M89V Sialic Acid Acetyl Esterase (SIAE) and All Other Non-Synonymous Common Variants of This Gene Are Catalytically Normal

Catalytically defective rare variants of Sialic acid Acetyl Esterase (SIAE) have previously been linked to autoimmunity. Studies presented here confirm that the M89V SIAE protein and all other products of common variant alleles of SIAE are catalytically normal. Although overexpressing transfected non-lymphoid cells secrete small amounts of SIAE that can associate with the cell surface, normal human lymphocytes do not exhibit cell surface SIAE, supporting genetic evidence in mice that indicates that this protein functions in a lymphocyte intrinsic manner. Analyses of the plasma proteome also indicate that SIAE is not secreted in vivo. A re-analysis exclusively of catalytically defective rare variant alleles of SIAE in subjects in which this gene was completely sequenced confirmed an association of SIAE with autoimmunity. A subset of catalytically defective rare variant SIAE alleles has previously been typed in a large genotyping study comparing a diverse group of disease subjects and controls; our re-analysis of this data shows that catalytically defective alleles are enriched in disease subjects. These data suggest that SIAE may be associated with autoimmunity and that further study of catalytically defective rare variant SIAE alleles in terms of autoimmune disease susceptibility is strongly warranted.     

Distribution of charged residues stabilizes individual helices in myoglobins

The effect of the distribution of charged residues on stability of alpha helices in isolated peptides and in globular proteins exemplified by myoglobins from 62 different species is discussed. A highly simplified set of rules is used to account for the interaction of charged groups with the dipole of an alpha helix. Only the position and sign of a charge with respect to the center of the helix and its ability to participate in intrahelical salt bridges determine its effect. These rules lead to a linear correlation between the helicity in variant C-peptide helices from RNAse and the extent to which the charge distribution opposes the helix dipole. Of the sample of 496 helices in the myoglobins studied, 456 exhibit arrangements of charges which oppose the effective dipole moment of the helix according to this calculation. A number of variants occur which leave the backbone moment of helices A-D unchanged, or even add to it. However no such variants exist in the sequences of helices E-H. We suggest that the E, F, G and H helices in myoglobins which show the strongest reversal of the helix dipole participate in the structures of early intermediates in folding of the chain. Stable helix structures should be more likely to occur in these isolated sequences also, and introduction of charge alterations in helices E to H should affect the initial refolding rate of mutant myoglobins.     

Diagnosing dementia: do we get it right?

To find out whether the diagnosis of dementia agreed with findings at necropsy a detailed assessment of 27 elderly patients (mean age 82 (range 70-94] presenting with dementia was conducted at a combined department of geriatric medicine and psychiatry for the elderly. On the basis of the results the cause of the dementia was diagnosed clinically. Neuropathological examinations were performed after death. The clinical diagnosis made during life was not supported by the findings at necropsy in 11 cases. Alzheimer''s disease was overdiagnosed in life (13 cases, of which only six were confirmed at necropsy). Although the clinical investigation was limited by availability of resources, neither cranial computed tomography nor the Hachinski score helped to distinguish between multi-infarct dementia and Alzheimer''s disease in this age group. This study confirms the value of neuropathological studies in the precise diagnosis of dementia.     

Contributions to the genus phytophthora de bary from india

The paper deals with some of the contributions made from India by various research workers towards our knowledge of the fungus genusPhytophthora de Bary, in the fields of morphology, disease production, occurrence and distribution of species, host range, physiology, taxonomy and control measures. Out of the total of fifteen species and five varieties ofPhytophthora reported from India, five species (viz.,P. arecae, P. palmivora, P. colocasiae, P. parasitica andP. infestans, and four varieties ofP. parasitica, viz.,P. parasitica var.macrospora, var.sesami, var.piperina and var.nicotianae) assume considerable parasitic roles inciting serious diseases like seedling-blights, wilts, cottoney-leaks, foot-rots, blights, budrot and rots of fruits, nuts, tubers and corms etc. They are widely distributed in various parts of this country, and are mostly prevalent in rainy seasons.Phytophthora palmivora, andP. parasitica were found to have a wide host range.     

