Insulin purification-Innovation continuum via synthesis of fundamentals, technology, and modeling.

Advancement in all disciplines (art, science, education, and engineering) requires a careful balance of disruption and advancement of classical techniques. Often technologies are created with a limited understanding of fundamental principles and are prematurely abandoned. Over time, knowledge improves, new opportunities are identified, and technology is reassessed in a different light leading to a renaissance. Recovery of biological products is currently experiencing such a renaissance. Crystallization is one example of an elegant and ancient technology that has been applied in many fields and was employed to purify insulins from naturally occurring sources. Crystallization can also be utilized to determine protein structures. However, a multitude of parameters can impact protein crystallization and the "hit rate" for identifying protein crystals is relatively low, so much so that the development of a crystallization process is often viewed as a combination of art and science even today. Supplying the worldwide requirement for insulin (and associated variants) requires significant advances in process intensification to support scale of production and to minimize the overall cost to enable broader access. Expanding beyond insulin, the increasing complexity and diversity of biologics agents challenge the current purification methodologies. To harness the full potential of biologics, there is a need to fully explore a broader range of purification technologies, including nonchromatographic approaches. This impetus requires one to challenge and revisit the classical techniques including crystallization, chromatography, and filtration from a different vantage point and with a new set of tools, including molecular modeling. Fortunately, computational biophysics tools now exist to provide insights into mechanisms of protein/ligand interactions and molecular assembly processes (including crystallization) that can be used to support de novo process development. For example, specific regions or motifs of insulins and ligands can be identified and used as targets to support crystallization or purification development. Although the modeling tools have been developed and validated for insulin systems, the same tools can be applied to more complex modalities and to other areas including formulation, where the issue of aggregation and concentration-dependent oligomerization could be mechanistically modeled. This paper will illustrate a case study juxtaposing historical approaches to insulin downstream processes to a recent production process highlighting the application and evolution of technologies. Insulin production from Escherichia coli via inclusion bodies is an elegant example since it incorporates virtually all the unit operations associated with protein production-recovery of cells, lysis, solubilization, refolding, purification, and crystallization. The case study will include an example of an innovative application of existing membrane technology to combine three-unit operations into one, significantly reducing solids handling and buffer consumption. Ironically, a new separations technology was developed over the course of the case study that could further simplify and intensify the downstream process, emphasizing and highlighting the ever-accelerating pace of innovation in downstream processing. Molecular biophysics modeling was also employed to enhance the mechanistic understanding of the crystallization and purification processes.

Investigating protein-excipient interactions of a multivalent VHH therapeutic protein using NMR spectroscopy.

ALPHABETICAL LIST OF ABBREVIATIONS: Fab Fragment antigen-binding; Fc Fragment crystallizable; HMW High molecular weight; ∆HMW Difference between HMW species at stress temperature and 5°C controls; IgG Immunoglobulin G; mAbs Monoclonal antibodies; MV-VHH Multivalent VHH molecule with the format aC-L1-aC-L1-aD; NMR Nuclear magnetic resonance; scFv Single-chain fragment variable; SEC Size-exclusion chromatography; VHH Variable domain of Heavy chain of Heavy chain-only antibody.

Mechanistic insights on novel small molecule allosteric activators of cGMP-dependent protein kinase PKG1α.

