De novo design of protein kinase inhibitors by in silico identification of hinge region-binding fragments

Modeling the Blood-Brain Barrier Permeability of Potential Heterocyclic Drugs via Biomimetic IAM Chromatography Technique Combined with QSAR Methodology

Penetration through the blood-brain barrier (BBB) is desirable in the case of potential pharmaceuticals acting on the central nervous system (CNS), but is undesirable in the case of drug candidates acting on the peripheral nervous system because it may cause CNS side effects. Therefore, modeling of the permeability across the blood-brain barrier (i.e., the logarithm of the brain to blood concentration ratio, log BB) of potential pharmaceuticals should be performed as early as possible in the preclinical phase of drug development. Biomimetic chromatography with immobilized artificial membrane (IAM) and the quantitative structure-activity relationship (QSAR) methodology were successful in modeling the blood-brain barrier permeability of 126 drug candidates, whose experimentally-derived lipophilicity indices and computationally-derived molecular descriptors (such as molecular weight (MW), number of rotatable bonds (NRB), number of hydrogen bond donors (HBD), number of hydrogen bond acceptors (HBA), topological polar surface area (TPSA), and polarizability (α)) varied by class. The QSARs model established by multiple linear regression showed a positive effect of the lipophilicity (log kw, IAM) and molecular weight of the compound, and a negative effect of the number of hydrogen bond donors and acceptors, on the log BB values. The model has been cross-validated, and all statistics indicate that it is very good and has high predictive ability. The simplicity of the developed model, and its usefulness in screening studies of novel drug candidates that are able to cross the BBB by passive diffusion, are emphasized.

How Ligands Interact with the Kinase Hinge

ATP-competitive kinase inhibitors form hydrogen bond interactions with the kinase hinge region at the adenine binding site. Thus, it is crucial to explore hinge-ligand recognition as part of a rational drug design strategy. Here, harnessing known ligand-bound kinase structures and experimental assay resources, we first created a kinase structure-assay database (KSAD) containing 2705 nM ligand-bound kinase complexes. Then, using KSAD, we systematically investigate hinge-ligand binding patterns using interaction fingerprints, thereby delineating 15 different hydrogen-bond interaction modes. We believe these results will be valuable for de novo drug design and/or scaffold hopping of kinase-targeted drugs.

Rational design of mini protein mimicking uricase: Encapsulation in ZIF-8 for uric acid detection

Five mini proteins mimicking uricase comprising 20, 40, 60, 80, and 100 amino acids were designed based on the conserved active site residues within the same dimer, using the crystal structure of tetrameric uricase from Arthrobacter globiformis (PDB ID: 2yzb) as a template. Based on molecular docking analysis, the smallest mini protein, mp20, shared similar residues to that of native uricase that formed hydrogen bonds with uric acid and was chosen for further studies. Although purified recombinant mp20 did not exhibit uricase activity, it showed specific binding towards uric acid and evinced excellent thermotolerance and structural stability at temperatures ranging from 10°C to 100°C, emulating its natural origin. To explore the potential of mp20 as a bioreceptor in uric acid sensing, mp20 was encapsulated within zeolitic imidazolate framework-8 (mp20@ZIF-8) followed by the modification on rGO-screen printed electrode (rGO/SPCE) to maintain the structural stability. An irreversible anodic peak and increased semicircular arcs of the Nyquist plot with an increase of the analyte concentrations were observed by utilizing cyclic voltammetry and electrochemical impedance spectroscopy (EIS), suggesting the detection of uric acid occurred, which is based on substrate-mp20 interaction.

KID: A Kinase-Focused Interaction Database and Its Application in the Construction of Kinase-Focused Molecule Databases

