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Huang, Fenglei; Browne, Clinton E.; Wu, Whei Mei; Juhász, Attila; F, Ji; Bodor, Nicholas

doi:10.1023/a:1026160023030

Cited by 16 publications

(3 citation statements)

References 32 publications

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“…Another isomerism also seems to have some effect on activity: among N-substituted atropine analogues, such as PcPATR_NA·Me 46 or PcHCTR_NA·Et, exo isomers, which have the bridged ester substituent closer to the shorter, unsubstituted ring (and, hence, in equatorial position; Figure ), seem slightly more active than the corresponding endo isomers, at least in receptor-binding studies. This is somewhat contrary to a previous observation that found better activity when the larger substituent was in the endo (axial) position .…”

Section: Resultsmentioning

confidence: 99%

“…Data Collection and Molecular Modeling. In vitro activity data (guinea pig ileum assay p A 2 and M 3 receptor binding p K i ) were collected from our previous publications; − , corresponding references are indicated for each compound in Table 1 of Supporting Information. In an attempt at systematization, a set of more-or-less descriptive names has also been assigned using this framework to all these quaternary soft anticholinergics; representative ones are as follows:…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, they include structures designed using either the soft analogue approach (soft quaternary anticholinergics, soft propantheline analogues) or the inactive metabolite-based approach (phenylmalonic analogues, − phenylsuccinic analogues, , phenylcyclopentyl atropine and glycopyrrolate analogues ,, ). More recently, within the inactive metabolite-based class a set of different structures ( 8 ) with the hydrolytically labile ester moiety attached to the quaternary nitrogen head of the atropine- or glycopyrrolate-type ring structure have been synthesized and tested. −

2 Representative structures for soft quaternary anticholinergics designed based on the inactive metabolite and the soft analogue approaches. …”

Section: Introductionmentioning

confidence: 99%

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Soft Quaternary Anticholinergics: Comprehensive Quantitative Structure−Activity Relationship (QSAR) with a Linearized Biexponential (LinBiExp) Model

Buchwald

Bodor

2006

J. Med. Chem.

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A comprehensive quantitative structure-activity relationship (QSAR) study is presented for quaternary soft anticholinergics including two distinctly different classes designed on the basis of the soft analogue and the inactive metabolite approaches. Because of the clear biphasic (bilinear) nature of the activity data when all structures (n = 76) were considered as a function of molecular size (volume), a nonlinear model had to be used, and a linearized biexponential (LinBiExp) model proved very adequate. LinBiExp can fit activity data that show a maximum (or a minimum) around a given parameter value but tend to show linearity away from this turning point. Contrary to Hansch-type parabolic models, LinBiExp represents a natural extension of linear models, and a direct correspondence between its parameters and those obtained earlier by linear regression on compound subsets covering more limited parameter ranges could be easily established. Stereospecificity was confirmed as important, and the presence of an acid moiety was found to essentially eliminate activity. The consideration of bilinear behavior, which most likely results from size limitations at the binding site, can also explain the embarrassingly low activity found for a relatively large compound predicted as highly active by Lien, Ariëns, and co-workers based on their QSAR study.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

2 Representative structures for soft quaternary anticholinergics designed based on the inactive metabolite and the soft analogue approaches. …”

Section: Introductionmentioning

confidence: 99%

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Soft Quaternary Anticholinergics: Comprehensive Quantitative Structure−Activity Relationship (QSAR) with a Linearized Biexponential (LinBiExp) Model

Buchwald

Bodor

2006

J. Med. Chem.

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Retrometabolism‐Based Drug Design and Targeting

Bodor

Buchwald

2010

Burger's Medicinal Chemistry and Drug Discovery

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Retrometabolic drug design (RMDD) approaches are systematic methodologies aimed to design safe compounds with an improved therapeutic index. RMDDs thoroughly integrate structure– activity and structure‐metabolism considerations into the entire design process and incorporate two major concepts aimed to design soft drugs and chemical delivery systems, respectively. Soft drugs (SDs) are new, active therapeutic agents designed to undergo predictable metabolism resulting in inactive metabolites after exerting their desired therapeutic effect(s). Chemical delivery systems (CDSs) are biologically inert molecules that provide enhanced and targeted delivery of an active drug to a particular organ or site through a designed sequential metabolism that involves several steps. Here, we present a comprehensive review including a general overview of the RMDD principles and a large number of specific examples from various pharmacological areas, including many recent developments, to illustrate RMDD concepts. Whenever possible, the rationale for the design as well as the pharmacokinetic and pharmacodynamic properties of the new therapeutic agents are briefly summarized and compared to those of the other compounds used in the same field.

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Structural Modifications of Drug Candidates: How Useful Are They in Improving PK Parameters of New Drugs? Part II: Drug Design Strategies

Nassar

2008

Drug Metabolism Handbook

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Abstract: A new class of anticholinergics was designed and synthesized, and the PK/PD evaluation confirmed they were potent "soft" anticholinergics; two of them showed muscarinic receptor subtype selectivity (M3/M2).

Cited by 16 publications

References 32 publications

Soft Quaternary Anticholinergics: Comprehensive Quantitative Structure−Activity Relationship (QSAR) with a Linearized Biexponential (LinBiExp) Model

Soft Quaternary Anticholinergics: Comprehensive Quantitative Structure−Activity Relationship (QSAR) with a Linearized Biexponential (LinBiExp) Model

Retrometabolism‐Based Drug Design and Targeting

Structural Modifications of Drug Candidates: How Useful Are They in Improving PK Parameters of New Drugs? Part II: Drug Design Strategies

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