MOLECULAR DYNAMICS AND CHEMINFORMATICS METHODS TO EXPLORE THE CHEMICAL REALITY

Part I: Antifreeze Peptides Organisms living in icy environments produce antifreeze proteins to control ice growth and recrystallization. It has been proposed that these molecules pin the surface of ice crystals, thus inducing the formation of a curved surface that arrests crystal growth. Such proteins are very appealing for many potential applications in food industry, material science and cryoconservation of organs and tissues. Unfortunately, their structural complexity has seriously hampered their practical use, while efficient and accessible synthetic analogues are highly desirable. In the present work, we used molecular dynamics based techniques to model the interaction of three short antifreeze synthetic peptides with an ice surface. The employed protocols succeeded in reproducing the ice pinning action of antifreeze peptides and the consequent ice growth arrest, as well as in distinguishing between antifreeze and control peptides, for which no such effect was observed. Principal components analysis of peptides trajectories in different simulation settings permitted to highlight the main structural features associated to antifreeze activity. Modeling results are highly correlated with experimentally measured properties, and insights on ice-peptide interactions and on conformational patterns favoring antifreeze activity will prompt the design of new and improved antifreeze peptides. Part II: Molecular Similarity Molecular similarity is an important notion in chemistry, with applications in fields such as chemical databases and drug design. Molecular similarity is also important in chemical legislation, in particular in the evaluation process for orphan drugs (i.e., drugs for rare diseases). A new molecule needs to be dissimilar from any other existing drug for a given disease to be assigned the financially advantageous status of orphan drug. Currently, there are many ways to define whether two molecules are similar or dissimilar. Thus far, the European Medicines Agency has used majority voting on discretional judgments of similarity when assessing new drugs for rare diseases. Similarity in an inherently subjective concept, which depends on individual factors such as gender, age, state of mind, and previous experiences. Automated procedures that quantitatively and objectively evaluate molecular similarity are needed. Existing automated procedures are quite effective, but only take into account 2D molecular properties. We improved upon existing similarity-prediction procedures by including calculated 3D properties in the computational models. We created a new data-set of molecular similarity assessments, that includes complex and borderline similarity scenarios. We used the new data-set to test the existing procedures, and to build new and improved computational models.