Kinase-targeted libraries: The design and synthesis of novel, potent, and selective kinase inhibitors

Poor Generalization by Current Deep Learning Models for Predicting Binding Affinities of Kinase Inhibitors

The extreme surge of interest over the past decade surrounding the use of neural networks has inspired many groups to deploy them for predicting binding affinities of drug-like molecules to their receptors. A model that can accurately make such predictions has the potential to screen large chemical libraries and help streamline the drug discovery process. However, despite reports of models that accurately predict quantitative inhibition using protein kinase sequences and inhibitors' SMILES strings, it is still unclear whether these models can generalize to previously unseen data. Here, we build a Convolutional Neural Network (CNN) analogous to those previously reported and evaluate the model over four datasets commonly used for inhibitor/kinase predictions. We find that the model performs comparably to those previously reported, provided that the individual data points are randomly split between the training set and the test set. However, model performance is dramatically deteriorated when all data for a given inhibitor is placed together in the same training/testing fold, implying that information leakage underlies the models' performance. Through comparison to simple models in which the SMILES strings are tokenized, or in which test set predictions are simply copied from the closest training set data points, we demonstrate that there is essentially no generalization whatsoever in this model. In other words, the model has not learned anything about molecular interactions, and does not provide any benefit over much simpler and more transparent models. These observations strongly point to the need for richer structure-based encodings, to obtain useful prospective predictions of not-yet-synthesized candidate inhibitors.

Identification of a Unique Cytotoxic Thieno[2,3-c]Pyrazole Derivative with Potent and Selective Anticancer Effects In Vitro

In recent years, the thienopyrazole moiety has emerged as a pharmacologically active scaffold with antitumoral and kinase inhibitory activity. In this study, high-throughput screening of 2000 small molecules obtained from the ChemBridge DIVERset library revealed a unique thieno[2,3-c]pyrazole derivative (Tpz-1) with potent and selective cytotoxic effects on cancer cells. Compound Tpz-1 consistently induced cell death at low micromolar concentrations (0.19 μM to 2.99 μM) against a panel of 17 human cancer cell lines after 24 h, 48 h, or 72 h of exposure. Furthermore, an in vitro investigation of Tpz-1's mechanism of action revealed that Tpz-1 interfered with cell cycle progression, reduced phosphorylation of p38, CREB, Akt, and STAT3 kinases, induced hyperphosphorylation of Fgr, Hck, and ERK 1/2 kinases, and disrupted microtubules and mitotic spindle formation. These findings support the continued exploration of Tpz-1 and other thieno[2,3-c]pyrazole-based compounds as potential small-molecule anticancer agents.

Comparative expression of soluble, active human kinases in specialized bacterial strains

Kinases act as molecular switches for cellular functions and are involved in multiple human pathogeneses, most notably cancer. There is a continuous need for soluble and active kinases for in-vitro drug discovery and structural biology purposes. Kinases remain challenging to express using Escherichia coli, the most widely utilized host for heterologous expression. In this work, four bacterial strains, BL21 (DE3), BL21 (DE3) pLysS, Rosetta, and Arctic Express, were chosen for parallel expression trials along with BL21 (DE3) complemented with folding chaperones DnaJ/K and GroEL/ES to compare their performance in producing soluble and active human kinases. Three representative diverse kinases were studied, Epidermal Growth Factor Receptor kinase domain, Aurora Kinase A kinase domain, and Mitogen-activated protein Kinase Kinase. The genes encoding the kinases were subcloned into pET15b bacterial plasmid and transformed into the bacterial strains. Soluble kinase expression was tested using different IPTG concentrations (1–0.05 mM) at varying temperatures (37°C– 10°C) and induction times (3–24 hours). The optimum conditions for each kinase in all strains were then used for 1L large scale cultures from which each kinase was purified to compare yield, purity, oligomerization status, and activity. Although using specialized strains achieved improvements in yield and/or activity for the three kinases, none of the tested strains was universally superior, highlighting the individuality in kinase expression.

