Biomedical subjects
Publications and source records attributed to Jeffrey R Huth.
We report the synthesis of kinase targeted libraries based on the thienopyrazole scaffold. Several thienopyrazole analogs have been identified as submicromolar inhibitors of KDR.
An analysis of heteronuclear-NMR-based screening data is used to derive relationships between the ability of small molecules to bind to a protein and various parameters that describe the protein binding site. It is found that a simple model including terms for polar and apolar surface area, surface complexity, and pocket dimensions accurately predicts the experimental screening hit rates with an R(2) of 0.72, an adjusted R(2) of 0.65, and a leave-one-out Q(2) of 0.56. Application of the model to predict the druggability of protein targets not used in the training set correctly classified 94% of the proteins for which high-affinity, noncovalent, druglike leads have been reported. In addition to understanding the pocket characteristics that contribute to high-affinity binding, the relationships that have been defined allow for quantitative comparative analyses of protein binding sites for use in target assessment and validation, virtual ligand screening, and structure-based drug design.
High-throughput screening (HTS) of large compound collections typically results in numerous small molecule hits that must be carefully evaluated to identify valid drug leads. Although several filtering mechanisms and other tools exist that can assist the chemist in this process, it is often the case that costly synthetic resources are expended in pursuing false positives. We report here a rapid and reliable NMR-based method for identifying reactive false positives including those that oxidize or alkylate a protein target. Importantly, the reactive species need not be the parent compound, as both reactive impurities and breakdown products can be detected. The assay is called ALARM NMR (a La assay to detect reactive molecules by nuclear magnetic resonance) and is based on monitoring DTT-dependent (13)C chemical shift changes of the human La antigen in the presence of a test compound or mixture. Extensive validation has been performed to demonstrate the reliability and utility of using ALARM NMR to assess thiol reactivity. This included comparing ALARM NMR to a glutathione-based fluorescence assay, as well as testing a collection of more than 3500 compounds containing HTS hits from 23 drug targets. The data show that current in silico filtering tools fail to identify more than half of the compounds that can act via reactive mechanisms. Significantly, we show how ALARM NMR data has been critical in identifying reactive compounds that would otherwise have been prioritized for lead optimization. In addition, a new filtering tool has been developed on the basis of the ALARM NMR data that can augment current in silico programs for identifying nuisance compounds and improving the process of hit triage.
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The advent of large-scale NMR-based screening has enabled new strategies for the design of novel, potent inhibitors of therapeutic targets. In particular, fragment-based strategies, in which molecular portions of the final high-affinity ligand are experimentally identified prior to chemical synthesis, have found widespread utility. This chapter will discuss some of the practical considerations for identifying and utilizing these fragment leads in drug design, with special emphasis on some of the lessons learned from more than a decade of industry experience.
The ability to predict whether a particular protein can bind with high affinity and specificity to small, drug-like compounds based solely on its 3D structure has been a longstanding goal of structural biologists and computational scientists. The promise is that an accurate prediction of protein druggability can capitalize on the huge investments already made in structural genomics initiatives by identifying highly druggable proteins and using this information in target identification and validation campaigns. Here we discuss the potential utility of tools that characterize protein targets and describe strategies for the optimal integration of protein druggability data with bioinformatic approaches to target selection.
Reversal of aberrant gene expression that is induced by the proto-oncogene c-myc is likely to be effective for treating a variety of tumors that rely on this pathway for growth. One strategy to down-regulate the c-myc pathway is to target transcription factors that regulate its own expression. A host of proteins act in coordination to regulate c-myc expression and any one of them are theoretical targets for small-molecule therapy. Experimentally, it has been shown that the far upstream element (FUSE) binding protein (FBP) is essential for c-myc expression, and reductions in FBP levels both reduce c-myc expression and correlate with slower cell growth. FBP binds to ssDNA by capturing exposed DNA bases in a hydrophobic pocket. This suggests that a small molecule could be designed to occupy this pocket and inhibit FBP function. Using a variety of screening methodologies, we have identified ligands that bind to the DNA binding pockets of the KH domains of FBP. Gel shift analyses using full length FBP and a related transcription factor confirm that a small-molecule lead compound inhibits DNA binding in a specific manner. The benzoylanthranilic acid compounds described here represent leads in the design of FBP inhibitors that can serve as useful tools in the study of c-myc regulation and in the development of therapeutics that target the c-myc pathway.
Bcl-xL is a member of the Bcl-2 family of proteins that are implicated to play a vital role in several diseases including cancer. Bcl-xL suppresses apoptosis; thus the inhibition of Bcl-xL function could restore the apoptotic process. To identify antagonists of Bcl-xL function, two ultra-high-throughput screens were implemented. An activity assay utilized fluorescence polarization, based on the binding of fluorescein-labeled peptide [the BH3 domain of BAD protein (F-Bad 6)] to Bcl-xL. A 384-well plate assay with mixtures of 10 drug compounds per well, combined with a fast plate reader, resulted in a throughput of 46,080 data points/day. Utilizing this screening format, 370,400 compounds were screened in duplicate and 425 inhibitors with an IC(50) below 100 microM were identified. The second assay format, affinity selection/mass spectrometry (ASMS), used ultrafiltration to separate Bcl-xL binders from nonbinders in mixtures of 2400 compounds. The bound species were subsequently separated from the protein and analyzed by flow injection electrospray mass spectrometry. Utilizing the ASMS format, 263,382 compounds were screened in duplicate and 29 binders with affinities below 100 microM were identified. Two novel classes of Bcl-xL inhibitors were identified by both methods and confirmed to bind (13)C-labeled Bcl-xL using heteronuclear magnetic resonance spectroscopy.
NMR has proven to be a valuable tool for identifying small molecule drug leads that serve as starting points for lead optimization programs. In addition, NMR screening can also be applied during lead optimization in order to improve the pharmacokinetic properties of a compound. In this paper we review the NMR methods that can be used for this purpose. Several examples are then summarized to demonstrate the usefulness of fragment-based approaches in optimizing the physical properties of potential drug candidates.
A detailed chemometric analysis of ligand binding to domain-3A of human serum albumin is described. NMR and fluorescence data on a set of 889 chemically diverse compounds were used to develop a group contribution model based on 74 chemical fragments that is in good agreement with the experimental data (R2 = 0.94, Q2 = 0.90). The structural descriptors used in this analysis comprise a convenient look-up table for quantitatively estimating the effect that a particular group will have on albumin binding. This information can be valuable for optimizing a particular series of compounds for drug development.