cGMP-dependent protein kinase (PKG) represents a compelling drug target for treatment of cardiovascular diseases. PKG1 is the major effector of beneficial cGMP signaling which is involved in smooth muscle relaxation and vascular tone, inhibition of platelet aggregation and signaling that leads to cardioprotection. In this study, a novel piperidine series of activators previously identified from an ultrahigh-throughput screen were validated to directly bind partially activated PKG1α and subsequently enhance its kinase activity in a concentration-dependent manner. Compounds from initial optimization efforts showed an ability to activate PKG1α independent of the endogenous activator, cGMP. We demonstrate these small molecule activators mimic the effect of cGMP on the kinetic parameters of PKG1α by positively modulating the KM of the peptide substrate and negatively modulating the apparent KM for ATP with increase in catalytic efficiency, kcat. In addition, these compounds also allosterically modulate the binding affinity of cGMP for PKG1α by increasing the affinity of cGMP for the high-affinity binding site (CNB-A) and decreasing the affinity of cGMP for the low-affinity binding site (CNB-B). We show the mode of action of these activators involves binding to an allosteric site within the regulatory domain, near the CNB-B binding site. To the best of our knowledge, these are the first reported non-cGMP mimetic small molecules shown to directly activate PKG1α. Insights into the mechanism of action of these compounds will enable future development of cardioprotective compounds that function through novel modes of action for the treatment of cardiovascular diseases.

Discovery of Insulin Receptor Partial Agonists MK-5160 and MK-1092 as Novel Basal Insulins with Potential to Improve Therapeutic Index.

We have identified a series of novel insulin receptor partial agonists (IRPAs) with a potential to mitigate the risk of hypoglycemia associated with the use of insulin as an antidiabetic treatment. These molecules were designed as dimers of native insulin connected via chemical linkers of variable lengths with optional capping groups at the N-terminals of insulin chains. Depending on the structure, the maximal activation level (%Max) varied in the range of ∼20-70% of native insulin, and EC50 values remained in sub-nM range. Studies in minipig and dog demonstrated that IRPAs had sufficient efficacy to normalize plasma glucose levels in diabetes, while providing reduction of hypoglycemia risk. IRPAs had a prolonged duration of action, potentially making them suitable for once-daily dosing. Two lead compounds with %Max values of 30 and 40% relative to native insulin were selected for follow up studies in the clinic.

NMR Data-Driven Docking of HDM2-Inhibitor Complexes.

We present an automated NMR-guided docking workflow that can be used to generate models of protein-ligand complexes based on data from NOE NMR experiments. The first step is to generate a number of intermolecular distance constraints from experimental NOE data. Then, the ligand is docked on an ensemble of receptor structures to account for protein flexibility, and multiple poses are generated. Finally, we use the NOE-based constraints to filter and score docking poses based on the percentage of NOE constraints that are consistent with protein-ligand interatomic distances. This workflow was successfully used during a lead optimization project to generate models of synthetic protein-protein interaction (PPI) inhibitors bound to the HDM2 protein.

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.

Probing IgG1 FC-Multimodal Nanoparticle Interactions: A Combined Nuclear Magnetic Resonance and Molecular Dynamics Simulations Approach.

In this study, NMR and molecular dynamics simulations were employed to study IgG1 FC binding to multimodal surfaces. Gold nanoparticles functionalized with two multimodal cation-exchange ligands (Capto and Nuvia) were synthesized and employed to carry out solution-phase NMR experiments with the FC. Experiments with perdeuterated 15N-labeled FC and the multimodal surfaces revealed micromolar residue-level binding affinities as compared to millimolar binding affinities with these ligands in free solution, likely due to cooperativity and avidity effects. The binding of FC with the Capto ligand nanoparticles was concentrated near an aliphatic cluster in the CH2/CH3 interface, which corresponded to a focused hydrophobic region. In contrast, binding with the Nuvia ligand nanoparticles was more diffuse and corresponded to a large contiguous positive electrostatic potential region on the side face of the FC. Results with lower-ligand-density nanoparticles indicated a decrease in binding affinity for both systems. For the Capto ligand system, several aliphatic residues on the FC that were important for binding to the higher-density surface did not interact with the lower-density nanoparticles. In contrast, no significant difference was observed in the interacting residues on the FC to the high- and low-ligand density Nuvia surfaces. The binding affinities of FC to both multimodal-functionalized nanoparticles decreased in the presence of salt due to the screening of multiple weak interactions of polar and positively charged residues. For the Capto ligand nanoparticle system, this resulted in an even more focused hydrophobic binding region in the interface of the CH2 and CH3 domains. Interestingly, for the Nuvia ligand nanoparticles, the presence of salt resulted in a large transition from a diffuse binding region to the same focused binding region determined for Capto nanoparticles at 150 mM salt. Molecular dynamics simulations corroborated the NMR results and provided important insights into the molecular basis of FC binding to these different multimodal systems containing clustered (observed at high-ligand densities) and nonclustered ligand surfaces. This combined biophysical and simulation approach provided significant insights into the interactions of FC with multimodal surfaces and sets the stage for future analyses with even more complex biotherapeutics.

