PROTEIN FUNCTION, DIVERISTY AND FUNCTIONAL INTERPLAY

Functional annotations of novel or unknown proteins is one of the central problems in post-genomics bioinformatics research. With the vast expansion of genomic and proteomic data and technologies over the last decade, development of automated function prediction (AFP) methods for large-scale identification of protein function has be-come imperative in many aspects. In this research, we address two important divergences from the “one protein – one function” concept on which all existing AFP methods are developed

The recognition of proteasomal receptors by Plasmodium falciparum DSK2

One of the pathways by which proteins are targeted for degradation by the proteasome involve transport by shuttle proteins to proteasomal receptors. The malaria parasite Plasmodium falciparum has recently been found to possess a similar pathway, with the shuttle protein PfDsk2 being the major player. In this study, we have demonstrated how PfDsk2 and its recognition by proteasomal receptors differ from the mammalian system. Our crystal structure of unbound PfDsk2 UBL domain at 1.30 Å revealed an additional

In-Depth Performance Evaluation of PFP and ESG Sequence-Based Function Prediction Methods in CAFA 2011 Experiment

Background Many Automatic Function Prediction (AFP) methods were developed to cope with an increasing growth of the number of gene sequences that are available from high throughput sequencing experiments. To support the development of AFP methods, it is essential to have community wide experiments for evaluating performance of existing AFP methods. Critical Assessment of Function Annotation (CAFA) is one such community experiment. The meeting of CAFA was held as a Special Interest Group (SIG) meeting at the Intelligent Systems in Molecular Biology (ISMB) conference in 2011. Here, we perform a detailed analysis of two sequence-based function prediction methods, PFP and ESG, which were developed in our lab, using the predictions submitted to CAFA. Results We evaluate PFP and ESG using four different measures in comparison with BLAST, Prior, and GOtcha. In addition to the predictions submitted to CAFA, we further investigate performance of a different scoring function to rank order predictions by PFP as well as PFP/ESG predictions enriched with Priors that simply adds frequently occurring Gene Ontology terms as a part of predictions. Prediction accuracies of each method were also evaluated separately for different functional categories. Successful and unsuccessful predictions by PFP and ESG are also discussed in comparison with BLAST. Conclusion The in-depth analysis discussed here will complement the overall assessment by the CAFA organizers. Since PFP and ESG are based on sequence database search results, our analyses are not only useful for PFP and ESG users but will also shed light on the relationship of the sequence similarity space and functions that can be inferred from the sequences

Emergence of Members of TRAF and DUB of Ubiquitin Proteasome System in the Regulation of Hypertrophic Cardiomyopathy

The ubiquitin proteasome system (UPS) plays an imperative role in many critical cellular processes, frequently by mediating the selective degradation of misfolded and damaged proteins and also by playing a non-degradative role especially important as in many signaling pathways. Over the last three decades, accumulated evidence indicated that UPS proteins are primal modulators of cell cycle progression, DNA replication, and repair, transcription, immune responses, and apoptosis. Comparatively, latest studies have demonstrated a substantial complexity by the UPS regulation in the heart. In addition, various UPS proteins especially ubiquitin ligases and proteasome have been identified to play a significant role in the cardiac development and dynamic physiology of cardiac pathologies such as ischemia/reperfusion injury, hypertrophy, and heart failure. However, our understanding of the contribution of UPS dysfunction in the plausible development of cardiac pathophysiology and the complete list of UPS proteins regulating these afflictions is still in infancy. The recent emergence of the roles of TNF receptor-associated factor (TRAFs) and deubiquitinating enzymes (DUBs) superfamily in hypertrophic cardiomyopathy has enhanced our knowledge. In this review, we have mainly compiled the TRAF superfamily of E3 ligases and few DUBs proteins with other well-documented E3 ligases such as MDM2, MuRF-1, Atrogin-I, and TRIM 32 that are specific to myocardial hypertrophy. In this review, we also aim to highlight their expression profile following physiological and pathological stimulation leading to the onset of hypertrophic phenotype in the heart that can serve as biomarkers and the opportunity for the development of novel therapies

Hexanary blends: a strategy towards thermally stable organic photovoltaics

Non-fullerene based organic solar cells display a high initial power conversion efficiency but continue to suffer from poor thermal stability, especially in case of devices with thick active layers. Mixing of five structurally similar acceptors with similar electron affinities, and blending with a donor polymer is explored, yielding devices with a power conversion efficiency of up to 17.6%. The hexanary device performance is unaffected by thermal annealing of the bulk-heterojunction active layer for at least 23 days at 130 \ub0C in the dark and an inert atmosphere. Moreover, hexanary blends offer a high degree of thermal stability for an active layer thickness of up to 390 nm, which is advantageous for high-throughput processing of organic solar cells. Here, a generic strategy based on multi-component acceptor mixtures is presented that permits to considerably improve the thermal stability of non-fullerene based devices and thus paves the way for large-area organic solar cells

Current Scenario of Molecular Diagnostics in Indian Healthcare Sector

After successfully accomplishing the Human genome project and opening new avenues for genome based diagnostics and therapy in healthcare sector, development of personalized medicine and advancing molecular diagnostics has been the prime agenda of scientists all-round the globe. Molecular diagnostics has made possible the diagnosis of the previously undetected viral nucleic acids, early access of data to doctors, a deeper understanding of the disease cause, treatment dose and success of the treatment depending upon the case. It has provided an immense scope of novel and more sophisticated biotechnology and biomedical tools to be employed in the sector procreating a new interdisciplinary field. The gene based testing in all fields has flourished in leaps and bounds after the prediction of >5% in 2005. Here we discuss the current scenario, scope and limitations of the Molecular diagnostics in terms of its significance in public health care

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent. Keywords: Protein function prediction, Disease gene prioritizationpublishedVersio