Protein kinases are important drug targets for the treatment of several diseases. The interaction between kinases and ligands is vital in the process of small-molecule kinase inhibitor (SMKI) design. In this study, we propose a method to extract fragments and amino acid residues from crystal structures for kinase-ligand interactions. In addition, core fragments that interact with the important hinge region of kinases were extracted along with their decorations. Based on the superimposed structural data of kinases from the kinase-ligand interaction fingerprint and structure database, we obtained two libraries, namely, a hinge-unfocused fragment-amino acid pair library (FAP Lib) that contains 6672 pairs of fragments and corresponding amino-acids, and a hinge-focused hinge binder library (HB Lib) of 3560 pairs of hinge-binding scaffolds with their corresponding decorations. These two libraries constitute a kinase-focused interaction database (KID). In depth analysis was conducted on KID to explore important characteristics of fragments in the design of SMKIs. With KID, we built two kinase-focused molecule databases, one called Recomb_DB, which contains 1,72,346 molecules generated through fragment recombination based on the FAP Lib, and another called RsdHB_DB, which contains 93,030 molecules generated based on our HB Lib using molecular generation methods. Compared with five databases both commercial and non-commercial, these two databases both ranked top 3 in scaffold diversity, top 4 in molecule fingerprint diversity, and are more focused on the chemical space of kinase inhibitors. Hence, KID presents a useful addition to existing databases for the exploration of novel SMKIs.

DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design

The field of machine learning for drug discovery is witnessing an explosion of novel methods. These methods are often benchmarked on simple physicochemical properties such as solubility or general druglikeness, which can be readily computed. However, these properties are poor representatives of objective functions in drug design, mainly because they do not depend on the candidate compound's interaction with the target. By contrast, molecular docking is a widely applied method in drug discovery to estimate binding affinities. However, docking studies require a significant amount of domain knowledge to set up correctly, which hampers adoption. Here, we present dockstring, a bundle for meaningful and robust comparison of ML models using docking scores. dockstring consists of three components: (1) an open-source Python package for straightforward computation of docking scores, (2) an extensive dataset of docking scores and poses of more than 260,000 molecules for 58 medically relevant targets, and (3) a set of pharmaceutically relevant benchmark tasks such as virtual screening or de novo design of selective kinase inhibitors. The Python package implements a robust ligand and target preparation protocol that allows nonexperts to obtain meaningful docking scores. Our dataset is the first to include docking poses, as well as the first of its size that is a full matrix, thus facilitating experiments in multiobjective optimization and transfer learning. Overall, our results indicate that docking scores are a more realistic evaluation objective than simple physicochemical properties, yielding benchmark tasks that are more challenging and more closely related to real problems in drug discovery.

O-methylated flavonol as a multi-kinase inhibitor of leukemogenic kinases exhibits a potential treatment for acute myeloid leukemia

BACKGROUND

Acute myeloid leukemia (AML) is a heterogeneous disease with poor overall survival characterized by various genetic changes. The continuous activation of oncogenic pathways leads to the development of drug resistance and limits current therapeutic efficacy. Therefore, a multi-targeting inhibitor may overcome drug resistance observed in AML treatment. Recently, groups of flavonoids, such as flavones and flavonols, have been shown to inhibit a variety of kinase activities, which provides potential opportunities for further anticancer applications.

PURPOSE

In this study, we evaluated the anticancer effects of flavonoid compounds collected from our in-house library and investigated their potential anticancer mechanisms by targeting multiple kinases for inhibition in AML cells.

METHODS

The cytotoxic effect of the compounds was detected by cell viability assays. The kinase inhibitory activity of the selected compound was detected by kinase-based and cell-based assays. The binding conformation and interactions were investigated by molecular docking analysis. Flow cytometry was used to evaluate the cell cycle distribution and cell apoptosis. The protein and gene expression were estimated by western blotting and qPCR, respectively.

RESULTS

In this study, an O-methylated flavonol (compound 11) was found to possess remarkable cytotoxic activity against AML cells compared to treatment in other cancer cell lines. The compound was demonstrated to act against multiple kinases, which play critical roles in survival signaling in AML, including FLT3, MNK2, RSK, DYRK2 and JAK2 with IC₅₀ values of 1 - 2 μM. Compared to our previous flavonoid compounds, which only showed inhibitions against MNKs or FLT3, compound 11 exhibited multiple kinase inhibitory abilities. Moreover, compound 11 showed effectiveness in inhibiting internal tandem duplications of FLT3 (FLT3-ITDs), which accounts for 25% of AML cases. The interactions between compound 11 and targeted kinases were investigated by molecular docking analysis. Mechanically, compound 11 caused dose-dependent accumulation of leukemic cells at the G₀/G₁ phase and followed by the cells undergoing apoptosis.

CONCLUSION

O-methylated flavonol, compound 11, can target multiple kinases, which may provide potential opportunities for the development of novel therapeutics for drug-resistant AMLs. This work provides a good starting point for further compound optimization.

