Literature DB >> 15090247

Driving affinity selection by centrifugal force.

J E Harlan1, D A Egan, U S Ladror, S Snyder, M I Tang, A Buko, T F Holzman.   

Abstract

We describe a new approach to affinity selection based on the application of centrifugal force to macromolecules in solution. The method relies on the well known macromolecular hydrodynamic principles of centrifugation. It can be automated and operated in a centralized fashion, or it can be decentralized and used by single researchers or networks of researchers with a minimal additional capital investment. In this method, a centrifugal driving force is used to establish a differential and selective concentration gradient between a therapeutic target and potential ligands in compound libraries. This concentration gradient, in turn, drives the binding of ligands. Once formed, the differential concentration gradient of target macromolecules and ligands is fractionated to capture the self-sorting binding events. Ligand binding is defined by the individual ligand binding constants, so tight binding ligands will essentially distribute identically with the protein target, and weaker binding ligands will not. The level of affinity needed to operationally define tight binding can be adjusted by selecting the initial concentration conditions or centrifugal force. A variety of rapid, commonly available, detection methods can be used to assess binding in the fractionated samples. The method can be broadly applied in drug discovery efforts to examine most types of cell-cell, protein-protein, and protein-small molecule interactions. We describe the application of this method to systems of small molecule interactions with several macromolecules of therapeutic interest.

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Year:  2003        PMID: 15090247     DOI: 10.1089/154065803322302763

Source DB:  PubMed          Journal:  Assay Drug Dev Technol        ISSN: 1540-658X            Impact factor:   1.738


  1 in total

1.  Design and characterization of an engineered gp41 protein from human immunodeficiency virus-1 as a tool for drug discovery.

Authors:  Kent D Stewart; Kevin Steffy; Kevin Harris; John E Harlan; Vincent S Stoll; Jeffrey R Huth; Karl A Walter; Emily Gramling-Evans; Renaldo R Mendoza; Jean M Severin; Paul L Richardson; Leo W Barrett; Edmund D Matayoshi; Kerry M Swift; Stephen F Betz; Steve W Muchmore; Dale J Kempf; Akhter Molla
Journal:  J Comput Aided Mol Des       Date:  2007-02-09       Impact factor: 3.686

  1 in total

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