Efficient Hit-to-Lead Searching of Kinase Inhibitor Chemical Space via Computational Fragment Merging

In early-stage drug discovery, the hit-to-lead optimization (or "hit expansion") stage entails starting from a newly identified active compound and improving its potency or other properties. Traditionally, this process relies on synthesizing and evaluating a series of analogues to build up structure-activity relationships. Here, we describe a computational strategy focused on kinase inhibitors, intended to expedite the process of identifying analogues with improved potency. Our protocol begins from an inhibitor of the target kinase and generalizes the synthetic route used to access it. By searching for commercially available replacements for the individual building blocks used to make the parent inhibitor, we compile an enumerated library of compounds that can be accessed using the same chemical transformations; these huge libraries can exceed many millions─or billions─of compounds. Because the resulting libraries are much too large for explicit virtual screening, we instead consider alternate approaches to identify the top-scoring compounds. We find that contributions from individual substituents are well described by a pairwise additivity approximation, provided that the corresponding fragments position their shared core in precisely the same way relative to the binding site. This key insight allows us to determine which fragments are suitable for merging into single new compounds and which are not. Further, the use of pairwise approximation allows interaction energies to be assigned to each compound in the library without the need for any further structure-based modeling: interaction energies instead can be reliably estimated from the energies of the component fragments, and the reduced computational requirements allow for flexible energy minimizations that allow the kinase to respond to each substitution. We demonstrate this protocol using libraries built from six representative kinase inhibitors drawn from the literature, which target five different kinases: CDK9, CHK1, CDK2, EGFR^T790M, and ACK1. In each example, the enumerated library includes additional analogues reported by the original study to have activity, and these analogues are successfully prioritized within the library. We envision that the insights from this work can facilitate the rapid assembly and screening of increasingly large libraries for focused hit-to-lead optimization. To enable adoption of these methods and to encourage further analyses, we disseminate the computational tools needed to deploy this protocol.

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).

Chemical Space Exploration of Oxetanes

This paper focuses on new derivatives bearing an oxetane group to extend accessible chemical space for further identification of kinase inhibitors. The ability to modulate kinase activity represents an important therapeutic strategy for the treatment of human illnesses. Known as a nonclassical isoster of the carbonyl group, due to its high polarity and great ability to function as an acceptor of hydrogen bond, oxetane seems to be an attractive and underexplored structural motif in medicinal chemistry.

Kinase shRNA screening reveals that TAOK3 enhances microtubule-targeted drug resistance of breast cancer cells via the NF-κB signaling pathway

BACKGROUND

Chemotherapy is currently one of the most effective treatments for advanced breast cancer. Anti-microtubule agents, including taxanes, eribulin and vinca-alkaloids are one of the primary major anti-breast cancer chemotherapies; however, chemoresistance remains a problem that is difficult to solve. We aimed to discover novel candidate protein targets to combat chemoresistance in breast cancer.

METHODS

A lentiviral shRNA-based high-throughput screening platform was designed and developed to screen the global kinome to find new therapeutic targets in paclitaxel-resistant breast cancer cells. The phenotypes were confirmed with alternative expression in vitro and in vivo. Molecular mechanisms were investigated using global phosphoprotein arrays and expression microarrays. Global microarray analysis was performed to determine TAOK3 and genes that induced paclitaxel resistance.

RESULTS

A serine/threonine kinase gene, TAOK3, was identified from 724 screened kinase genes. TAOK3 shRNA exhibited the most significant reduction in IC50 values in response to paclitaxel treatment. Ectopic downregulation of TAOK3 resulted in paclitaxel-resistant breast cancer cells sensitize to paclitaxel treatment in vitro and in vivo. The expression of TAOK3 also was correlated to sensitivity to two other anti-microtubule drugs, eribulin and vinorelbine. Our TAOK3-modulated microarray analysis indicated that NF-κB signaling played a major upstream regulation role. TAOK3 inhibitor, CP43, and shRNA of NF-κB both reduced the paclitaxel resistance in TAOK3 overexpressed cells. In clinical microarray databases, high TAOK3 expressed breast cancer patients had poorer prognoses after adjuvant chemotherapy.

CONCLUSIONS

Here we identified TAOK3 overexpression increased anti-microtubule drug resistance through upregulation of NF-κB signaling, which reduced cell death in breast cancer. Therefore, inhibition of the interaction between TAOK3 and NF-κB signaling may have therapeutic implications for breast cancer patients treated with anti-microtubule drugs. Video abstract.

Application of a Substrate-Mediated Selection with c-Src Tyrosine Kinase to a DNA-Encoded Chemical Library

As aberrant activity of protein kinases is observed in many disease states, these enzymes are common targets for therapeutics and detection of activity levels. The development of non-natural protein kinase substrates offers an approach to protein substrate competitive inhibitors, a class of kinase inhibitors with promise for improved specificity. Also, kinase activity detection approaches would benefit from substrates with improved activity and specificity. Here, we apply a substrate-mediated selection to a peptidomimetic DNA-encoded chemical library for enrichment of molecules that can be phosphorylated by the protein tyrosine kinase, c-Src. Several substrates were identified and characterized for activity. A lead compound (SrcDEL10) showed both the ability to serve as a substrate and to promote ATP hydrolysis by the kinase. In inhibition assays, compounds displayed IC_50's ranging from of 8-100 µM. NMR analysis of SrcDEL10 bound to the c-Src:ATP complex was conducted to characterize the binding mode. An ester derivative of the lead compound demonstrated cellular activity with inhibition of Src-dependent signaling in cell culture. Together, the results show the potential for substrate-mediated selections of DNA-encoded libraries to discover molecules with functions other than simple protein binding and offer a new discovery method for development of synthetic tyrosine kinase substrates.

