Towards the online computer-aided design of catalytic pockets.

The engineering of catalysts with desirable properties can be accelerated by computer-aided design. To achieve this aim, features of molecular catalysts can be condensed into numerical descriptors that can then be used to correlate reactivity and structure. Based on such descriptors, we have introduced topographic steric maps that provide a three-dimensional image of the catalytic pocket-the region of the catalyst where the substrate binds and reacts-enabling it to be visualized and also reshaped by changing various parameters. These topographic steric maps, especially when used in conjunction with density functional theory calculations, enable catalyst structural modifications to be explored quickly, making the online design of new catalysts accessible to the wide chemical community. In this Perspective, we discuss the application of topographic steric maps either to rationalize the behaviour of known catalysts-from synthetic molecular species to metalloenzymes-or to design improved catalysts.

Social support for collaboration and group awareness in life science research teams.

BACKGROUND: Next-generation sequencing (NGS) technologies have revolutionarily reshaped the landscape of '-omics' research areas. They produce a plethora of information requiring specific knowledge in sample preparation, analysis and characterization. Additionally, expertise and competencies are required when using bioinformatics tools and methods for efficient analysis, interpretation, and visualization of data. These skills are rarely covered in a single laboratory. More often the samples are isolated and purified in a first laboratory, sequencing is performed by a private company or a specialized lab, while the produced data are analyzed by a third group of researchers. In this scenario, the support, the communication, and the information sharing among researchers represent the key points to build a common knowledge and to meet the project objectives. RESULTS: We present ElGalaxy, a system designed and developed to support collaboration and information sharing among researchers. Specifically, we integrated collaborative functionalities within an application usually adopted by Life Science researchers. ElGalaxy, therefore, is the result of the integration of Galaxy, i.e., a Workflow Management System, with Elgg, i.e., a Social Network Engine. CONCLUSIONS: ElGalaxy enables scientists, that work on the same experiment, to collaborate and share information, to discuss about methods, and to evaluate results of the individual steps, as well as of entire activities, performed during their experiments. ElGalaxy also allows a greater team awareness, especially when experiments are carried out with researchers which belong to different and distributed research centers.

Introducing a Clustering Step in a Consensus Approach for the Scoring of Protein-Protein Docking Models.

Correctly scoring protein-protein docking models to single out native-like ones is an open challenge. It is also an object of assessment in CAPRI (Critical Assessment of PRedicted Interactions), the community-wide blind docking experiment. We introduced in the field the first pure consensus method, CONSRANK, which ranks models based on their ability to match the most conserved contacts in the ensemble they belong to. In CAPRI, scorers are asked to evaluate a set of available models and select the top ten ones, based on their own scoring approach. Scorers' performance is ranked based on the number of targets/interfaces for which they could provide at least one correct solution. In such terms, blind testing in CAPRI Round 30 (a joint prediction round with CASP11) has shown that critical cases for CONSRANK are represented by targets showing multiple interfaces or for which only a very small number of correct solutions are available. To address these challenging cases, CONSRANK has now been modified to include a contact-based clustering of the models as a preliminary step of the scoring process. We used an agglomerative hierarchical clustering based on the number of common inter-residue contacts within the models. Two criteria, with different thresholds, were explored in the cluster generation, setting either the number of common contacts or of total clusters. For each clustering approach, after selecting the top (most populated) ten clusters, CONSRANK was run on these clusters and the top-ranked model for each cluster was selected, in the limit of 10 models per target. We have applied our modified scoring approach, Clust-CONSRANK, to SCORE_SET, a set of CAPRI scoring models made recently available by CAPRI assessors, and to the subset of homodimeric targets in CAPRI Round 30 for which CONSRANK failed to include a correct solution within the ten selected models. Results show that, for the challenging cases, the clustering step typically enriches the ten top ranked models in native-like solutions. The best performing clustering approaches we tested indeed lead to more than double the number of cases for which at least one correct solution can be included within the top ten ranked models.

CONSRANK: a server for the analysis, comparison and ranking of docking models based on inter-residue contacts.

SUMMARY: Herein, we present CONSRANK, a web tool for analyzing, comparing and ranking protein-protein and protein-nucleic acid docking models, based on the conservation of inter-residue contacts and its visualization in 2D and 3D interactive contact maps. AVAILABILITY AND IMPLEMENTATION: CONSRANK is accessible as a public web tool at https://www.molnac.unisa.it/BioTools/consrank/. CONTACT: romina.oliva@uniparthenope.it.

COCOMAPS: a web application to analyze and visualize contacts at the interface of biomolecular complexes.

SUMMARY: Herein we present COCOMAPS, a novel tool for analyzing, visualizing and comparing the interface in protein-protein and protein-nucleic acids complexes. COCOMAPS combines traditional analyses and 3D visualization of the interface with the effectiveness of intermolecular contact maps. AVAILABILITY: COCOMAPS is accessible as a public web tool at http://www.molnac.unisa.it/BioTools/cocomaps CONTACT: romina.oliva@uniparthenope.it; lcavallo@unisa.it.