New opportunities for kinase drug repurposing and target discovery

A comprehensive exploration of the druggable conformational space of protein kinases using AI-predicted structures

Protein kinase function and interactions with drugs are controlled in part by the movement of the DFG and ɑC-Helix motifs that are related to the catalytic activity of the kinase. Small molecule ligands elicit therapeutic effects with distinct selectivity profiles and residence times that often depend on the active or inactive kinase conformation(s) they bind. Modern AI-based structural modeling methods have the potential to expand upon the limited availability of experimentally determined kinase structures in inactive states. Here, we first explored the conformational space of kinases in the PDB and models generated by AlphaFold2 (AF2) and ESMFold, two prominent AI-based protein structure prediction methods. Our investigation of AF2's ability to explore the conformational diversity of the kinome at various multiple sequence alignment (MSA) depths showed a bias within the predicted structures of kinases in DFG-in conformations, particularly those controlled by the DFG motif, based on their overabundance in the PDB. We demonstrate that predicting kinase structures using AF2 at lower MSA depths explored these alternative conformations more extensively, including identifying previously unobserved conformations for 398 kinases. Ligand enrichment analyses for 23 kinases showed that, on average, docked models distinguished between active molecules and decoys better than random (average AUC (avgAUC) of 64.58), but select models perform well (e.g., avgAUCs for PTK2 and JAK2 were 79.28 and 80.16, respectively). Further analysis explained the ligand enrichment discrepancy between low- and high-performing kinase models as binding site occlusions that would preclude docking. The overall results of our analyses suggested that, although AF2 explored previously uncharted regions of the kinase conformational space and select models exhibited enrichment scores suitable for rational drug discovery, rigorous refinement of AF2 models is likely still necessary for drug discovery campaigns.

TBK1, a prioritized drug repurposing target for amyotrophic lateral sclerosis: evidence from druggable genome Mendelian randomization and pharmacological verification in vitro

BACKGROUND

There is a lack of effective therapeutic strategies for amyotrophic lateral sclerosis (ALS); therefore, drug repurposing might provide a rapid approach to meet the urgent need for treatment.

METHODS

To identify therapeutic targets associated with ALS, we conducted Mendelian randomization (MR) analysis and colocalization analysis using cis-eQTL of druggable gene and ALS GWAS data collections to determine annotated druggable gene targets that exhibited significant associations with ALS. By subsequent repurposing drug discovery coupled with inclusion criteria selection, we identified several drug candidates corresponding to their druggable gene targets that have been genetically validated. The pharmacological assays were then conducted to further assess the efficacy of genetics-supported repurposed drugs for potential ALS therapy in various cellular models.

RESULTS

Through MR analysis, we identified potential ALS druggable genes in the blood, including TBK1 [OR 1.30, 95%CI (1.19, 1.42)], TNFSF12 [OR 1.36, 95%CI (1.19, 1.56)], GPX3 [OR 1.28, 95%CI (1.15, 1.43)], TNFSF13 [OR 0.45, 95%CI (0.32, 0.64)], and CD68 [OR 0.38, 95%CI (0.24, 0.58)]. Additionally, we identified potential ALS druggable genes in the brain, including RESP18 [OR 1.11, 95%CI (1.07, 1.16)], GPX3 [OR 0.57, 95%CI (0.48, 0.68)], GDF9 [OR 0.77, 95%CI (0.67, 0.88)], and PTPRN [OR 0.17, 95%CI (0.08, 0.34)]. Among them, TBK1, TNFSF12, RESP18, and GPX3 were confirmed in further colocalization analysis. We identified five drugs with repurposing opportunities targeting TBK1, TNFSF12, and GPX3, namely fostamatinib (R788), amlexanox (AMX), BIIB-023, RG-7212, and glutathione as potential repurposing drugs. R788 and AMX were prioritized due to their genetic supports, safety profiles, and cost-effectiveness evaluation. Further pharmacological analysis revealed that R788 and AMX mitigated neuroinflammation in ALS cell models characterized by overly active cGAS/STING signaling that was induced by MSA-2 or ALS-related toxic proteins (TDP-43 and SOD1), through the inhibition of TBK1 phosphorylation.