An account of the genus pythium Pringsheim in India

Summary Of the 20 species ofPythium reported from India, not more than seven assume parasitic role inciting mainly diseases in seed bed and sometimes in the fields such as damping-off, seedling blights and foot rots. The paper gives a brief account of the taxonomy of the Indian species and methods of controlling the diseases incited by them.     

Some conditions apply: Systems for studying Plasmodium falciparum protein function

Malaria, caused by infection with Plasmodium parasites, remains a significant global health concern. For decades, genetic intractability and limited tools hindered our ability to study essential proteins and pathways in Plasmodium falciparum, the parasite associated with the most severe malaria cases. However, recent years have seen major leaps forward in the ability to genetically manipulate P. falciparum parasites and conditionally control protein expression/function. The conditional knockdown systems used in P. falciparum target all 3 components of the central dogma, allowing researchers to conditionally control gene expression, translation, and protein function. Here, we review some of the common knockdown systems that have been adapted or developed for use in P. falciparum. Much of the work done using conditional knockdown approaches has been performed in asexual, blood-stage parasites, but we also highlight their uses in other parts of the life cycle and discuss new ways of applying these systems outside of the intraerythrocytic stages. With the use of these tools, the field’s understanding of parasite biology is ever increasing, and promising new pathways for antimalarial drug development are being discovered.     

Partner-specific prediction of RNA-binding residues in proteins: A critical assessment

RNA-protein interactions play essential roles in regulating gene expression. While some RNA-protein interactions are “specific”, that is, the RNA-binding proteins preferentially bind to particular RNA sequence or structural motifs, others are “non-RNA specific.” Deciphering the protein-RNA recognition code is essential for comprehending the functional implications of these interactions and for developing new therapies for many diseases. Because of the high cost of experimental determination of protein-RNA interfaces, there is a need for computational methods to identify RNA-binding residues in proteins. While most of the existing computational methods for predicting RNA-binding residues in RNA-binding proteins are oblivious to the characteristics of the partner RNA, there is growing interest in methods for partner-specific prediction of RNA binding sites in proteins. In this work, we assess the performance of two recently published partner-specific protein-RNA interface prediction tools, PS-PRIP, and PRIdictor, along with our own new tools. Specifically, we introduce a novel metric, RNA-specificity metric (RSM), for quantifying the RNA-specificity of the RNA binding residues predicted by such tools. Our results show that the RNA-binding residues predicted by previously published methods are oblivious to the characteristics of the putative RNA binding partner. Moreover, when evaluated using partner-agnostic metrics, RNA partner-specific methods are outperformed by the state-of-the-art partner-agnostic methods. We conjecture that either (a) the protein-RNA complexes in PDB are not representative of the protein-RNA interactions in nature, or (b) the current methods for partner-specific prediction of RNA-binding residues in proteins fail to account for the differences in RNA partner-specific versus partner-agnostic protein-RNA interactions, or both.     

Predicting binding sites of hydrolase-inhibitor complexes by combining several methods

Background

Protein-protein interactions play a critical role in protein function. Completion of many genomes is being followed rapidly by major efforts to identify interacting protein pairs experimentally in order to decipher the networks of interacting, coordinated-in-action proteins. Identification of protein-protein interaction sites and detection of specific amino acids that contribute to the specificity and the strength of protein interactions is an important problem with broad applications ranging from rational drug design to the analysis of metabolic and signal transduction networks.

Results

In order to increase the power of predictive methods for protein-protein interaction sites, we have developed a consensus methodology for combining four different methods. These approaches include: data mining using Support Vector Machines, threading through protein structures, prediction of conserved residues on the protein surface by analysis of phylogenetic trees, and the Conservatism of Conservatism method of Mirny and Shakhnovich. Results obtained on a dataset of hydrolase-inhibitor complexes demonstrate that the combination of all four methods yield improved predictions over the individual methods.

Conclusions

We developed a consensus method for predicting protein-protein interface residues by combining sequence and structure-based methods. The success of our consensus approach suggests that similar methodologies can be developed to improve prediction accuracies for other bioinformatic problems.