Identification of preferred multimodal ligand-binding regions on IgG1 FC using nuclear magnetic resonance and molecular dynamics simulations.

In this study, the binding of multimodal chromatographic ligands to the IgG1 FC domain were studied using nuclear magnetic resonance and molecular dynamics simulations. Nuclear magnetic resonance experiments carried out with chromatographic ligands and a perdeuterated 15 N-labeled FC domain indicated that while single-mode ion exchange ligands interacted very weakly throughout the FC surface, multimodal ligands containing negatively charged and aromatic moieties interacted with specific clusters of residues with relatively high affinity, forming distinct binding regions on the FC . The multimodal ligand-binding sites on the FC were concentrated in the hinge region and near the interface of the CH 2 and CH 3 domains. Furthermore, the multimodal binding sites were primarily composed of positively charged, polar, and aliphatic residues in these regions, with histidine residues exhibiting some of the strongest binding affinities with the multimodal ligand. Interestingly, comparison of protein surface property data with ligand interaction sites indicated that the patch analysis on FC corroborated molecular-level binding information obtained from the nuclear magnetic resonance experiments. Finally, molecular dynamics simulation results were shown to be qualitatively consistent with the nuclear magnetic resonance results and to provide further insights into the binding mechanisms. An important contribution to multimodal ligand-FC binding in these preferred regions was shown to be electrostatic interactions and π-π stacking of surface-exposed histidines with the ligands. This combined biophysical and simulation approach has provided a deeper molecular-level understanding of multimodal ligand-FC interactions and sets the stage for future analyses of even more complex biotherapeutics.

Biophysical and Immunological Characterization and In Vivo Pharmacokinetics and Toxicology in Nonhuman Primates of the Anti-PD-1 Antibody Pembrolizumab.

The programmed cell death 1 (PD-1) pathway represents a major immune checkpoint, which may be engaged by cells in the tumor microenvironment to overcome active T-cell immune surveillance. Pembrolizumab (Keytruda®, MK-3475) is a potent and highly selective humanized mAb of the IgG4/kappa isotype designed to directly block the interaction between PD-1 and its ligands, PD-L1 and PD-L2. This blockade enhances the functional activity of T cells to facilitate tumor regression and ultimately immune rejection. Pembrolizumab binds to human and cynomolgus monkey PD-1 with picomolar affinity and blocks the binding of human and cynomolgus monkey PD-1 to PD-L1 and PD-L2 with comparable potency. Pembrolizumab binds both the C'D and FG loops of PD-1. Pembrolizumab overcomes human and cynomolgus monkey PD-L1-mediated immune suppression in T-cell cultures by enhancing IL2 production following staphylococcal enterotoxin B stimulation of healthy donor and cancer patient cells, and IFNγ production in human primary tumor histoculture. Ex vivo and in vitro studies with human and primate T cells show that pembrolizumab enhances antigen-specific T-cell IFNγ and IL2 production. Pembrolizumab does not mediate FcR or complement-driven effector function against PD-1-expressing cells. Pembrolizumab displays dose-dependent clearance and half-life in cynomolgus monkey pharmacokinetic and toxicokinetic studies typical for human IgG4 antibodies. In nonhuman primate toxicology studies, no findings of toxicologic significance were observed. The preclinical data for pembrolizumab are consistent with the clinical anticancer activity and safety that has been demonstrated in human clinical trials.

