Contemporary Accounts in Drug Discovery and Development. Группа авторов

Figure 2.2 Structures of ND‐022 and ND‐630.

      2.3.2 Optimizing Selectivity in Lead Optimization for Tyrosine Kinase 2

      The Janus kinase (JAK) family, comprised of Janus kinase 1 (JAK1), Janus kinase 2 (JAK2), Janus kinase 3 (JAK3), and tyrosine kinase 2 (TYK2), controls a variety of inflammation pathways, which may be relevant to the treatment of autoimmune disorders such as psoriasis, inflammatory bowel disease, and rheumatoid arthritis [114]. A variety of drug therapies inhibit these kinases, including Ruxolitinib, Tofacitinib, Baricitinib, Fedratinib, and Upadacitinib [114–118]. However, significant side effects are sometimes observed with these therapies. For example, inhibition of JAK2 can lead to anemia, and inhibition of JAK1 and JAK3 can lead to increased risk of infection [112]. Interestingly, genome‐wide and phenome‐wide association studies suggest the safety profile of a TYK2 selective drug therapy might have an improved safety profile while remaining efficacious for the treatment of autoimmune disorders [119–121].

The preceding opportunity notwithstanding, designing a highly selective TYK2 inhibitor is a substantial challenge. The four Janus family kinases have a high degree of structural and sequence similarity, especially so in the active site regions of the receptors [112, 122] (Figure 2.3). This has led to very few selective TYK2 drug therapies being advanced into clinical trials [123]. Nimbus therapeutics' approach to solving this difficult challenge in late‐stage lead optimization was to employ rigorous physics‐based methods at an unprecedented scale, including free energy calculation‐based scoring of 4000 design ideas over a six month period to identify molecules predicted by the free energy calculations to be potent and selective inhibitors of TYK2 [112]. Of these 4000 evaluated compounds, 46 were advanced to synthesis and assay with 9 of the compounds meeting the targeted property profile. This computational modeling hit rate of 20% identifying satisfactory chemical matter should be viewed as outstanding given the difficulty of the challenge. Preclinical studies of several of these compounds further demonstrated outstanding efficacy in mouse model of psoriasis, and the discovery project has succeeded to advance a TYK2 inhibitor into clinical studies [112, 124].

Figure 2.3 Superimposed crystal structures of TYK2, JAK1, JAK2, and JAK3 cocrystalized with tofacitinib.

      Source: Reproduced with permission. Copyright© 2017, Elsevier [112].

      2.3.3 Discovery of Novel Allosteric Covalent Inhibitors of KRAS^G12C

KRAS mutations are widely observed in a variety of cancers [125]. The G12C mutation has received a great deal of recent attention, since it creates an allosteric pocket that can be exploited by covalent ligands to inactivate the protein [125]. Seeking to build on this growing body of work, researchers at Bayer Pharmaceuticals employed a modern computational approach to identify novel allosteric inhibitors, as depicted in Figure 2.4 [125]. In this workflow, seven million putative design ideas were first computationally enumerated and then advanced to a computational screening funnel where more approximate methods, i.e. pharmacophore analysis and MM‐GB/SA scoring, were used to reject unpromising design ideas, and then more accurate and computationally intensive methods, i.e. free energy calculations, were used to finalize those molecules which were advanced to synthesis. The results of this effort led to only four of the original seven million design ideas being designated for synthesis and assay. This effort led directly to the development of a novel congeneric series with KRAS^G12C activity, and may constitute an important step along the path of the discovery of KRAS‐targeted drug therapies.

Figure 2.4 (a) Inhibitors known to bind to the switch‐II pocket of KRAS^G12C. (b) Fragmentation of the inhibitor structure before enumeration, including a depiction of the nature and size of the used fragment libraries. (c) Enumeration and prioritization workflow [125].

      Source: Reproduced under the terms of the Creative Commons Attribution License.

      2.3.4 Supporting Hit to Lead Exploration for a Series of Phosphodiesterase 2A Inhibitors

Phosphodiesterase enzymes are important regulators of intracellular signal transduction and can be divided into 12 families [125–127]. Phosphodiesterase 2A (PDE2A) is expressed within the brain, and it is believed that inhibition of PDE2A may improve cognitive function [128, 129]. In order to exploit this emerging biology, researchers at Janssen Pharmaceutical utilized free energy calculations to optimize a hit compound identified in a high‐throughput experimental screen to a lead series suitable for advancement into lead optimization [130]. The initial hit compound was found to have an IC₅₀ value of 66 nM, but only an 8× selectivity versus antitarget PDE10A. As such, this hit compound was crystalized to facilitate a computational modeling drive design campaign where free energy calculations would be utilized to improve the properties of derivative molecules to establish a lead series suitable for initiation of lead optimization. During this campaign, 250 putative design ideas were scored with free energy calculations, and 100 of the top performing compounds were advanced to synthesis and assay (Figure 2.5). The calculations were found to be highly accurate with an R ² value of 0.57 and mean unsigned error of 0.79 kcal/mol. In some ways more important than the accuracy of the calculations, these modeling efforts lead directly to the identification of a lead compound with single digit nanomolar potency and 100× selectivity versus antitarget PDE10A (Figure 2.6). This lead compound was further shown to have in vivo target occupancy and was of sufficient quality to justify initiation of lead optimization.

Figure 2.5 Correlation of experimental and calculated binding activity (∂G) for the compounds synthesized

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