To avoid high costs and to provide safety during exploratory stages, most manufacturers of drugs run simulations of molecular interactions. Subsequently, the outputs are used for analyzing the movements of atoms (in the context of multiple molecules that they belong to), with a goal to detect whether certain events of interest occur. Such events typically mean that certain properties of the drug under development are satisfied (or not). In this demo paper, we describe a system for detecting the formation and persistence of Hydrogen Bonds (HBs) during the evolution of a given chemical compound, based on simulation data. The rationale is that such phenomena (occurrence and duration) indicate desirable properties throughout certain interactions. Our prototype system allows the users to analyze the simulation datasets in a manner that enables: (1) detection of persistent, long-lasting HBs; (2) generation of a detailed report; (3) providing a visual representation of the persistent HBs (if they occur within the data set).

We address the problem of combining proximity and semantic criteria for detecting co-moving clusters of interest in atomic trajectories. Specifically, we are interested in the motion of atoms from different molecules that at some point form a Hydrogen Bond (HB) and that HB persists over time with additional constraints within clusters. Moreover, it is permissible that an HB within a cluster is disrupted for a brief period. To enable the detection of such phenomena, we introduce the notion of Bond-Aware Relaxed Moving Clusters (BARMC) pattern and present a Naïve algorithm for its detection.