Effective Reaction-Based De Novo Strategy for Kinase Targets: A Case Study on MERTK Inhibitors

Reaction-based de novo design is the computational generation of novel molecular structures by linking building blocks using reaction vectors derived from chemistry knowledge. In this work, we first adopted a recurrent neural network (RNN) model to generate three groups of building blocks with different functional groups and then constructed an in silico target-focused combinatorial library based on chemical reaction rules. Mer tyrosine kinase (MERTK) was used as a study case. Combined with a scaffold enrichment analysis, 15 novel MERTK inhibitors covering four scaffolds were achieved. Among them, compound 5a obtained an IC₅₀ value of 53.4 nM against MERTK without any further optimization. The efficiency of hit identification could be significantly improved by shrinking the compound library with the fragment iterative optimization strategy and enriching the dominant scaffold in the hinge region. We hope that this strategy can provide new insights for accelerating the drug discovery process.

Exploring nod factor receptors activation process in chickpea by bridging modelling, docking and molecular dynamics simulations

Plasma membrane-bound receptor proteins play crucial roles in the perception and further transmission of regulatory signals to modulate numerous developmental and metabolic events. Precise functioning and fine-tuning of Nod factor receptor (NFR) mediated signalling is a critical requirement for root nodule symbiosis. Here, we have identified, cloned and phylogenetically characterized chickpea NFR1 and NFR5, which are showing significant homology with other legume NFR receptors. Homology modelling and molecular dynamics simulations highlight the molecular structure of ligand binding ectodomains [EDs] and cytosolic kinase domains [KDs] of NFRs in chickpea. Our detailed structural analysis also revealed that both NFR1 and NFR5 share resemblance as well as dissimilarity in sequence, structure and substrate-binding pocket. Further, molecular docking simulations provide us adequate insights into the active site of receptors where the Nod factor (NF) binds. The outcome of this work sheds light on the binding specificity of NFs towards NFRs and thus may significantly contribute to the design of new strategies in improving root-nodule symbiosis towards meeting the agricultural demands.

Drugging the Undruggable: How Isoquinolines and PKA Initiated the Era of Designed Protein Kinase Inhibitor Therapeutics

In 1984, Japanese researchers led by the biochemist Hiroyoshi Hidaka described the first synthetic protein kinase inhibitors based on an isoquinoline sulfonamide structure (Hidaka et al. Biochemistry, 1984 Oct 9; 23(21): 5036-41. doi: 10.1021/bi00316a032). These led to the first protein kinase inhibitor approved for medical use (fasudil), an inhibitor of the AGC subfamily Rho kinase. With potencies strong enough to compete against endogenous ATP, the isoquinoline compounds established the druggability of the ATP binding site. Crystal structures of their protein kinase complexes, including with cAMP-dependent protein kinase (PKA), showed interactions that, on the one hand, could mimic ATP but, on the other hand, could be optimized for high potency binding, kinase selectivity, and diversification away from adenosine. They also showed the flexibility of the glycine-rich loop, and PKA became a major prototype for crystallographic and nuclear magnetic resonance (NMR) studies of protein kinase mechanism and dynamic activity control. Since fasudil, more than 70 kinase inhibitors have been approved for clinical use, involving efforts that progressively have introduced new paradigms of data-driven drug discovery. Publicly available data alone comprise over 5000 protein kinase crystal structures and hundreds of thousands of binding data. Now, new methods, including artificial intelligence techniques and expansion of protein kinase targeting approaches, together with the expiration of patent protection for optimized inhibitor scaffolds, promise even greater advances in drug discovery. Looking back to the time of the first isoquinoline hinge binders brings the current state-of-the-art into stark contrast. Appropriately for this Perspective article, many of the milestone papers during this time were published in Biochemistry (now ACS Biochemistry).

Downfalls of Chemical Probes Acting at the Kinase ATP-Site: CK2 as a Case Study

Protein kinases are a large class of enzymes with numerous biological roles and many have been implicated in a vast array of diseases, including cancer and the novel coronavirus infection COVID-19. Thus, the development of chemical probes to selectively target each kinase is of great interest. Inhibition of protein kinases with ATP-competitive inhibitors has historically been the most widely used method. However, due to the highly conserved structures of ATP-sites, the identification of truly selective chemical probes is challenging. In this review, we use the Ser/Thr kinase CK2 as an example to highlight the historical challenges in effective and selective chemical probe development, alongside recent advances in the field and alternative strategies aiming to overcome these problems. The methods utilised for CK2 can be applied to an array of protein kinases to aid in the discovery of chemical probes to further understand each kinase's biology, with wide-reaching implications for drug development.

