ProDy: protein dynamics inferred from theory and experiments.

Summary: We developed a Python package, ProDy, for structure-based analysis of protein dynamics. ProDy allows for quantitative characterization of structural variations in heterogeneous datasets of structures experimentally resolved for a given biomolecular system, and for comparison of these variations with the theoretically predicted equilibrium dynamics. Datasets include structural ensembles for a given family or subfamily of proteins, their mutants and sequence homologues, in the presence/absence of their substrates, ligands or inhibitors.

Discovery of modulators of protein-protein interactions: current approaches and limitations.

Protein-protein interactions are involved in most of the essential processes that occur in living organisms from cell motility to DNA replication, which makes them interesting targets for drug discovery. However, due to the lack of deep pockets, and the large contact surfaces involved in these interactions, they are considered challenging targets and have been often times dismissed as "undruggable". Nonetheless, significant efforts in pharmaceutical and academic laboratories have been devoted to finding ways to exploit protein-protein interactions as drug targets.

ANCHOR: a web server and database for analysis of protein-protein interaction binding pockets for drug discovery.

ANCHOR is a web-based tool whose aim is to facilitate the analysis of protein-protein interfaces with regard to its suitability for small molecule drug design. To this end, ANCHOR exploits the so-called anchor residues, i.e.

A Gibbs sampling approach to detection of tree motifs.

This paper introduces a method to detect tree patterns (tree motifs) in a database of rooted unordered labeled trees. The method can be viewed as an extension of the Gibbs sampling approach to detect sequence motifs. Basically, we enumerate tree topologies and for each topology we seek within the database for tree motifs with the given topology.