In silico optimization of pharmacokinetic properties and receptor binding affinity simultaneously: a ‘parallel progression approach to drug design’ applied to β-blockers

Abstract

The present work exploits the potential of in silico approaches for minimizing attrition of leads in the later stages of drug development. We propose a theoretical approach, wherein ‘parallel’ information is generated to simultaneously optimize the pharmacokinetics (PK) and pharmacodynamics (PD) of lead candidates. β-blockers, though in use for many years, have suboptimal PKs; hence are an ideal test series for the ‘parallel progression approach’. This approach utilizes molecular modeling tools viz. hologram quantitative structure activity relationships, homology modeling, docking, predictive metabolism, and toxicity models. Validated models have been developed for PK parameters such as volume of distribution (log V_d) and clearance (log Cl), which together influence the half-life (t_1/2) of a drug. Simultaneously, models for PD in terms of inhibition constant pK_i have been developed. Thus, PK and PD properties of β-blockers were concurrently analyzed and after iterative cycling, modifications were proposed that lead to compounds with optimized PK and PD. We report some of the resultant re-engineered β-blockers with improved half-lives and pK_i values comparable with marketed β-blockers. These were further analyzed by the docking studies to evaluate their binding poses. Finally, metabolic and toxicological assessment of these molecules was done through in silico methods. The strategy proposed herein has potential universal applicability, and can be used in any drug discovery scenario; provided that the data used is consistent in terms of experimental conditions, endpoints, and methods employed. Thus the ‘parallel progression approach’ helps to simultaneously fine-tune various properties of the drug and would be an invaluable tool during the drug development process.

Keywords:

• parallel progression approach
• simultaneous optimization
• in silico
• pharmacokinetics
• pharmacodynamics
• β-blockers

Disclosure statement

In accordance with Taylor & Francis policy, the authors declare that there is no conflict of interest regarding the research presented.

Additional information

Funding

This work was supported by Council of Scientific and Industrial Research (CSIR) grant number [Award-id: Scheme No.: 01/(2399)/10/EMR-II].