Fragment Binding to Kinase Hinge: If Charge Distribution and Local pKa Shifts Mislead Popular Bioisosterism Concepts

Medicinal-chemistry optimization follows strategies replacing functional groups and attaching larger substituents at a promising lead scaffold. Well-established bioisosterism rules are considered, however, it is difficult to estimate whether the introduced modifications really match the required properties at a binding site. The electron density distribution and pKa values are modulated influencing protonation states and bioavailability. Considering the adjacent H-bond donor/acceptor pattern of the hinge binding motif in a kinase, we studied by crystallography a set of fragments to map the required interaction pattern. Unexpectedly, benzoic acid and benzamidine, decorated with the correct substituents, are totally bioisosteric just as carboxamide and phenolic OH. A mono-dentate pyridine nitrogen out-performs bi-dentate functionalities. The importance of correctly designing pKa values of attached functional groups by additional substituents at the parent scaffold is rendered prominent.

Synthesis, Structure and Cytotoxicity Testing of Novel 7-(4,5-dihydro-1H-imidazol-2-yl)-2-aryl-6,7-dihydro-2H-imidazo[2,1-c][1,2,4]triazol-3(5H)-Imine Derivatives

The appropriate 1-arylhydrazinecarbonitriles 1a-c are subjected to the reaction with 2-chloro-4,5-dihydro-1H-imidazole (2), yielding 7-(4,5-dihydro-1H-imidazol-2-yl)-2-aryl-6,7-dihydro-2H-imidazo[2,1-c][1,2,4]triazol-3(5H)-imines 3a-c, which are subsequently converted into the corresponding amides 4a-e, 8a-c, sulfonamides 5a-n, 9, ureas 6a-I, and thioureas 7a-d. The structures of the newly prepared derivatives 3a-c, 4a-e, 5a-n, 6a-i, 7a-d, 8a-c, and 9 are confirmed by IR, NMR spectroscopic data, as well as single-crystal X-ray analyses of 5e and 8c. The in vitro cytotoxic potency of these compounds is determined on a panel of human cancer cell lines, and the relationships between structure and antitumor activity are discussed. The most active 4-chloro-N-(2-(4-chlorophenyl)-7-(4,5-dihydro-1H-imidazol-2-yl)-6,7-dihydro-2H-imidazo[2,1-c][1,2,4]triazol-3(5H)-ylidene)benzamide (4e) and N-(7-(4,5-dihydro-1H-imidazol-2-yl)-2-(p-tolyl)-6,7-dihydro-2H-imidazo[2,1-c][1,2,4]triazol-3(5H)-ylidene)-[1,1'-biphenyl]-4-sulfonamide (5l) inhibits the growth of the cervical cancer SISO and bladder cancer RT-112 cell lines with IC50 values in the range of 2.38-3.77 μM. Moreover, N-(7-(4,5-dihydro-1H-imidazol-2-yl)-2-phenyl-6,7-dihydro-2H-imidazo[2,1-c][1,2,4]triazol-3(5H)-ylidene)-4-phenoxybenzenesulfonamide (5m) has the best selectivity towards the SISO cell line and induces apoptosis in this cell line.

KinFragLib: Exploring the Kinase Inhibitor Space Using Subpocket-Focused Fragmentation and Recombination

Protein kinases play a crucial role in many cell signaling processes, making them one of the most important families of drug targets. In this context, fragment-based drug design strategies have been successfully applied to develop novel kinase inhibitors. These strategies usually follow a knowledge-driven approach to optimize a focused set of fragments to a potent kinase inhibitor. Alternatively, KinFragLib explores and extends the chemical space of kinase inhibitors using data-driven fragmentation and recombination. The method builds on available structural kinome data from the KLIFS database for over 2500 kinase DFG-in structures cocrystallized with noncovalent kinase ligands. The computational fragmentation method splits the ligands into fragments with respect to their 3D proximity to six predefined functionally relevant subpocket centers. The resulting fragment library consists of six subpocket pools with over 7000 fragments, available at https://github.com/volkamerlab/KinFragLib. KinFragLib offers two main applications: on the one hand, in-depth analyses of the chemical space of known kinase inhibitors, subpocket characteristics, and connections, and on the other hand, subpocket-informed recombination of fragments to generate potential novel inhibitors. The latter showed that recombining only a subset of 624 representative fragments generated 6.7 million molecules. This combinatorial library contains, besides some known kinase inhibitors, more than 99% novel chemical matter compared to ChEMBL and 63% molecules compliant with Lipinski's rule of five.