Tumor-induced neoangiogenesis and receptor tyrosine kinases - Mechanisms and strategies for acquired resistance

BACKGROUND

Angiogenesis is essential for tumor growth, proliferation and metastasis. Tumor-related angiogenesis is complex and involves multiple signaling pathways. Controlling angiogenesis is a promising strategy for limiting cancer progression.

SCOPE OF REVIEW

Several receptor tyrosine kinases influence the angiogenic response via multiple signaling molecules and pathways. Understanding the functional interaction of kinases in the angiogenic process and development of resistance to kinase inhibition is essential for future successful therapeutic strategies.

MAJOR CONCLUSIONS

Strategies that target receptor tyrosine kinases and other tumor microenvironment factors simultaneously, or sequentially, are required for achieving an efficient and robust anti-angiogenic response.

GENERAL SIGNIFICANCE

Understanding the molecular mechanism of angiogenesis has improved, and has led, to the clinical development and approval of anti-angiogenic drugs. While many patients have benefited from these agents, their limited efficacy and the development of resistance remains a challenge. This review highlights current therapies and challenges associated with targeting angiogenesis in cancer.

Identification of Novel Cdc7 Kinase Inhibitors as Anti-Cancer Agents that Target the Interaction with Dbf4 by the Fragment Complementation and Drug Repositioning Approach

BACKGROUND

Cdc7-Dbf4 is a conserved serine/threonine kinase that plays an important role in initiation of DNA replication and DNA damage tolerance in eukaryotic cells. Cdc7 has been found overexpressed in human cancer cell lines and tumor tissues, and the knockdown of Cdc7 expression causes an p53-independent apoptosis, suggesting that Cdc7 is a target for cancer therapy. Only a handful Cdc7 kinase inhibitors have been reported. All Cdc7 kinase inhibitors, including PHA-767491, were identified and characterized as ATP-competitive inhibitors. Unfortunately, these ATP-competitive Cdc7 inhibitors have no good effect on clinical trial.

METHODS

Here, we have developed a novel drug-screening platform to interrupt the interaction between Cdc7 and Dbf4 based on Renilla reniformis luciferase (Rluc)-linked protein-fragment complementation assay (Rluc-PCA). Using drug repositioning approach, we found several promising Cdc7 inhibitors for cancer therapy from a FDA-approved drug library.

FINDINGS

Our data showed that dequalinium chloride and clofoctol we screened inhibit S phase progression, accumulation in G2/M phase, and Cdc7 kinase activity. In addition, in vivo mice animal study suggests that dequalinium chloride has a promising anti-tumor activity in oral cancer. Interestingly, we also found that dequalinium chloride and clofoctol sensitize the effect of platinum compounds and radiation due to synergistic effect. In conclusion, we identified non-ATP-competitive Cdc7 kinase inhibitors that not only blocks DNA synthesis at the beginning but also sensitizes cancer cells to DNA damage agents.

INTERPRETATION

The inhibitors will be a promising anti-cancer agent and enhance the therapeutic effect of chemotherapy and radiation for current cancer therapy. FUND: This work was supported by grants from the Ministry of Science and Technology, Ministry of Health and Welfare, and National Health Research Institutes, Taiwan.

Protocols for the Design of Kinase-focused Compound Libraries

Protocols for the design of kinase-focused compound libraries are presented. Kinase-focused compound libraries can be differentiated based on the design goal. Depending on whether the library should be a discovery library specific for one particular kinase, a general discovery library for multiple distinct kinase projects, or even phenotypic screening, there exists today a variety of in silico methods to design candidate compound libraries. We address the following scenarios: 1) Datamining of SAR databases and kinase focused vendor catalogues; 2) Predictions and virtual screening; 3) Structure-based design of combinatorial kinase inhibitors; 4) Design of covalent kinase inhibitors; 5) Design of macrocyclic kinase inhibitors; and 6) Design of allosteric kinase inhibitors and activators.

