A general approach to site-specific antibody drug conjugates.

Using an expanded genetic code, antibodies with site-specifically incorporated nonnative amino acids were produced in stable cell lines derived from a CHO cell line with titers over 1 g/L. Using anti-5T4 and anti-Her2 antibodies as model systems, site-specific antibody drug conjugates (NDCs) were produced, via oxime bond formation between ketones on the side chain of the incorporated nonnative amino acid and hydroxylamine functionalized monomethyl auristatin D with either protease-cleavable or noncleavable linkers. When noncleavable linkers were used, these conjugates were highly stable and displayed improved in vitro efficacy as well as in vivo efficacy and pharmacokinetic stability in rodent models relative to conventional antibody drug conjugates conjugated through either engineered surface-exposed or reduced interchain disulfide bond cysteine residues. The advantages of the oxime-bonded, site-specific NDCs were even more apparent when low-antigen-expressing (2+) target cell lines were used in the comparative studies. NDCs generated with protease-cleavable linkers demonstrated that the site of conjugation had a significant impact on the stability of these rationally designed prodrug linkers. In a single-dose rat toxicology study, a site-specific anti-Her2 NDC was well tolerated at dose levels up to 90 mg/kg. These experiments support the notion that chemically defined antibody conjugates can be synthesized in commercially relevant yields and can lead to antibody drug conjugates with improved properties relative to the heterogeneous conjugates formed by nonspecific chemical modification.

Peripheral Administration of a Long-Acting Peptide Oxytocin Receptor Agonist Inhibits Fear-Induced Freezing.

Oxytocin (OT) modulates the expression of social and emotional behaviors and consequently has been proposed as a pharmacologic treatment of psychiatric diseases, including autism spectrum disorders and schizophrenia; however, endogenous OT has a short half-life in plasma and poor permeability across the blood-brain barrier. Recent efforts have focused on the development of novel drug delivery methods to enhance brain penetration, but few efforts have aimed at improving its half-life. To explore the behavioral efficacy of an OT analog with enhanced plasma stability, we developed PF-06655075 (PF1), a novel non-brain-penetrant OT receptor agonist with increased selectivity for the OT receptor and significantly increased pharmacokinetic stability. PF-06478939 was generated with only increased stability to disambiguate changes to selectivity versus stability. The efficacy of these compounds in evoking behavioral effects was tested in a conditioned fear paradigm. Both central and peripheral administration of PF1 inhibited freezing in response to a conditioned fear stimulus. Peripheral administration of PF1 resulted in a sustained level of plasma concentrations for greater than 20 hours but no detectable accumulation in brain tissue, suggesting that plasma or cerebrospinal fluid exposure was sufficient to evoke behavioral effects. Behavioral efficacy of peripherally administered OT receptor agonists on conditioned fear response opens the door to potential peripheral mechanisms in other behavioral paradigms, whether they are mediated by direct peripheral activation or feed-forward responses. Compound PF1 is freely available as a tool compound to further explore the role of peripheral OT in behavioral response.

Stapled α-helical peptide drug development: a potent dual inhibitor of MDM2 and MDMX for p53-dependent cancer therapy.

Stapled α-helical peptides have emerged as a promising new modality for a wide range of therapeutic targets. Here, we report a potent and selective dual inhibitor of MDM2 and MDMX, ATSP-7041, which effectively activates the p53 pathway in tumors in vitro and in vivo. Specifically, ATSP-7041 binds both MDM2 and MDMX with nanomolar affinities, shows submicromolar cellular activities in cancer cell lines in the presence of serum, and demonstrates highly specific, on-target mechanism of action. A high resolution (1.7-Å) X-ray crystal structure reveals its molecular interactions with the target protein MDMX, including multiple contacts with key amino acids as well as a role for the hydrocarbon staple itself in target engagement. Most importantly, ATSP-7041 demonstrates robust p53-dependent tumor growth suppression in MDM2/MDMX-overexpressing xenograft cancer models, with a high correlation to on-target pharmacodynamic activity, and possesses favorable pharmacokinetic and tissue distribution properties. Overall, ATSP-7041 demonstrates in vitro and in vivo proof-of-concept that stapled peptides can be developed as therapeutically relevant inhibitors of protein-protein interaction and may offer a viable modality for cancer therapy.

Development of an informatics platform for therapeutic protein and peptide analytics.