Three-Dimensional Interactions Analysis of the Anticancer Target c-Src Kinase with Its Inhibitors

Src family kinases (SFKs) constitute the biggest family of non-receptor tyrosine kinases considered as therapeutic targets for cancer therapy. An aberrant expression and/or activation of the proto-oncogene c-Src kinase, which is the oldest and most studied member of the family, has long been demonstrated to play a major role in the development, growth, progression and metastasis of numerous human cancers, including colon, breast, gastric, pancreatic, lung and brain carcinomas. For these reasons, the pharmacological inhibition of c-Src activity represents an effective anticancer strategy and a few compounds targeting c-Src, together with other kinases, have been approved as drugs for cancer therapy, while others are currently undergoing preclinical studies. Nevertheless, the development of potent and selective inhibitors of c-Src aimed at properly exploiting this biological target for the treatment of cancer still represents a growing field of study. In this review, the co-crystal structures of c-Src kinase in complex with inhibitors discovered in the past two decades have been described, highlighting the key ligand-protein interactions necessary to obtain high potency and the features to be exploited for addressing selectivity and drug resistance issues, thus providing useful information for the design of new and potent c-Src kinase inhibitors.

Inhibition of Resistance-Refractory P. falciparum Kinase PKG Delivers Prophylactic, Blood Stage, and Transmission-Blocking Antiplasmodial Activity

The search for antimalarial chemotypes with modes of action unrelated to existing drugs has intensified with the recent failure of first-line therapies across Southeast Asia. Here, we show that the trisubstituted imidazole MMV030084 potently inhibits hepatocyte invasion by Plasmodium sporozoites, merozoite egress from asexual blood stage schizonts, and male gamete exflagellation. Metabolomic, phosphoproteomic, and chemoproteomic studies, validated with conditional knockdown parasites, molecular docking, and recombinant kinase assays, identified cGMP-dependent protein kinase (PKG) as the primary target of MMV030084. PKG is known to play essential roles in Plasmodium invasion of and egress from host cells, matching MMV030084's activity profile. Resistance selections and gene editing identified tyrosine kinase-like protein 3 as a low-level resistance mediator for PKG inhibitors, while PKG itself never mutated under pressure. These studies highlight PKG as a resistance-refractory antimalarial target throughout the Plasmodium life cycle and promote MMV030084 as a promising Plasmodium PKG-targeting chemotype.

Discovery of a novel kinase hinge binder fragment by dynamic undocking

A virtual screening workflow for fragment-sized kinase inhibitors is presented, along with a newly identified and validated hinge binder fragment.

One of the key motifs of type I kinase inhibitors is their interactions with the hinge region of ATP binding sites. These interactions contribute significantly to the potency of the inhibitors; however, only a tiny fraction of the available chemical space has been explored with kinase inhibitors reported in the last twenty years. This paper describes a workflow utilizing docking with rDock and dynamic undocking (DUck) for the virtual screening of fragment libraries in order to identify fragments that bind to the kinase hinge region. We have identified 8-amino-2H-isoquinolin-1-one (MR1), a novel and potent hinge binding fragment, which was experimentally tested on a diverse set of kinases, and is hereby suggested for future fragment growing or merging efforts against various kinases, particularly MELK. Direct binding of MR1 to MELK was confirmed by STD-NMR, and its binding to the ATP-pocket was confirmed by a new competitive binding assay based on microscale thermophoresis.

