NMR in structure-based drug design

Combining structural and coevolution information to unveil allosteric sites

Understanding allosteric regulation in biomolecules is of great interest to pharmaceutical research and computational methods emerged during the last decades to characterize allosteric coupling. However, the prediction of allosteric sites in a protein structure remains a challenging task. Here, we integrate local binding site information, coevolutionary information, and information on dynamic allostery into a structure-based three-parameter model to identify potentially hidden allosteric sites in ensembles of protein structures with orthosteric ligands. When tested on five allosteric proteins (LFA-1, p38-α, GR, MAT2A, and BCKDK), the model successfully ranked all known allosteric pockets in the top three positions. Finally, we identified a novel druggable site in MAT2A confirmed by X-ray crystallography and SPR and a hitherto unknown druggable allosteric site in BCKDK validated by biochemical and X-ray crystallography analyses. Our model can be applied in drug discovery to identify allosteric pockets.

Exiting the tunnel of uncertainty: crystal soak to validated hit

Crystallographic fragment screens provide an efficient and effective way to identify small-molecule ligands of a crystallized protein. Due to their low molecular weight, such hits tend to have low, often unquantifiable, affinity for their target, complicating the twin challenges of validating the hits as authentic solution-phase ligands of the target and identifying the `best' hit(s) for further elaboration. In this article, approaches that address these challenges are assessed. Using retrospective analysis of a recent ATAD2 hit-identification campaign, alongside other examples of successful fragment-screening campaigns, it is suggested that hit validation and prioritization are best achieved by a `triangulation' approach in which the results of multiple available biochemical and biophysical techniques are correlated to develop qualitative structure-activity relationships (SARs). Such qualitative SARs may indeed be the only means by which to navigate a project through the tunnel of uncertainty that prevails before on-scale biophysical, biochemical and/or biological measurements become possible.

NMR in target driven drug discovery: why not?

No matter the source of compounds, drug discovery campaigns focused directly on the target are entirely dependent on a consistent stream of reliable data that reports on how a putative ligand interacts with the protein of interest. The data will derive from many sources including enzyme assays and many types of biophysical binding assays such as TR-FRET, SPR, thermophoresis and many others. Each method has its strengths and weaknesses, but none is as information rich and broadly applicable as NMR. Here we provide a number of examples of the utility of NMR for enabling and providing ongoing support for the early pre-clinical phase of small molecule drug discovery efforts. The examples have been selected for their usefulness in a commercial setting, with full understanding of the need for speed, cost-effectiveness and ease of implementation.

The role of NMR in leveraging dynamics and entropy in drug design

Nuclear magnetic resonance (NMR) spectroscopy has contributed to structure-based drug development (SBDD) in a unique way compared to the other biophysical methods. The potency of a ligand binding to a protein is dictated by the binding free energy, which is an intricate interplay between entropy and enthalpy. In addition to providing the atomic resolution structural information, NMR can help to identify protein-ligand interactions that potentially contribute to the enthalpic component of the free energy. NMR can also illuminate dynamic aspects of the interaction, which correspond to the entropic term of the free energy. The ability of NMR to access both terms in the free energy equation stems from the suite of experiments developed to shed light on various aspects that contribute to both entropy and enthalpy, deepening our understanding of the biological function of macromolecules and assisting to target them in physiological conditions. Here we provide a brief account of the contribution of NMR to SBDD, highlighting hallmark examples and discussing the challenges that demand further method development. In the era of integrated biology, the unique ability of NMR to directly ascertain structural and dynamical aspects of macromolecule and monitor changes in these properties upon engaging a ligand can be combined with computational and other structural and biophysical methods to provide a more complete picture of the energetics of drug engagement with the target. Such efforts can be used to engineer better drugs.

Structure-based drug design: aiming for a perfect fit

Knowledge of the three-dimensional structure of therapeutically relevant targets has informed drug discovery since the first protein structures were determined using X-ray crystallography in the 1950s and 1960s. In this editorial we provide a brief overview of the powerful impact of structure-based drug design (SBDD), which has its roots in computational and structural biology, with major contributions from both academia and industry. We describe advances in the application of SBDD for integral membrane protein targets that have traditionally proved very challenging. We emphasize the major progress made in fragment-based approaches for which success has been exemplified by over 30 clinical drug candidates and importantly three FDA-approved drugs in oncology. We summarize the articles in this issue that provide an excellent snapshot of the current state of the field of SBDD and fragment-based drug design and which offer key insights into exciting new developments, such as the X-ray free-electron laser technology, cryo-electron microscopy, open science approaches and targeted protein degradation. We stress the value of SBDD in the design of high-quality chemical tools that are used to interrogate biology and disease pathology, and to inform target validation. We emphasize the need to maintain the scientific rigour that has been traditionally associated with structural biology and extend this to other methods used in drug discovery. This is particularly important because the quality and robustness of any form of contributory data determines its usefulness in accelerating drug design, and therefore ultimately in providing patient benefit.