In Silico Identification of a Novel Hinge-Binding Scaffold for Kinase Inhibitor Discovery

To explore novel kinase hinge-binding scaffolds, we carried out structure-based virtual screening against p38α MAPK as a model system. With the assistance of developed kinase-specific structural filters, we identify a novel lead compound that selectively inhibits a panel of kinases with threonine as the gatekeeper residue, including BTK and LCK. These kinases play important roles in lymphocyte activation, which encouraged us to design novel kinase inhibitors as drug candidates for ameliorating inflammatory diseases and cancers. Therefore, we chemically modified our substituted triazole-class lead compound to improve the binding affinity and selectivity via a "minimal decoration" strategy, which resulted in potent and selective kinase inhibitors against LCK (18 nM) and BTK (8 nM). Subsequent crystallographic experiments validated our design. These rationally designed compounds exhibit potent on-target inhibition against BTK in B cells or LCK in T cells, respectively. Our work demonstrates that structure-based virtual screening can be applied to facilitate the development of novel chemical entities in crowded chemical space in the field of kinase inhibitor discovery.

Docking-based structural splicing and reassembly strategy to develop novel deazapurine derivatives as potent B-RafV600E inhibitors

The mutation of B-Raf^V600E is widespread in a variety of human cancers. Its inhibitors vemurafenib and dabrafenib have been launched as drugs for treating unresectable melanoma, demonstrating that B-Raf^V600E is an ideal drug target. This study focused on developing novel B-Raf^V600E inhibitors as drug leads against various cancers with B-Raf^V600E mutation. Using molecular modeling approaches, 200 blockbuster drugs were spliced to generate 283 fragments followed by molecular docking to identify potent fragments. Molecular structures of potential inhibitors of B-Raf^V600E were then obtained by fragment reassembly followed by docking to predict the bioactivity of the reassembled molecules. The structures with high predicted bioactivity were synthesized, followed by in vitro study to identify potent B-Raf^V600E inhibitors. A highly potent fragment binding to the hinge area of B-Raf^V600E was identified via a docking-based structural splicing approach. Using the fragment, 14 novel structures were designed by structural reassembly, two of which were predicted to be as strong as marketed B-Raf^V600E inhibitors. Biological evaluation revealed that compound 1m is a potent B-Raf^V600E inhibitor with an IC₅₀ value of 0.05 μmol/L, which was lower than that of vemurafenib (0.13 μmol/L). Moreover, the selectivity of 1m against B-Raf^WT was enhanced compared with vemurafenib. In addition, 1m exhibits desirable solubility, bioavailability and metabolic stability in in vitro assays. Thus, a highly potent and selective B-Raf^V600E inhibitor was designed via a docking-based structural splicing and reassembly strategy and was validated by medicinal synthesis and biological evaluation.

Twenty years on: the impact of fragments on drug discovery

After 20 years of sometimes quiet growth, fragment-based drug discovery (FBDD) has become mainstream. More than 30 drug candidates derived from fragments have entered the clinic, with two approved and several more in advanced trials. FBDD has been widely applied in both academia and industry, as evidenced by the large number of papers from universities, non-profit research institutions, biotechnology companies and pharmaceutical companies. Moreover, FBDD draws on a diverse range of disciplines, from biochemistry and biophysics to computational and medicinal chemistry. As the promise of FBDD strategies becomes increasingly realized, now is an opportune time to draw lessons and point the way to the future. This Review briefly discusses how to design fragment libraries, how to select screening techniques and how to make the most of information gleaned from them. It also shows how concepts from FBDD have permeated and enhanced drug discovery efforts.

Identifying GSK-3β kinase inhibitors of Alzheimer's disease: Virtual screening, enzyme, and cell assays

Glycogen synthase kinase 3β (GSK-3β) is widely known as a critical target protein for treating Alzheimer's disease (AD). We utilized virtual screening to search databases for compounds with the potential to be used in drugs targeting GSK-3β kinase, and kinase as well as cell assays to investigate top-scored, selected compounds. Virtual screening of >1.1 million compounds in the ZINC and in-house databases was conducted using an optimized computational protocol in the docking program GOLD. Of the top-ranked compounds, 16 underwent a luminescent kinase assay and a cell assay using HEK293 cells expressing DsRed-tagged ΔK280 in the repeat domain of tau (tauRD). The compounds VB-003 (a potent GSK-3β inhibitor) and VB-008 (AM404, an anandamide transport inhibitor), with determined IC50 values of 0.25 and 5.4μM, respectively, were identified as reducing tau aggregation. Both compounds increased expression of phospho-GSK-3β (Ser9) and reduced endogenous tau phosphorylation at the sites of Ser202, Thr231, and Ser396. In the ∆K280 tauRD-DsRed SH-SY5Y cells, VB-008, but not VB-003, enhanced HSPB1 and GRP78 expression, increased ∆K280 tauRD-DsRed solubility, and promoted neurite outgrowth. Thus VB-008 performed best to the end of the present study. The identified compound VB-008 may guide the identification and synthesis of potential inhibitors analogous to this compound.