CONCLUSIONS

Our MR analyses provided genetic evidence supporting TBK1, TNFSF12, RESP18, and GPX3 as druggable genes for ALS treatment. Among the drug candidates targeting the above genes with repurposing opportunities, FDA-approved drug-R788 and AMX served as effective TBK1 inhibitors. The subsequent pharmacological studies validated the potential of R788 and AMX for treating specific ALS subtypes through the inhibition of TBK1 phosphorylation.

Innovative strategies for measuring kinase activity to accelerate the next wave of novel kinase inhibitors

The development of protein kinase inhibitors (PKIs) has gained significance owing to their therapeutic potential for diseases like cancer. In addition, there has been a rise in refining kinase activity assays, each possessing unique biological and analytical characteristics crucial for PKI development. However, the PKI development pipeline experiences high attrition rates and approved PKIs exhibit unexploited potential because of variable patient responses. Enhancing PKI development efficiency involves addressing challenges related to understanding the PKI mechanism of action and employing biomarkers for precision medicine. Selecting appropriate kinase activity assays for these challenges can overcome these attrition rate issues. This review delves into the current obstacles in kinase inhibitor development and elucidates kinase activity assays that can provide solutions.

Current trends and future prospects of drug repositioning in gastrointestinal oncology

Gastrointestinal (GI) cancers comprise a significant number of cancer cases worldwide and contribute to a high percentage of cancer-related deaths. To improve survival rates of GI cancer patients, it is important to find and implement more effective therapeutic strategies with better prognoses and fewer side effects. The development of new drugs can be a lengthy and expensive process, often involving clinical trials that may fail in the early stages. One strategy to address these challenges is drug repurposing (DR). Drug repurposing is a developmental strategy that involves using existing drugs approved for other diseases and leveraging their safety and pharmacological data to explore their potential use in treating different diseases. In this paper, we outline the existing therapeutic strategies and challenges associated with GI cancers and explore DR as a promising alternative approach. We have presented an extensive review of different DR methodologies, research efforts and examples of repurposed drugs within various GI cancer types, such as colorectal, pancreatic and liver cancers. Our aim is to provide a comprehensive overview of employing the DR approach in GI cancers to inform future research endeavors and clinical trials in this field.

Exploring the Druggable Conformational Space of Protein Kinases Using AI-Generated Structures

Protein kinase function and interactions with drugs are controlled in part by the movement of the DFG and ɑC-Helix motifs, which enable kinases to adopt various conformational states. Small molecule ligands elicit therapeutic effects with distinct selectivity profiles and residence times that often depend on the kinase conformation(s) they bind. However, the limited availability of experimentally determined structural data for kinases in inactive states restricts drug discovery efforts for this major protein family. Modern AI-based structural modeling methods hold potential for exploring the previously experimentally uncharted druggable conformational space for kinases. Here, we first evaluated the currently explored conformational space of kinases in the PDB and models generated by AlphaFold2 (AF2) (1) and ESMFold (2), two prominent AI-based structure prediction methods. We then investigated AF2's ability to predict kinase structures in different conformations at various multiple sequence alignment (MSA) depths, based on this parameter's ability to explore conformational diversity. Our results showed a bias within the PDB and predicted structural models generated by AF2 and ESMFold toward structures of kinases in the active state over alternative conformations, particularly those conformations controlled by the DFG motif. Finally, we demonstrate that predicting kinase structures using AF2 at lower MSA depths allows the exploration of the space of these alternative conformations, including identifying previously unobserved conformations for 398 kinases. The results of our analysis of structural modeling by AF2 create a new avenue for the pursuit of new therapeutic agents against a notoriously difficult-to-target family of proteins.

