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.

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.

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.

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.

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.

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.

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.