Imputation of sensory properties using deep learning.

Predicting the sensory properties of compounds is challenging due to the subjective nature of the experimental measurements. This testing relies on a panel of human participants and is therefore also expensive and time-consuming. We describe the application of a state-of-the-art deep learning method, Alchemite™, to the imputation of sparse physicochemical and sensory data and compare the results with conventional quantitative structure-activity relationship methods and a multi-target graph convolutional neural network. The imputation model achieved a substantially higher accuracy of prediction, with improvements in R2 between 0.26 and 0.45 over the next best method for each sensory property. We also demonstrate that robust uncertainty estimates generated by the imputation model enable the most accurate predictions to be identified and that imputation also more accurately predicts activity cliffs, where small changes in compound structure result in large changes in sensory properties. In combination, these results demonstrate that the use of imputation, based on data from less expensive, early experiments, enables better selection of compounds for more costly studies, saving experimental time and resources.

PF-06804103, A Site-specific Anti-HER2 Antibody-Drug Conjugate for the Treatment of HER2-expressing Breast, Gastric, and Lung Cancers.

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.

Site Selection: a Case Study in the Identification of Optimal Cysteine Engineered Antibody Drug Conjugates.

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.

Advances in the development of novel aggrecanase inhibitors.

IMPORTANCE OF THE FIELD: 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. AREAS COVERED IN THIS REVIEW: This article reviews patent applications containing compounds claimed to have aggrecanase inhibitory activity which were published from 2005 through August 2010. WHAT THE READER WILL GAIN: 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. TAKE HOME MESSAGE: 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.

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.

Development of QSAR models for microsomal stability: identification of good and bad structural features for rat, human and mouse microsomal stability.

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 Naïve 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.

Escape from flatland: increasing saturation as an approach to improving clinical success.

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.

Synthesis and pharmacological evaluation of aminopyrimidine series of 5-HT1A partial agonists.

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.

Direct oxa-Pictet-Spengler cyclization to the natural (3a,5)-trans-stereochemistry in the syntheses of (+)-7-deoxyfrenolicin B and (+)-7-deoxykalafungin.

The pyranonaphthoquinones (+)-7-deoxyfrenolicin B and (+)-7-deoxykalafungin were synthesized in four steps using an oxa-Pictet-Spengler cyclization that directly provided the natural (3a,5)-trans-substituted dihydronaphthopyrans with high diastereoselectivity. This outcome is in contrast to the unnatural (3a,5)-cis-substituted dihydronaphthopyrans reported under similar conditions for the syntheses of (+)-frenolicin B and (+)-kalafungin. Computational modeling is presented that provides insight into this unusual stereoselectivity.