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The approval of ado-trastuzumab emtansine (T-DM1) in HER2+ metastatic breast cancer validated HER2 as a target for HER2-specific antibody–drug conjugates (ADC). Despite its demonstrated clinical efficacy, certain inherent properties within T-DM1 hamper this compound from achieving the full potential of targeting HER2-expressing solid tumors with ADCs. Here, we detail the discovery of PF-06804103, an anti-HER2 ADC designed to have a widened therapeutic window compared with T-DM1. We utilized an empirical conjugation site screening campaign to identify the engineered ĸkK183C and K290C residues as those that maximized in vivo ADC stability, efficacy, and safety for a four drug–antibody ratio (DAR) ADC with this linker–payload combination. PF-06804103 incorporates the following novel design elements: (i) a new auristatin payload with optimized pharmacodynamic properties, (ii) a cleavable linker for optimized payload release and enhanced antitumor efficacy, and (iii) an engineered cysteine site–specific conjugation approach that overcomes the traditional safety liabilities of conventional conjugates and generates a homogenous drug product with a DAR of 4. PF-06804103 shows (i) an enhanced efficacy against low HER2-expressing breast, gastric, and lung tumor models, (ii) overcomes in vitro- and in vivo–acquired T-DM1 resistance, and (iii) an improved safety profile by enhancing ADC stability, pharmacokinetic parameters, and reducing off-target toxicities. Herein, we showcase our platform approach in optimizing ADC design, resulting in the generation of the anti-HER2 ADC, PF-06804103. The design elements of identifying novel sites of conjugation employed in this study serve as a platform for developing optimized ADCs against other tumor-specific targets.

As the antibody drug conjugate (ADC) community continues to shift towards site-specific conjugation technology, there is a growing need to understand how the site of conjugation impacts the biophysical and biological properties of an ADC. In order to address this need, we prepared a carefully selected series of engineered cysteine ADCs and proceeded to systematically evaluate their potency, stability, and PK exposure. The site of conjugation did not have a significant influence on the thermal stability and in vitro cytotoxicity of the ADCs. However, we demonstrate that the rate of cathepsin-mediated linker cleavage is heavily dependent upon site and is closely correlated with ADC hydrophobicity, thus confirming other recent reports of this phenomenon. Interestingly, conjugates with high rates of cathepsin-mediated linker cleavage did not exhibit decreased plasma stability. In fact, the major source of plasma instability was shown to be retro-Michael mediated deconjugation. This process is known to be impeded by succinimide hydrolysis, and thus, we undertook a series of mutational experiments demonstrating that basic residues located nearby the site of conjugation can be a significant driver of succinimide ring opening. Finally, we show that total antibody PK exposure in rat was loosely correlated with ADC hydrophobicity. It is our hope that these observations will help the ADC community to build “design rules” that will enable more efficient prosecution of next-generation ADC discovery programs.

Aggrecanases are members of a disintegrin and metalloprotease with thrombospondin motif family of zinc metalloproteases involved in the cleavage of aggrecan fragments in cartilage. Inhibition of aggrecanase activity in osteoarthritis (OA) patients should both provide symptomatic relief of OA pain as well as OA disease modification.This article reviews patent applications containing compounds claimed to have aggrecanase inhibitory activity which were published from 2005 through August 2010.Readers will be informed of the different classes of disclosed aggrecanase inhibitors and gain an understanding of how these series interact with the various components of the catalytic sites of these enzymes.Patenting in the area of aggrecanase inhibitors has been modest. Most of the patented chemical matter are lipophilic, acidic compounds with molecular mass (MM)400: properties that usually do not imbue good systemic compound exposure. Possibly due to these properties and poor exposure, there are no late state aggrecanase compounds in the clinic to our knowledge. The future development of lower MM, less acidic aggrecanase inhibitors with good pharmacokinetic profiles could increase activity in this field as aggrecanases are well-validated targets for diseases such as OA.

An efficient synthesis of an alkylphenyl ether based peptidomimetic is described. The compound mimics three key amino acids of omega-conotoxin MVIIA from the cone shell Conus magus and may provide an entry to the design of low molecular weight antagonists of N-type neuronal calcium channels.

