Best Practices in Utilization of 2D-NMR Spectral Data as the Input for Chemometric Analysis in Biopharmaceutical Applications

Structural Relationships to Efficacy for Prazole-Derived Antivirals

Here, an in vitro characterization of a family of prazole derivatives that covalently bind to the C73 site on Tsg101 and assay their ability to inhibit viral particle production is presented. Structurally, increased steric bulk on the 4-pyridyl of the prazole expands the prazole site on the UEV domain toward the β-hairpin in the Ub-binding site and is coupled to increased inhibition of virus-like particle production in HIV-1. Increased bulk also increased toxicity, which is alleviated by increasing flexibility. Further, the formation of a novel secondary Tsg101 adduct for several of the tested compounds and the commercial drug lansoprazole. The secondary adduct involved the loss of the 4-pyridyl substituent to form an irreversible species, with implications for increasing the half-life of the active species or its specificity toward Tsg101 UEV. It is also determined that sulfide derivatives display effective viral inhibition, presumably through cellular sulfoxidation, allowing for delayed conversion within the cellular environment, and identify SARS-COV-2 as a target of prazole inhibition. These results open multiple avenues for the design of prazole derivatives for antiviral applications.

Structural Fingerprinting of Antisense Oligonucleotide Therapeutics by Solution NMR Spectroscopy

PURPOSE

Antisense oligonucleotide (ASO) therapeutics are an emerging class of biopharmaceuticals to treat and prevent diseases, particularly those involving "undruggable" protein targets. Impurities generated throughout the ASO drug manufacturing and formulation pipeline can be detrimental to drug safety and efficacy. Therefore, analytical techniques are needed to rigorously characterize these molecules for quality assurance purposes.

METHODS

We demonstrate 1D and 2D nuclear magnetic resonance (NMR) spectroscopy methods that can generate high-resolution structural "fingerprints" of ASOs.

RESULTS AND CONCLUSIONS

1D 1H and 31P measurements are shown to provide rapid initial assessment of the ASO integrity. In particular, a well-resolved pair of 31P signals arising from the 5´-end of the phosphorodiamidate morpholino oligomer (PMO) are sensitive to complex formation and oligomerization state. 2D 1H-1H, 1H-13C, and 1H-15 N experiments, although less sensitive, are further shown to enable resonance assignment, which will allow the tracking of structural changes at high-resolution during the drug development and manufacturing processes. We further anticipate that the described NMR approaches will be broadly applicable to fully formulated ASO therapeutics, including modalities other than PMOs.

Solid-State NMR Characterization of Lyophilized Formulations of Monoclonal Antibody Therapeutics

Monoclonal antibodies (mAbs) are an important and growing class of biotherapeutic drugs. Method development for the characterization of critical quality attributes, including higher-order structure (HOS), of mAbs remains an area of active inquiry. Recently, solution-state nuclear magnetic resonance (NMR) spectroscopy has received increased attention and is a means for reliable, high-resolution HOS characterization of aqueous-based preparations of mAbs. While mAbs are predominantly formulated in solution, up to 20% are prepared as solid amorphous powders and techniques for the robust characterization of HOS in the solid state remain limited. We propose here the use of solid-state NMR (ssNMR) fingerprinting to inform directly on the HOS of solid preparations of mAbs. Using lyophilized samples of the NISTmAb reference material prepared with different formulation conditions, we demonstrate that ¹H-¹³C cross-polarization (hC-CP) buildup spectral series at natural isotopic abundance mAb samples are sensitive to differences in formulation. We also demonstrate that principal component analysis (PCA) can be used to differentiate the samples from one another in a user-independent manner while also highlighting areas where expert analysis can provide structural details about important molecular interactions in solid-phase protein formulations. Results from this study contribute to establishing the foundation for the use of ssNMR for HOS characterization of solid-phase biotherapeutics.