Significance Statement

Greater abundance of kinase structural data in inactive conformations, currently lacking in structural databases, would improve our understanding of how protein kinases function and expand drug discovery and development for this family of therapeutic targets. Modern approaches utilizing artificial intelligence and machine learning have potential for efficiently capturing novel protein conformations. We provide evidence for a bias within AlphaFold2 and ESMFold to predict structures of kinases in their active states, similar to their overrepresentation in the PDB. We show that lowering the AlphaFold2 algorithm's multiple sequence alignment depth can help explore kinase conformational space more broadly. It can also enable the prediction of hundreds of kinase structures in novel conformations, many of whose models are likely viable for drug discovery.

Applications of promiscuity of FDA-approved kinase inhibitors in drug repositioning and toxicity

Promiscuity of therapeutics has important implications in treatment and toxicity. So far, a comprehensive understanding of promiscuity related to kinase inhibitors is lacking and such an analysis may offer potential opportunities for drug repurposing. In the present study, profiling of inhibitor-specific kinases based on the available biochemical IC50s was performed, fold-change of IC50 values for additional targets were calculated by taking the primary target as the reference kinase, and finally the promiscuity degree (PD) for FDA-approved kinase inhibitors was calculated. Surprisingly, class II inhibitors showed more PD than that of the class I inhibitors. We further identified cancer types and sub-types in which additional kinase targets or off-targets of inhibitors were overexpressed for potential drug repurposing. In addition, the expression of these kinases in normal human tissues were also profiled to predict toxicity following drug repositioning. Taken together, the study offers opportunities for cancer treatment in a kinase-specific manner.

Anti-Leukaemic Activity of Rilpivirine Is Mediated by Aurora A Kinase Inhibition

Acute myeloid leukaemia (AML) affects predominantly elderly people and has an incidence of 1% of all cancers and 2% of all cancer deaths. Despite using intensive chemotherapy and allogeneic stem cell transplantation, the treatment options for AML remain open for innovation. Thus, there is a need to explore alternative therapies such as less toxic targeted therapies in AML. Aurora A kinase is a well-established target for the treatment of various cancers, including AML. This kinase plays a pivotal role in the cell-division cycle, particularly in different stages of mitosis, and is also involved in many other cellular regulatory processes. In a previous study, we demonstrated that the anti-viral drug rilpivirine is an Aurora A kinase inhibitor. In the current study, we have further explored the selectivity of rilpivirine for Aurora A kinase inhibition by testing this drug against a panel of 429 kinases. Concurrently, we demonstrated that rilpivirine significantly inhibited the proliferation of AML cells in a time- and concentration-dependent manner that was preceded by G₂/M cell-cycle arrest leading to the induction of apoptosis. Consistent with its kinase inhibitory role, rilpivirine modulated the expression of critical proteins in the Aurora A kinase-signalling pathway. Importantly, orally administered rilpivirine significantly inhibited tumour growth in an HL-60 xenograft model without showing body weight changes or other clinical signs of toxicity. Furthermore, rilpivirine enhanced the anti-proliferative efficacy of the conventional anti-leukaemic chemotherapeutic agent cytarabine. Collectively, these findings provide the stimulus to explore further the anti-leukaemic activity of the anti-viral drug rilpivirine.

An attention mechanism-based LSTM network for cancer kinase activity prediction

Despite the endeavours and achievements made in treating cancers during the past decades, resistance to available kinase drugs continues to be a major problem in cancer therapies. Thus, it is highly desirable to develop computational models that can predict the bioactivity of a compound against cancer kinases. Here, we present a Long Short-Term Memory (LSTM) framework for predicting the activities of lead molecules against seven different kinases. A total of 14,907 compounds from the ChEMBL database were selected for model building. Two different molecular representations, namely, 2D descriptors and MACCS fingerprints were subjected to the LSTM method for the training process. We also successfully integrated an attention mechanism into our model, which helped us to interpret the contribution of chemical features on kinase activity. The attention mechanism extracted the significant chemical moieties more effectively by taking them into consideration during the activity prediction. The recorded accuracies in the test sets for both 2D descriptors and MACCS fingerprints-based models were 0.81 and 0.78, respectively. The receiver operating characteristic curve (ROC)-area under the curve (AUC) score for both models was in the range of 0.8-0.99. The proposed framework can be a good starting point for the development of new cancer kinase drugs.

