Toward reduction in animal sacrifice for drugs: molecular modeling of Macaca fascicularis P450 2C20 for virtual screening of Homo sapiens P450 2C8 substrates

Identification of small molecular inhibitors for efflux protein Rv2688c of Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) is the pathogen, which causes tuberculosis. The development of multidrug-resistant and extensively drug-resistant strains in Mtb is due to an efflux mechanism of antibiotics in the bacteria. The efflux pump proteins in the bacteria are implicated in the active efflux of antibiotics. The efflux pump protein, "fluoroquinolones export ATP-binding protein Rv2688c" (FEAB), is considered as a potential therapeutic target to prevent tuberculosis. In the present work, in silico protocols are applied to identify inhibitors for the FEAB protein to arrest the efflux mechanism. Comparative modeling techniques are used to build the protein structure. The generated structure consists of 9 helices, 13 beta strands, and 3 β sheets. The active site is predicted using active site prediction server tools. The virtual screening protocols are carried out to generate small ligand inhibitor structures. The identified ligand molecules show selective binding with Ser97, Glu99, Lys149, Asp171, Glu172, and Ser175 amino acid residues of the protein. The ligand molecules are subjected to in silico prediction of pharmaco kinetic properties, and the predicted IC₅₀ (HERG) of all the molecules are less than -5.0, which is indicative of the identified ligand molecules is being potentially good FEAB inhibitors.

Improved Homology Model of the Human all-trans Retinoic Acid Metabolizing Enzyme CYP26A1

A new CYP26A1 homology model was built based on the crystal structure of cyanobacterial CYP120A1. The model quality was examined for stereochemical accuracy, folding reliability, and absolute quality using a variety of different bioinformatics tools. Furthermore, the docking capabilities of the model were assessed by docking of the natural substrate all-trans-retinoic acid (atRA), and a group of known azole- and tetralone-based CYP26A1 inhibitors. The preferred binding pose of atRA suggests the (4S)-OH-atRA metabolite production, in agreement with recently available experimental data. The distances between the ligands and the heme group iron of the enzyme are in agreement with corresponding distances obtained for substrates and azole inhibitors for other cytochrome systems. The calculated theoretical binding energies agree with recently reported experimental data and show that the model is capable of discriminating between natural substrate, strong inhibitors (R116010 and R115866), and weak inhibitors (liarozole, fluconazole, tetralone derivatives).

Modelling three-dimensional protein structures for applications in drug design

A structural perspective of drug target and anti-target proteins, and their molecular interactions with biologically active molecules, largely advances many areas of drug discovery, including target validation, hit and lead finding and lead optimisation. In the absence of experimental 3D structures, protein structure prediction often offers a suitable alternative to facilitate structure-based studies. This review outlines recent methodical advances in homology modelling, with a focus on those techniques that necessitate consideration of ligand binding. In this context, model quality estimation deserves special attention because the accuracy and reliability of different structure prediction techniques vary considerably, and the quality of a model ultimately determines its usefulness for structure-based drug discovery. Examples of G-protein-coupled receptors (GPCRs) and ADMET-related proteins were selected to illustrate recent progress and current limitations of protein structure prediction. Basic guidelines for good modelling practice are also provided.