Improving protein secondary structure prediction using a simple k-mer model

Motivation: Some first order methods for protein sequence analysis inherently treat each position as independent. We develop a general framework for introducing longer range interactions. We then demonstrate the power of our approach by applying it to secondary structure prediction; under the independence assumption, sequences produced by existing methods can produce features that are not protein like, an extreme example being a helix of length 1. Our goal was to make the predictions from state of the art methods more realistic, without loss of performance by other measures

Specific "scientific" data structures, and their processing

Programming physicists use, as all programmers, arrays, lists, tuples, records, etc., and this requires some change in their thought patterns while converting their formulae into some code, since the "data structures" operated upon, while elaborating some theory and its consequences, are rather: power series and Pad\'e approximants, differential forms and other instances of differential algebras, functionals (for the variational calculus), trajectories (solutions of differential equations), Young diagrams and Feynman graphs, etc. Such data is often used in a [semi-]numerical setting, not necessarily "symbolic", appropriate for the computer algebra packages. Modules adapted to such data may be "just libraries", but often they become specific, embedded sub-languages, typically mapped into object-oriented frameworks, with overloaded mathematical operations. Here we present a functional approach to this philosophy. We show how the usage of Haskell datatypes and - fundamental for our tutorial - the application of lazy evaluation makes it possible to operate upon such data (in particular: the "infinite" sequences) in a natural and comfortable manner.Comment: In Proceedings DSL 2011, arXiv:1109.032

Structure-Based Exploration and Exploitation of the S4 Subsite of Norovirus 3CL Protease in the Design of Potent and Permeable Inhibitors

Human noroviruses are the primary cause of epidemic and sporadic acute gastroenteritis. The worldwide high morbidity and mortality associated with norovirus infections, particularly among the elderly, immunocompromised patients and children, constitute a serious public health concern. There are currently no approved human vaccines or norovirus-specific small-molecule therapeutics or prophylactics. Norovirus 3CL protease has recently emerged as a potential therapeutic target for the development of anti-norovirus agents. We hypothesized that the S4 subsite of the enzyme may provide an effective means of designing potent and cell permeable inhibitors of the enzyme. We report herein the structure-guided exploration and exploitation of the S4 subsite of norovirus 3CL protease in the design and synthesis of effective inhibitors of the protease

Medium Chain Fatty Acids Are Selective Peroxisome Proliferator Activated Receptor (PPAR) γ Activators and Pan-PPAR Partial Agonists

Thiazolidinediones (TZDs) act through peroxisome proliferator activated receptor (PPAR) γ to increase insulin sensitivity in type 2 diabetes (T2DM), but deleterious effects of these ligands mean that selective modulators with improved clinical profiles are needed. We obtained a crystal structure of PPARγ ligand binding domain (LBD) and found that the ligand binding pocket (LBP) is occupied by bacterial medium chain fatty acids (MCFAs). We verified that MCFAs (C8–C10) bind the PPARγ LBD in vitro and showed that they are low-potency partial agonists that display assay-specific actions relative to TZDs; they act as very weak partial agonists in transfections with PPARγ LBD, stronger partial agonists with full length PPARγ and exhibit full blockade of PPARγ phosphorylation by cyclin-dependent kinase 5 (cdk5), linked to reversal of adipose tissue insulin resistance. MCFAs that bind PPARγ also antagonize TZD-dependent adipogenesis in vitro. X-ray structure B-factor analysis and molecular dynamics (MD) simulations suggest that MCFAs weakly stabilize C-terminal activation helix (H) 12 relative to TZDs and this effect is highly dependent on chain length. By contrast, MCFAs preferentially stabilize the H2-H3/β-sheet region and the helix (H) 11-H12 loop relative to TZDs and we propose that MCFA assay-specific actions are linked to their unique binding mode and suggest that it may be possible to identify selective PPARγ modulators with useful clinical profiles among natural products

Formal Model of MOS Clocking Disciples

This paper presents a formalization of clocking disciplines used to prevent race conditions in VLSI circuits. A signal-labeling scheme for the two-phase clocking discipline informally described in Mead and Conway [MC] is presented. Rules are given for checking the correct labeling of a circuit consisting of combinatorial logic and memory elements. The signal-labeling conventions are based in part on those of Noice, Mathews, and Newkirk [NMN]. A formal basis is presented for constructing signal-labeling schemes for multi-phase clocks (both overlapping and non-overlapping) from a definition of the master timing signals. The two-phase scheme is shown to be a special case of this general method. The method is also illustrated for four-phase overlapping clocks