We report the first large-scale systematic quantitative structure-activity relationship (QSAR) study of barbiturates, correlating molecular structures with anticonvulsant activity. To achieve this QSAR study, we devised a four-step strategy. In step 1, an optimal quantum mechanical technique for determining the geometry and shape (conformation) of barbiturates was ascertained; this is the AM1 semiempirical molecular orbital method. In step 2, the AM1 method was used to optimize the structures and molecular properties of 48 barbiturates with varying anticonvulsant activity. In step 3, discriminant analysis and regression analysis statistical calculations were used to correlate the molecular properties of the 48 analogues against maximal electroshock (MES) and subcutaneous metrazol (s.c.Met)-induced seizures. In step 4, the contribution of molecular electrostatic properties to barbiturate anticonvulsant activity was further refined by quantum mechanical derived molecular electrostatic potential (MEP) maps. Using this four-step strategy, we defined the pharmacophore, the portion of a molecule responsible for bioactivity, for anti-MES and anti-s.c.Met activity. For anti-s.c.Met activity, barbiturate lipophilicity and geometry are important considerations; for anti-MES activity, barbiturate topologic and electronic properties have increased relevance.

The story of kinase inhibitors as drugs is largely also the story of the interplay between kinase mutations and drug discovery for cancer.1 In 2001, the small molecule kinase inhibitor, imatinib mesylate (Gleevec, 5.1) was first approved for use in various leukemias in the United States.2 This drug ...

The optimization of the anticonvulsant activity of dihydropyridine calcium channel blockers (DHPs) requires suitable structure-activity studies, which in turn require reliable methods of conformational analysis. The utility of AM1, MNDO, and PM3 as methods of conformational analysis for the DHPs was critically assessed. Eighteen DHPs were fully optimized using AM1, MNDO, and PM3, and the results were compared with crystal geometries. AM1 was best suited to the modelling of DHP geometries, based on root mean square fit analysis and the treatment of specific functional groups. The performance of the three techniques was related to the corrective term of the core repulsion function of the semiempirical hamiltonians.

An efficient synthesis of an alkylphenyl ether based peptidomimetic is described. The compound mimics three key amino acids of omega-conotoxin MVIIA from the cone shell Conus magus and may provide an entry to the design of low molecular weight antagonists of N-type neuronal calcium channels.

Omega-conotoxin MVIIA, a highly potent antagonist of the N-type voltage sensitive calcium channel, has shown utility in several models of pain and ischemia. We report a series of three alkylphenyl ether based analogues which mimic three key amino acids of the toxin. Two of the compounds have been found to exhibit IC50 values of 2.7 and 3.3 μM at the human N-type voltage sensitive calcium channel.

The development and synthesis of anticonvulsant new chemical entities that are distinct from the cyclic ureides in current clinical use is a continuing neuropharmacologic priority. The design of neuronal specific dihydropyridines active at the L-type calcium channel protein represents a rational approach to this design problem. To provide the structural data required for the design of anticonvulsant dihydropyridines, an AM1 semi-empirical molecular orbital study has been undertaken. Forty-six dihydropyridine calcium channel antagonists have been fully optimized at the AM1 level. Each of the 46 analogues was considered in six conformations to provide a systematic evaluation of changes in ester and phenyl ring orientation. The calculational validity of the AM1 Hamiltonian when applied to dihydropyridines was demonstrated by comparing AM1-optimized structures to experimental (X-ray crystallographic) and abinitio molecular orbital (STO 3G basis set) geometries. For each dihydropyridine, 79 AM1-derived geometric and electronic descriptors were obtained. The resulting descriptor matrix comparing structural descriptors with biological activity was statistically reduced to provide regression and discriminant structure–activity models for dihydropyridine calcium channel antagonism.

The medicinal chemistry community has become increasingly aware of the value of tracking calculated physical properties such as molecular weight, topological polar surface area, rotatable bonds, and hydrogen bond donors and acceptors. We hypothesized that the shift to high-throughput synthetic practices over the past decade may be another factor that may predispose molecules to fail by steering discovery efforts toward achiral, aromatic compounds. We have proposed two simple and interpretable measures of the complexity of molecules prepared as potential drug candidates. The first is carbon bond saturation as defined by fraction sp(3) (Fsp(3)) where Fsp(3) = (number of sp(3) hybridized carbons/total carbon count). The second is simply whether a chiral carbon exists in the molecule. We demonstrate that both complexity (as measured by Fsp(3)) and the presence of chiral centers correlate with success as compounds transition from discovery, through clinical testing, to drugs. In an attempt to explain these observations, we further demonstrate that saturation correlates with solubility, an experimental physical property important to success in the drug discovery setting.

