Quantitative Microdialysis: Experimental Protocol and Software for Small Molecule Protein Affinity Determination and for Exclusion of Compounds with Poor Physicochemical Properties

Recent advances in computational and experimental protein-ligand affinity determination techniques

INTRODUCTION

Modern drug discovery revolves around designing ligands that target the chosen biomolecule, typically proteins. For this, the evaluation of affinities of putative ligands is crucial. This has given rise to a multitude of dedicated computational and experimental methods that are constantly being developed and improved.

AREAS COVERED

In this review, the authors reassess both the industry mainstays and the newest trends among the methods for protein - small-molecule affinity determination. They discuss both computational affinity predictions and experimental techniques, describing their basic principles, main limitations, and advantages. Together, this serves as initial guide to the currently most popular and cutting-edge ligand-binding assays employed in rational drug design.

EXPERT OPINION

The affinity determination methods continue to develop toward miniaturization, high-throughput, and in-cell application. Moreover, the availability of data analysis tools has been constantly increasing. Nevertheless, cross-verification of data using at least two different techniques and careful result interpretation remain of utmost importance.

Multiplex measurement of protein-peptide dissociation constants using dialysis and mass spectrometry

We propose a high-throughput method for quantitively measuring hundreds of protein-peptide binding affinities in parallel. In this assay a solution of protein is dialyzed into a buffer containing a pool of potential binding peptides, such that upon equilibration the relative abundance of a peptide species is mathematically related to that peptide's dissociation constant, K_d . We use isobaric multiplexed quantitative proteomics to simultaneously determine the relative abundance, and hence the K_d and its associated error, for an entire peptide library. We apply this technique, which we call PEDAL (Parallel Equilibrium Dialysis for Affinity Learning), to determine accurate K_d 's between a PDZ domain and hundreds of peptides, spanning an affinity range of multiple orders of magnitude in a single experiment. PEDAL is a convenient, fast, and low-cost method for measuring large numbers of protein-peptide affinities in parallel, providing a rare combination of true in-solution binding equilibria with the ability to multiplex. This article is protected by copyright. All rights reserved.

Biophysical Approaches for the Characterization of Protein-Metabolite Interactions

With an estimate of hundred thousands of protein molecules per cell and the number of metabolites several orders of magnitude higher, protein-metabolite interactions are omnipresent. In vitro analyses are one of the main pillars on the way to establish a solid understanding of how these interactions contribute to maintaining cellular homeostasis. A repertoire of biophysical techniques is available by which protein-metabolite interactions can be quantitatively characterized in terms of affinity, specificity, and kinetics in a broad variety of solution environments. Several of those provide information on local or global conformational changes of the protein partner in response to ligand binding. This review chapter gives an overview of the state-of-the-art biophysical toolbox for the study of protein-metabolite interactions. It briefly introduces basic principles, highlights recent examples from the literature, and pinpoints promising future directions.

Using ELP Repeats as a Scaffold for De Novo Construction of Gadolinium-Binding Domains within Multifunctional Recombinant Proteins for Targeted Delivery of Gadolinium to Tumour Cells

Three artificial proteins that bind the gadolinium ion (Gd3+) with tumour-specific ligands were de novo engineered and tested as candidate drugs for binary radiotherapy (BRT) and contrast agents for magnetic resonance imaging (MRI). Gd3+-binding modules were derived from calmodulin. They were joined with elastin-like polypeptide (ELP) repeats from human elastin to form the four-centre Gd3+-binding domain (4MBS-domain) that further was combined with F3 peptide (a ligand of nucleolin, a tumour marker) to form the F3-W4 block. The F3-W4 block was taken alone (E2-13W4 protein), as two repeats (E1-W8) and as three repeats (E1-W12). Each protein was supplemented with three copies of the RGD motif (a ligand of integrin αvβ3) and green fluorescent protein (GFP). In contrast to Magnevist (a Gd-containing contrast agent), the proteins exhibited three to four times higher accumulation in U87MG glioma and A375 melanoma cell lines than in normal fibroblasts. The proteins remained for >24 h in tumours induced by Ca755 adenocarcinoma in C57BL/6 mice. They exhibited stability towards blood proteases and only accumulated in the liver and kidney. The technological advantages of using the engineered proteins as a basis for developing efficient and non-toxic agents for early diagnosis of tumours by MRI as well as part of BRT were demonstrated.