In search of the protein native state with a probabilistic sampling approach

The three-dimensional structure of a protein is a key determinant of its biological function. Given the cost and time required to acquire this structure through experimental means, computational models are necessary to complement wet-lab efforts. Many computational techniques exist for navigating the high-dimensional protein conformational search space, which is explored for low-energy conformations that comprise a protein's native states. This work proposes two strategies to enhance the sampling of conformations near the native state. An enhanced fragment library with greater structural diversity is used to expand the search space in the context of fragment-based assembly. To manage the increased complexity of the search space, only a representative subset of the sampled conformations is retained to further guide the search towards the native state. Our results make the case that these two strategies greatly enhance the sampling of the conformational space near the native state. A detailed comparative analysis shows that our approach performs as well as state-of-the-art ab initio structure prediction protocols.     

In search of RNase P RNA from microbial genomes

A simple procedure has been developed to quickly retrieve and validate the DNA sequence encoding the RNA subunit of ribonuclease P (RNase P RNA) from microbial genomes. RNase P RNA sequences were identified from 94% of bacterial and archaeal complete genomes where previously no RNase P RNA was annotated. A sequence was found in camelpox virus, highly conserved in all orthopoxviruses (including smallpox virus), which could fold into a putative RNase P RNA in terms of conserved primary features and secondary structure. New structure features of RNase P RNA that enable one to distinguish bacteria from archaea and eukarya were found. This RNA is yet another RNA that can be a molecular criterion to divide the living world into three domains (bacteria, archaea, and eukarya). The catalytic center of this RNA, and its detection from some environmental whole genome shotgun sequences, is also discussed.     

In search of new mutants in cell-signaling systems of the nematodeCaenorhabditis elegans

Development of multicellular organisms is controlled mainly by cell-signaling systems. In this review I first discuss methods of genetic analysis and properties of mutants of cell-signaling systems in general and in the nematodeC. elegans. Then, I describe two of our approaches to isolating new mutants in cell-signaling ofC. elegans. The first approach is to select for mutants that have the same visible phenotype as those in known cell-signaling genes. In a survey of larval lethal mutations we found that there are quite a few mutants in which the inner surface of the body wall is detached from the outer surface of the intestine. Some of them map in genes that are known to act in cell-signaling systems in vulval induction or sex myoblast migration, which are not essential to the growth and survival ofC. elegans. Therefore, we think many of the mutations of the above phenotype disrupt cell-signaling in an unidentified essential function, and also cell-signaling in the non-essential functions. The second approach is to isolate mutants resistant to a drug expected to disturb cell-signaling. As the drug we have chosen sodium fluoride, which depletes calcium ion, activates G-proteins and inactivates some phosphatases. The mutants are grouped into two classes (three and two genes, respectively) according to degree of fluoride-resistance and growth rate of larvae. Although there is so far no direct evidence that these mutants are related to cell-signaling, they show complex epistasis that can be explained by a model consisting of a cell-signaling pathway.     

In search of morphogenes

May we talk about morphogenes as it is actually done about oncogenes? The author reviews some recent experimental discoveries which launch embryology on a new way: rethinking mitosis, studying cell movement and adhesion, neuronal migration, the role of gap-junctions, cell-death programmation. Embryology and genetics are today converging on identic aims, particularly in the fields of the homeotic genes and of transgenic animals.     

Guiding probabilistic search of the protein conformational space with structural profiles

The roughness of the protein energy surface poses a significant challenge to search algorithms that seek to obtain a structural characterization of the native state. Recent research seeks to bias search toward near-native conformations through one-dimensional structural profiles of the protein native state. Here we investigate the effectiveness of such profiles in a structure prediction setting for proteins of various sizes and folds. We pursue two directions. We first investigate the contribution of structural profiles in comparison to or in conjunction with physics-based energy functions in providing an effective energy bias. We conduct this investigation in the context of Metropolis Monte Carlo with fragment-based assembly. Second, we explore the effectiveness of structural profiles in providing projection coordinates through which to organize the conformational space. We do so in the context of a robotics-inspired search framework proposed in our lab that employs projections of the conformational space to guide search. Our findings indicate that structural profiles are most effective in obtaining physically realistic near-native conformations when employed in conjunction with physics-based energy functions. Our findings also show that these profiles are very effective when employed instead as projection coordinates to guide probabilistic search toward undersampled regions of the conformational space.     

In search of lost introns

Many fundamental questions concerning the emergence and subsequent evolution of eukaryotic exon-intron organization are still unsettled. Genome-scale comparative studies, which can shed light on crucial aspects of eukaryotic evolution, require adequate computational tools. We describe novel computational methods for studying spliceosomal intron evolution. Our goal is to give a reliable characterization of the dynamics of intron evolution. Our algorithmic innovations address the identification of orthologous introns, and the likelihood-based analysis of intron data. We discuss a compression method for the evaluation of the likelihood function, which is noteworthy for phylogenetic likelihood problems in general. We prove that after O(n l) preprocessing time, subsequent evaluations take O(n l/log l) time almost surely in the Yule-Harding random model of n-taxon phylogenies, where l is the input sequence length. We illustrate the practicality of our methods by compiling and analyzing a data set involving 18 eukaryotes, which is more than in any other study to date. The study yields the surprising result that ancestral eukaryotes were fairly intron-rich. For example, the bilaterian ancestor is estimated to have had more than 90% as many introns as vertebrates do now. AVAILABILITY: The Java implementations of the algorithms are publicly available from the corresponding author's site http://www.iro.umontreal.ca/~csuros/introns/. Data are available on request.