Exploring the Conformational Landscape and Stability of Aurora A Using Ion-Mobility Mass Spectrometry and Molecular Modeling

Protein kinase inhibitors are highly effective in treating diseases driven by aberrant kinase signaling and as chemical tools to help dissect the cellular roles of kinase signaling complexes. Evaluating the effects of binding of small molecule inhibitors on kinase conformational dynamics can assist in understanding both inhibition and resistance mechanisms. Using gas-phase ion-mobility mass spectrometry (IM-MS), we characterize changes in the conformational landscape and stability of the protein kinase Aurora A (Aur A) driven by binding of the physiological activator TPX2 or small molecule inhibition. Aided by molecular modeling, we establish three major conformations, the relative abundances of which were dependent on the Aur A activation status: one highly populated compact conformer similar to that observed in most crystal structures, a second highly populated conformer possessing a more open structure infrequently found in crystal structures, and an additional low-abundance conformer not currently represented in the protein databank. Notably, inhibitor binding induces more compact configurations of Aur A, as adopted by the unbound enzyme, with both IM-MS and modeling revealing inhibitor-mediated stabilization of active Aur A.

Targeting Protein Kinases and Epigenetic Control as Combinatorial Therapy Options for Advanced Prostate Cancer Treatment

Prostate cancer (PC), the fifth leading cause of cancer-related mortality worldwide, is known as metastatic bone cancer when it spreads to the bone. Although there is still no effective treatment for advanced/metastatic PC, awareness of the molecular events that contribute to PC progression has opened up opportunities and raised hopes for the development of new treatment strategies. Androgen deprivation and androgen-receptor-targeting therapies are two gold standard treatments for metastatic PC. However, acquired resistance to these treatments is a crucial challenge. Due to the role of protein kinases (PKs) in the growth, proliferation, and metastases of prostatic tumors, combinatorial therapy by PK inhibitors may help pave the way for metastatic PC treatment. Additionally, PC is known to have epigenetic involvement. Thus, understanding epigenetic pathways can help adopt another combinatorial treatment strategy. In this study, we reviewed the PKs that promote PC to advanced stages. We also summarized some PK inhibitors that may be used to treat advanced PC and we discussed the importance of epigenetic control in this cancer. We hope the information presented in this article will contribute to finding an effective treatment for the management of advanced PC.

Computational modeling identifies multitargeted kinase inhibitors as effective therapies for metastatic, castration-resistant prostate cancer

Metastatic, castration-resistant prostate cancer (mCRPC) is an advanced prostate cancer with limited therapeutic options and poor patient outcomes. To investigate whether multitargeted kinase inhibitors (KIs) represent an opportunity for mCRPC drug development, we applied machine learning–based functional screening and identified two KIs, PP121 and SC-1, which demonstrated strong suppression of CRPC growth in vitro and in vivo. Furthermore, we show the marked ability of these KIs to improve on standard-of-care chemotherapy in both tumor response and survival, suggesting that combining multitargeted KIs with chemotherapy represents a promising avenue for mCRPC treatment. Overall, our findings demonstrate the application of a multidisciplinary strategy that blends bench science with machine-learning approaches for rapidly identifying KIs that result in desired phenotypic effects.

Castration-resistant prostate cancer (CRPC) is an advanced subtype of prostate cancer with limited therapeutic options. Here, we applied a systems-based modeling approach called kinome regularization (KiR) to identify multitargeted kinase inhibitors (KIs) that abrogate CRPC growth. Two predicted KIs, PP121 and SC-1, suppressed CRPC growth in two-dimensional in vitro experiments and in vivo subcutaneous xenografts. An ex vivo bone mimetic environment and in vivo tibia xenografts revealed resistance to these KIs in bone. Combining PP121 or SC-1 with docetaxel, standard-of-care chemotherapy for late-stage CRPC, significantly reduced tibia tumor growth in vivo, decreased growth factor signaling, and vastly extended overall survival, compared to either docetaxel monotherapy. These results highlight the utility of computational modeling in forming physiologically relevant predictions and provide evidence for the role of multitargeted KIs as chemosensitizers for late-stage, metastatic CRPC.

