Application of a novel in silico high-throughput screen to identify selective inhibitors for protein–protein interactions

Abstract

Increasing numbers of target protein structures available for computational studies makes the structure-based screening paradigm more attractive for initial hit indentification. We have developed a novel in silico screening methodology incorporating Molecular Mechanics (MM)/ implicit solvent methods to evaluate binding free energies and applied this technology to the identification of inhibitors of the TLR4/MD-2 interaction.* Corresponding author. Tel.: +1 303 492 6786; fax: +1 303 492 5894, hang.yin@colorado.edu.Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. In order to improve affinity prediction accuracy without reducing screening speed, we developed a sequence of MM methods with implicit solvent models to evaluate binding free energies. Many recent investigations have revealed that similar methods, such as the MM/ Poisson Boltzman-Surface Area (MM/PB-SA) approach proved to be highly capable of predicting the binding free energies. NIH Public Access[23] To get through the bottleneck posed by the computationally demanding MD-based methods, we used a combination of the two: fast molecular docking for the generation of binding poses and MD simulations to rank the ligand poses according to their binding affinities implemented in QUANTUM. [23][24][25][26] To confine the amount of necessary calculations to a reasonable level, we performed extensive clustering of the ligand libraries to ensure the least possible computational work, while keeping as much of the full chemical diversity of the available library as possible. Finally, we conducted profiling of hits against a library of ca. 500 representative human proteins as a selectivity filter. As a proof of concept, screening was conducted against both TLR4 and MD-2 to validate our strategy and to maximize the potential of discovering a useful small molecule inhibitor. Compounds 1 and 2 were identified as potential TLR4-and MD-2-specific antagonists, respectively, with predicted K d values less than 10 μM (Figure 1).Because biophysical evaluation of TLR4 inhibitors is challenging due to the limited availability of TLR4 (recombinant expression of TLR4, an immune receptor that senses LPS, is not achievable in high-yielding bacterial systems), compounds 1 and 2 were tested in mammalian cells using a previously established TLR4 signaling assay. A challenge when developing TLR4 inhibitors is engineering selectivity against other TLRs. We investigated the selectivity of 1 by measuring nitric oxide (NO) production in RAW264.7 cells. RAW cells express all TLRs and each specific TLR can be individually activated by treatment w...

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