Profiling Insulin Oligomeric States by 1H NMR Spectroscopy for Formulation Development of Ultra-Rapid-Acting Insulin.

Formulations that can increase the dissociation of insulin oligomers into monomers/dimers are important considerations in the development of ultra-rapid-acting insulins with faster onset and shorter duration of actions. Here we present a novel strategy to characterize the oligomeric states of insulin in solution that leverages the ability of nuclear magnetic resonance spectroscopy to assess higher-order structure of proteins in solution. The oligomeric structures and solution behaviors of 2 fast-acting insulins, aspart and lispro, with varying excipient concentrations were studied using 1D and diffusion profiling methods. These methods can provide insight on the structural differences and distributions of the molecular association states in different insulin formulations, which is consistent with other orthogonal biophysical characterization tools. In addition, these methods also highlight their sensitivity to subtle changes in solution behaviors in response to excipient that are difficult to monitor with other tools. This work introduces the utility of 1D and diffusion profiling methods to characterize the oligomeric assembly of fast-acting insulins, suggesting promising applications in compound screening, excipient selection, and formulation development of fast-acting insulins as well as other peptide or protein therapeutics.

NMR Assessment of Therapeutic Peptides and Proteins: Correlations That Reveal Interactions and Motions.

NMR measurements of rotational and translational diffusion are used to characterize the solution behavior of a wide variety of therapeutic proteins and peptides. The timescales of motions sampled in these experiments reveal complicated intrinsic solution behavior such as flexibility, that is central to function, as well as self-interactions, stress-induced conformational changes and other critical attributes that can be discovery and development liabilities. Trends from proton transverse relaxation (R2 ) and hydrodynamic radius (Rh ) are correlated and used to identify and differentiate intermolecular from intramolecular interactions. In this study, peptide behavior is consistent with complicated multimer self-assembly, while multi-domain protein behavior is dominated by intramolecular interactions. These observations are supplemented by simulations that include effects from slow transient interactions and rapid internal motions. R2 -Rh correlations provide a means to profile protein motions as well as interactions. The approach is completely general and can be applied to therapeutic and target protein characterization.

Diffusion Profiling of Therapeutic Proteins by Using Solution NMR Spectroscopy.

Characterizing changes to structure and behavior is an important aspect of therapeutic protein development. NMR spectroscopy is well suited to study interactions and higher-order structure that could impact biological function and safety. We used NMR diffusion methods to describe the overall behavior of proteins in solution by defining a "diffusion profile" that captures the complexities in diffusion behavior. Diffusion profiles offer a simple means to interpret protein solution behavior as a distribution of sizes and association states. As a characterization method, diffusion profiling is well suited to complement and augment traditional biophysical and NMR methods to probe the solution behavior of therapeutic proteins.

Discovery of Selective RNA-Binding Small Molecules by Affinity-Selection Mass Spectrometry.

Recent advances in understanding the relevance of noncoding RNA (ncRNA) to disease have increased interest in drugging ncRNA with small molecules. The recent discovery of ribocil, a structurally distinct synthetic mimic of the natural ligand of the flavin mononucleotide (FMN) riboswitch, has revealed the potential chemical diversity of small molecules that target ncRNA. Affinity-selection mass spectrometry (AS-MS) is theoretically applicable to high-throughput screening (HTS) of small molecules binding to ncRNA. Here, we report the first application of the Automated Ligand Detection System (ALIS), an indirect AS-MS technique, for the selective detection of small molecule-ncRNA interactions, high-throughput screening against large unbiased small-molecule libraries, and identification and characterization of novel compounds (structurally distinct from both FMN and ribocil) that target the FMN riboswitch. Crystal structures reveal that different compounds induce various conformations of the FMN riboswitch, leading to different activity profiles. Our findings validate the ALIS platform for HTS screening for RNA-binding small molecules and further demonstrate that ncRNA can be broadly targeted by chemically diverse yet selective small molecules as therapeutics.

