title: 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 Vd) and clearance (log Cl), which together influence the half-life (t1/2) of a drug. Simultaneously, models for PD in terms of inhibition constant pKi 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 pKi 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.
authors: a Department of Pharmaceutical Chemistry , C.U. Shah College of Pharmacy, S.N.D.T. Women's University , Mumbai , Maharashtra , India.|e Mumbai Educational Trust , Institute of Pharmacy , Bandra Reclamation, Bandra (W), Mumbai , India.
authors: Poonam
authors: P
authors: Advani
authors: b Department of Pharmaceutical Chemistry , Bombay College of Pharmacy , Mumbai , Maharashtra , India.
authors: Blessy
authors: B
authors: Joseph
authors: b Department of Pharmaceutical Chemistry , Bombay College of Pharmacy , Mumbai , Maharashtra , India.
authors: Premlata
authors: P
authors: Ambre
authors: b Department of Pharmaceutical Chemistry , Bombay College of Pharmacy , Mumbai , Maharashtra , India.
authors: Raghuvir
authors: R
authors: Pissurlenkar
authors: b Department of Pharmaceutical Chemistry , Bombay College of Pharmacy , Mumbai , Maharashtra , India.
authors: Vijay
authors: V
authors: Khedkar
authors: b Department of Pharmaceutical Chemistry , Bombay College of Pharmacy , Mumbai , Maharashtra , India.
authors: Krishna
authors: K
authors: Iyer
authors: c Department of Pharmaceutical Chemistry , Poona College of Pharmacy, Bharati Vidyapeeth Deemed University , Pune , India.
authors: Satish
authors: S
authors: Gabhe
authors: d Spring Bank Pharmaceuticals, Inc. , Milford , MA , USA.
authors: Radhakrishnan P
authors: RP
authors: Iyer
authors: b Department of Pharmaceutical Chemistry , Bombay College of Pharmacy , Mumbai , Maharashtra , India.
authors: Evans
authors: E
authors: Coutinho
mesh_terms: D000319:Adrenergic beta-Antagonists / Q000737:chemistry / Q000493:pharmacokinetics* / Q000633:toxicity; D003198:Computer Simulation; D015195:Drug Design; D006207:Half-Life; D006801:Humans; D056004:Molecular Dynamics Simulation; D021281:Quantitative Structure-Activity Relationship; D011943:Receptors, Adrenergic, beta / Q000378:metabolism*; D015203:Reproducibility of Results; D040681:Structural Homology, Protein
chemical_list: D000319:Adrenergic beta-Antagonists; D011943:Receptors, Adrenergic, beta
keywords: in silico; parallel progression approach; pharmacodynamics; pharmacokinetics; simultaneous optimization; β-blockers