The momentum gained by research on biologics has not been met yet with equal thrust on the informatics side. There is a noticeable lack of software for data management that empowers the bench scientists working on the development of biologic therapeutics. SARvision|Biologics is a tool to analyze data associated with biopolymers, including peptides, antibodies, and protein therapeutics programs. The program brings under a single user interface tools to filter, mine, and visualize data as well as those algorithms needed to organize sequences. As part of the data-analysis tools, we introduce two new concepts: mutation cliffs and invariant maps. Invariant maps show the variability of properties when a monomer is maintained constant in a position of the biopolymer. Mutation cliff maps draw attention to pairs of sequences where a single or limited number of point mutations elicit a large change in a property of interest. We illustrate the program and its applications using a peptide data set collected from the literature.

Discovery of Sulanemadlin (ALRN-6924), the First Cell-Permeating, Stabilized α-Helical Peptide in Clinical Development.

We report the discovery of sulanemadlin (ALRN-6924), the first cell-permeating, stabilized α-helical peptide to enter clinical trials. ALRN-6924 is a "stapled peptide" that mimics the N-terminal domain of the p53 tumor suppressor protein. It binds with high affinity to both MDM2 and MDMX (also known as MDM4), the endogenous inhibitors of p53, to activate p53 signaling in cells having a non-mutant, or wild-type TP53 genotype (TP53-WT). Iterative structure-activity optimization endowed ALRN-6924 with favorable cell permeability, solubility, and pharmacokinetic and safety profiles. Intracellular proteolysis of ALRN-6924 forms a long-acting active metabolite with potent MDM2 and MDMX binding affinity and slow dissociation kinetics. At high doses, ALRN-6924 exhibits on-mechanism anticancer activity in TP53-WT tumor models. At lower doses, ALRN-6924 transiently arrests the cell cycle in healthy tissues to protect them from chemotherapy without protecting the TP53-mutant cancer cells. These results support the continued clinical evaluation of ALRN-6924 as an anticancer and chemoprotection agent.

Synthesis and biological evaluation of ((4-keto)-phenoxy)methyl biphenyl-4-sulfonamides: a class of potent aggrecanase-1 inhibitors.

The prevention of aggrecan (a key component of cartilage) cleavage via the inhibition of aggrecanase-1 may provide a unique opportunity to stop the progression of cartilage degradation in osteoarthritis. The evaluation of a series of biphenylsulfonamides resulted in the identification of the ((4-keto)-phenoxy)methyl biphenyl-4-sulfonamides analogs (19-21 and 24) with improved Agg-1 inhibition and MMP-2, MMP-13 activity.

The Role of Bridging Water and Hydrogen Bonding as Key Determinants of Noncovalent Protein-Carbohydrate Recognition.

Mechanisms of protein-carbohydrate recognition attract a lot of interest due to their roles in various cellular processes and metabolism disorders. We have performed a large-scale analysis of protein structures solved in complex with glucose, galactose and their substituted analogues. We found that, on average, sugar molecules establish five hydrogen bonds (HBs) in the binding site, including one to three HBs with bridging water molecules. The free energy contribution of bridging and direct HBs was estimated using the free energy perturbation (FEP+) methodology for mono- and disaccharides that bind to l-ABP, ttGBP, TrmB, hGalectin-1 and hGalectin-3. We show that removing hydroxy groups that are engaged in direct HBs with the charged groups of Asp, Arg and Glu residues, protein backbone amide or buried water dramatically decreases binding affinity. In contrast, all solvent-exposed hydroxy groups and hydroxy groups engaged in HBs with the solvent-exposed bridging water molecules contribute weakly to binding affinity and so can be replaced to optimize ligand potency. Finally, we rationalize an effect of binding site water replacement on the binding affinity to l-ABP.

Modeling mutations in protein structures.

We describe an automated method for the modeling of point mutations in protein structures. The protein is represented by all non-hydrogen atoms. The scoring function consists of several types of physical potential energy terms and homology-derived restraints. The optimization method implements a combination of conjugate gradient minimization and molecular dynamics with simulated annealing. The testing set consists of 717 pairs of known protein structures differing by a single mutation. Twelve variations of the scoring function were tested in three different environments of the mutated residue. The best-performing protocol optimizes all the atoms of the mutated residue, with respect to a scoring function that includes molecular mechanics energy terms for bond distances, angles, dihedral angles, peptide bond planarity, and non-bonded atomic contacts represented by Lennard-Jones potential, dihedral angle restraints derived from the aligned homologous structure, and a statistical potential for non-bonded atomic interactions extracted from a large set of known protein structures. The current method compares favorably with other tested approaches, especially when predicting long and flexible side-chains. In addition to the thoroughness of the conformational search, sampled degrees of freedom, and the scoring function type, the accuracy of the method was also evaluated as a function of the flexibility of the mutated side-chain, the relative volume change of the mutated residue, and its residue type. The results suggest that further improvement is likely to be achieved by concentrating on the improvement of the scoring function, in addition to or instead of increasing the variety of sampled conformations.

