Vibrational Spectroscopy of Homo- and Heterochiral Amino Acid Dimers: Conformational Landscapes

The homo- and heterochiral protonated dimers of asparagine with serine and with valine were investigated using infrared multiple-photon dissociation (IRMPD) spectroscopy. Extensive quantum-chemical calculations were used in a three-tiered strategy to screen the conformational spaces of all four dimer species. The resulting binary structures were further grouped into five different types based on their intermolecular binding topologies and subunit configurations. For each dimer species, there are eight to fourteen final conformational geometries within a 10 kJ mol−1 window of the global minimum structure for each species. The comparison between the experimental IRMPD spectra and the simulated harmonic IR features allowed us to clearly identify the types of structures responsible for the observation. The monomeric subunits of the observed homo- and heterochiral dimers are compared to the corresponding protonated/neutral amino acid monomers observed experimentally in previous IRMDP/rotational spectroscopic studies. Possible chirality and kinetic influences on the experimental IRMPD spectra are discussed.

Characterizing Protein Conformational Spaces using Dimensionality Reduction and Algebraic Topology

Datasets representing the conformational landscapes of protein structures are high dimensional and hence present computational challenges. Efficient and effective dimensionality reduction of these datasets is therefore paramount to our ability to analyze the conformational landscapes of proteins and extract important information regarding protein folding, conformational changes and binding. Representing the structures with fewer attributes that capture the most variance of the data, makes for quicker and precise analysis of these structures. In this work we make use of dimensionality reduction methods for reducing the number of instances and for feature reduction. The reduced dataset that is obtained is then subjected to topological and quantitative analysis. In this step we perform hierarchical clustering to obtain different sets of conformation clusters that may correspond to intermediate structures. The structures represented by these conformations are then analyzed by studying their high dimension topological properties to identify truly distinct conformations and holes in the conformational space that may represent high energy barriers. Our results show that the clusters closely follow known experimental results about intermediate structures, as well as binding and folding events.

DOCKING STUDIES OF CURCUMIN AS A POTENTIAL LEAD COMPOUND TO DEVELOP NOVEL DIPEPTYDYL PEPTIDASE-4 INHIBITORS

Interaction of curcumin to dipeptydyl peptidase-4 (DPP-4) has been studied by employing docking method using Molecular Operating Environment (MOE) and AutoDock as the docking software applications. Although MOE can sample more conformational spaces that represent the original interaction poses than AutoDock, both softwares serve as valid and acceptable docking applications to study the interactions of small compound to DPP-4. The calculated free energy of binding (DGbinding) results from MOE and AutoDock shows that curcumin is needed to be optimized to reach similar or better DGbinding compare to the reference compound. Curcumin can be considered as a good lead compound in the development of new DPP-4 inhibitor. The results of these studies can serve as an initial effort of the further study. Keywords: curcumin, docking, molecular operating environment (MOE), AutoDock, dipeptydyl peptidase-4 (DPP-4)