Adam I. Green

Bio: Adam I. Green is an academic researcher from University of Leeds. The author has contributed to research in topics: Drug discovery & Carbenoid. The author has an hindex of 3, co-authored 5 publications receiving 13 citations. Previous affiliations of Adam I. Green include University of Pennsylvania.

Focused Libraries for Epigenetic Drug Discovery: The Importance of Isosteres.

Abstract: Epigenetic drug discovery provides a wealth of opportunities for the discovery of new therapeutics but has been hampered by low hit rates, frequent identification of false-positives, and poor synthetic tractability. A key reason for this is that few screening collections consider the unique requirements of epigenetic targets despite significant medicinal chemistry interest. Here we analyze the suitability of some commercially available screening collections in the context of epigenetic drug discovery, with a particular focus on lysine post-translational modifications, and show that even privileged motifs found in U.S. Food and Drug Administration (FDA)-approved drugs are not present in these collections. We propose that the incorporation of epigenetic bioisosteres should become central in the design of new focused screening collections and highlight some opportunities for the development of synthetic methods which may improve the tractability of hit molecules.

Activity-Directed Synthesis of Inhibitors of the p53/hDM2 Protein-Protein Interaction

Abstract: Protein-protein interactions (PPIs) provide a rich source of potential targets for drug discovery and biomedical science research. However, the identification of structural-diverse starting points for discovery of PPI inhibitors remains a significant challenge. Activity-directed synthesis (ADS), a function-driven discovery approach, was harnessed in the discovery of the p53/hDM2 PPI. Over two rounds of ADS, 346 microscale reactions were performed, with prioritisation on the basis of the activity of the resulting product mixtures. Four distinct and novel series of PPI inhibitors were discovered that, through biophysical characterisation, were shown to have promising ligand efficiencies. It was thus shown that ADS can facilitate ligand discovery for a target that does not have a defined small-molecule binding site, and can provide distinctive starting points for the discovery of PPI inhibitors.

Computational Mapping of Dirhodium(II) Catalysts

Abstract: The chemistry of dirhodium(II) catalysts is highly diverse, and can enable the synthesis of many different molecular classes. A tool to aid in catalyst selection, independent of mechanism and reactivity, would therefore be highly desirable. Here, we describe the development of a database for dirhodium(II) catalysts that is based on the principal component analysis of DFT-calculated parameters capturing their steric and electronic properties. This database maps the relevant catalyst space, and may facilitate exploration of the reactivity landscape for any process catalysed by dirhodium(II) complexes. We have shown that one of the principal components of these catalysts correlates with the outcome (e.g. yield, selectivity) of a transformation used in a molecular discovery project. Furthermore, we envisage that this approach will assist the selection of more effective catalyst screening sets, and, hence, the data-led optimisation of a wide range of rhodium-catalysed transformations.

Efficient Approaches for the Synthesis of Diverse α-Diazo Amides

Abstract: Metal-catalysed carbenoid chemistry can be exploited for the synthesis of diverse ranges of small molecules from α-diazo carbonyl compounds. In this paper, three synthetic approaches to α-diazo amides are described, and their scope and limitations are determined. On the basis of these synthetic studies, recommendations are provided to assist the selection of the most appropriate approach for specific classes of product. The availability of practical and efficient syntheses of diverse α-diazo acetamides is expected to facilitate the discovery of many different classes of bioactive small molecules.

Photochemical synthesis of an epigenetic focused tetrahydroquinoline library

Abstract: Discovery of epigenetic chemical probes is an important area of research with potential to deliver drugs for a multitude of diseases. However, commercially available libraries frequently used in drug discovery campaigns contain molecules that are focused on a narrow range of chemical space primarily driven by ease of synthesis and previously targeted enzyme classes (e.g., kinases) resulting in low hit rates for epigenetic targets. Here we describe the design and synthesis of a compound collection that augments current screening collections by the inclusion of privileged isosteres for epigenetic targets.

Building a Toolbox for the Analysis and Prediction of Ligand and Catalyst Effects in Organometallic Catalysis.

Abstract: Computers have become closely involved with most aspects of modern life, and these developments are tracked in the chemical sciences Recent years have seen the integration of computing across chemical research, made possible by investment in equipment, software development, improved networking between researchers, and rapid growth in the application of predictive approaches to chemistry, but also a change of attitude rooted in the successes of computational chemistry-it is now entirely possible to complete research projects where computation and synthesis are cooperative and integrated, and work in synergy to achieve better insights and improved results It remains our ambition to put computational prediction before experiment, and we have been working toward developing the key ingredients and workflows to achieve thisThe ability to precisely tune selectivity along with high catalyst activity make organometallic catalysts using transition metal (TM) centers ideal for high-value-added transformations, and this can make them appealing for industrial applications However, mechanistic variations of TM-catalyzed reactions across the vast chemical space of different catalysts and substrates are not fully explored, and such an exploration is not feasible with current resources This can lead to complete synthetic failures when new substrates are used, but more commonly we see outcomes that require further optimization, such as incomplete conversion, insufficient selectivity, or the appearance of unwanted side products These processes consume time and resources, but the insights and data generated are usually not tied to a broader predictive workflow where experiments test hypotheses quantitatively, reducing their impactThese failures suggest at least a partial deviation of the reaction pathway from that hypothesized, hinting at quite complex mechanistic manifolds for organometallic catalysts that are affected by the combination of input variables Mechanistic deviation is most likely when challenging multifunctional substrates are being used, and the quest for so-called privileged catalysts is quickly replaced by a need to screen catalyst libraries until a new "best" match between the catalyst and substrate can be identified and the reaction conditions can be optimized As a community we remain confined to broad interpretations of the substrate scope of new catalysts and focus on small changes based on idealized catalytic cycles rather than working toward a "big data" view of organometallic homogeneous catalysis with routine use of predictive models and transparent data sharingDatabases of DFT-calculated steric and electronic descriptors can be built for such catalysts, and we summarize here how these can be used in the mapping, interpretation, and prediction of catalyst properties and reactivities Our motivation is to make these databases useful as tools for synthetic chemists so that they challenge and validate quantitative computational approaches In this Account, we demonstrate their application to different aspects of catalyst design and discovery and their integration with computational mechanistic studies and thus describe the progress of our journey toward truly predictive models in homogeneous organometallic catalysis

Natural product-informed exploration of chemical space to enable bioactive molecular discovery.

Abstract: The search for new bioactive molecules remains an open challenge limiting our ability to discover new drugs to treat disease and chemical probes to comprehensively study biological processes. The vastness of chemical space renders its exploration unfeasible by synthesis alone. Historically, chemists have tended to explore chemical space unevenly without committing to systematic frameworks for navigation. This minireview covers a range of approaches that take inspiration from the structure or origin of natural products, and help focus molecular discovery on biologically-relevant regions of chemical space. All these approaches have enabled the discovery of distinctive and novel bioactive small molecules such as useful chemical probes of biological mechanisms. This minireview comments on how such approaches may be developed into more general frameworks for the systematic identification of currently unexplored regions of biologically-relevant chemical space, a challenge that is central to both chemical biology and medicinal chemistry.