A graph-based approach to construct target-focused libraries for virtual screening

Background

Due to exorbitant costs of high-throughput screening, many drug discovery projects commonly employ inexpensive virtual screening to support experimental efforts. However, the vast majority of compounds in widely used screening libraries, such as the ZINC database, will have a very low probability to exhibit the desired bioactivity for a given protein. Although combinatorial chemistry methods can be used to augment existing compound libraries with novel drug-like compounds, the broad chemical space is often too large to be explored. Consequently, the trend in library design has shifted to produce screening collections specifically tailored to modulate the function of a particular target or a protein family.

Methods

Assuming that organic compounds are composed of sets of rigid fragments connected by flexible linkers, a molecule can be decomposed into its building blocks tracking their atomic connectivity. On this account, we developed eSynth, an exhaustive graph-based search algorithm to computationally synthesize new compounds by reconnecting these building blocks following their connectivity patterns.

Results

We conducted a series of benchmarking calculations against the Directory of Useful Decoys, Enhanced database. First, in a self-benchmarking test, the correctness of the algorithm is validated with the objective to recover a molecule from its building blocks. Encouragingly, eSynth can efficiently rebuild more than 80 % of active molecules from their fragment components. Next, the capability to discover novel scaffolds is assessed in a cross-benchmarking test, where eSynth successfully reconstructed 40 % of the target molecules using fragments extracted from chemically distinct compounds. Despite an enormous chemical space to be explored, eSynth is computationally efficient; half of the molecules are rebuilt in less than a second, whereas 90 % take only about a minute to be generated.

Conclusions

eSynth can successfully reconstruct chemically feasible molecules from molecular fragments. Furthermore, in a procedure mimicking the real application, where one expects to discover novel compounds based on a small set of already developed bioactives, eSynth is capable of generating diverse collections of molecules with the desired activity profiles. Thus, we are very optimistic that our effort will contribute to targeted drug discovery. eSynth is freely available to the academic community at www.brylinski.org/content/molecular-synthesis.Graphical abstract

Discovery of wrightiadione as a novel template for the TrkA kinase inhibitors

Enzymatic kinase assays and docking simulation studies have shown that the natural product wrightiadione displays inhibitory activity toward TrkA and PLK3. In this study, the template of wrightiadione served as a starting point for Trk inhibitor development campaigns. Molecular simulation provided structural insights for the design of derivatives that were efficiently generated by our recently developed 3-step tandem synthetic approach, resulting in the discovery of compound 2h with biochemical potency at the single-digit micromolar level.

Screening technologies for small molecule discovery: the state of the art

Screening, high-throughput screening, and ultra-high-throughput screening are all really just points on a spectrum that represent differing applications of the same process: the creation of biologically relevant assays that are relevant, reproducible, reliable, and robust. Whether the discovery program is developing a pharmaceutical, an academic probe, cosmetics, pesticides, or a toxicity monitoring assay, the development of a screen focuses on generating a method that will reliably deliver reproducible results over a period of weeks, months, or years and that will generate consistent results for every test along the way. This review provides both historical perspective on how this unique scientific discipline evolved and commentary on the current state of the art technologies and techniques.

Cell biology. Reversible centriole depletion with an inhibitor of Polo-like kinase 4

Centrioles are ancient organelles that build centrosomes, the major microtubule-organizing centers of animal cells. Extra centrosomes are a common feature of cancer cells. To investigate the importance of centrosomes in the proliferation of normal and cancer cells, we developed centrinone, a reversible inhibitor of Polo-like kinase 4 (Plk4), a serine-threonine protein kinase that initiates centriole assembly. Centrinone treatment caused centrosome depletion in human and other vertebrate cells. Centrosome loss irreversibly arrested normal cells in a senescence-like G1 state by a p53-dependent mechanism that was independent of DNA damage, stress, Hippo signaling, extended mitotic duration, or segregation errors. In contrast, cancer cell lines with normal or amplified centrosome numbers could proliferate indefinitely after centrosome loss. Upon centrinone washout, each cancer cell line returned to an intrinsic centrosome number "set point." Thus, cells with cancer-associated mutations fundamentally differ from normal cells in their response to centrosome loss.

