As the sequence identity between a pair of proteins decreases, alignment strategies that are based on sequence and/or sequence profiles become progressively less effective in identifying the correct structural correspondence between residue pairs. This significantly reduces the ability of comparative modeling-based approaches to build accurate structural models. Incorporating predicted informat...

Reduced computer modeling of proteins now has a history of about 30 years. In spite of the enormous increase in computing abilities, reduced models are still very important tools for theoretical studies of protein structure, dynamics and thermodynamics. Very simple, highly idealized lattice (and recently also off-lattice) models could be studied in great detail, providing valuable insight into ...

Protein data has an explosive increasing rate both in volume and diversity, yet many of its structures remain unresolved, as well their functions remain to be identified. The conventional sequence alignment tools are insufficient in remote homology detection, while the current structural alignment tools would encounter the difficulties for proteins of unresolved structure. Here, we aimed to ove...

Structural pattern recognition describes and classifies data based on the relationships of features and parts. Topological invariants, like the Euler number, characterize the structure of objects of any dimension. Cohomology can provide more refined algebraic invariants to a topological space than does homology. It assigns ‘quantities’ to the chains used in homology to characterize holes of any...

BDNF (Brain derived neurotrophic factor) is a secretion protein and a member of the neurotrophin family of growth factors. Structural and functional characterization of BDNF Varanus komodoensis is of interest while its structure remains unknown. Thus, a homology molecular model of BDNF was constructed for gleaning possible structural insights. The model was compared with the structure of the ho...