Characterising proteolysis during SARS-CoV-2 infection identifies viral cleavage sites and cellular targets with therapeutic potential

SARS-CoV-2 is the causative agent behind the COVID-19 pandemic, responsible for over 170 million infections, and over 3.7 million deaths worldwide. Efforts to test, treat and vaccinate against this pathogen all benefit from an improved understanding of the basic biology of SARS-CoV-2. Both viral and cellular proteases play a crucial role in SARS-CoV-2 replication. Here, we study proteolytic cleavage of viral and cellular proteins in two cell line models of SARS-CoV-2 replication using mass spectrometry to identify protein neo-N-termini generated through protease activity. We identify previously unknown cleavage sites in multiple viral proteins, including major antigens S and N: the main targets for vaccine and antibody testing efforts. We discover significant increases in cellular cleavage events consistent with cleavage by SARS-CoV-2 main protease, and identify 14 potential high-confidence substrates of the main and papain-like proteases. We show that siRNA depletion of these cellular proteins inhibits SARS-CoV-2 replication, and that drugs targeting two of these proteins: the tyrosine kinase SRC and Ser/Thr kinase MYLK, show a dose-dependent reduction in SARS-CoV-2 titres. Overall, our study provides a powerful resource to understand proteolysis in the context of viral infection, and to inform the development of targeted strategies to inhibit SARS-CoV-2 and treat COVID-19.

Repurposing existing therapeutics, its importance in oncology drug development: Kinases as a potential target

Repurposing the large arsenal of existing non‐cancer drugs is an attractive proposition to expand the clinical pipelines for cancer therapeutics. The earlier successes in repurposing resulted primarily from serendipitous findings, but more recently, drug or target‐centric systematic identification of repurposing opportunities continues to rise. Kinases are one of the most sought‐after anti‐cancer drug targets over the last three decades. There are many non‐cancer approved drugs that can inhibit kinases as “off‐targets” as well as many existing kinase inhibitors that can target new additional kinases in cancer. Identifying cancer‐associated kinase inhibitors through mining commercial drug databases or new kinase targets for existing inhibitors through comprehensive kinome profiling can offer more effective trial‐ready options to rapidly advance drugs for clinical validation. In this review, we argue that drug repurposing is an important approach in modern drug development for cancer therapeutics. We have summarized the advantages of repurposing, the rationale behind this approach together with key barriers and opportunities in cancer drug development. We have also included examples of non‐cancer drugs that inhibit kinases or are associated with kinase signalling as a basis for their anti‐cancer action.

KiRNet: Kinase-centered network propagation of pharmacological screen results

The ever-increasing size and scale of biological information have popularized network-based approaches as a means to interpret these data. We develop a network propagation method that integrates kinase-inhibitor-focused functional screens with known protein-protein interactions (PPIs). This method, dubbed KiRNet, uses an a priori edge-weighting strategy based on node degree to establish a pipeline from a kinase inhibitor screen to the generation of a predictive PPI subnetwork. We apply KiRNet to uncover molecular regulators of mesenchymal cancer cells driven by overexpression of Frizzled 2 (FZD2). KiRNet produces a network model consisting of 166 high-value proteins. These proteins exhibit FZD2-dependent differential phosphorylation, and genetic knockdown studies validate their role in maintaining a mesenchymal cell state. Finally, analysis of clinical data shows that mesenchymal tumors exhibit significantly higher average expression of the 166 corresponding genes than epithelial tumors for nine different cancer types.

