Moving beyond Rules: The Development of a Central Nervous System Multiparameter Optimization (CNS MPO) Approach To Enable Alignment of Druglike Properties

Abstract

The interplay among commonly used physicochemical properties in drug design was examined and utilized to create a prospective design tool focused on the alignment of key druglike attributes. Using a set of six physicochemical parameters ((a) lipophilicity, calculated partition coefficient (ClogP); (b) calculated distribution coefficient at pH=7.4 (ClogD); (c) molecular weight (MW); (d) topological polar surface area (TPSA); (e) number of hydrogen bond donors (HBD); (f) most basic center (pK a )), a druglikeness central nervous system multiparameter optimization (CNS MPO) algorithm was built and applied to a set of marketed CNS drugs (N=119) and Pfizer CNS candidates (N = 108), as well as to a large diversity set of Pfizer proprietary compounds (N = 11 303). The novel CNS MPO algorithm showed that 74% of marketed CNS drugs displayed a high CNS MPO score (MPO desirability score g 4, using a scale of 0-6), in comparison to 60% of the Pfizer CNS candidates. This analysis suggests that this algorithm could potentially be used to identify compounds with a higher probability of successfully testing hypotheses in the clinic. In addition, a relationship between an increasing CNS MPO score and alignment of key in vitro attributes of drug discovery (favorable permeability, P-glycoprotein (P-gp) efflux, metabolic stability, and safety) was seen in the marketed CNS drug set, the Pfizer candidate set, and the Pfizer proprietary diversity set. The CNS MPO scoring function offers advantages over hard cutoffs or utilization of single parameters to optimize structureactivity relationships (SAR) by expanding medicinal chemistry design space through a holistic assessment approach. Based on six physicochemical properties commonly used by medicinal chemists, the CNS MPO function may be used prospectively at the design stage to accelerate the identification of compounds with increased probability of success.

P2X receptor antagonists for pain management: examination of binding and physicochemical properties

“…Celecoxib and duloxetine are the two drugs just under the desirable CNS MPO score of >4. Although this is a relatively small sample size, this MPO analysis is fairly consistent with the observed data from the original publication where 26% of CNS drugs have MPO scores of <4 [24]. This analysis can be readily applied to the evaluation of novel ligands with the expectation that [37] compounds falling within the yellow box will generally have more drug-like characteristics compared to compounds falling outside of the yellow box.…”

“…This score is expressed as a single number ranging from 0 to 6. The reader is referred to this review and the references therein for full details [24]. In this study, the authors found that 74% of currently marketed CNS drugs have an MPO score greater than 4, which defines the desirable drug-like space.…”

“…These parameters have been used to assess the relative probability of success of clinical lead optimization research for specific drug-like compounds that have demonstrated proof of concept in subsequent clinical testing [15][16][17][18][19][20][21][22][23]. Recently, Wager et al [24] analyzed currently marketed drugs for a variety of central nervous system (CNS) disorders and developed a multi-parameter optimization (MPO) score, which is calculated from six in silico physicochemical properties (ClogP, ClogD, TPSA, MW, HBD, and pK a ). This score is expressed as a single number ranging from 0 to 6.…”

The Block Relevance (BR) analysis supports the dominating effect of solutes hydrogen bond acidity on ΔlogPoct–tol

“…For instance, the counts of hydrogen bond donor and acceptor groups are part of the Ro5 parameters (Lipinski et al, 1997) used to predict druglike properties and permeability; moreover, HBD count is a parameter in the CNS Multi-Parameter Optimization score (Wager et al, 2010).…”

Classics in Chemical Neuroscience: Diazepam (Valium)

“…While it is now accepted that these properties are consistent with good CNS penetration and drug metabolism properties, diazepam and its numerous relatives can be credited with significantly influencing these criteria in a number of comparative databases used to define the guidelines. 7 First synthesized by Leo Sternbach at Hoffman-La Roche in the late 1950s (Scheme 1), the aryl 1,4-benzodiazepine's syntheses came from the observation that quinazoline-3-oxides such as 7 8 produced ring-expanded products on treatment with hydroxide, ammonia or primary amines via initial attack at the 2-position of the quinoxaline ring (rather than simple displacement of the chloride). 9 The first clinically approved benzodiazepine, chlordiazepoxide (Librium 2), was prepared by reaction of methylamine with compound 7.…”