Correlated analytical and functional evaluation of higher order structure perturbations from oxidation of NISTmAb

The clinical efficacy and safety of protein-based drugs such as monoclonal antibodies (mAbs) rely on the integrity of the protein higher order structure (HOS) during product development, manufacturing, storage, and patient administration. As mAb-based drugs are becoming more prevalent in the treatment of many illnesses, the need to establish metrics for quality attributes of mAb therapeutics through high-resolution techniques is also becoming evident. To this end, here we used a forced degradation method, time-dependent oxidation by hydrogen peroxide, on the model biotherapeutic NISTmAb and evaluated the effects on HOS with orthogonal analytical methods and a functional assay. To monitor the oxidation process, the experimental workflow involved incubation of NISTmAb with hydrogen peroxide in a benchtop nuclear magnetic resonance spectrometer (NMR) that followed the reaction kinetics, in real-time through the water proton transverse relaxation rate R₂(¹H₂O). Aliquots taken at defined time points were further analyzed by high-field 2D ¹H-¹³C methyl correlation fingerprint spectra in parallel with other analytical techniques, including thermal unfolding, size-exclusion chromatography, and surface plasmon resonance, to assess changes in stability, heterogeneity, and binding affinities. The complementary measurement outputs from the different techniques demonstrate the utility of combining NMR with other analytical tools to monitor oxidation kinetics and extract the resulting structural changes in mAbs that are functionally relevant, allowing rigorous assessment of HOS attributes relevant to the efficacy and safety of mAb-based drug products.

2D NMR Analysis as a Sensitive Tool for Evaluating the Higher-Order Structural Integrity of Monoclonal Antibody against COVID-19

The higher-order structure (HOS) of protein therapeutics has been confirmed as a critical quality parameter. In this study, we compared 2D ¹H-¹³C ALSOFAST-HMQC NMR spectra with immunochemical ELISA-based analysis to evaluate their sensitivity in assessing the HOS of a potent human monoclonal antibody (mAb) for the treatment of coronavirus disease 2019 (COVID-19). The study confirmed that the methyl region of the 2D ¹H-¹³C NMR spectrum is sensitive to changes in the secondary and tertiary structure of the mAb, more than ELISA immunoassay. Because of its highly detailed level of characterization (i.e., many ¹H-¹³C cross-peaks are used for statistical comparability), the NMR technique also provided a more informative outcome for the product characterization of biopharmaceuticals. This NMR approach represents a powerful tool in assessing the overall higher-order structural integrity of mAb as an alternative to conventional immunoassays.

Interlaboratory Studies Using the NISTmAb to Advance Biopharmaceutical Structural Analytics

Biopharmaceuticals such as monoclonal antibodies are required to be rigorously characterized using a wide range of analytical methods. Various material properties must be characterized and well controlled to assure that clinically relevant features and critical quality attributes are maintained. A thorough understanding of analytical method performance metrics, particularly emerging methods designed to address measurement gaps, is required to assure methods are appropriate for their intended use in assuring drug safety, stability, and functional activity. To this end, a series of interlaboratory studies have been conducted using NISTmAb, a biopharmaceutical-representative and publicly available monoclonal antibody test material, to report on state-of-the-art method performance, harmonize best practices, and inform on potential gaps in the analytical measurement infrastructure. Reported here is a summary of the study designs, results, and future perspectives revealed from these interlaboratory studies which focused on primary structure, post-translational modifications, and higher order structure measurements currently employed during biopharmaceutical development.

Chemometric Analysis of NMR Spectra and Machine Learning to Investigate Membrane Fouling

Efficient membrane filtration requires the understanding of the membrane foulants and the functional properties of different membrane types in water purification. In this study, dead-end filtration of aquaculture system effluents was performed and the membrane foulants were investigated via nuclear magnetic resonance (NMR) spectroscopy. Several machine learning models (Random Forest; RF, Extreme Gradient Boosting; XGBoost, Support Vector Machine; SVM, and Neural Network; NN) were constructed, one to predict the maximum transmembrane pressure, for revealing the chemical compounds causing fouling, and the other to classify the membrane materials based on chemometric analysis of NMR spectra, for determining their effect on the properties of the different membrane types tested. Especially, RF models exhibited high accuracy; the important chemical shifts observed in both the regression and classification models suggested that the proportional patterns of sugars and proteins are key factors in the fouling progress and the classification of membrane types. Therefore, the proposed strategy of chemometric analysis of NMR spectra is suitable for membrane research, which aims at investigating comprehensively the fouling phenomenon and how the foulants and environmental conditions vary according to the filtration systems.

