Edward Jolyon Griffen

Matched molecular pair analysis in drug discovery.

Multiple parameter optimisation in drug discovery is difficult, but Matched Molecular Pair Analysis (MMPA) can help. Computer algorithms can process data in an unbiased way to yield design rules and suggest better molecules, cutting the number of design cycles. The approach often makes more suggestions than can be processed manually and methods to deal with this are proposed. However, there is a paucity of contextually specific design rules, which would truly make the technique powerful. By combining extracted information from multiple sources there is an opportunity to solve this problem and advance medicinal chemistry in a matter of months rather than years.

WizePairZ: a novel algorithm to identify, encode, and exploit matched molecular pairs with unspecified cores in medicinal chemistry.

An algorithm to automatically identify and extract matched molecular pairs from a collection of compounds has been developed, allowing the learning associated with each molecular transformation to be readily exploited in drug discovery projects. Here, we present the application to an example data set of 11 histone deacetylase inhibitors. The matched pairs were identified, and corresponding differences in activity and lipophilicity were recorded. These property differences were associated with the chemical transformations encoded in the SMIRKS reaction notation. The transformations identified a subseries with the optimal balance of these two parameters. Enumeration of a virtual library of compounds using the extracted transformations identified two additional compounds initially excluded from the analysis with an accurate estimation of their biological activity. We describe how the WizePairZ system can be used to archive and apply medicinal chemistry knowledge from one drug discovery project to another as well as identify common bioisosteres.

DNA-dependent protein kinase (DNA-PK) inhibitors: Structure–activity relationships for O-alkoxyphenylchromen-4-one probes of the ATP-binding domain

Introduction of an O-alkoxyphenyl substituent at the 8-position of the 2-morpholino-4H-chromen-4-one pharmacophore enabled regions of the ATP-binding site of DNA-dependent protein kinase (DNA-PK) to be probed further. Structure-activity relationships have been elucidated for inhibition of DNA-PK and PI3K (p110α), with N-(2-(cyclopropylmethoxy)-4-(2-morpholino-4-oxo-4H-chromen-8-yl)phenyl)-2-morpholinoacetamide 11a being identified as a potent and selective DNA-PK inhibitor (IC(50)=8 nM).

An Orally Bioavailable, Indole-3-glyoxylamide Based Series of Tubulin Polymerization Inhibitors Showing Tumor Growth Inhibition in a Mouse Xenograft Model of Head and Neck Cancer

A number of indole-3-glyoxylamides have previously been reported as tubulin polymerization inhibitors, although none has yet been successfully developed clinically. We report here a new series of related compounds, modified according to a strategy of reducing aromatic ring count and introducing a greater degree of saturation, which retain potent tubulin polymerization activity but with a distinct SAR from previously documented libraries. A subset of active compounds from the reported series is shown to interact with tubulin at the colchicine binding site, disrupt the cellular microtubule network, and exert a cytotoxic effect against multiple cancer cell lines. Two compounds demonstrated significant tumor growth inhibition in a mouse xenograft model of head and neck cancer, a type of the disease which often proves resistant to chemotherapy, supporting further development of the current series as potential new therapeutics.

WizePairZ: A Novel Algorithm to Identify, Encode, and Exploit Matched Molecular Pairs with Unspecified Cores in Medicinal Chemistry

An algorithm to automatically identify and extract matched molecular pairs from a collection of compounds has been developed, allowing the learning associated with each molecular transformation to be readily exploited in drug discovery projects. Here, we present the application to an example data set of 11 histone deacetylase inhibitors. The matched pairs were identified, and corresponding differences in activity and lipophilicity were recorded. These property differences were associated with the chemical transformations encoded in the SMIRKS reaction notation. The transformations identified a subseries with the optimal balance of these two parameters. Enumeration of a virtual library of compounds using the extracted transformations identified two additional compounds initially excluded from the analysis with an accurate estimation of their biological activity. We describe how the WizePairZ system can be used to archive and apply medicinal chemistry knowledge from one drug discovery project to another as well as identify common bioisosteres.

Can we accelerate medicinal chemistry by augmenting the chemist with Big Data and artificial intelligence

AI comes to lead optimization: medicinal chemistry in all disease areas can be accelerated by exploiting our pre-competitive knowledge in an unbiased way.

Turbocharging Matched Molecular Pair Analysis: Optimizing the Identification and Analysis of Pairs

We have applied the two most commonly used methods for automatic matched pair identification, obtained the optimum settings, and discovered that the two methods are synergistic. A turbocharging approach to matched pair analysis is advocated in which a first round (a conservative categorical approach that uses an analogy with coin flips, heads corresponding to an increase in a measured property, tails to a decrease, and a biased coin to a structural change that reliably causes a change in that property) provides the settings for a second round (which uses the magnitude of the change in properties). Increased chemical specificity allows reliable knowledge to be extracted from smaller sets of pairs, and an assay-specific upper limit can be placed on the number of pairs required before adequate sampling of variability has been achieved.

Matched Molecular Pair Analysis

The aim of this article is to highlight the areas in which matched molecular pair analysis has progressed in the last decade and new directions and challenges that are currently being addressed.