Modelling three-dimensional protein structures for applications in drug design

Abstract

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 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.

Beware of docking!

“…There are several docking programs for a user to choose from based on his or her particular requirements. At present, docking algorithms emphasize different aspects of structure-based drug design (SBDD), such as fragment-based drug design [11][12][13], flexible docking [14], docking in water, solvation, and specific pH [15,16]. For example, if we need to screen more than 10 000 compounds from a database, then flexible docking maybe not a good choice unless we have a very powerful and high-speed computer.…”

Modeling and resistant alleles explain the selectivity of antimalarial compound 49c towards apicomplexan aspartyl proteases

“…For the three models, the template similarity was around 50%, which is considered sufficient to generate suitable homology models for structure-based studies in absence of an experimental structure (Schmidt et al, 2014). For the three models, the template similarity was around 50%, which is considered sufficient to generate suitable homology models for structure-based studies in absence of an experimental structure (Schmidt et al, 2014).…”

Expanding the horizons of G protein-coupled receptor structure-based ligand discovery and optimization using homology models

“…As a basic premise, the intended application of the model 95 should determine its desired quality 157 . As a basic premise, the intended application of the model 95 should determine its desired quality 157 .…”