NMR Binding and Functional Assays for Detecting Inhibitors of S. aureus MnaA.

Nonessential enzymes in the staphylococcal wall teichoic acid (WTA) pathway serve as highly validated ß-lactam potentiation targets. MnaA (UDP-GlcNAc 2-epimerase) plays an important role in an early step of WTA biosynthesis by providing an activated form of ManNAc. Identification of a selective MnaA inhibitor would provide a tool to interrogate the contribution of the MnaA enzyme in the WTA pathway as well as serve as an adjuvant to restore ß-lactam activity against methicillin-resistant Staphylococcus aureus (MRSA). However, development of an epimerase functional assay can be challenging since both MnaA substrate and product (UDP-GlcNAc/UDP-ManNAc) share an identical molecular weight. Herein, we developed a nuclear magnetic resonance (NMR) functional assay that can be combined with other NMR approaches to triage putative MnaA inhibitors from phenotypic cell-based screening campaigns. In addition, we determined that tunicamycin, a potent WTA pathway inhibitor, inhibits both S. aureus MnaA and a functionally redundant epimerase, Cap5P.

Discovery and Hit-to-Lead Optimization of Non-ATP Competitive MK2 (MAPKAPK2) Inhibitors.

A novel series of non-ATP-competitive MK2 inhibitors based on a furan-2-carboxyamide scaffold was discovered through high-throughput screening using the affinity selection-mass spectrometry-based Automated Ligand Identification System platform. Medicinal chemistry efforts optimized the initial screening hit to leadlike compounds with significant improvements in biochemical and cellular potencies, while maintaining excellent kinase selectivity and in vitro pharmacokinetic properties. Biophysical and biochemical studies confirmed the unique non-ATP-competitive binding mode of this series and suggested that highly selective inhibitors of MK2 should be feasible by targeting the outside ATP pocket.

Screening of protein kinases by ATP-STD NMR spectroscopy.

ATP-STD NMR takes advantage of Mg2+ binding to ATP to adjust the ATP affinity for protein kinases permitting a wide range of Ki's to be determined for ATP competitive ligands. Substituting Mn2+ for Mg2+ creates a paramagnetic probe (MnATP) from which the proximity of non-ATP competitive ligands can be inferred. Internal standards and references are used to reduce false positives due to protein or compound degradation. Use of the natural ATP ligand confers active site-specificity that is not available a priori from other ligand binding experiments.

Non-peptidic small-molecule inhibitors of the single-chain hepatitis C virus NS3 protease/NS4A cofactor complex discovered by structure-based NMR screening.

NMR-based screening of a customized fragment library identified 16 small-molecule hits that bind weakly (K(D) approximately 100 microM to 10 mM) to substrate binding sites of the NS4A-bound NS3 protease of the hepatitis C virus (HCV). Analogues for five classes of NMR hits were evaluated by a combination of NMR and biochemical data yielding SAR and, in most cases, optimized hits with improved potencies (K(D) approximately K(I) approximately 40 microM to 1 mM). NMR chemical shift perturbation data were used to establish the binding location and orientation of the active site directed scaffolds in these five analogue series. Two of these scaffolds, which bind the enzyme at the proximal S1-S3 and S2' substrate binding sites, were linked together producing competitive inhibitors of the HCV NS3 protease with potencies in the micromolar range. This example illustrates that the low molecular weight scaffolds discovered from structure-based NMR screening can be optimized with focused structure-guided chemistry to produce potent nonpeptidic small-molecule inhibitors of the HCV NS3 protease.

A model analysis of costs of blood pressure destabilization and edema associated with rofecoxib and celecoxib among older patients with osteoarthritis and hypertension in a Medicare Choice population.

