SIMS: A Hybrid Method for Rapid Conformational Analysis

Proteins are at the root of many biological functions, often performing complex tasks as the result of large changes in their structure. Describing the exact details of these conformational changes, however, remains a central challenge for computational biology due the enormous computational requirements of the problem. This has engendered the development of a rich variety of useful methods designed to answer specific questions at different levels of spatial, temporal, and energetic resolution. These methods fall largely into two classes: physically accurate, but computationally demanding methods and fast, approximate methods. We introduce here a new hybrid modeling tool, the Structured Intuitive Move Selector (SIMS), designed to bridge the divide between these two classes, while allowing the benefits of both to be seamlessly integrated into a single framework. This is achieved by applying a modern motion planning algorithm, borrowed from the field of robotics, in tandem with a well-established protein modeling library. SIMS can combine precise energy calculations with approximate or specialized conformational sampling routines to produce rapid, yet accurate, analysis of the large-scale conformational variability of protein systems. Several key advancements are shown, including the abstract use of generically defined moves (conformational sampling methods) and an expansive probabilistic conformational exploration. We present three example problems that SIMS is applied to and demonstrate a rapid solution for each. These include the automatic determination of ﾑﾑactiveﾒﾒ residues for the hinge-based system Cyanovirin-N, exploring conformational changes involving long-range coordinated motion between non-sequential residues in Ribose- Binding Protein, and the rapid discovery of a transient conformational state of Maltose-Binding Protein, previously only determined by Molecular Dynamics. For all cases we provide energetic validations using well-established energy fields, demonstrating this framework as a fast and accurate tool for the analysis of a wide range of protein flexibility problems

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Omics-based molecular techniques in oral pathology centred cancer: Prospect and challenges in Africa

: The completion of the human genome project and the accomplished milestones in the human proteome project; as well as the progress made so far in computational bioinformatics and “big data” processing have contributed immensely to individualized/personalized medicine in the developed world.At the dawn of precision medicine, various omics-based therapies and bioengineering can now be applied accurately for the diagnosis, prognosis, treatment, and risk stratifcation of cancer in a manner that was hitherto not thought possible. The widespread introduction of genomics and other omics-based approaches into the postgraduate training curriculum of diverse medical and dental specialties, including pathology has improved the profciency of practitioners in the use of novel molecular signatures in patient management. In addition, intricate details about disease disparity among diferent human populations are beginning to emerge. This would facilitate the use of tailor-made novel theranostic methods based on emerging molecular evidences

Metabolomic derangements are associated with mortality in critically ill adult patients

Objective: To identify metabolomic biomarkers predictive of Intensive Care Unit (ICU) mortality in adults. Rationale: Comprehensive metabolomic profiling of plasma at ICU admission to identify biomarkers associated with mortality has recently become feasi

Exome sequencing of extreme phenotypes identifies DCTN4 as a modifier of chronic pseudomonas aeruginosa infection in cystic fibrosis

Exome sequencing has become a powerful and effective strategy for the discovery of genes underlying Mendelian disorders. However, use of exome sequencing to identify variants associated with complex traits has been more challenging, partly because the sample sizes needed for adequate power may be very large. One strategy to increase efficiency is to sequence individuals who are at both ends of a phenotype distribution (those with extreme phenotypes). Because the frequency of alleles that contribute to the trait are enriched in one or both phenotype extremes, a modest sample size can potentially be used to identify novel candidate genes and/or alleles. As part of the National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project (ESP), we used an extreme phenotype study design to discover that variants in DCTN4, encoding a dynactin protein, are associated with time to first P. aeruginosa airway infection, chronic P. aeruginosa infection and mucoid P. aeruginosa in individuals with cystic fibrosis