Identification of protein kinase CK2 inhibitors using solvent dipole ordering virtual screening

Novel protein kinase CK2 inhibitors were identified using the solvent dipole ordering virtual screening method. A total of 26 compounds categorized in 15 distinct scaffold classes inhibited greater than 50% of enzyme activity at 50 μM, and eight exhibited IC50 values less than 10 μM. Most of the identified compounds are lead-like and dissimilar to known inhibitors. The crystal structures of two of the CK2 complexes revealed the high accuracy of the predicted binding modes.

Small molecule substrate phosphorylation site inhibitors of protein kinases: approaches and challenges

Protein kinases are important mediators of cellular communication and attractive drug targets for many diseases. Although success has been achieved with developing ATP-competitive kinase inhibitors, the disadvantages of ATP-competitive inhibitors have led to increased interest in targeting sites outside of the ATP binding pocket. Kinase inhibitors with substrate-competitive, ATP-noncompetitive binding modes are promising due to the possibility of increased selectivity and better agreement between biochemical and in vitro potency. However, the difficulty of identifying these types of inhibitors has resulted in significantly fewer small molecule substrate phosphorylation site inhibitors being reported compared to ATP-competitive inhibitors. This review surveys reported substrate phosphorylation site inhibitors and methods that can be applied to the discovery of such inhibitors, including a discussion of the challenges inherent to these screening methods.

Synthesis and biological evaluation of novel derivatives of gambogenic acid as anticancer agents

A series of novel derivatives of gambogenic acid (GNA) were synthesized and evaluated for their in vitro antiproliferative activity against four kinds of tumor cell lines. These compounds displayed potent antiproliferative activity. In particular, compound 3f exhibited superior antiproliferative activity against these tumor cell lines than GNA.

A chemo-centric view of human health and disease

Efforts to compile the phenotypic effects of drugs and environmental chemicals offer the opportunity to adopt a chemo-centric view of human health that does not require detailed mechanistic information. Here, we consider thousands of chemicals and analyze the relationship of their structures with adverse and therapeutic responses. Our study includes molecules related to the etiology of 934 health threatening conditions and used to treat 835 diseases. We first identify chemical moieties that could be independently associated with each phenotypic effect. Using these fragments, we build accurate predictors for approximately 400 clinical phenotypes, finding many privileged and liable structures. Finally, we connect two diseases if they relate to similar chemical structures. The resulting networks of human conditions are able to predict disease comorbidities, as well as identifying potential drug side effects and opportunities for drug repositioning, and show a remarkable coincidence with clinical observations.

Fragment-based approaches to the discovery of kinase inhibitors

Protein kinases are one of the most important families of drug targets, and aberrant kinase activity has been linked to a large number of disease areas. Although eminently targetable using small molecules, kinases present a number of challenges as drug targets, not least obtaining selectivity across such a large and relatively closely related target family. Fragment-based drug discovery involves screening simple, low-molecular weight compounds to generate initial hits against a target. These hits are then optimized to more potent compounds via medicinal chemistry, usually facilitated by structural biology. Here, we will present a number of recent examples of fragment-based approaches to the discovery of kinase inhibitors, detailing the construction of fragment-screening libraries, the identification and validation of fragment hits, and their optimization into potent and selective lead compounds. The advantages of fragment-based methodologies will be discussed, along with some of the challenges associated with using this route. Finally, we will present a number of key lessons derived both from our own experience running fragment screens against kinases and from a large number of published studies.

Building in molecular diversity for targeted libraries

The use of gene-focussed libraries for screening against protein targets can improve timelines for drug discovery projects. This is especially true when the library is based on a novel core scaffold, avoiding the potential need to scaffold hop from early hits. Identification of an appropriate novel scaffold is therefore integral to the success of such a library. In this article we outline a new method to aid scaffold design that combines structure- based virtual screening (VS) with a second phase in which fragmentation of the output is made before the final scaffold design step. Through consideration of a refined set of bound fragments, in the context of the compounds from which they originated, appropriate vectors for appended R-groups can be assigned before validation of the final library.