BACKGROUND: Economic analyses consider all costs relevant to the use of a particular treatment or treatments. Recently, head-to-head, randomized, controlled trials have shown a significantly higher incidence of blood pressure (BP) destabilization and clinically significant edema with rofecoxib than with celecoxib among older, hypertensive patients with osteoarthritis (OA). OBJECTIVE: The objective of this analysis was to estimate the COX-2 specific inhibitor medication costs, in addition to the costs of drugs and physicians' fees, for BP destabilization and clinically significant edema associated with the use of rofecoxib 25 mg QD and celecoxib 200 mg QD in patients with OA and hypertension in a Medicare Choice population (aged > or = 65 years). METHODS: A decision analysis model was constructed to determine the costs (from the payer's perspective) of treating patients in this population with either of the 2 regimens for 6 weeks. The analysis used pooled data from 2 recent, independently conducted, multicenter, double-blind, randomized, controlled trials of OA patients aged > or = 65 years with treated hypertension who received either celecoxib 200 mg QD or rofecoxib 25 mg QD for 6 weeks. In the individual trials, rofecoxib was associated with significantly higher rates of destabilized BP (P < 0.032 and P < 0.001) and edema (P < 0.01 and P = 0.045) than celecoxib. RESULTS: For a 100,000-member Medicare Choice population, an estimated 25,630 persons would have OA and hypertension (stages I-III), and an estimated 5126 of these patients would use celecoxib or rofecoxib. The estimated costs were 33,938 dollars (6.2%) higher if all hypertensive patients with OA were treated with rofecoxib rather than celecoxib for 6 weeks. The cost per day of use was 0.16 dollars less with celecoxib, and per-patient, per-month costs were 4.79 dollars lower. CONCLUSION: Celecoxib was a less costly treatment option than rofecoxib among OA patients with hypertension aged > or = 65 years, based on our model of the direct costs of COX-2 specific inhibitor therapy combined with those associated with physician monitoring and treatment of edema and BP destabilization.

Flexible lid to the p53-binding domain of human Mdm2: implications for p53 regulation.

The stabilization of p53 against Mdm2-mediated degradation is an important event in DNA damage response. Initial models of p53 stabilization focused on posttranslational modification of p53 that would disrupt the p53-Mdm2 interaction. The N-terminal regions of both p53 and Mdm2 are modified in vivo in response to cellular stress, suggesting that modifications to Mdm2 also may affect the p53-Mdm2 interaction. Our NMR studies of apo-Mdm2 have found that, in addition to Mdm2 residues 25-109 that form the well ordered p53-binding domain that was observed in the p52-Mdm2 complex, Mdm2 residues 16-24 form a lid that closes over the p53-binding site. The Mdm2 lid, which is strictly conserved in mammals, may help to stabilize apo-Mdm2. It also competes weakly with peptidic and nonpeptidic antagonists. Modifications to the Mdm2 lid may disrupt p53-Mdm2 binding leading to p53 stabilization. Mdm2 and Mdm4 possess nearly identical p53-binding domains but different lids suggesting that lid modifications may select for p53 binding.

Spatial localization of ligand binding sites from electron current density surfaces calculated from NMR chemical shift perturbations.

Rapid, accurate structure determination of protein-ligand complexes is an essential component in structure-based drug design. We have developed a method that uses NMR protein chemical shift perturbations to spatially localize a ligand when it is complexed with a protein. Chemical shift perturbations on the protein arise primarily from the close proximity of electron current density from the ligand. In our approach the location of the center of the electron current density for a ligand aromatic ring was approximated by a point-dipole, and dot densities were used to represent ligand positions that are allowed by the experimental data. The dot density is increased in the region of space that is consistent for the most data. A surface can be formed in regions of the highest dot density that correlates to the center of the ligand aromatic ring. These surfaces allow for the rapid evaluation of ligand binding, which is demonstrated on a model system and on real data from HCV NS3 protease and HCV NS3 helicase, where the location of ligand binding can be compared to that obtained from difference electron density from X-ray crystallography.