Drug candidates short-listed on the basis of protein-specific charges
At the heart of many diseases lies an abnormal protein and modulating the protein's activity with small therapeutic molecules could prove effective. Optimal efficiency of a drug candidate often depends on its docking ability onto the target molecule. Lead optimisation tunes the properties of a potential drug to increase its binding and potency. Recent advances in linear-scaling density functional theory (DFT) software have enabled quantum mechanical simulation of biomolecules comprising thousands of atoms and even large proteins. The EU-funded PSCDD (Protein-specific charges for drug discovery) project has used linear scaling density functional theory (DFT) software to derive parameters of an entire target protein directly from a single quantum mechanical simulation. Taking the polarisation of the protein's native state into the determination of the force field procedure will improve the drug discovery process by designing the most promising compounds. The PSCDD researchers focused on inhibition of the HIV-1 reverse transcriptase protein and used two complementary software packages to investigate factors affecting protein-ligand binding. They also implemented an enhanced sampling procedure to improve efficiency, which is included in the latest software release. A library of bonding parameters consistent with those of the derived non-bonded force field has been developed. Validation of these parameters is continuing against experimentally measured p38 MAP kinase inhibitors, work that is to be published. Dissemination includes another 11 papers, presentation at 14 seminars and two conferences – American Chemical Society and the Psi-K electronic structure. Synergy between computation and experiment has been confirmed and methods developed by the project could be taken up by the pharmaceutical industry on a widespread basis.
Keywords
Drug candidates, protein-specific charges, target molecule, lead optimisation, PSCDD
