New Inhibitors of the Tat–TAR RNA Interaction Found with a “Fuzzy” Pharmacophore Model

Renner, Steffen; Ludwig, Verena; Boden, Oliver; Scheffer, Ute; Göbel, Michael; Schneider, Gisbert

doi:10.1002/cbic.200400376

Cited by 43 publications

(35 citation statements)

References 33 publications

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“…Several drug design efforts for targeting RNA have already been attempted with various levels of success (see, for example, Johansson et al 2005;Mayer and James 2005;Renner et al 2005;Yu et al 2005;Mayer et al 2006;Nakatani et al 2006). With the increasing evidence of the importance of RNA in regulation of the cell, these efforts will increase as well.…”

Section: Introductionmentioning

confidence: 99%

DOCK 6: Combining techniques to model RNA–small molecule complexes

Lang¹,

Brozell²,

Mukherjee³

et al. 2009

RNA

664

638

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With an increasing interest in RNA therapeutics and for targeting RNA to treat disease, there is a need for the tools used in protein-based drug design, particularly DOCKing algorithms, to be extended or adapted for nucleic acids. Here, we have compiled a test set of RNA-ligand complexes to validate the ability of the DOCK suite of programs to successfully recreate experimentally determined binding poses. With the optimized parameters and a minimal scoring function, 70% of the test set with less than seven rotatable ligand bonds and 26% of the test set with less than 13 rotatable bonds can be successfully recreated within 2 Å heavy-atom RMSD. When DOCKed conformations are rescored with the implicit solvent models AMBER generalized Born with solvent-accessible surface area (GB/SA) and Poisson-Boltzmann with solvent-accessible surface area (PB/SA) in combination with explicit water molecules and sodium counterions, the success rate increases to 80% with PB/SA for less than seven rotatable bonds and 58% with AMBER GB/SA and 47% with PB/SA for less than 13 rotatable bonds. These results indicate that DOCK can indeed be useful for structure-based drug design aimed at RNA. Our studies also suggest that RNA-directed ligands often differ from typical protein-ligand complexes in their electrostatic properties, but these differences can be accommodated through the choice of potential function. In addition, in the course of the study, we explore a variety of newly added DOCK functions, demonstrating the ease with which new functions can be added to address new scientific questions.

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Section: Introductionmentioning

confidence: 99%

DOCK 6: Combining techniques to model RNA–small molecule complexes

Lang¹,

Brozell²,

Mukherjee³

et al. 2009

RNA

664

638

View full text Add to dashboard Cite

show abstract

“…Consequently, such methods have been employed for the design of screening libraries, relying on their scaffold-hopping potential. [2,3,[8][9][10][11][12] In this study we compared the scaffold-hopping efficiency of topological, three-dimensional and molecular-surface-based pharmacophore pair descriptors with a popular substructure fingerprint method.…”

mentioning

confidence: 99%

Scaffold‐Hopping Potential of Ligand‐Based Similarity Concepts

Renner

Schneider

2006

ChemMedChem

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“…In the latter approach, overlap in pre-defined pharmacophore space is used as an indicator of molecular similarity, which reduces the difficulty of predicting and comparing only one specific pharmacophore model. A conceptually similar approach is the use of "fuzzy" pharmacophore representations for similarity searching [54,55] that also increases the chances of scaffold hopping through pharmacophore searching [56].…”

Section: Limitations Of Pharmacophore-based Methodsmentioning

confidence: 99%

Towards Unified Compound Screening Strategies: A Critical Evaluation of Error Sources in Experimental and Virtual High‐Throughput Screening

Parker

Bajorath

2006

QSAR Comb. Sci.

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This contribution focuses on an assessment of errors in experimental and virtual screening. Sources of errors in high-throughput screening can be classified as logistic, measurement-related, or strategic. Biological assays formatted for high throughput are generally susceptible to small but systematic errors arising from a variety of sources, and the correction of such errors often requires the application of advanced data analysis methods. For virtual screening, chemical space design and molecular similarity analysis play crucial roles and similarity-based methods also have principal limitations, as discussed herein. In addition, the relative performance of computational screening methods, regardless of their specific features, generally displays strong compound class dependence. However, given their opportunities and limitations, experimental and computational screening can be carried out in a highly complementary manner and integrated screening strategies are thought to have significant potential in pharmaceutical research.

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New Inhibitors of the Tat–TAR RNA Interaction Found with a “Fuzzy” Pharmacophore Model

Cited by 43 publications

References 33 publications

DOCK 6: Combining techniques to model RNA–small molecule complexes

DOCK 6: Combining techniques to model RNA–small molecule complexes

Scaffold‐Hopping Potential of Ligand‐Based Similarity Concepts

Towards Unified Compound Screening Strategies: A Critical Evaluation of Error Sources in Experimental and Virtual High‐Throughput Screening

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