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All-atom molecular dynamics simulations are performed on the unphosphorylated and phosphorylated unbound glycogen synthase kinase 3[beta] (GSK-3[beta]) and the phosphorylated GSK-3[beta] bound to a peptide substrate, its product, and a derived inhibitor. The studies have shown that binding of specific peptides at the remote binding site has led to stabilization of the activation loop located in the active site, which might enhance the catalytic activity of the kinase.

The studies which demonstrate the impact of binding two molecules of diazepam on the properties of human cytochrome P450 3A4 (CYP3A4) regulated by high-valent iron-oxo species (Cpd I) is reported.

The impact of the addition of an effector diazepam molecule on an active oxidized diazepam in the active site of CYP3A4 and on the interactions of the effector with the protein is investigated. The results indicate that the effector substrate interacts both with the active substrate and with the enzyme, which results in side chain reorientation with relatively minor long-range effects.

Virtual screening is emerging as a productive and cost-effective technology in rational drug design for the identification of novel lead compounds. An important model for virtual screening is the pharmacophore. Pharmacophore is the spatial configuration of essential features that enable a ligand molecule to interact with a specific target receptor. In the absence of a known receptor structure, a pharmacophore can be identified from a set of ligands that have been observed to interact with the target receptor. Here, we present a novel computational method for pharmacophore detection and virtual screening. The pharmacophore detection module is able to (i) align multiple flexible ligands in a deterministic manner without exhaustive enumeration of the conformational space, (ii) detect subsets of input ligands that may bind to different binding sites or have different binding modes, (iii) address cases where the input ligands have different affinities by defining weighted pharmacophores based on the number of ligands that share them, and (iv) automatically select the most appropriate pharmacophore candidates for virtual screening. The algorithm is highly efficient, allowing a fast exploration of the chemical space by virtual screening of huge compound databases. The performance of PharmaGist was successfully evaluated on a commonly used data set of G-Protein Coupled Receptor alpha1A. Additionally, a large-scale evaluation using the DUD (directory of useful decoys) data set was performed. DUD contains 2950 active ligands for 40 different receptors, with 36 decoy compounds for each active ligand. PharmaGist enrichment rates are comparable with other state-of-the-art tools for virtual screening.

We present a novel generic computational method to assess protein nanotubes with variable diameter sizes at the atomic level given their low resolution protomeric structures. The method is based on the symmetrical assembly of a repeating protein subunit into a nanotube. Given the protein unit-cell, and the tube diameter and helicity, we carry out all-atom molecular dynamics simulations, combined with a unique mathematical transformation. This allows us to mimic nanotubes of even huge sizes without end or edge effects. All our simulation setups attempt to explicitly adhere to the conditions under which the experiments were conducted. Thus, we are able to obtain high resolution atomic-scale structures at reasonable computational costs. We expect that our approach would prove useful in assessing protein nanotubes, as well as in silico constructions of novel nanobiomaterials.

The unique properties of fullerenes have raised the interest of using them for biomedical applications. Within this framework, the interactions of fullerenes with proteins have been an exciting research target, yet little is known about how native proteins can bind fullerenes, and what is the nature of these interactions. Moreover, though some proteins have been shown to interact with fullerenes, up to date, no crystal structure of such complexes was obtained. Here we report docking studies aimed at examining the interactions of fullerene in two forms (C60 nonsubstituted fullerene and carboxyfullerene) with four proteins that are known to bind fullerene derivatives: HIV protease, fullerene-specific antibody, human serum albumin, and bovine serum albumin. Our work provides docking models with detailed binding pockets information, which closely match available experimental data. We further compare the predicted binding sites using a novel multiple binding site alignment method. A high similarity between the physicochemical properties and surface geometry was found for fullerene's binding sites of HIV protease and the human and bovine serum albumins.