Genome-Targeted Drug Design: Understanding the Netropsin-DNA Interaction

Department of Biochemistry & Molecular Biology, Howard University College of Medicine, Washington, DC 20059, USA.
The open conference proceedings journal 01/2010; 1(1):157-163. DOI: 10.2174/22102892010010100157
Source: PubMed


Knowledge of the sequence of the human genome has provided significant opportunities to exploit DNA as a target in the rational design of therapeutic agents. Among agents that target DNA, netropsin exhibits a strong preference for binding A/T rich regions. In order to investigate the key factors responsible for DNA recognition and binding by netropsin, molecular dynamics simulations were carried out on a DNA-netropsin complex in which two netropsin molecules are bound to each AATT site of the 16-mer d(CTTAATTCGAATTAAG)(2). In this complex, the two netropsins are bound to the DNA minor groove in a head-to-head orientation with the guanidinium-termini of both netropsins pointed toward the center of the DNA. Despite their identical environments, molecular dynamics simulations showed that the two netropsins exhibited differences in their respective RMS behaviors, binding energies, minor groove width fluctuations, and rotations of their structural planes. These observations suggest that DNA recognition and binding by small molecules may be governed by mechanism(s) that are much more complex than initially anticipated and may represent unexpected challenges in genome-targeted drug design.

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    ABSTRACT: Although the molecular mechanism and thermodynamic profile of a wide variety of chemical agents have been examined intensively in the past decades in terms of specific recognition of their protein receptors, to date the physicochemical nature of DNA–drug recognition and association still remains largely unexplored. The present study focused on understanding the structural basis, energetic landscape, and biological implications underlying the binding of small-molecule ligands to their cognate or non-cognate DNA receptors. First, a new method to capture the structural features of DNA–drug complex architecture was proposed and then used to correlate the extracted features with binding affinity of the complexes. By employing this method, a statistical regression-based predictor was developed to quantitatively evaluate the interaction potency of drug compounds with DNA in a fast and reliable manner. Subsequently, we use the predictor to examine the binding behavior of a number of structure-available, affinity-known DNA–drug complexes as well as a large pool of randomly generated DNA decoys in complex with the same drugs. It was found that (1) as compared with protein–DNA recognition, small-molecule agents have relatively low specificity in selecting their cognate DNA targets from the background of numerous random decoys; (2) the abundance of A–T base pairs in the DNA core motif exhibits a significant positive correlation with the affinity of drug ligand binding to the DNA receptor; and (3) high affinity seems not to be closely related to high selectivity for a DNA-targeting drug, although high-affinity drug entities have a greater possibility of being ranked computationally as top binders. We hope that this work will provide a preliminary insight into the molecular origin of sequence-specific interactions in DNA–drug recognition. Figure QSAR modeling procedure used to associate structural features with binding affinity of DNA–drug complexes
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