Rodell C. Barrientos

Electrostatic repulsion hydrophilic interaction liquid chromatography (ERLIC) provides unique selectivity for highly polar and charged analytes, yet method development remains challenging. Careful optimization of organic solvent gradients and buffer concentrations is essential to achieve optimal selectivity. However, application of a pH gradient in addition to organic solvent and buffer concentration gradients can enable mixed-mode interactions beyond those governed solely by electrostatic repulsion. In this work, we introduce Electrostatic Attraction/Repulsion Hydrophilic Interaction Liquid Chromatography (EARLIC), a novel separation mode that extends the selectivity of ERLIC by leveraging both electrostatic attraction and repulsion through pH gradient modulation of analyte−stationary phase interactions. Fundamental retention mechanism differences between these separation modes are proposed while also outlining key chromatography practices for enhanced selectivity. In addition, an ERLIC/EARLIC screening platform integrating cation and anion exchange columns with twelve mobile phases to systematically modulate electrostatic and hydrophilic interactions is introduced. Automated column and mobile phase switching valves enabled rapid scouting and efficient assay development while also minimizing manual intervention. This workflow demonstrated broad applicability across nucleotides, N-glycans, synthetic precursors, intact glycoproteins, and aminoglycoside antibiotics. Compared to classical HILIC, EARLIC improved retention of highly hydrophilic species, delivered sharper peaks in high-salt matrices, and provided orthogonal selectivity for charged moieties. Coupling ERLIC/EARLIC to mass spectrometry streamlined sensitive quantitation of kanamycin in cell culture matrices, confirming compatibility with complex sample loads. This analytical framework establishes a systematic approach for selecting the optimal combination of stationary phase charge, buffer system, ionic strength, pH, and organic fraction, accelerating ERLIC/EARLIC adoption across both academic and industrial sectors.

Accelerating the discovery and development of life-saving therapeutics and vaccines requires a commensurate level of analytical innovations, especially high-throughput (HT) methodologies for simultaneous multicomponent analyses traditionally used in fast-paced laboratory settings. HT screening is a critical step to enable lead candidate design, selection, and formulation at aggressive timelines. Current methods used for this purpose, such as liquid chromatography-mass spectrometry (LC-MS)-based approaches, are intrinsically low-throughput. Such assays are less meaningful in settings where processing thousands of samples is required to guide critical decisions quickly. Acoustic droplet ejection-open-port interface-mass spectrometry (ADE-OPI-MS) is a cutting-edge technology that eliminates the need for LC by introducing nanoliter-scale samples to an MS via acoustic ejection at speeds of <1 s per sample while minimizing matrix effects and data variability compared to more established HT sample introduction methods. Previously, ADE-OPI-MS has been demonstrated for purified protein standards in simple matrices, but its use on proteins within complex matrices remains underexplored. Biopharmaceutical samples often contain salts, buffers, and other components that make sample detection challenging without some form of sample cleanup. Herein, an integrated workflow combining sample preparation, detection, and quantification for ADE-OPI-MS is introduced, streamlining relative quantification of products spiked into complex matrices. Using this analytical framework, effective quantification of myoglobin, virus-like particle L1 protein, and monoclonal antibodies in complex cell lysate and drug process matrices is straightforward while also minimizing manual labor with automatable sample preparation capable of analyzing a full 384-well plate in under 12.5 min.

Noncanonical amino acids (ncAAs) are valuable building blocks for therapeutic design. Prolines are particularly useful because their cyclic cores can limit the conformational flexibility of a larger molecular framework, allowing such scaffolds to be further tuned to enhance engagement with their biological targets. Herein, we describe a convergent approach to synthesizing noncanonical prolines from readily available starting materials mediated by a tryptophan synthase β-subunit (TrpB)-imine reductase (IRED) cascade. In the first step, the TrpB catalyzes C−C bond formation between a ketone substrate and an l-serine- or l-threonine (l-Thr)-derived amino acrylate intermediate. In the second step, the IRED reduces the resulting cyclic imine, in some cases simultaneously setting two stereocenters via a dynamic kinetic resolution. With this one-pot, sequential cascade, we demonstrate the synthesis of mono-, bi-, and tricyclic prolines bearing as many as four chiral centers, including three examples that contain a remote desymmetrized stereocenter and one example featuring an l-Thr-derived, fully functionalized pyrrolidine ring. Furthermore, we show that a d-proline is formed from l-amino acid starting materials, which has not been observed in closed-shell tryptophan synthase catalysis previously. This cascade is a scalable, operationally simple method to synthesize new prolines, and is poised to expand the development of therapeutics featuring structurally complex ncAAs.

Historically, many compelling therapeutic targets have been accessible only by injectable biologic drugs. Macrocyclic peptides, such as the proprotein convertase subtilisin/kexin type 9 inhibitor enlicitide for the treatment of atherosclerotic cardiovascular disease, are beginning to unlock these targets to orally administered therapies to enable broader patient access. We report the convergent biocatalytic assembly of enlicitide from simple building blocks enabled by a suite of engineered enzymes to catalyze selective peptide fragment formation, coupling, and macrocyclization in a protecting group–free manner. Together with efficient crystallizations that obviate the need for chromatography, this approach reduces the number of steps by greater than half compared with prior state-of-the-art methods, addressing long-standing synthetic challenges and offering a sustainable blueprint for the scalable development of complex peptide therapeutics.