Structural Fingerprinting of Short Interfering RNA Therapeutics by Solution Nuclear Magnetic Resonance Spectroscopy

Nucleic acids are an increasingly popular platform for the development of biotherapeutics to treat a wide variety of illnesses, including diseases where traditional drug development efforts have failed. To date, there are 14 short oligonucleotide therapeutics and 2 messenger RNA (mRNA) vaccines approved by the U.S. Food and Drug Administration (FDA), which demonstrates the potential of nucleic acids as a platform for the development of safe and effective medicines and vaccines. Despite the increasing popularity of nucleic acid-based drugs, there has been a paucity of high-resolution structural techniques applied to rigorously characterize these molecules during drug development. Here, we present application of nuclear magnetic resonance (NMR) methods to structurally "fingerprint" short oligonucleotide therapeutics at natural isotope abundance under full formulation conditions. The NMR methods described herein leverage signals arising from the native structural features of nucleic acids, including imino, aromatic, and ribose resonances, in addition to non-native chemistries, such as 2'-fluoro (2'-F), 2'-O-methyl (2'-OMe), and phosphorothioate (PS) modifications, introduced during drug development. We demonstrate the utility of the NMR methods to structurally "fingerprint" a model short interfering RNA (siRNA) and a sample that simulated the drug product Givosiran. We anticipate broad applicability of the NMR methods to other nucleic acid-based therapeutics due to the generalized nature of the approach and ability to monitor many quality attributes simultaneously.

Quantification of natural abundance NMR data differentiates the solution behavior of monoclonal antibodies and their fragments

Biotherapeutics are an important class of molecules for the treatment of a wide range of diseases. They include low molecular weight peptides, highly engineered protein scaffolds and monoclonal antibodies. During their discovery and development, assessments of the biophysical attributes is critical to understanding the solution behavior of therapeutic proteins and for de-risking liabilities. Thus, methods that can quantify, characterize, and provide a basis to inform risks and drive the selection of more optimal antibody and alternative scaffolds are needed. Nuclear Magnetic Resonance (NMR) spectroscopy is a technique that provides a means to probe antibody and antibody-like molecules in solution, at atomic resolution, under any formulated conditions. Here, all samples were profiled at natural abundance requiring no isotope enrichment. We present a numerical approach that quantitates two-dimensional methyl spectra. The approach was tested with a reference dataset that contained different types of antibody and antibody-like molecules. This dataset was processed through a procedure we call a Random Sampling of NMR Peaks for Covariance Analysis. This analysis revealed that the first two components were well correlated with the hydrodynamic radius of the molecules included in the reference set. Higher-order principal components were also linked to dynamic features between different tethered antibody-like molecules and contributed to decisions around candidate selection. The reference set provides a basis to characterize molecules with unknown solution behavior and is sensitive to the behavior of a molecule formulated under different conditions. The approach is independent of protein design, scaffold, formulation and provides a facile method to quantify solution behavior.

Principal Component Analysis of 1D 1H Diffusion Edited NMR Spectra of Protein Therapeutics

The one-dimensional (1D) diffusion edited proton NMR method, Protein Fingerprint by Lineshape Enhancement (PROFILE) has been demonstrated to be suitable for higher order structure (HOS) characterization of protein therapeutics including monoclonal antibodies. Recent reports in the literature have demonstrated its advantages for HOS characterization over traditional methods such as circular dichroism and Fourier-transform infrared spectroscopy. Previously, we have demonstrated that the PROFILE method is complementary with high resolution 2D methyl correlated NMR methods and how both may be deployed as a multi-modal platform to further the utility of NMR for HOS characterization. A major limitation of the PROFILE method remains its need for high signal to noise data due to its reliance on convolution difference processing and linear correlation metrics to assess spectral similarity. Here we present an alternative method for analyzing 1D diffusion edited spectra, which overcomes this limitation by using nonlinear iterative partial least squares (NIPALS) principal component analysis, and which we dub PROtein Fingerprint Observed Using NIPALS Decomposition (PROFOUND). We demonstrate that results from the PROFOUND method are robust with respect to instrument, operator and in the presence of high experimental noise and how it may be employed to provide quantitative assessment of spectral similarity.

