Consensus Virtual Screening Identified [1,2,4]Triazolo[1,5-b]isoquinolines As MELK Inhibitor Chemotypes.

Maternal Embryonic Leucine-zipper Kinase (MELK) is a current oncotarget involved in a diverse range of human cancers, with the usage of MELK inhibitors being explored clinically. Here, we aimed to discover new MELK inhibitor chemotypes from our in-house compound library with a consensus-based virtual screening workflow, employing three screening concepts. After careful retrospective validation, prospective screening and in vitro enzyme inhibition testing revealed a series of [1,2,4]triazolo[1,5-b]isoquinolines as a new structural class of MELK inhibitors, with the lead compound of the series exhibiting a sub-micromolar inhibitory activity. The structure-activity relationship of the series was explored by testing further analogs based on a structure-guided selection process. Importantly, the present work marks the first disclosure of the synthesis and bioactivity of this class of compounds.

Discovery of selective fragment-sized immunoproteasome inhibitors.

Proteasomes contribute to maintaining protein homeostasis and their inhibition is beneficial in certain types of cancer and in autoimmune diseases. However, the inhibition of the proteasomes in healthy cells leads to unwanted side-effects and significant effort has been made to identify inhibitors specific for the immunoproteasome, especially to treat diseases which manifest increased levels and activity of this proteasome isoform. Here, we report our efforts to discover fragment-sized inhibitors of the human immunoproteasome. The screening of an in-house library of structurally diverse fragments resulted in the identification of benzo[d]oxazole-2(3H)-thiones, benzo[d]thiazole-2(3H)-thiones, benzo[d]imidazole-2(3H)-thiones, and 1-methylbenzo[d]imidazole-2(3H)-thiones (with a general term benzoXazole-2(3H)-thiones) as inhibitors of the chymotrypsin-like (ß5i) subunit of the immunoproteasome. A subsequent structure-activity relationship study provided us with an insight regarding growing vectors. Binding to the ß5i subunit was shown and selectivity against the ß5 subunit of the constitutive proteasome was determined. Thorough characterization of these compounds suggested that they inhibit the immunoproteasome by forming a disulfide bond with the Cys48 available specifically in the ß5i active site. To obtain fragments with biologically more tractable covalent interactions, we performed a warhead scan, which yielded benzoXazole-2-carbonitriles as promising starting points for the development of selective immunoproteasome inhibitors with non-peptidic scaffolds.

Discovery of Immunoproteasome Inhibitors Using Large-Scale Covalent Virtual Screening.

Large-scale virtual screening of boronic acid derivatives was performed to identify nonpeptidic covalent inhibitors of the ß5i subunit of the immunoproteasome. A hierarchical virtual screening cascade including noncovalent and covalent docking steps was applied to a virtual library of over 104,000 compounds. Then, 32 virtual hits were selected, out of which five were experimentally confirmed. Biophysical and biochemical tests showed micromolar binding affinity and time-dependent inhibitory potency for two compounds. These results validate the computational protocol that allows the screening of large compound collections. One of the lead-like boronic acid derivatives identified as a covalent immunoproteasome inhibitor is a suitable starting point for chemical optimization.

Binary similarity measures for fingerprint analysis of qualitative metabolomic profiles.

INTRODUCTION: Contemporary metabolomic fingerprinting is based on multiple spectrometric and chromatographic signals, used either alone or combined with structural and chemical information of metabolic markers at the qualitative and semiquantitative level. However, signal shifting, convolution, and matrix effects may compromise metabolomic patterns. Recent increase in the use of qualitative metabolomic data, described by the presence (1) or absence (0) of particular metabolites, demonstrates great potential in the field of metabolomic profiling and fingerprint analysis. OBJECTIVES: The aim of this study is a comprehensive evaluation of binary similarity measures for the elucidation of patterns among samples of different botanical origin and various metabolomic profiles. METHODS: Nine qualitative metabolomic data sets covering a wide range of natural products and metabolomic profiles were applied to assess 44 binary similarity measures for the fingerprinting of plant extracts and natural products. The measures were analyzed by the novel sum of ranking differences method (SRD), searching for the most promising candidates. RESULTS: Baroni-Urbani-Buser (BUB) and Hawkins-Dotson (HD) similarity coefficients were selected as the best measures by SRD and analysis of variance (ANOVA), while Dice (Di1), Yule, Russel-Rao, and Consonni-Todeschini 3 ranked the worst. ANOVA revealed that concordantly and intermediately symmetric similarity coefficients are better candidates for metabolomic fingerprinting than the asymmetric and correlation based ones. The fingerprint analysis based on the BUB and HD coefficients and qualitative metabolomic data performed equally well as the quantitative metabolomic profile analysis. CONCLUSION: Fingerprint analysis based on the qualitative metabolomic profiles and binary similarity measures proved to be a reliable way in finding the same/similar patterns in metabolomic data as that extracted from quantitative data.

Structure-based Virtual Screening Approaches in Kinase-directed Drug Discovery.

Protein kinases are one of the most targeted protein families in current drug discovery pipelines. They are implicated in many oncological, inflammatory, CNS-related and other clinical indications. Virtual screening is a computational technique with a diverse set of available tools that has been shown many times to provide novel starting points for kinase-directed drug discovery. This review starts with a concise overview of the function, structural features and inhibitory mechanisms of protein kinases. In addition to briefly reviewing the practical aspects of structure-based virtual screenings, we discuss several case studies to illustrate the state of the art in the virtual screening for type I, type II, allosteric (type III-V) and covalent (type VI) kinase inhibitors. With this review, we strive to provide a summary of the latest advances in the structure-based discovery of novel kinase inhibitors, as well as a practical tool to anyone who wishes to embark on such an endeavor.

Ensemble docking-based virtual screening yields novel spirocyclic JAK1 inhibitors.

Small molecule inhibition of Janus kinases (JAKs) has been demonstrated as a viable strategy for the treatment of various inflammatory conditions and continues to emerge in cancer-related indications. In this study, a large supplier database was screened to identify novel chemistry starting points for JAK1. The docking-based screening was followed up by testing ten hit compounds experimentally, out of which five have displayed single-digit micromolar and submicromolar IC50 values on JAK1. Thus, the study was concluded with the discovery of five novel JAK inhibitors from a tiny screening deck with a remarkable hitrate of 50%. The results have highlighted spirocyclic pyrrolopyrimidines with submicromolar JAK1 IC50 values and a preference for JAK1 over JAK2 as potential starting points in developing a novel class of JAK1 inhibitors.

Discovery of Subtype Selective Janus Kinase (JAK) Inhibitors by Structure-Based Virtual Screening.

Janus kinase inhibitors represent a promising opportunity for the pharmaceutical intervention of various inflammatory and oncological indications. Subtype selective inhibition of these enzymes, however, is still a very challenging goal. In this study, a novel, customized virtual screening protocol was developed with the intention of providing an efficient tool for the discovery of subtype selective JAK2 inhibitors. The screening protocol involves protein ensemble-based docking calculations combined with an Interaction Fingerprint (IFP) based scoring scheme for estimating ligand affinities and selectivities, respectively. The methodology was validated in retrospective studies and was applied prospectively to screen a large database of commercially available compounds. Six compounds were identified and confirmed in vitro, with an indazole-based hit exhibiting promising selectivity for JAK2 vs JAK1. Having demonstrated that the described methodology is capable of identifying subtype selective chemical starting points with a favorable hit rate (11%), we believe that the presented screening concept can be useful for other kinase targets with challenging selectivity profiles.