Nanomedicine for Gene Delivery and Drug Repurposing in the Treatment of Muscular Dystrophies

Muscular Dystrophies (MDs) are a group of rare inherited genetic muscular pathologies encompassing a variety of clinical phenotypes, gene mutations and mechanisms of disease. MDs undergo progressive skeletal muscle degeneration causing severe health problems that lead to poor life quality, disability and premature death. There are no available therapies to counteract the causes of these diseases and conventional treatments are administered only to mitigate symptoms. Recent understanding on the pathogenetic mechanisms allowed the development of novel therapeutic strategies based on gene therapy, genome editing CRISPR/Cas9 and drug repurposing approaches. Despite the therapeutic potential of these treatments, once the actives are administered, their instability, susceptibility to degradation and toxicity limit their applications. In this frame, the design of delivery strategies based on nanomedicines holds great promise for MD treatments. This review focuses on nanomedicine approaches able to encapsulate therapeutic agents such as small chemical molecules and oligonucleotides to target the most common MDs such as Duchenne Muscular Dystrophy and the Myotonic Dystrophies. The challenge related to in vitro and in vivo testing of nanosystems in appropriate animal models is also addressed. Finally, the most promising nanomedicine-based strategies are highlighted and a critical view in future developments of nanomedicine for neuromuscular diseases is provided.

Emerging antiviral therapeutics for human adenovirus infection: Recent developments and novel strategies

Human adenoviruses (HAdV) are ubiquitous human pathogens that cause a significant burden of respiratory, ocular, and gastrointestinal illnesses. Although HAdV infections are generally self-limiting, pediatric and immunocompromised individuals are at particular risk for developing severe disease. Currently, no approved antiviral therapies specific to HAdV exist. Recent outbreaks underscore the need for effective antiviral agents to treat life-threatening infections. In this review we will focus on recent developments in search of potential therapeutic agents for controlling HAdV infections, with a focus on those targeting post-entry stages of the virus replicative cycle.

Discovery of DB18, a potent inhibitor of CLK kinases with a high selectivity against DYRK1A kinase

We describe in this paper the synthesis of a novel series of anilino-2-quinazoline derivatives. These compounds have been screened against a panel of eight mammalian kinases and in parallel they were tested for cytotoxicity on a representative panel of seven cancer cell lines. One of them (DB18) has been found to be a very potent inhibitor of human "CDC2-like kinases" CLK1, CLK2 and CLK4, with IC50 values in the 10-30 nM range. Interestingly, this molecule is inactive at 100 μM on the closely related "dual-specificity tyrosine-regulated kinase 1A" (DYRK1A). Extensive molecular simulation studies have been performed on the relevant kinases to explain the strong affinity of this molecule on CLKs, as well as its selectivity against DYRK1A.

Same but different - Molecular comparison of human KTI12 and PSTK

Kti12 and PSTK are closely related and highly similar proteins implicated in different aspects of tRNA metabolism. Kti12 has been identified as an essential regulatory factor of the Elongator complex, involved in the modification of uridine bases in eukaryotic tRNAs. PSTK phosphorylates the tRNA^Sec-bound amino acid serine, which is required to synthesize selenocysteine. Kti12 and PSTK have previously been studied independently in various organisms, but only appear simultaneously in some animalia, including humans. As Kti12- and PSTK-related pathways are clinically relevant, it is of prime importance to understand their biological functions and mutual relationship in humans. Here, we use different tRNA substrates to directly compare the enzymatic activities of purified human KTI12 and human PSTK proteins. Our complementary Co-IP and BioID2 approaches in human cells confirm that Elongator is the main interaction partner of KTI12 but additionally indicate potential links to proteins involved in vesicular transport, RNA metabolism and deubiquitination. Moreover, we identify and validate a yet uncharacterized interaction between PSTK and γ-taxilin. Foremost, we demonstrate that human KTI12 and PSTK do not share interactors or influence their respective biological functions. Our data provide a comprehensive analysis of the regulatory networks controlling the activity of the human Elongator complex and selenocysteine biosynthesis.