Lead optimization via high-throughput molecular docking.

Structure-based lead optimization approaches are increasingly playing a role in the drug-discovery process. Recent advances in 'high-throughput' molecular docking methods and examples of their successful use in lead optimization are reviewed. Measures of docking accuracy, scoring function comparisons, and consensus approaches are discussed. Differences in docking protocols typically used for lead optimization versus lead generation are highlighted; this section includes a discussion of the latest methods for the incorporation of protein flexibility. New approaches developed specifically for the design of combinatorial libraries as well as those designed or used for 'fragment' versus lead optimization are presented. Finally, potential future improvements to the technology are outlined.

Predicting the Effect of Amino Acid Single-Point Mutations on Protein Stability-Large-Scale Validation of MD-Based Relative Free Energy Calculations.

The stability of folded proteins is critical to their biological function and for the efficacy of protein therapeutics. Predicting the energetic effects of protein mutations can improve our fundamental understanding of structural biology, the molecular basis of diseases, and possible routes to addressing those diseases with biological drugs. Identifying the effect of single amino acid point mutations on the thermodynamic equilibrium between the folded and unfolded states of a protein can pinpoint residues of critical importance that should be avoided in the process of improving other properties (affinity, solubility, viscosity, etc.) and suggest changes at other positions for increasing stability in protein engineering. Multiple computational tools have been developed for in silico predictions of protein stability in recent years, ranging from sequence-based empirical approaches to rigorous physics-based free energy methods. In this work, we show that FEP+, which is a free energy perturbation method based on all-atom molecular dynamics simulations, can provide accurate thermal stability predictions for a wide range of biologically relevant systems. Significantly, the FEP+ approach, while originally developed for relative binding free energies of small molecules to proteins and not specifically fitted for protein stability calculations, performs well compared to other methods that were fitted specifically to predict protein stability. Here, we present the broadest validation of a rigorous free energy-based approach applied to protein stability reported to date: 700+ single-point mutations spanning 10 different protein targets. Across the entire data set, we correctly classify the mutations as stabilizing or destabilizing in 84% of the cases, and obtain statistically significant predictions as compared with experiment [average error of ~1.6kcal/mol and coefficient of determination (R2) of 0.40]. This study demonstrates, for the first time in a large-scale validation, that rigorous free energy calculations can be used to predict changes in protein stability from point mutations without parameterization or system-specific customization, although further improvements should be possible with additional sampling and a better representation of the unfolded state of the protein. Here, we describe the FEP+ method as applied to protein stability calculations, summarize the large-scale retrospective validation results, and discuss limitations of the method, along with future directions for further improvements.

Generation of specific inhibitors of SUMO-1- and SUMO-2/3-mediated protein-protein interactions using Affimer (Adhiron) technology.

Because protein-protein interactions underpin most biological processes, developing tools that target them to understand their function or to inform the development of therapeutics is an important task. SUMOylation is the posttranslational covalent attachment of proteins in the SUMO family (SUMO-1, SUMO-2, or SUMO-3), and it regulates numerous cellular pathways. SUMOylated proteins are recognized by proteins with SUMO-interaction motifs (SIMs) that facilitate noncovalent interactions with SUMO. We describe the use of the Affimer system of peptide display for the rapid isolation of synthetic binding proteins that inhibit SUMO-dependent protein-protein interactions mediated by SIMs both in vitro and in cells. Crucially, these synthetic proteins did not prevent SUMO conjugation either in vitro or in cell-based systems, enabling the specific analysis of SUMO-mediated protein-protein interactions. Furthermore, through structural analysis and molecular modeling, we explored the molecular mechanisms that may underlie their specificity in interfering with either SUMO-1-mediated interactions or interactions mediated by either SUMO-2 or SUMO-3. Not only will these reagents enable investigation of the biological roles of SUMOylation, but the Affimer technology used to generate these synthetic binding proteins could also be exploited to design or validate reagents or therapeutics that target other protein-protein interactions.

Fragment-based drug design.

