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      An improved relaxed complex scheme for receptor flexibility in computer-aided drug design

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          Abstract

          The interactions among associating (macro)molecules are dynamic, which adds to the complexity of molecular recognition. While ligand flexibility is well accounted for in computational drug design, the effective inclusion of receptor flexibility remains an important challenge. The relaxed complex scheme (RCS) is a promising computational methodology that combines the advantages of docking algorithms with dynamic structural information provided by molecular dynamics (MD) simulations, therefore explicitly accounting for the flexibility of both the receptor and the docked ligands. Here, we briefly review the RCS and discuss new extensions and improvements of this methodology in the context of ligand binding to two example targets: kinetoplastid RNA editing ligase 1 and the W191G cavity mutant of cytochrome c peroxidase. The RCS improvements include its extension to virtual screening, more rigorous characterization of local and global binding effects, and methods to improve its computational efficiency by reducing the receptor ensemble to a representative set of configurations. The choice of receptor ensemble, its influence on the predictive power of RCS, and the current limitations for an accurate treatment of the solvent contributions are also briefly discussed. Finally, we outline potential methodological improvements that we anticipate will assist future development.

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          Most cited references 75

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          A semiempirical free energy force field with charge-based desolvation.

          The authors describe the development and testing of a semiempirical free energy force field for use in AutoDock4 and similar grid-based docking methods. The force field is based on a comprehensive thermodynamic model that allows incorporation of intramolecular energies into the predicted free energy of binding. It also incorporates a charge-based method for evaluation of desolvation designed to use a typical set of atom types. The method has been calibrated on a set of 188 diverse protein-ligand complexes of known structure and binding energy, and tested on a set of 100 complexes of ligands with retroviral proteases. The force field shows improvement in redocking simulations over the previous AutoDock3 force field.
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            The many roles of computation in drug discovery.

            An overview is given on the diverse uses of computational chemistry in drug discovery. Particular emphasis is placed on virtual screening, de novo design, evaluation of drug-likeness, and advanced methods for determining protein-ligand binding.
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              The statistical-thermodynamic basis for computation of binding affinities: a critical review.

              Although the statistical thermodynamics of noncovalent binding has been considered in a number of theoretical papers, few methods of computing binding affinities are derived explicitly from this underlying theory. This has contributed to uncertainty and controversy in certain areas. This article therefore reviews and extends the connections of some important computational methods with the underlying statistical thermodynamics. A derivation of the standard free energy of binding forms the basis of this review. This derivation should be useful in formulating novel computational methods for predicting binding affinities. It also permits several important points to be established. For example, it is found that the double-annihilation method of computing binding energy does not yield the standard free energy of binding, but can be modified to yield this quantity. The derivation also makes it possible to define clearly the changes in translational, rotational, configurational, and solvent entropy upon binding. It is argued that molecular mass has a negligible effect upon the standard free energy of binding for biomolecular systems, and that the cratic entropy defined by Gurney is not a useful concept. In addition, the use of continuum models of the solvent in binding calculations is reviewed, and a formalism is presented for incorporating a limited number of solvent molecules explicitly.
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                Author and article information

                Contributors
                +1-858-5342913 , +1-858-5344974 , ramaro@mccammon.ucsd.edu
                rbaron@mccammon.ucsd.edu
                Journal
                J Comput Aided Mol Des
                Journal of Computer-Aided Molecular Design
                Springer Netherlands (Dordrecht )
                0920-654X
                1573-4951
                15 January 2008
                September 2008
                : 22
                : 9
                : 693-705
                Affiliations
                [1 ]Department of Chemistry and Biochemistry, University of California at San Diego, La Jolla, CA 92093-0365 USA
                [2 ]Center for Theoretical Biological Physics, University of California at San Diego, La Jolla, CA 92039-0365 USA
                [3 ]Department of Pharmacology, University of California at San Diego, La Jolla, CA 92093-0365 USA
                [4 ]Howard Hughes Medical Institute, University of California at San Diego, La Jolla, CA 92093-0365 USA
                Article
                9159
                10.1007/s10822-007-9159-2
                2516539
                18196463
                © Springer Science+Business Media B.V. 2008
                Categories
                Article
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                © Springer Science+Business Media B.V. 2008

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