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Biomedical subjects

Philip J Hajduk

Publications and source records attributed to Philip J Hajduk.

At least 19 recordsLinked to original sources
PubMed2006

Fragment-based drug design: how big is too big?

Much has been discussed about the proper physicochemical properties (e.g., molecular weight, hydrophobicity, etc.) that should be considered when utilizing fragment leads in drug design. However, little has been reported as to what emphasis, if any, should be placed on the potency of the resulting fragment leads. In this report, a retrospective analysis of 18 highly optimized inhibitors is described in which the compounds were systematically deconstructed until the minimal binding elements could be identified. An analysis of the potency changes that were observed as the leads were reduced in size indicate that a nearly linear relationship exists between molecular weight and binding affinity over the entire range of sizes and potencies represented in the dataset. On the basis of these observations, prediction maps can be constructed that enable critical and quantitative assessments of the process of lead identification and optimization. These data place well-defined limits on the ideal size and potency of fragment leads that are being considered for use in fragment-based drug design.

Drug Design↗
PubMed2006

Discovery of a potent inhibitor of the antiapoptotic protein Bcl-xL from NMR and parallel synthesis.

The antiapoptotic proteins Bcl-x(L) and Bcl-2 play key roles in the maintenance of normal cellular homeostasis. However, their overexpression can lead to oncogenic transformation and is responsible for drug resistance in certain types of cancer. This makes Bcl-x(L) and Bcl-2 attractive targets for the development of potential anticancer agents. Here we describe the structure-based discovery of a potent Bcl-x(L) inhibitor directed at a hydrophobic groove on the surface of the protein. This groove represents the binding site for BH3 peptides from proapoptotic Bcl-2 family members such as Bak and Bad. Application of NMR-based screening yielded an initial biaryl acid with an affinity (K(d)) of approximately 300 microM for the protein. Following the classical "SAR by NMR" approach, a second-site ligand was identified that bound proximal to the first-site ligand in the hydrophobic groove. From NMR-based structural studies and parallel synthesis, a potent ligand was obtained, which binds to Bcl-x(L) with an inhibition constant (K(i)) of 36 +/- 2 nM.

Aniline Compounds↗
PubMed2006

High-level bacterial expression and purification of human SirT2 protein for NMR studies.

Silent information regulator 2 (Sir2) proteins are a class of protein deacetylase enzymes that play key roles in transcriptional gene silencing, DNA repair, and aging. Here, we describe the high-level bacterial expression and purification of a human SirT2 construct that yields high resolution NMR spectra. By removing the N-terminal helix alpha0 and using Thioredoxin as a fusion partner, greater than 10 mg/L of purified protein can be obtained from minimal media. The protein is fully functional and enables NMR-based screening and structural studies of this important protein.

Escherichia coli↗
PubMed2006

Structural studies of Bcl-xL/ligand complexes using 19F NMR.

Fluorine atoms are often incorporated into drug molecules as part of the lead optimization process in order to improve affinity or modify undesirable metabolic and pharmacokinetic profiles. From an NMR perspective, the abundance of fluorinated drug leads provides an exploitable niche for structural studies using 19F NMR in the drug discovery process. As 19F has no interfering background signal from biological sources, 19F NMR studies of fluorinated drugs bound to their protein receptors can yield easily interpretable and unambiguous structural constraints. 19F can also be selectively incorporated into proteins to obtain additional constraints for structural studies. Despite these advantages, 19F NMR has rarely been exploited for structural studies due to its broad lines in macromolecules and their ligand complexes, leading to weak signals in 1H/19F heteronuclear NOE experiments. Here we demonstrate several different experimental strategies that use 19F NMR to obtain ligand-protein structural constraints for ligands bound to the anti-apoptotic protein Bcl-xL, a drug target for anti-cancer therapy. These examples indicate the applicability of these methods to typical structural problems encountered in the drug development process.

Fluorine Compounds↗
PubMed2006

Structure-based optimization of MurF inhibitors.

The D-Ala-D-Ala adding enzyme (MurF) from Streptococcus pneumoniae catalyzes the ATP-dependent formation of the UDP-MurNAc-pentapeptide, a critical component of the bacterial cell wall. MurF is a potential target for antibacterial design because it is unique to bacteria and performs an essential non-redundant function in the bacterial cell. The recent discovery and subsequent cocrystal structure determination of MurF in complex with a new class of inhibitors served as a catalyst to begin a medicinal chemistry program aimed at improving their potency. We report here a multidisciplinary approach to this effort that allowed for rapid generation of cocrystal structures, thereby providing the crystallographic information critical for driving the inhibitor optimization process. This effort resulted in the discovery of low-nanomolar inhibitors of this bacterial enzyme.

Crystallization↗
PubMed2006

SAR by NMR: putting the pieces together.

It has been nearly ten years since the introduction of SAR by NMR and the advent of fragment-based drug design. During this time, we have gained a tremendous amount of knowledge about protein druggability, the limits of chemical diversity, and crafting high-affinity ligands from low molecular weight, weakly binding leads. This review will describe the concept of fragment-based drug design, discuss why it works, and illustrate the power of the approach with two case studies on the design of potent inhibitors of matrix metalloproteinases and Bcl-2 family proteins.

