Literature DB >> 24168238

A novel method for high throughput lipophilicity determination by microscale shake flask and liquid chromatography tandem mass spectrometry.

Baiwei Lin1, Joseph H Pease.   

Abstract

Modern small molecule drug design requires the optimization of not only the binding characteristics of the molecule but also its physicochemical properties for ADMET performance. A key physical property is lipophilicity and medicinal chemists need rapid access to high quality data in order to drive their decision making. Traditionally lipophilicity (log D) measurements are performed with a shake flask method and UV determination. This method suffers from low sensitivity and is not easily converted to a high throughput format. Over the past decade, several groups have taken different approaches to improve this assay, including replacing the shake flask method with one that utilizes reverse phase HPLC. Here we describe a new microscale shake flask method that utilizes UPLC-MS/MS to achieve increased throughput, sensitivity and accuracy. Approaches for assessing data quality are also described. This platform technology only requires micrograms of compound and is routinely used by most small molecule drug discovery project teams at Genentech.

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Year:  2013        PMID: 24168238     DOI: 10.2174/1386207311301010007

Source DB:  PubMed          Journal:  Comb Chem High Throughput Screen        ISSN: 1386-2073            Impact factor:   1.339


  12 in total

1.  The influence of hydrogen bonding on partition coefficients.

Authors:  Nádia Melo Borges; Peter W Kenny; Carlos A Montanari; Igor M Prokopczyk; Jean F R Ribeiro; Josmar R Rocha; Geraldo Rodrigues Sartori
Journal:  J Comput Aided Mol Des       Date:  2017-01-04       Impact factor: 3.686

2.  Why Decreasing Lipophilicity Alone Is Often Not a Reliable Strategy for Extending IV Half-life.

Authors:  Fabio Broccatelli; Ignacio Aliagas; Hao Zheng
Journal:  ACS Med Chem Lett       Date:  2018-04-19       Impact factor: 4.345

3.  Octanol-water partition coefficient measurements for the SAMPL6 blind prediction challenge.

Authors:  Mehtap Işık; Dorothy Levorse; David L Mobley; Timothy Rhodes; John D Chodera
Journal:  J Comput Aided Mol Des       Date:  2019-12-19       Impact factor: 3.686

4.  Prediction of cyclohexane-water distribution coefficients for the SAMPL5 data set using molecular dynamics simulations with the OPLS-AA force field.

Authors:  Ian M Kenney; Oliver Beckstein; Bogdan I Iorga
Journal:  J Comput Aided Mol Des       Date:  2016-08-31       Impact factor: 3.686

5.  Calculation of distribution coefficients in the SAMPL5 challenge from atomic solvation parameters and surface areas.

Authors:  Diogo Santos-Martins; Pedro Alexandrino Fernandes; Maria João Ramos
Journal:  J Comput Aided Mol Des       Date:  2016-09-01       Impact factor: 3.686

6.  Blind prediction of distribution in the SAMPL5 challenge with QM based protomer and pK a corrections.

Authors:  Frank C Pickard; Gerhard König; Florentina Tofoleanu; Juyong Lee; Andrew C Simmonett; Yihan Shao; Jay W Ponder; Bernard R Brooks
Journal:  J Comput Aided Mol Des       Date:  2016-09-19       Impact factor: 3.686

7.  LogD Contributions of Substituents Commonly Used in Medicinal Chemistry.

Authors:  Matthew L Landry; James J Crawford
Journal:  ACS Med Chem Lett       Date:  2019-12-11       Impact factor: 4.345

8.  Cell Active Hydroxylactam Inhibitors of Human Lactate Dehydrogenase with Oral Bioavailability in Mice.

Authors:  Hans E Purkey; Kirk Robarge; Jinhua Chen; Zhongguo Chen; Laura B Corson; Charles Z Ding; Antonio G DiPasquale; Peter S Dragovich; Charles Eigenbrot; Marie Evangelista; Benjamin P Fauber; Zhenting Gao; Hongxiu Ge; Anna Hitz; Qunh Ho; Sharada S Labadie; Kwong Wah Lai; Wenfeng Liu; Yajing Liu; Chiho Li; Shuguang Ma; Shiva Malek; Thomas O'Brien; Jodie Pang; David Peterson; Laurent Salphati; Steve Sideris; Mark Ultsch; BinQing Wei; Ivana Yen; Qin Yue; Huihui Zhang; Aihe Zhou
Journal:  ACS Med Chem Lett       Date:  2016-08-26       Impact factor: 4.345

9.  Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge.

Authors:  Ariën S Rustenburg; Justin Dancer; Baiwei Lin; Jianwen A Feng; Daniel F Ortwine; David L Mobley; John D Chodera
Journal:  J Comput Aided Mol Des       Date:  2016-10-07       Impact factor: 3.686

10.  Comparison of logP and logD correction models trained with public and proprietary data sets.

Authors:  Ignacio Aliagas; Alberto Gobbi; Man-Ling Lee; Benjamin D Sellers
Journal:  J Comput Aided Mol Des       Date:  2022-04-01       Impact factor: 3.686

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