Theresa L. Johnson

Molecular dynamics simulation and binding energy calculation for estimation of oligonucleotide duplex thermostability in RNA-based therapeutics.

For oligonucleotide-based therapeutics, a thorough understanding of the thermodynamic properties of duplex formation is critical to developing stable and potent drugs. For unmodified small interfering RNA (siRNA), DNA antisense oligonucleotide (AON) and locked nucleic acid (LNA), DNA/LNA modified oligonucleotides, nearest neighbor (NN) methods can be effectively used to quickly and accurately predict duplex thermodynamic properties such as melting point. Unfortunately, for chemically modified olignonucleotides, there has been no accurate prediction method available. Here we describe the potential of estimating melting temperature (T(m)) for nonstandard oligonucleotides by using the correlation of the experimental T(m) with the calculated duplex binding energy (BE) for oligonucleotides of a given length. This method has been automated into a standardized molecular dynamics (MD) protocol through Pipeline Pilot (PP) using the CHARMm component in Discovery Studio (DS). Results will be presented showing the correlation of the predicted data with experiment for both standard and chemically modified siRNA and AON.

The Design, Synthesis and Potential Utility of Fluorescence Probes that Target DFG-out Conformation of p38alpha for High Throughput Screening Binding Assay.

The design, synthesis and utility of fluorescence probes that bind to the DFG‐out conformation of p38α kinase are described. Probes that demonstrate good affinity for p38α, have been identified and one of the probes, PF‐04438255, has been successfully used in an high throughput screening (HTS) assay to identify two novel non‐classical p38α inhibitors. In addition, a cascade activity assay was utilized to validate the selective binding of these non‐classical kinase inhibitors to the unactive form of the enzyme.

Application of Free–Wilson Selectivity Analysis for Combinatorial Library Design

In this chapter we present an application of in silico quantitative structure-activity relationship (QSAR) models to establish a new ligand-based computational approach for generating virtual libraries. The Free-Wilson methodology was applied to extract rules from two data sets containing compounds which were screened against either kinase or PDE gene family panels. The rules were used to make predictions for all compounds enumerated from their respective virtual libraries. We also demonstrate the construction of R-group selectivity profiles by deriving activity contributions against each protein target using the QSAR models. Such selectivity profiles were used together with protein structural information from X-ray data to provide a better understanding of the subtle selectivity relationships between kinase and PDE family members.

Optimization of the efflux ratio and permeability of covalent irreversible BTK inhibitors

Brutons tyrosine kinase (Btk) is a member of the Tec kinase family that is expressed in cells of hematopoietic lineage (e.g. B cells, macrophages, monocytes, and mast cells). Small molecule covalent irreversible Btk inhibitors targeting Cys481 within the ATP-binding pocket have been applied in the treatment of B-cell malignancies. Starting from a fragment, we discovered a novel series of potent covalent irreversible Btk inhibitors that bear N-linked groups occupying the solvent accessible pocket (SAP) of the active site of the Btk kinase domain. The hit molecules, however, displayed high P-gp mediated efflux ratio (ER) and poor A-B permeability in Caco-2 assay. By decreasing tPSA, installing steric hindrance and adjusting clogP, one top molecule 9 was discovered, which showed a 99% decrease in efflux ratio and a 90-fold increase in A-B permeability compared to hit molecule 1.