Fragment-based drug design (FBDD), which is comprised of both fragment screening and the use of fragment hits to design leads, began more than 15 years ago and has been steadily gaining in popularity and utility. Its origin lies on the fact that the coverage of chemical space and the binding efficiency of hits are directly related to the size of the compounds screened. Nevertheless, FBDD still faces challenges, among them developing fragment screening libraries that ensure optimal coverage of chemical space, physical properties and chemical tractability. Fragment screening also requires sensitive assays, often biophysical in nature, to detect weak binders. In this chapter we will introduce the technologies used to address these challenges and outline the experimental advantages that make FBDD one of the most popular new hit-to-lead process.

A structural informatics approach to mine kinase knowledge bases.

In this paper, we describe a combination of structural informatics approaches developed to mine data extracted from existing structure knowledge bases (Protein Data Bank and the GVK database) with a focus on kinase ATP-binding site data. In contrast to existing systems that retrieve and analyze protein structures, our techniques are centered on a database of ligand-bound geometries in relation to residues lining the binding site and transparent access to ligand-based SAR data. We illustrate the systems in the context of the Abelson kinase and related inhibitor structures.

A protein relational database and protein family knowledge bases to facilitate structure-based design analyses.

The Protein Data Bank is the most comprehensive source of experimental macromolecular structures. It can, however, be difficult at times to locate relevant structures with the Protein Data Bank search interface. This is particularly true when searching for complexes containing specific interactions between protein and ligand atoms. Moreover, searching within a family of proteins can be tedious. For example, one cannot search for some conserved residue as residue numbers vary across structures. We describe herein three databases, Protein Relational Database, Kinase Knowledge Base, and Matrix Metalloproteinase Knowledge Base, containing protein structures from the Protein Data Bank. In Protein Relational Database, atom-atom distances between protein and ligand have been precalculated allowing for millisecond retrieval based on atom identity and distance constraints. Ring centroids, centroid-centroid and centroid-atom distances and angles have also been included permitting queries for pi-stacking interactions and other structural motifs involving rings. Other geometric features can be searched through the inclusion of residue pair and triplet distances. In Kinase Knowledge Base and Matrix Metalloproteinase Knowledge Base, the catalytic domains have been aligned into common residue numbering schemes. Thus, by searching across Protein Relational Database and Kinase Knowledge Base, one can easily retrieve structures wherein, for example, a ligand of interest is making contact with the gatekeeper residue.

CONFIRM: connecting fragments found in receptor molecules.

A novel algorithm for the connecting of fragment molecules is presented and validated for a number of test systems. Within the CONFIRM (Connecting Fragments Found in Receptor Molecules) approach a pre-prepared library of bridges is searched to extract those which match a search criterion derived from known experimental or computational binding information about fragment molecules within a target binding site. The resulting bridge 'hits' are then connected, in an automated fashion, to the fragments and docked into the target receptor. Docking poses are assessed in terms of root-mean-squared deviation from the known positions of the fragment molecules, as well as docking score should known inhibitors be available. The creation of the bridge library, the full details and novelty of the CONFIRM algorithm, and the general applicability of this approach within the field of fragment-based de novo drug design are discussed.

Design and synthesis of 3,3-piperidine hydroxamate analogs as selective TACE inhibitors.

Structure-based methods were used to design beta-sulfone 3,3-piperidine hydroxamates as TACE inhibitors with the aim of improving selectivity for TACE versus MMP-13. Several compounds in this series were synthesized and evaluated in enzymatic and cell-based assays. These analogs exhibit excellent in vitro potency against isolated TACE enzyme and show good selectivity for TACE over the related metalloproteases MMP-2, -13, and -14.

Functional, biophysical, and structural bases for antibacterial activity of tigecycline.

Tigecycline is a novel glycylcycline antibiotic that possesses broad-spectrum activity against many clinically relevant species of bacterial pathogens. The mechanism of action of tigecycline was delineated using functional, biophysical, and molecular modeling experiments in this study. Functional assays showed that tigecycline specifically inhibits bacterial protein synthesis with potency 3- and 20-fold greater than that of minocycline and tetracycline, respectively. Biophysical analyses demonstrated that isolated ribosomes bind tigecycline, minocycline, and tetracycline with dissociation constant values of 10(-8), 10(-7), and >10(-6) M, respectively. A molecular model of tigecycline bound to the ribosome was generated with the aid of a 3.40-angstrom resolution X-ray diffraction structure of the 30S ribosomal subunit from Thermus thermophilus. This model places tigecycline in the A site of the 30S subunit and involves substantial interactions with residues of H34 of the ribosomal subunit. These interactions were not observed in a model of tetracycline binding. Modeling data were consistent with the biochemical and biophysical data generated in this and other recent studies and suggested that tigecycline binds to bacterial ribosomes in a novel way that allows it to overcome tetracycline resistance due to ribosomal protection.