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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.

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.

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.

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.