The Groebke-Blackburn-Bienaymé Reaction

Imidazo[1,2-a]pyridine is a well-known scaffold in many marketed drugs, such as Zolpidem, Minodronic acid, Miroprofen and DS-1 and it also serves as a broadly applied pharmacophore in drug discovery. The scaffold revoked a wave of interest when Groebke, Blackburn and Bienaymé reported independently a new three component reaction resulting in compounds with the imidazo[1,2-a]-heterocycles as a core structure. During the course of two decades the Groebke Blackburn Bienaymé (GBB-3CR) reaction has emerged as a very important multicomponent reaction (MCR), resulting in over a hundred patents and a great number of publications in various fields of interest. Now two compounds derived from GBB-3CR chemistry received FDA approval. To celebrate the first 20 years of GBB-chemistry, we present an overview of the chemistry of the GBB-3CR, including an analysis of each of the three starting material classes, solvents and catalysts. Additionally, a list of patents and their applications and a more in-depth summary of the biological targets that were addressed, including structural biology analysis, is given.

Aminoazole-Based Diversity-Oriented Synthesis of Heterocycles

The comprehensive review contains the analysis of literature data concerning reactions of heterocyclization of aminoazoles and demonstrates the application of these types of transformations in diversity-oriented synthesis. The review is oriented to wide range of chemists working in the field of organic synthesis and both experimental and theoretical studies of nitrogen-containing heterocycles.

Ligand-Based Pharmacophore Screening Strategy: a Pragmatic Approach for Targeting HER Proteins

Targeting ErbB family of receptors is an important therapeutic option, because of its essential role in the broad spectrum of human cancers, including non-small cell lung cancer (NSCLC). Therefore, in the present work, considerable effort has been made to develop an inhibitor against HER family proteins, by combining the use of pharmacophore modelling, docking scoring functions, and ADME property analysis. Initially, a five-point pharmacophore model was developed using known HER family inhibitors. The generated model was then used as a query to screen a total of 468,880 compounds of three databases namely ZINC, ASINEX, and DrugBank. Subsequently, docking analysis was carried out to obtain hit molecules that could inhibit the HER receptors. Further, analysis of GLIDE scores and ADME properties resulted in one hit namely BAS01025917 with higher glide scores, increased CNS involvement, and good pharmaceutically relevant properties than reference ligand, afatinib. Furthermore, the inhibitory activity of the lead compounds was validated by performing molecular dynamic simulations. Of note, BAS01025917 was found to possess scaffolds with a broad spectrum of antitumor activity. We believe that this novel hit molecule can be further exploited for the development of a pan-HER inhibitor with low toxicity and greater potential.

H3B-6527 Is a Potent and Selective Inhibitor of FGFR4 in FGF19-Driven Hepatocellular Carcinoma

Activation of the fibroblast growth factor receptor FGFR4 by FGF19 drives hepatocellular carcinoma (HCC), a disease with few, if any, effective treatment options. While a number of pan-FGFR inhibitors are being clinically evaluated, their application to FGF19-driven HCC may be limited by dose-limiting toxicities mediated by FGFR1-3 receptors. To evade the potential limitations of pan-FGFR inhibitors, we generated H3B-6527, a highly selective covalent FGFR4 inhibitor, through structure-guided drug design. Studies in a panel of 40 HCC cell lines and 30 HCC PDX models showed that FGF19 expression is a predictive biomarker for H3B-6527 response. Moreover, coadministration of the CDK4/6 inhibitor palbociclib in combination with H3B-6527 could effectively trigger tumor regression in a xenograft model of HCC. Overall, our results offer preclinical proof of concept for H3B-6527 as a candidate therapeutic agent for HCC cases that exhibit increased expression of FGF19. Cancer Res; 77(24); 6999-7013. ©2017 AACR.

Data driven polypharmacological drug design for lung cancer: analyses for targeting ALK, MET, and EGFR

Drug design of protein kinase inhibitors is now greatly enabled by thousands of publicly available X-ray structures, extensive ligand binding data, and optimized scaffolds coming off patent. The extensive data begin to enable design against a spectrum of targets (polypharmacology); however, the data also reveal heterogeneities of structure, subtleties of chemical interactions, and apparent inconsistencies between diverse data types. As a result, incorporation of all relevant data requires expert choices to combine computational and informatics methods, along with human insight. Here we consider polypharmacological targeting of protein kinases ALK, MET, and EGFR (and its drug resistant mutant T790M) in non small cell lung cancer as an example. Both EGFR and ALK represent sources of primary oncogenic lesions, while drug resistance arises from MET amplification and EGFR mutation. A drug which inhibits these targets will expand relevant patient populations and forestall drug resistance. Crizotinib co-targets ALK and MET. Analysis of the crystal structures reveals few shared interaction types, highlighting proton-arene and key CH–O hydrogen bonding interactions. These are not typically encoded into molecular mechanics force fields. Cheminformatics analyses of binding data show EGFR to be dissimilar to ALK and MET, but its structure shows how it may be co-targeted with the addition of a covalent trap. This suggests a strategy for the design of a focussed chemical library based on a pan-kinome scaffold. Tests of model compounds show these to be compatible with the goal of ALK, MET, and EGFR polypharmacology.