Assessment of the Higher-Order Structure of Formulated Monoclonal Antibody Therapeutics by 2D Methyl Correlated NMR and Principal Component Analysis

Characterization of the higher-order structure (HOS) of protein therapeutics, and in particular of monoclonal antibodies, by 2D ¹ H-¹³ C methyl correlated NMR has been demonstrated as precise and robust. Such characterization can be greatly enhanced when collections of spectra are analyzed using multivariate approaches such as principal component analysis (PCA), allowing for the detection and identification of small structural differences in drug substance that may otherwise fall below the limit of detection of conventional spectral analysis. A major limitation to this approach is the presence of aliphatic signals from formulation or excipient components, which result in spectral interference with the protein signal of interest; however, the recently described Selective Excipient Reduction and Removal (SIERRA) filter greatly reduces this issue. Here we will outline how basic 2D ¹ H-¹³ C methyl-correlated NMR may be combined with the SIERRA approach to collect 'clean' NMR spectra of formulated monoclonal antibody therapeutics (i.e., drug substance spectra free of interfering component signals), and how series of such spectra may be used for HOS characterization by direct PCA of the series spectral matrix. © 2020 U.S. Government. Basic Protocol 1: NMR data acquisition Basic Protocol 2: Full spectral matrix data processing and analysis Support Protocol: Data visualization and cluster analysis.

Role of NMR in High Ordered Structure Characterization of Monoclonal Antibodies

Obtaining high ordered structure (HOS) information is of importance to guarantee the efficacy and safety of monoclonal antibodies (mAbs) in clinical application. Assessment of HOS should ideally be performed in a non-invasive manner under their formulated storage conditions, as any perturbation can introduce unexpected detritions. However, most of the currently available techniques only indirectly report HOS of mAbs and/or require a certain condition to conduct the analyses. Besides, the flexible multidomain architecture of mAbs has hampered atomic-resolution structural analyses using X-ray crystallography and cryo-electron microscopy. In contrast, the ability of nuclear magnetic resonance (NMR) spectroscopy to structurally analyze biomolecules in various conditions in a non-invasive and quantitative manner is suitable to meet the needs. However, the application of NMR to mAbs is not straightforward due to the high molecular weight of the system. In this review, we will discuss how NMR techniques have been applied to HOS analysis of mAbs, along with the recent advances of the novel ¹⁵N direct detection NMR strategy that allows for obtaining the structural fingerprint of mAbs at lower temperatures under multiple formulation conditions. The potential application of these NMR strategies will benefit next-generation mAbs, such as antibody-drug conjugates and bispecific antibodies.

Principal component analysis for automated classification of 2D spectra and interferograms of protein therapeutics: influence of noise, reconstruction details, and data preparation

Protein therapeutics have numerous critical quality attributes (CQA) that must be evaluated to ensure safety and efficacy, including the requirement to adopt and retain the correct three-dimensional fold without forming unintended aggregates. Therefore, the ability to monitor protein higher order structure (HOS) can be valuable throughout the lifecycle of a protein therapeutic, from development to manufacture. 2D NMR has been introduced as a robust and precise tool to assess the HOS of a protein biotherapeutic. A common use case is to decide whether two groups of spectra are substantially different, as an indicator of difference in HOS. We demonstrate a quantitative use of principal component analysis (PCA) scores to perform this decision-making, and demonstrate the effect of acquisition and processing details on class separation using samples of NISTmAb monoclonal antibody Reference Material subjected to two different oxidative stress protocols. The work introduces an approach to computing similarity from PCA scores based upon the technique of histogram intersection, a method originally developed for retrieval of images from large databases. Results show that class separation can be robust with respect to random noise, reconstruction method, and analysis region selection. By contrast, details such as baseline distortion can have a pronounced effect, and so must be controlled carefully. Since the classification approach can be performed without the need to identify peaks, results suggest that it is possible to use even more efficient measurement strategies that do not produce spectra that can be analyzed visually, but nevertheless allow useful decision-making that is objective and automated.