KLIFS: a knowledge-based structural database to navigate kinase-ligand interaction space

Protein kinases regulate the majority of signal transduction pathways in cells and have become important targets for the development of designer drugs. We present a systematic analysis of kinase-ligand interactions in all regions of the catalytic cleft of all 1252 human kinase-ligand cocrystal structures present in the Protein Data Bank (PDB). The kinase-ligand interaction fingerprints and structure database (KLIFS) contains a consistent alignment of 85 kinase ligand binding site residues that enables the identification of family specific interaction features and classification of ligands according to their binding modes. We illustrate how systematic mining of kinase-ligand interaction space gives new insights into how conserved and selective kinase interaction hot spots can accommodate the large diversity of chemical scaffolds in kinase ligands. These analyses lead to an improved understanding of the structural requirements of kinase binding that will be useful in ligand discovery and design studies.

S6K2: The Neglected S6 Kinase Family Member

S6 kinase 2 (S6K2) is a member of the AGC kinases super-family. Its closest homolog, S6K1, has been extensively studied along the years. However, due to the belief in the community that the high degree of identity between these two isoforms would translate in essentially identical biological functions, S6K2 has been largely neglected. Nevertheless, recent research has clearly highlighted that these two proteins significantly differ in their roles in vitro as well as in vivo. These findings are significant to our understanding of S6 kinase signaling and the development of therapeutic strategies for several diseases including cancer. Here, we will focus on S6K2 and review the protein–protein interactions and specific substrates that determine the selective functions of this kinase.

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

Protein kinases constitute an attractive family of enzyme targets with high relevance to cell and disease biology. Small molecule inhibitors are powerful tools to dissect and elucidate the function of kinases in chemical biology research and to serve as potential starting points for drug discovery. However, the discovery and development of novel inhibitors remains challenging. Here, we describe a structure-based de novo design approach that generates novel, hinge-binding fragments that are synthetically feasible and can be elaborated to small molecule libraries. Starting from commercially available compounds, core fragments were extracted, filtered for pharmacophoric properties compatible with hinge-region binding, and docked into a panel of protein kinases. Fragments with a high consensus score were subsequently short-listed for synthesis. Application of this strategy led to a number of core fragments with no previously reported activity against kinases. Small libraries around the core fragments were synthesized, and representative compounds were tested against a large panel of protein kinases and subjected to co-crystallization experiments. Each of the tested compounds was active against at least one kinase, but not all kinases in the panel were inhibited. A number of compounds showed high ligand efficiencies for therapeutically relevant kinases; among them were MAPKAP-K3, SRPK1, SGK1, TAK1, and GCK for which only few inhibitors are reported in the literature.

Drugs by numbers: reaction-driven de novo design of potent and selective anticancer leads

A potent and selective inhibitor of the anticancer target Polo-like kinase 1 was found by computer-based molecular design. This type II kinase inhibitor was synthesized as suggested by the design software DOGS and exhibited significant antiproliferative effects against HeLa cells without affecting nontransformed cells. The study provides a proof-of-concept for reaction-based de novo design as a leading tool for drug discovery.

Design of chemical libraries for screening

IMPORTANCE OF THE FIELD

The ultimate goal of discovery screening is to have a fast and cost-effective strategy to meet the demands of producing high-content lead series with improved prospects for clinical success. While high-throughput screening (HTS) dominates the drug discovery landscape, other processes and technologies have emerged, including high-content screening and fragment-based design to provide alternatives that may be more suitable for certain targets. There has been a growing interest in reducing the number of compounds to be screened to prevent the escalation in the costs, time and resources associated with HTS campaigns. Library design plays a central role in these efforts.

AREAS COVERED IN THIS REVIEW

This opinion provides a survey of some recent developments in the diversity based library design process, but within a historical context. In particular, the importance of chemotyping and substructure analysis and the challenges presented by novel lead discovery technologies that require the design of libraries for screening are discussed.

WHAT THE READER WILL GAIN

Readers will gain an appreciation of some developments in the field of library design and the factors that are driving the development of new library design technologies; specifically, challenges presented for chemoinformatics with the novel screening technologies in diversity based screening and compound filtering.

TAKE HOME MESSAGE

Chemotyping and substrutural analysis are techniques that have been underutilized in the process of library design. However, they offer a direct way to evaluate libraries and have been successfully used to develop predictive methodologies. Tools are available to this end, but the full power of the approach has not been realized yet.

A chemical biology strategy to analyze rheostat-like protein kinase-dependent regulation

Protein kinases may function more like variable rheostats rather than two-state switches. However, we lack approaches to properly analyze this aspect of kinase-dependent regulation. To address this, we develop a strategy in which a kinase inhibitor is identified using genetics-based screens, kinase mutations that confer resistance are characterized, and dose-dependent responses of isogenic drug-sensitive and resistant cells to inhibitor treatments are compared. This approach has the advantage that function of wild-type kinase, rather than mutants, is examined. To develop this approach, we focus on Ark1, the fission yeast member of the conserved Aurora kinase family. Applying this approach reveals that proper chromosome compaction in fission yeast needs high Ark1 activity, while other processes depend on significantly lower activity levels. Our strategy is general and can be used to examine the functions of other molecular rheostats.

