Literature DB >> 17899391

Epik: a software program for pK( a ) prediction and protonation state generation for drug-like molecules.

John C Shelley1, Anuradha Cholleti, Leah L Frye, Jeremy R Greenwood, Mathew R Timlin, Makoto Uchimaya.   

Abstract

Epik is a computer program for predicting pK(a) values for drug-like molecules. Epik can use this capability in combination with technology for tautomerization to adjust the protonation state of small drug-like molecules to automatically generate one or more of the most probable forms for use in further molecular modeling studies. Many medicinal chemicals can exchange protons with their environment, resulting in various ionization and tautomeric states, collectively known as protonation states. The protonation state of a drug can affect its solubility and membrane permeability. In modeling, the protonation state of a ligand will also affect which conformations are predicted for the molecule, as well as predictions for binding modes and ligand affinities based upon protein-ligand interactions. Despite the importance of the protonation state, many databases of candidate molecules used in drug development do not store reliable information on the most probable protonation states. Epik is sufficiently rapid and accurate to process large databases of drug-like molecules to provide this information. Several new technologies are employed. Extensions to the well-established Hammett and Taft approaches are used for pK(a) prediction, namely, mesomer standardization, charge cancellation, and charge spreading to make the predicted results reflect the nature of the molecule itself rather just for the particular Lewis structure used on input. In addition, a new iterative technology for generating, ranking and culling the generated protonation states is employed.

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Year:  2007        PMID: 17899391     DOI: 10.1007/s10822-007-9133-z

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  386 in total

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2.  Multiple ligand docking by Glide: implications for virtual second-site screening.

Authors:  Márton Vass; Ákos Tarcsay; György M Keserű
Journal:  J Comput Aided Mol Des       Date:  2012-05-26       Impact factor: 3.686

3.  Tautomerism in chemical information management systems.

Authors:  Wendy A Warr
Journal:  J Comput Aided Mol Des       Date:  2010-04-06       Impact factor: 3.686

4.  Tautomerism, Hammett sigma, and QSAR.

Authors:  Yvonne Connolly Martin
Journal:  J Comput Aided Mol Des       Date:  2010-03-18       Impact factor: 3.686

5.  Towards the comprehensive, rapid, and accurate prediction of the favorable tautomeric states of drug-like molecules in aqueous solution.

Authors:  Jeremy R Greenwood; David Calkins; Arron P Sullivan; John C Shelley
Journal:  J Comput Aided Mol Des       Date:  2010-03-31       Impact factor: 3.686

6.  Dynamics and structural determinants of ligand recognition of the 5-HT6 receptor.

Authors:  Márton Vass; Balázs Jójárt; Ferenc Bogár; Gábor Paragi; György M Keserű; Ákos Tarcsay
Journal:  J Comput Aided Mol Des       Date:  2015-11-16       Impact factor: 3.686

7.  Drug screening strategy for human membrane proteins: from NMR protein backbone structure to in silica- and NMR-screened hits.

Authors:  Steffen Lindert; Innokentiy Maslennikov; Ellis J C Chiu; Levi C Pierce; J Andrew McCammon; Senyon Choe
Journal:  Biochem Biophys Res Commun       Date:  2014-02-10       Impact factor: 3.575

8.  An explicit-solvent hybrid QM and MM approach for predicting pKa of small molecules in SAMPL6 challenge.

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Journal:  J Comput Aided Mol Des       Date:  2018-10-01       Impact factor: 3.686

9.  Exploring the Carbamazepine Interaction with Human Pregnane X Receptor and Effect on ABCC2 Using in Vitro and in Silico Approach.

Authors:  Gurpreet K Grewal; Khuraijam D Singh; Neha Kanojia; Chitra Rawat; Samiksha Kukal; Ajay Jajodia; Anshika Singhal; Richa Misra; Selvaraman Nagamani; Karthikeyan Muthusamy; Ritushree Kukreti
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10.  A combined treatment of hydration and dynamical effects for the modeling of host-guest binding thermodynamics: the SAMPL5 blinded challenge.

Authors:  Rajat Kumar Pal; Kamran Haider; Divya Kaur; William Flynn; Junchao Xia; Ronald M Levy; Tetiana Taran; Lauren Wickstrom; Tom Kurtzman; Emilio Gallicchio
Journal:  J Comput Aided Mol Des       Date:  2016-09-30       Impact factor: 3.686

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