The characterization of pc-polylines representing protein backbones.

The backbone of a protein is typically represented as either a C -polyline, a three-dimensional (3D) polyline that passes through the C atoms, or a tuple of ϕ,ψ pairs while its fold is usually assigned using the 3D topological arrangement of the secondary structure elements (SSEs). It is tricky to obtain the SSE composition for a protein from the C -polyline representation while its 3D SSE arrangement is not apparent in the two-dimensional (2D) ϕ,ψ representation. In this article, we first represent the backbone of a protein as a pc-polyline that passes through the centers of its peptide planes.

A New Secondary Structure Assignment Algorithm Using Cα Backbone Fragments.

The assignment of secondary structure elements in proteins is a key step in the analysis of their structures and functions. We have developed an algorithm, SACF (secondary structure assignment based on Cα fragments), for secondary structure element (SSE) assignment based on the alignment of Cα backbone fragments with central poses derived by clustering known SSE fragments. The assignment algorithm consists of three steps: First, the outlier fragments on known SSEs are detected.

Amino Acids in Nine Ligand-Prefer Ramachandran Regions.

Several secondary structures, such as π-helix and left-handed helix, have been frequently identified at protein ligand-binding sites. A secondary structure is considered to be constrained to a specific region of dihedral angles. However, a comprehensive analysis of the correlation between main chain dihedral angles and ligand-binding sites has not been performed.

An Accurate Model for Biomolecular Helices and Its Application to Helix Visualization.

Helices are the most abundant secondary structural elements in proteins and the structural forms assumed by double stranded DNAs (dsDNA). Though the mathematical expression for a helical curve is simple, none of the previous models for the biomolecular helices in either proteins or DNAs use a genuine helical curve, likely because of the complexity of fitting backbone atoms to helical curves. In this paper we model a helix as a series of different but all bona fide helical curves; each one best fits the coordinates of four consecutive backbone Cα atoms for a protein or P atoms for a DNA molecule.

A geometric clustering algorithm with applications to structural data.

An important feature of structural data, especially those from structural determination and protein-ligand docking programs, is that their distribution could be mostly uniform. Traditional clustering algorithms developed specifically for nonuniformly distributed data may not be adequate for their classification. Here we present a geometric partitional algorithm that could be applied to both uniformly and nonuniformly distributed data.

Highly selective aza-nitrile inhibitors for cathepsin K, structural optimization and molecular modeling.

As a new type of cathepsin K inhibitor, azadipeptide nitriles have the characteristics of proteolytic stability and excellent inhibitory activity, but they exhibit barely any satisfactory selectivity. Great efforts have focused on improving their selectivity toward cathepsin K. In this sequential study, we report the further structural optimization, synthesis, molecular modeling, and in vitro enzymatic assays of a new series of potent and selective inhibitors of cathepsin K without the P2-P3 amide linker.

A compound-based computational approach for the accurate determination of hot spots.

A plethora of both experimental and computational methods have been proposed in the past 20 years for the identification of hot spots at a protein-protein interface. The experimental determination of a protein-protein complex followed by alanine scanning mutagenesis, though able to determine hot spots with much precision, is expensive and has no guarantee of success while the accuracy of the current computational methods for hot-spot identification remains low. Here, we present a novel structure-based computational approach that accurately determines hot spots through docking into a set of proteins homologous to only one of the two interacting partners of a compound capable of disrupting the protein-protein interaction (PPI).

Highly selective azadipeptide nitrile inhibitors for cathepsin K: design, synthesis and activity assays.

We have developed a series of azadipeptide nitriles with different P3 groups. A triaryl meta-phenyl derivative, compound 13, was not only a potent inhibitor for cathepsin K (K(i) = 0.0031 nM), but also highly selective over both cathepsins B and S (~1000-fold).