Literature DB >> 7525921

Estimation and correlation of drug water solubility with pharmacological parameters required for biological activity.

M M Morelock1, L L Choi, G L Bell, J L Wright.   

Abstract

A procedure for estimating the molar water solubility (S) for a series of structurally related drug compounds is presented. HPLC methods for the determination of partition coefficients (P) are combined with semiempirical calculations for S. Multidimensional plots are developed with the physical constants S and P along the x and y axes and with a biological response, e.g. IC50 or ED50, along the z axis. Other attributes, e.g. bioavailability or biodistribution, can be added by color coding, shading, or numbering. Since the methods have a high throughput capability, parameters governing the events leading to pharmacological action [i.e. gastrointestinal dissolution (S), absorption (P), blood level (bioavailability), and biological action (IC50, EC50)] can be correlated for drug series comprising large numbers of compounds.

Entities:  

Mesh:

Substances:

Year:  1994        PMID: 7525921     DOI: 10.1002/jps.2600830706

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  8 in total

1.  Estimation of aqueous solubility of organic compounds with QSPR approach.

Authors:  Hua Gao; Veerabahu Shanmugasundaram; Pil Lee
Journal:  Pharm Res       Date:  2002-04       Impact factor: 4.200

2.  Computer-aided discovery of anti-HIV agents.

Authors:  William L Jorgensen
Journal:  Bioorg Med Chem       Date:  2016-07-21       Impact factor: 3.641

3.  Picomolar Inhibitors of HIV-1 Reverse Transcriptase: Design and Crystallography of Naphthyl Phenyl Ethers.

Authors:  Won-Gil Lee; Kathleen M Frey; Ricardo Gallardo-Macias; Krasimir A Spasov; Mariela Bollini; Karen S Anderson; William L Jorgensen
Journal:  ACS Med Chem Lett       Date:  2014-10-13       Impact factor: 4.345

4.  Cocrystal Solubility Product Prediction Using an in combo Model and Simulations to Improve Design of Experiments.

Authors:  Alex Avdeef
Journal:  Pharm Res       Date:  2018-02-02       Impact factor: 4.200

5.  Picomolar inhibitors of HIV reverse transcriptase featuring bicyclic replacement of a cyanovinylphenyl group.

Authors:  Won-Gil Lee; Ricardo Gallardo-Macias; Kathleen M Frey; Krasimir A Spasov; Mariela Bollini; Karen S Anderson; William L Jorgensen
Journal:  J Am Chem Soc       Date:  2013-10-24       Impact factor: 15.419

6.  Optimization of diarylazines as anti-HIV agents with dramatically enhanced solubility.

Authors:  Mariela Bollini; José A Cisneros; Krasimir A Spasov; Karen S Anderson; William L Jorgensen
Journal:  Bioorg Med Chem Lett       Date:  2013-07-08       Impact factor: 2.823

7.  Diaryl ethers with carboxymethoxyphenacyl motif as potent HIV-1 reverse transcriptase inhibitors with improved solubility.

Authors:  Tomasz Frączek; Rafał Kamiński; Agnieszka Krakowiak; Evelien Naessens; Bruno Verhasselt; Piotr Paneth
Journal:  J Enzyme Inhib Med Chem       Date:  2018-12       Impact factor: 5.051

8.  Novel Solubility Prediction Models: Molecular Fingerprints and Physicochemical Features vs Graph Convolutional Neural Networks.

Authors:  Sumin Lee; Myeonghun Lee; Ki-Won Gyak; Sung Dug Kim; Mi-Jeong Kim; Kyoungmin Min
Journal:  ACS Omega       Date:  2022-04-04
  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.