Kinome-wide activity modeling from diverse public high-quality data sets

Large corpora of kinase small molecule inhibitor data are accessible to public sector research from thousands of journal article and patent publications. These data have been generated employing a wide variety of assay methodologies and experimental procedures by numerous laboratories. Here we ask the question how applicable these heterogeneous data sets are to predict kinase activities and which characteristics of the data sets contribute to their utility. We accessed almost 500,000 molecules from the Kinase Knowledge Base (KKB) and after rigorous aggregation and standardization generated over 180 distinct data sets covering all major groups of the human kinome. To assess the value of the data sets, we generated hundreds of classification and regression models. Their rigorous cross-validation and characterization demonstrated highly predictive classification and quantitative models for the majority of kinase targets if a minimum required number of active compounds or structure-activity data points were available. We then applied the best classifiers to compounds most recently profiled in the NIH Library of Integrated Network-based Cellular Signatures (LINCS) program and found good agreement of profiling results with predicted activities. Our results indicate that, although heterogeneous in nature, the publically accessible data sets are exceedingly valuable and well suited to develop highly accurate predictors for practical Kinome-wide virtual screening applications and to complement experimental kinase profiling.

Approaches to discover non-ATP site kinase inhibitors

This review will highlight the most commonly used methods to discover small molecule Type III/IV kinase inhibitors.

On the origins of drug polypharmacology

The ability of many drugs, unintended most often, to interact with multiple proteins is commonly referred to as polypharmacology. Could this be a reminiscent chemical signature of early protein evolution?

Novel kinase inhibitors by reshuffling ligand functionalities across the human kinome

Protein kinases remain among the most versatile and prospective therapeutic drug targets with currently 15 distinct compounds approved for use in humans and numerous clinical development programs. The vast majority of kinase inhibitors bind at the ATP site. Here we present an integrated workflow to amplify the rapidly increasing space of structurally resolved small molecule kinase ligands to generate novel inhibitors. Our approach considers both receptor-based similarity constraints in cocomplexes and ligand-based filtering/refinement methods to generate novel, drug-like matter. After building a comprehensive database of the structural kinome and identifying ATP-competitive ligands, we leverage local site similarities and site alignments to shuffle ligand fragments across the kinome. After extensive curation and standardization, our automated protocol starting from 936 cocrystal ATP-competitive binding sites generated about 150,000 new ligand structures among them over 26,000 lead-/drug-like compounds; the majority of those are novel based on structural similarity and scaffolds. In a retrospective analysis we demonstrate that our protocol produced known potent kinase inhibitors and we show how docking can be applied to prioritize the most likely efficacious compounds. Our workflow emulates a common strategy in medicinal chemistry to identify and swap corresponding moieties from known inhibitors to generate novel and potent leads. Here, we systematize and automate this approach leveraging available knowledge covering the entire human Kinome.

Fragment screening of cyclin G-associated kinase by weak affinity chromatography

Fragment-based drug discovery (FBDD) has become a new strategy for drug discovery where lead compounds are evolved from small molecules. These fragments form low affinity interactions (dissociation constant (K_D) = mM − μM) with protein targets, which require fragment screening methods of sufficient sensitivity. Weak affinity chromatography (WAC) is a promising new technology for fragment screening based on selective retention of fragments by a drug target. Kinases are a major pharmaceutical target, and FBDD has been successfully applied to several of these targets. In this work, we have demonstrated the potential to use WAC in combination with mass spectrometry (MS) detection for fragment screening of a kinase target—cyclin G-associated kinase (GAK). One hundred seventy fragments were selected for WAC screening by virtual screening of a commercial fragment library against the ATP-binding site of five different proteins. GAK protein was immobilized on a capillary HPLC column, and compound binding was characterized by frontal affinity chromatography. Compounds were screened in sets of 13 or 14, in combination with MS detection for enhanced throughput. Seventy-eight fragments (46 %) with K_D < 200 μM were detected, including a few highly efficient GAK binders (K_D of 2 μM; ligand efficiency = 0.51). Of special interest is that chiral screening by WAC may be possible, as two stereoisomeric fragments, which both contained one chiral center, demonstrated twin peaks. This ability, in combination with the robustness, sensitivity, and simplicity of WAC makes it a new method for fragment screening of considerable potential.