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.

High throughput microsomal stability assays have been widely implemented in drug discovery and many companies have accumulated experimental measurements for thousands of compounds. Such datasets have been used to develop in silico models to predict metabolic stability and guide the selection of promising candidates for synthesis. This approach has proven most effective when selecting compounds from proposed virtual libraries prior to synthesis. However, these models are not easily interpretable at the structural level, and thus provide little insight to guide traditional synthetic efforts. We have developed global classification models of rat, mouse and human liver microsomal stability using in-house data. These models were built with FCFP_6 fingerprints using a Naive Bayesian classifier within Pipeline Pilot. The test sets were correctly classified as stable or unstable with satisfying accuracies of 78, 77 and 75% for rat, human and mouse models, respectively. The prediction confidence was assigned using the Bayesian score to assess the applicability of the models. Using the resulting models, we developed a novel data mining strategy to identify structural features associated with good and bad microsomal stability. We also used this approach to identify structural features which are good for one species but bad for another. With these findings, the structure-metabolism relationships are likely to be understood faster and earlier in drug discovery.

The practice of virtual screening (VS) to identify chemical leads to known or novel targets is becoming a core function of the computational chemist within industry. By employing a range of techniques, when attempting to identify compounds with activity against a biological target, a small focused subset of a larger collection of compounds can be identified and tested, often with results much better than selecting a similar number of compounds at random. We will review the key methods available, their relative success, and provide practical insights into best practices and key gaps. We will also argue that the capability of VS methods has grown to a point where fuller integration with experimental methods, including HTS, could increase the effectiveness of both.

Aminopyrimidine 2 (4-(1-(2-(1H-indol-3-yl)ethyl)piperidin-3-yl)-N-cyclopropylpyrimidin-2-amine) emerged from a high throughput screen as a novel 5-HT(1A) agonist. This compound showed moderate potency for 5-HT(1A) in binding and functional assays, as well as moderate metabolic stability. Implementation of a strategy for improving metabolic stability by lowering the lipophilicity (cLogD) led to identification of methyl ether 31 (4-(1-(2-(1H-indol-3-yl)ethyl)piperidin-3-yl)-N-(2-methoxyethyl)pyrimidin-2-amine) as a substantially improved compound within the series.

An increasingly important component of medicinal chemistry research is the exploitation of high throughput chemistry technology. As these techniques are harnessed to the requirements of the bench chemist, the type of library design must also change to reflect the priorities associated with individual projects. Whereas library design for general screening purposed attempts to generate a diverse set of compounds, project-based library design has the goal of maximizing the number of compounds active at a given biological target. Furthermore, the design strategy and software tools change if the protein structure is known for the target. Studies on model systems have suggested a number of strategies that can enrich the active compounds in an array design. These methods use high performance computing as a filter to aid in compound library design.

Omega-conotoxin MVIIA, a highly potent antagonist of the N-type voltage sensitive calcium channel, has shown utility in several models of pain and ischemia. We report a series of three alkylphenyl ether based analogues which mimic three key amino acids of the toxin. Two of the compounds have been found to exhibit IC50 values of 2.7 and 3.3 μM at the human N-type voltage sensitive calcium channel.

Activation of poly(ADP-ribose) polymerase (PARP) is an important factor in controlling cell survival or death. As a consequence, therapeutic interventions with PARP-1 inhibitors are sought in different pathological conditions such as cancer, cardiovascular and inflammatory diseases, as well as brain ischemia. In the first part of this work, as a continuation of our efforts in the field, we report the design, synthesis and biological appraisal of novel potent PARP-1 inhibitors. A crystallization experiment is carried out to ascertain the mode of binding to PARP-1 of the most potent compound, namely 2-((dimethylamino)methyl)-9-hydroxythieno[2,3-c]isoquinolin-5(4H)-one (HYDAMTIQ), whilst molecular modeling studies are performed to infer the role of water molecules in ligand binding. In the second part of the work, we discuss the results of HYDAMTIQ in models of brain ischemia as well as its preliminary physicochemical and pharmacokinetic characterization. Collectively, the data obtained qualify HYDAMTIQ as a novel lead candidate for advancement to clinical settings of brain ischemia.