Animals↗
PubMed2006

Nuclear magnetic resonance in target profiling and compound file enhancement.

Nuclear magnetic resonance (NMR) has matured as an important tool in drug discovery and development, with firm establishment of its roles in lead generation and optimization through application of NMR-based fragment screening and structure-based drug design. Besides these applications, NMR technology has expanded to make contributions both earlier and later in the drug discovery process. This review will focus on the impact of NMR in the early stages of drug discovery, in particular in characterizing the viability of targets for further discovery exercises and improving high-throughput screening through compound file-enhancement initiatives.

Animals↗
PubMed2005

Nuclear magnetic resonance structural studies of a potassium channel-charybdotoxin complex.

Ion channels play critical roles in signaling processes and are attractive targets for treating various diseases. Here we describe an NMR-based strategy for structural analyses of potassium channel-ligand complexes using KcsA (residues 1-132, with six mutations to impart toxin binding and to mimic the eukaryotic hERG channel). Using this approach, we determined the solution structure of KcsA in complex with the high-affinity peptide antagonist charybdotoxin. The structural data reveal how charybdotoxin binds to the closed form of KcsA and makes specific contacts with the extracellular surface of the ion channel, resulting in pore blockage. This represents the first direct structural information about an ion channel complexed to a peptide antagonist and provides an experimental framework for understanding and interpreting earlier mutational analyses. The strategy presented here overcomes many of the limitations of conventional NMR approaches to helical membrane protein structure determination and can be applied in the study of the binding of druglike molecules to this important class of proteins.

Amino Acid Sequence↗
PubMed2005

An inhibitor of Bcl-2 family proteins induces regression of solid tumours.

Proteins in the Bcl-2 family are central regulators of programmed cell death, and members that inhibit apoptosis, such as Bcl-X(L) and Bcl-2, are overexpressed in many cancers and contribute to tumour initiation, progression and resistance to therapy. Bcl-X(L) expression correlates with chemo-resistance of tumour cell lines, and reductions in Bcl-2 increase sensitivity to anticancer drugs and enhance in vivo survival. The development of inhibitors of these proteins as potential anti-cancer therapeutics has been previously explored, but obtaining potent small-molecule inhibitors has proved difficult owing to the necessity of targeting a protein-protein interaction. Here, using nuclear magnetic resonance (NMR)-based screening, parallel synthesis and structure-based design, we have discovered ABT-737, a small-molecule inhibitor of the anti-apoptotic proteins Bcl-2, Bcl-X(L) and Bcl-w, with an affinity two to three orders of magnitude more potent than previously reported compounds. Mechanistic studies reveal that ABT-737 does not directly initiate the apoptotic process, but enhances the effects of death signals, displaying synergistic cytotoxicity with chemotherapeutics and radiation. ABT-737 exhibits single-agent-mechanism-based killing of cells from lymphoma and small-cell lung carcinoma lines, as well as primary patient-derived cells, and in animal models, ABT-737 improves survival, causes regression of established tumours, and produces cures in a high percentage of the mice.

Animals↗
PubMed2005

Druggability indices for protein targets derived from NMR-based screening data.

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.

Algorithms↗
PubMed2005

ALARM NMR: a rapid and robust experimental method to detect reactive false positives in biochemical screens.

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.

Autoantigens↗
PubMed2005

TINS, target immobilized NMR screening: an efficient and sensitive method for ligand discovery.

We propose a ligand screening method, called TINS (target immobilized NMR screening), which reduces the amount of target required for the fragment-based approach to drug discovery. Binding is detected by comparing 1D NMR spectra of compound mixtures in the presence of a target immobilized on a solid support to a control sample. The method has been validated by the detection of a variety of ligands for protein and nucleic acid targets (K(D) from 60 to 5000 muM). The ligand binding capacity of a protein was undiminished after 2000 different compounds had been applied, indicating the potential to apply the assay for screening typical fragment libraries. TINS can be used in competition mode, allowing rapid characterization of the ligand binding site. TINS may allow screening of targets that are difficult to produce or that are insoluble, such as membrane proteins.

Binding Sites↗
PubMed2005

Utilization of NMR-derived fragment leads in drug design.

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.

Drug Design↗
PubMed2005

Predicting protein druggability.

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.

Binding Sites↗
PubMed2005

Structure of MurF from Streptococcus pneumoniae co-crystallized with a small molecule inhibitor exhibits interdomain closure.

In a broad genomics analysis to find novel protein targets for antibiotic discovery, MurF was identified as an essential gene product for Streptococcus pneumonia that catalyzes a critical reaction in the biosynthesis of the peptidoglycan in the formation of the cell wall. Lacking close relatives in mammalian biology, MurF presents attractive characteristics as a potential drug target. Initial screening of the Abbott small-molecule compound collection identified several compounds for further validation as pharmaceutical leads. Here we report the integrated efforts of NMR and X-ray crystallography, which reveal the multidomain structure of a MurF-inhibitor complex in a compact conformation that differs dramatically from related structures. The lead molecule is bound in the substrate-binding region and induces domain closure, suggestive of the domain arrangement for the as yet unobserved transition state conformation for MurF enzymes. The results form a basis for directed optimization of the compound lead by structure-based design to explore the suitability of MurF as a pharmaceutical target.

Amino Acid Sequence↗