Chalcone-based Selective Inhibitors of a C4 Plant Key Enzyme as Novel Potential Herbicides

Weeds are a challenge for global food production due to their rapidly evolving resistance against herbicides. We have identified chalcones as selective inhibitors of phosphoenolpyruvate carboxylase (PEPC), a key enzyme for carbon fixation and biomass increase in the C4 photosynthetic pathway of many of the world's most damaging weeds. In contrast, many of the most important crop plants use C3 photosynthesis. Here, we show that 2',3',4',3,4-Pentahydroxychalcone (IC50 = 600 nM) and 2',3',4'-Trihydroxychalcone (IC50 = 4.2 μM) are potent inhibitors of C4 PEPC but do not affect C3 PEPC at a same concentration range (selectivity factor: 15-45). Binding and modeling studies indicate that the active compounds bind at the same site as malate/aspartate, the natural feedback inhibitors of the C4 pathway. At the whole plant level, both substances showed pronounced growth-inhibitory effects on the C4 weed Amaranthus retroflexus, while there were no measurable effects on oilseed rape, a C3 plant. Growth of selected soil bacteria was not affected by these substances. Our chalcone compounds are the most potent and selective C4 PEPC inhibitors known to date. They offer a novel approach to combat C4 weeds based on a hitherto unexplored mode of allosteric inhibition of a C4 plant key enzyme.

Benzobisthiazoles Represent a Novel Scaffold for Kinase Inhibitors of CLK Family Members

Protein kinases are essential regulators of most cellular processes and are involved in the etiology and progression of multiple diseases. The cdc2-like kinases (CLKs) have been linked to various neurodegenerative disorders, metabolic regulation, and virus infection, and the kinases have been recognized as potential drug targets. Here, we have developed a screening workflow for the identification of potent CLK2 inhibitors and identified compounds with a novel chemical scaffold structure, the benzobisthiazoles, that has not been previously reported for kinase inhibitors. We propose models for binding of these compounds to CLK family proteins and key residues in CLK2 that are important for the compound interactions and the kinase activity. We identified structural elements within the benzobisthiazole that determine CLK2 and CLK3 inhibition, thus providing a rationale for selectivity assays. In summary, our results will inform structure-based design of CLK family inhibitors based on the novel benzobisthiazole scaffold.

Panel docking of small-molecule libraries - Prospects to improve efficiency of lead compound discovery

Computational docking as a means to prioritise small molecules in drug discovery projects remains a highly popular in silico screening approach. Contemporary docking approaches without experimental parametrisation can reliably differentiate active and inactive chemotypes in a protein binding site, but the absence of a correlation between the score of a predicted binding pose and the biological activity of the molecule presents a clear limitation. Several novel or improved computational approaches have been developed in the recent past to aid in screening and profiling of small-molecule ligands for drug discovery, but also more broadly in developing conceptual relationships between different protein targets by chemical probing. Among those new methodologies is a strategy known as inverse virtual screening, which involves the docking of a compound into different protein structures. In the present article, we review the different computational screening methodologies that employ docking of atomic models, and, by means of a case study, present an approach that expands the inverse virtual screening concept. By computationally screening a reasonably sized library of 1235 compounds against a panel of 48 mostly human kinases, we have been able to identify five groups of putative lead compounds with substantial diversity when compared to each other. One representative of each of the five groups was synthesised, and tested in kinase inhibition assays, yielding two compounds with micro-molar inhibition in five human kinases. This highly economic and cost-effective methodology holds great promise for drug discovery projects, especially in cases where a group of target proteins share high structural similarity in their binding sites.

Synthetic approaches and functionalizations of imidazo[1,2-a]pyrimidines: an overview of the decade

This review gives an overview to the synthesis of the imidazo[1,2-a]pyrimidines on the basis of multicomponent reactions, condensation reactions, intramolecular cyclizations etc. along with its reactivity at 3-position.