Methodological advancements for characterising protein side chains by NMR spectroscopy

Biomolecular NMR spectroscopy in the era of artificial intelligence

Biomolecular nuclear magnetic resonance (NMR) spectroscopy and artificial intelligence (AI) have a burgeoning synergy. Deep learning-based structural predictors have forever changed structural biology, yet these tools currently face limitations in accurately characterizing protein dynamics, allostery, and conformational heterogeneity. We begin by highlighting the unique abilities of biomolecular NMR spectroscopy to complement AI-based structural predictions toward addressing these knowledge gaps. We then highlight the direct integration of deep learning approaches into biomolecular NMR methods. AI-based tools can dramatically improve the acquisition and analysis of NMR spectra, enhancing the accuracy and reliability of NMR measurements, thus streamlining experimental processes. Additionally, deep learning enables the development of novel types of NMR experiments that were previously unattainable, expanding the scope and potential of biomolecular NMR spectroscopy. Ultimately, a combination of AI and NMR promises to further revolutionize structural biology on several levels, advance our understanding of complex biomolecular systems, and accelerate drug discovery efforts.

Continuous Validation Across Macromolecular Structure Determination Process

The overall quality of the experimentally determined structures contained in the PDB is exceptionally high, mainly due to the continuous improvement of model building and structural validation programs. Improving reproducibility on a large scale requires expanding the concept of validation in structural biology and all other disciplines to include a broader framework that encompasses the entire project. A successful approach to science requires diligent attention to detail and a focus on the future. An earnest commitment to data availability and reuse is essential for scientific progress, be that by human minds or artificial intelligence.

In-Cell Structural Biology by NMR: The Benefits of the Atomic Scale

In-cell structural biology aims at extracting structural information about proteins or nucleic acids in their native, cellular environment. This emerging field holds great promise and is already providing new facts and outlooks of interest at both fundamental and applied levels. NMR spectroscopy has important contributions on this stage: It brings information on a broad variety of nuclei at the atomic scale, which ensures its great versatility and uniqueness. Here, we detail the methods, the fundamental knowledge, and the applications in biomedical engineering related to in-cell structural biology by NMR. We finally propose a brief overview of the main other techniques in the field (EPR, smFRET, cryo-ET, etc.) to draw some advisable developments for in-cell NMR. In the era of large-scale screenings and deep learning, both accurate and qualitative experimental evidence are as essential as ever to understand the interior life of cells. In-cell structural biology by NMR spectroscopy can generate such a knowledge, and it does so at the atomic scale. This review is meant to deliver comprehensive but accessible information, with advanced technical details and reflections on the methods, the nature of the results, and the future of the field.

Observation of Arginine Side-Chain Motions Coupled to the Global Conformational Exchange Process in Deubiquitinase A

Coupled motions have been demonstrated to be functionally important in a number of enzymes. Noncovalent side-chain interactions play essential roles in coordinating the motions across different structural elements in a protein. However, most of the dynamic studies of proteins are focused on backbone amides or methyl groups in the side chains and little is known about the polar and charged side chains. We have previously characterized the conformational dynamics of deubiquitinase A (DUBA), an isopeptidase, on the microsecond-to-millisecond (μs-ms) time scales with the amide ¹H Carr-Purcell-Meiboom-Gill (CPMG) experiment. We detected a global conformational exchange process on a time scale of approximately 200 μs, which involves most of the structural elements in DUBA, including the active site and the substrate binding interface. Here, we extend our previous study on backbone amides to the arginine side-chain N^ε-H^ε groups using a modified ¹H CPMG pulse sequence that can efficiently detect both backbone amide and arginine side-chain N^ε-H^ε signals in a single experiment. We found that the side chains of three arginines display motions on the same time scale as the backbone amides. Mutations of two of the three arginines to alanines result in a decrease in enzyme activity. One of these two arginines is located in a loop involved in substrate binding. This loop is not visible in the backbone amide-detected experiments due to excess line broadening induced by motions on the μs-ms time scales. These results clearly demonstrate that the motions of some arginine side chains are coupled to the global conformational exchange process and provide an additional probe for motions in a functionally important loop that did not yield visible backbone amide signals, suggesting the value of side-chain experiments on DUBA. The modified ¹H CPMG pulse sequence allows the simultaneous characterization of backbone and arginine side-chain dynamics without any increase in data acquisition time and can be applied to the dynamic studies of any protein that displays measurable amide ¹H relaxation dispersion.

Insights into the Cross Talk between Effector and Allosteric Lobes of KRAS from Methyl Conformational Dynamics

KRAS is the most frequently mutated RAS protein in cancer patients, and it is estimated that about 20% of the cancer patients in the United States carried mutant RAS proteins. To accelerate therapeutic development, structures and dynamics of RAS proteins had been extensively studied by various biophysical techniques for decades. Although 31P NMR studies revealed population equilibrium of the two major states in the active GMPPNP-bound form, more complex conformational dynamics in RAS proteins and oncogenic mutants subtly modulate the interactions with their downstream effectors. We established a set of customized NMR relaxation dispersion techniques to efficiently and systematically examine the ms-μs conformational dynamics of RAS proteins. This method allowed us to observe varying synchronized motions that connect the effector and allosteric lobes in KRAS. We demonstrated the role of conformational dynamics of KRAS in controlling its interaction with the Ras-binding domain of the downstream effector RAF1, the first kinase in the MAPK pathway. This allows one to explain, as well as to predict, the altered binding affinities of various KRAS mutants, which was neither previously reported nor apparent from the structural perspective.

Large Chaperone Complexes Through the Lens of Nuclear Magnetic Resonance Spectroscopy

Molecular chaperones are the guardians of the proteome inside the cell. Chaperones recognize and bind unfolded or misfolded substrates, thereby preventing further aggregation; promoting correct protein folding; and, in some instances, even disaggregating already formed aggregates. Chaperones perform their function by means of an array of weak protein-protein interactions that take place over a wide range of timescales and are therefore invisible to structural techniques dependent upon the availability of highly homogeneous samples. Nuclear magnetic resonance (NMR) spectroscopy, however, is ideally suited to study dynamic, rapidly interconverting conformational states and protein-protein interactions in solution, even if these involve a high-molecular-weight component. In this review, we give a brief overview of the principles used by chaperones to bind their client proteins and describe NMR methods that have emerged as valuable tools to probe chaperone-substrate and chaperone-chaperone interactions. We then focus on a few systems for which the application of these methods has greatly increased our understanding of the mechanisms underlying chaperone functions. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.