Antibody-drug conjugates are a promising class of therapeutics that offer targeted cancer treatments with fewer side effects. Optimizing the mAb, linker, payload, conjugation site, and drug-to-antibody ratio (DAR) are crucial for developing ADC candidates. However, assessing the influence of each factor on the higher-order structure (HOS) of the ADC remains challenging due to their complexity and heterogeneity, and the development of high-throughput workflows capable of detecting subtle changes in structure and stability would be advantageous. Here, we used ion mobility-mass spectrometry (IM-MS) and collision induced unfolding (CIU) to investigate the impact of linker-payload (LP) structure and conjugation strategy on the HOS and stability of ADCs. Site-specific conjugation to engineered cysteines revealed that LPs with different structures differentially affect the gas-phase stability of the Fc domain, and a correlation between gas-phase stability (CIU₅₀) and thermal stability (T_m) of the ADC was observed. Conjugation at interchain cysteine residues disrupted the HOS of the ADC to a greater extent compared to site-specific conjugates, as evidenced by higher root-mean-square deviation values. CIU data revealed differences in conformation and stability in ADCs with different DARs and different positional isomers with the same DAR. These findings demonstrate the utility of IM-MS and CIU as a high-throughput, information-rich assay for probing the HOS and stability of ADCs during their discovery and development.

Identifying and quantifying an active adjuvant along with its degradants in drug formulations is essential for ensuring the safety and efficacy of the drug product. QS-21 is a potent adjuvant that is being evaluated in several clinical trials and is currently formulated in licensed vaccines that protect against shingles, malaria, and RSV. In aqueous environments, QS-21 is subject to hydrolytic degradation that is influenced by pH and temperature, resulting in the formation of a degradant known as QS-21 Hydrolyzed Product, QS-21 HP, which can occur during manufacturing and/or prolonged storage. The intact QS-21 and QS-21 HP induce distinct immune response profiles, making it critical to monitor the degradation of QS-21 in vaccine adjuvant formulations. To date, there has been a paucity of reliable assays for QS-21, its isomers, and degradant QS-21 HP in liposomal adjuvant formulations available that can be transferred seamlessly in quality control (QC) environments. Herein, we introduce a simple and QC-friendly liquid chromatography coupled to a charged aerosol detector (LC-CAD) enabled by stationary phase screening combined with in silico method development optimization. The method exploits 2.7 µm fused-core phenyl hexyl particles, ensuring its versatility in standard and ultra-high pressure LC systems. This approach demonstrates a high correlation between predicted retention time (RT) and experimental outcomes with overall ∆RT <4%. In addition, this assay shows great linearity, precision, specificity, and accuracy to advance process development characterization of new vaccine formulations.

Liquid chromatography is a cornerstone analytical technique for separating, quantifying, and purifying components from complex mixtures. To accelerate method screening, we herein introduce an uncertainty-aware graph-based neural network that predicts retention times across multiple column chemistries and buffer pH conditions. Specifically, the multiple condition retention time model, MC-Retention, incorporates explicit column and buffer descriptors and is trained on a newly assembled data set produced by screening 480 analytes under eight chromatography conditions. By being able to accurately model multiple chromatographic methods simultaneously, MC-Retention can substantially reduce the time and resources required for LC method screening and development. With an aggregate R² of 0.86 and a mean absolute error (MAE) of 15.5 s during cross-validation, MC-Retention's respectable performance is greatly enhanced for analytes made present during training for one of the four column chemistries, when those analytes are otherwise not associated with the columns being validated. This selective training of analytes for a single column chemistry reduces error by 50%, with an R² of 0.95 and MAE of 8.2 s in aggregate. Additionally, we demonstrate that MC-Retention effectively identifies optimal conditions for separating amide bond-forming reaction components, while also supplying calibrated uncertainty estimates for its retention time predictions.

Noncanonical amino acids (ncAAs) are valuable building blocks for novel therapeutics. Prolines are particularly useful because their cyclic cores can limit the conformational flexibility of a larger molecular framework, allowing such scaffolds to be further tuned to enhance engagement with their biological targets. Herein, we describe a convergent approach to synthesizing noncanonical prolines from readily available starting materials mediated by a tryptophan synthase β-subunit (TrpB)-imine reductase (IRED) cascade. In the first step, the TrpB catalyzes ketone substrate activation and C–C bond formation with an L-serine- or L-threonine (L-Thr)-derived amino acrylate intermediate. In the second step, the IRED reduces the cyclic imine intermediate, in some cases simultaneously setting two stereocenters via a dynamic kinetic resolution. With this one-pot, sequential cascade, we demonstrate the synthesis of mono-, bi-, and tricyclic prolines bearing as many as four chiral centers, including three examples possessing a remote desymmetrized stereocenter and one example possessing an L-Thr-derived, fully functionalized pyrrolidine ring. Furthermore, we show that D-prolines are accessible from L-amino acid starting materials, which has not been observed in tryptophan synthase catalysis previously. This cascade is a scalable, operation-ally simple method to synthesize new prolines, and is poised to expand the development of novel therapeutics featuring structurally complex ncAAs.