Toward a more efficient handling of conformational flexibility in computer-assisted modelling of drug molecules

Impacts of noncovalent interactions involving sulfur atoms on protein stability, structure, folding, and bioactivity

This review discusses the various types of noncovalent interactions in which sulfur atoms participate and their effects on protein stability, structure, folding and bioactivity. Current approaches and recommendations for modelling these noncovalent interactions (in terms of both geometries and interaction energies) are highlighted.

QM/MM refinement and analysis of protein bound retinoic acid

Retinoic acid (RA) is a vitamin A derivative, which modifies the appearance of fine wrinkles and roughness of facial skin and treats acne and activates gene transcription by binding to heterodimers of the retinoic acid receptor (RAR) and the retinoic X receptor (RXR). There are series of protein bound RA complexes available in the protein databank (PDB), which provides a broad range of information about the different bioactive conformations of RA. To gain further insights into the observed bioactive RA conformations we applied quantum mechanic (QM)/molecular mechanic (MM) approaches to re-refine the available RA protein-ligand complexes. MP2 complete basis set (CBS) extrapolations single energy calculations are also carried out for both the experimental conformations and QM optimized geometries of RA in the gas as well as solution phase. The results demonstrate that the re-refined structures show better geometries for RA than seen in the originally deposited PDB structures through the use of QMs for the ligand in the X-ray refinement procedure. QM/MM re-refined conformations also reduced the computed strain energies found in the deposited crystal conformations for RA. Finally, the dependence of ligand strain on resolution is analyzed. It is shown that ligand strain is not converged in our calculations and is likely an artifact of the typical resolutions employed to study protein-ligand complexes.

Drug design for ever, from hype to hope

In its first 25 years JCAMD has been disseminating a large number of techniques aimed at finding better medicines faster. These include genetic algorithms, COMFA, QSAR, structure based techniques, homology modelling, high throughput screening, combichem, and dozens more that were a hype in their time and that now are just a useful addition to the drug-designers toolbox. Despite massive efforts throughout academic and industrial drug design research departments, the number of FDA-approved new molecular entities per year stagnates, and the pharmaceutical industry is reorganising accordingly. The recent spate of industrial consolidations and the concomitant move towards outsourcing of research activities requires better integration of all activities along the chain from bench to bedside. The next 25 years will undoubtedly show a series of translational science activities that are aimed at a better communication between all parties involved, from quantum chemistry to bedside and from academia to industry. This will above all include understanding the underlying biological problem and optimal use of all available data.

The binding conformation of Taxol in beta-tubulin: a model based on electron crystallographic density

The chemotherapeutic drug Taxol is known to interact within a specific site on beta-tubulin. Although the general location of the site has been defined by photoaffinity labeling and electron crystallography, the original data were insufficient to make an absolute determination of the bound conformation. We have now correlated the crystallographic density with analysis of Taxol conformations and have found the unique solution to be a T-shaped Taxol structure. This T-shaped or butterfly structure is optimized within the beta-tubulin site and exhibits functional similarity to a portion of the B9-B10 loop in the alpha-tubulin subunit. The model provides structural rationalization for a sizeable body of Taxol structure-activity relationship data, including binding affinity, photoaffinity labeling, and acquired mutation in human cancer cells.