) were obtained. These experiments demonstrate the viability of the allophenylnorstatine scaffold in the design of powerful and selective plasmepsin inhibitors.     

Reaction of sunflower varieties to Sclerotinia sclerotiorum under various inoculation methods,time of field evaluation and phylogenic stages of host

Sunflower cultivation is affected seriously by Sclerotinia sclerotiorum (Lib.) de Bary in Iran, particularly north-western areas. Because of economic and environmental harms by chemical control, it is necessary to develop cultivars with adequate genetic resistance for reduction of yield losses. The purpose of this study was to find an effective method of inoculation with S. sclerotiorum under field evaluations. Three stem-inoculation techniques including: 1 – mycelium plug, 2 – oxalic acid solution (OAS) and 3 – infested wheat seeds with Sclerotinia mycelium were employed under field conditions. Four genotypes including Ghalami (local variety in market), Confeta, Allstar and Master were used in this study. The lesion length, lesion width and lesion as up and down leading on the stem from inoculation site were measured after 3, 7, 10 and 14 days of inoculation. The analysis of variance showed significant difference between all employed techniques and incubation days after inoculation. Mycelial plug (MP) inoculation technique produced significantly more developed lesions on the treated stems. In spite of this effect, Master variety demonstrated reasonable resistance reaction against the disease. The progress of disease in wounded treatments was also faster than the non-wounded ones. And, the shortest time to obtain significant differences between varieties was 10?days after inoculation. By comparison of results of lesion length at flowering and seed-filling stages, the more obvious effectiveness of the disease was observed at the second stage. Finally, there were negative correlations between mean temperature and mean lesion length in all three inoculation methods.     

Error minimization explains the codon usage of highly expressed genes in Escherichia coli

Different organisms use synonymous codons with different preferences. Several measures have been introduced to compute the extent of codon usage bias within a gene or genome, among which the codon adaptation index (CAI) has been shown to be well correlated with mRNA levels of Escherichia coli. In this work an error adaptation index (eAI) is introduced, which estimates the level at which a gene can tolerate the effects of mistranslations. It is shown that the eAI has a strong correlation with CAI, as well as with mRNA levels, which suggests that the codons of highly expressed genes are selected so that mistranslation would have the minimum possible effect on the structure and function of the related proteins.     

A structural approach reveals how neighbouring C2H2 zinc fingers influence DNA binding specificity

Development of an accurate protein–DNA recognition code that can predict DNA specificity from protein sequence is a central problem in biology. C₂H₂ zinc fingers constitute by far the largest family of DNA binding domains and their binding specificity has been studied intensively. However, despite decades of research, accurate prediction of DNA specificity remains elusive. A major obstacle is thought to be the inability of current methods to account for the influence of neighbouring domains. Here we show that this problem can be addressed using a structural approach: we build structural models for all C₂H₂-ZF–DNA complexes with known binding motifs and find six distinct binding modes. Each mode changes the orientation of specificity residues with respect to the DNA, thereby modulating base preference. Most importantly, the structural analysis shows that residues at the domain interface strongly and predictably influence the binding mode, and hence specificity. Accounting for predicted binding mode significantly improves prediction accuracy of predicted motifs. This new insight into the fundamental behaviour of C₂H₂-ZFs has implications for both improving the prediction of natural zinc finger-binding sites, and for prioritizing further experiments to complete the code. It also provides a new design feature for zinc finger engineering.     

Optimality of codon usage in Escherichia coli due to load minimization

The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslational errors and point mutations, an ability which in term is designated "load minimization". One parameter involved in calculating the load minimizing property of the genetic code is codon usage. In most bacteria, synonymous codons are not used with equal frequencies. Different factors have been proposed to contribute to codon usage preference. It has been shown that the codon preference is correlated with the composition of the tRNA pool. Selection for translational efficiency and translational accuracy both result in such a correlation. In this work, it is shown that codon usage bias in Escherichia coli works so as to minimize the consequences of translational errors, i.e. optimized for load minimization.