Summary: Size-exclusion chromatography (SEC) coupled to small-angle X-ray scattering (SAXS), also known as inline SEC-SAXS, is being increasingly used for the structural analysis of biological macromolecules, complexes and mixtures in solution. A single SEC-SAXS run generates thousands of individual SAXS profiles from the eluting solute and their analysis requires a correct identification of buffer and sample regions, a rather laborous task. We present CHROMIXS (as in CHROMatography Inline X-ray Scattering), a program for rapid reduction and analysis, both automatically and interactively, of SEC-SAXS data. Availability and implementation: CHROMIXS is freely available to academic users as part of the ATSAS software suite (www.embl-hamburg.de/biosaxs/download.html). Contact: [email protected] or [email protected].

MOTIVATION: Small angle X-ray scattering (SAXS) is an established method for studying biological macromolecules in solution, whereby the experimental scattering patterns relate to the quaternary and tertiary structure of the macromolecule. Here we present DARA, a web-server, that queries over 150 000 scattering profiles pre-computed from the high resolution models of macromolecules and biological assemblies in the Protein Data Bank, to rapidly find nearest neighbours of a given experimental or theoretical SAXS pattern. Identification of the best scattering equivalents provides a straightforward and automated way of structural assessment of macromolecules based on a SAXS profile. DARA results are useful e.g. for fold recognition and finding of biologically active oligomers. AVAILABILITY AND IMPLEMENTATION: http://dara.embl-hamburg.de/.

UNLABELLED: Complex formation and conformational transitions of biological macromolecules in solution can be effectively studied using the information about overall shape and size provided by small angle X-ray scattering (SAXS). Hybrid modeling is often applied to integrate high-resolution models into SAXS data analysis. To facilitate this task, we present SASpy, a PyMOL plugin that provides an easy-to-use graphical interface for SAXS-based hybrid modeling. Through a few mouse clicks in SASpy, low-resolution models can be superimposed to high-resolution structures, theoretical scattering profiles and fits can be calculated and displayed on-the-fly. Mouse-based manual rearrangements of complexes are conveniently applied to rapidly check and interactively refine tentative models. Interfaces to automated rigid-body and flexible refinement of macromolecular models against the experimental SAXS data are provided. AVAILABILITY AND IMPLEMENTATION: SASpy is available as open source at: github.com/emblsaxs/saspy/. Working installations of both PyMOL (www.pymol.org) and ATSAS (www.embl-hamburg.de/biosaxs/download.html) are required. CONTACT: [email protected] or [email protected].

Abstract Summary: The regulation of protein activity is a key aspect of life at the molecular level. Unveiling its details is thus crucial to understanding signalling and metabolic pathways. The most common and powerful mechanism of protein-function regulation is allostery, which has been increasingly calling the attention of medicinal chemists due to its potential for the discovery of novel therapeutics. In this context, PARS is a simple and fast method that queries protein dynamics and structural conservation to identify pockets on a protein structure that may exert a regulatory effect on the binding of a small-molecule ligand. Availability: PARS is freely available as a web server at http://bioinf.uab.cat/pars. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

BACKGROUND: Allostery is one of the most powerful and common ways of regulation of protein activity. However, for most allosteric proteins identified to date the mechanistic details of allosteric modulation are not yet well understood. Uncovering common mechanistic patterns underlying allostery would allow not only a better academic understanding of the phenomena, but it would also streamline the design of novel therapeutic solutions. This relatively unexplored therapeutic potential and the putative advantages of allosteric drugs over classical active-site inhibitors fuel the attention allosteric-drug research is receiving at present. A first step to harness the regulatory potential and versatility of allosteric sites, in the context of drug-discovery and design, would be to detect or predict their presence and location. In this article, we describe a simple computational approach, based on the effect allosteric ligands exert on protein flexibility upon binding, to predict the existence and position of allosteric sites on a given protein structure. RESULTS: By querying the literature and a recently available database of allosteric sites, we gathered 213 allosteric proteins with structural information that we further filtered into a non-redundant set of 91 proteins. We performed normal-mode analysis and observed significant changes in protein flexibility upon allosteric-ligand binding in 70% of the cases. These results agree with the current view that allosteric mechanisms are in many cases governed by changes in protein dynamics caused by ligand binding. Furthermore, we implemented an approach that achieves 65% positive predictive value in identifying allosteric sites within the set of predicted cavities of a protein (stricter parameters set, 0.22 sensitivity), by combining the current analysis on dynamics with previous results on structural conservation of allosteric sites. We also analyzed four biological examples in detail, revealing that this simple coarse-grained methodology is able to capture the effects triggered by allosteric ligands already described in the literature. CONCLUSIONS: We introduce a simple computational approach to predict the presence and position of allosteric sites in a protein based on the analysis of changes in protein normal modes upon the binding of a coarse-grained ligand at predicted cavities. Its performance has been demonstrated using a newly curated non-redundant set of 91 proteins with reported allosteric properties. The software developed in this work is available upon request from the authors.

Abstract Motivation: The overall performance of several molecular biology techniques involving DNA/DNA hybridization depends on the accurate prediction of the experimental value of a critical parameter: the melting temperature Tm. Till date, many computer software programs based on different methods and/or parameterizations are available for the theoretical estimation of the experimental Tm value of any given short oligonucleotide sequence. However, in most cases, large and significant differences in the estimations of Tm were obtained while using different methods. Thus, it is difficult to decide which Tm value is the accurate one. In addition, it seems that most people who use these methods are unaware about the limitations, which are well described in the literature but not stated properly or restricted the inputs of most of the web servers and standalone software programs that implement them. Results: A quantitative comparison on the similarities and differences among some of the published DNA/DNA Tm calculation methods is reported. The comparison was carried out for a large set of short oligonucleotide sequences ranging from 16 to 30 nt long, which span the whole range of CG-content. The results showed that significant differences were observed in all the methods, which in some cases depend on the oligonucleotide length and CG-content in a non-trivial manner. Based on these results, the regions of consensus and disagreement for the methods in the oligonucleotide feature space were reported. Owing to the lack of sufficient experimental data, a fair and complete assessment of accuracy for the different methods is not yet possible. Inspite of this limitation, a consensus Tm with minimal error probability was calculated by averaging the values obtained from two or more methods that exhibit similar behavior to each particular combination of oligonucleotide length and CG-content class. Using a total of 348 DNA sequences in the size range between 16mer and 30mer, for which the experimental Tm data are available, we demonstrated that the consensus Tm is a robust and accurate measure. It is expected that the results of this work would be constituted as a useful set of guidelines to be followed for the successful experimental implementation of various molecular biology techniques, such as quantitative PCR, multiplex PCR and the design of optimal DNA microarrays. Availability: A binary software distribution to calculate the consensus Tm described in this work for thousands of oligonucleotides simultaneously for the LINUX operating system is freely available upon request to the authors or from our website http://protein.bio.puc.cl/melting-temperatures.html Contact: [email protected] Supplementary information: The large set of oligonucleotides, the detailed results of the comparative and accuracy benchmarks, and hundreds of comparative graphs generated during this work are available at our website http://protein.bio.puc.cl/melting-temperatures.html