Thrombosis in IBD in the Era of JAK Inhibition

Patients with inflammatory bowel diseases (IBD) have an increased risk of thrombosis. The interaction between inflammation and coagulation has extensively been studied. It is well-- known that some drugs can influence the haemostatic system, but several concerns on the association between therapies and increased risk of thrombosis remain open. While biologics seem to have a protective role against thrombosis via their anti-inflammatory effect, some concerns about an increased risk of thrombosis with JAK inhibitors have been raised. We conducted a literature review to assess the association between biologics/small molecules and venous/arterial thrombotic complications. An increased risk of venous and arterial thrombosis was found in patients treated with corticosteroids, whereas anti-TNFα were considered protective agents. No thromboembolic adverse event was reported with vedolizumab and ustekinumab. In addition, thromboembolic events rarely occurred in patients with ulcerative colitis (UC) after therapy with tofacitinib. The overall risk of both venous and arterial thrombosis was not increased based on the available evidence. Finally, in the era of JAK inhibitors, the treatment should be individualized by evaluating the pre-existing potential thrombotic risk balanced with the intrinsic risk of the medication used.

Integrated Omics of Metastatic Colorectal Cancer

We integrate the genomics, proteomics, and phosphoproteomics of 480 clinical tissues from 146 patients in a Chinese colorectal cancer (CRC) cohort, among which 70 had metastatic CRC (mCRC). Proteomic profiling differentiates three CRC subtypes characterized by distinct clinical prognosis and molecular signatures. Proteomic and phosphoproteomic profiling of primary tumors alone successfully distinguishes cases with metastasis. Metastatic tissues exhibit high similarities with primary tumors at the genetic but not the proteomic level, and kinase network analysis reveals significant heterogeneity between primary colorectal tumors and their liver metastases. In vivo xenograft-based drug tests using 31 primary and metastatic tumors show personalized responses, which could also be predicted by kinase-substrate network analysis no matter whether tumors carry mutations in the drug-targeted genes. Our study provides a valuable resource for better understanding of mCRC and has potential for clinical application.

An insight into the recent development of the clinical candidates for the treatment of malaria and their target proteins

Malaria is an endemic disease, prevalent in tropical and subtropical regions which cost half of million deaths annually. The eradication of malaria is one of the global health priority nevertheless, current therapeutic efforts seem to be insufficient due to the emergence of drug resistance towards most of the available drugs, even first-line treatment ACT, unavailability of the vaccine, and lack of drugs with a new mechanism of action. Intensification of antimalarial research in recent years has resulted into the development of single dose multistage therapeutic agents which has advantage of overcoming the antimalarial drug resistance. The present review explored the current progress in the development of new promising antimalarials against prominent target proteins that have the potential to be a clinical candidate. Here, we also reviewed different aspects of drug resistance and highlighted new drug candidates that are currently in a clinical trial or clinical development, along with a few other molecules with excellent antimalarial activity overs ACTs. The summarized scientific value of previous approaches and structural features of antimalarials related to the activity are highlighted that will be helpful for the development of next-generation antimalarials.

Overcoming cancer therapeutic bottleneck by drug repurposing

Ever present hurdles for the discovery of new drugs for cancer therapy have necessitated the development of the alternative strategy of drug repurposing, the development of old drugs for new therapeutic purposes. This strategy with a cost-effective way offers a rare opportunity for the treatment of human neoplastic disease, facilitating rapid clinical translation. With an increased understanding of the hallmarks of cancer and the development of various data-driven approaches, drug repurposing further promotes the holistic productivity of drug discovery and reasonably focuses on target-defined antineoplastic compounds. The "treasure trove" of non-oncology drugs should not be ignored since they could target not only known but also hitherto unknown vulnerabilities of cancer. Indeed, different from targeted drugs, these old generic drugs, usually used in a multi-target strategy may bring benefit to patients. In this review, aiming to demonstrate the full potential of drug repurposing, we present various promising repurposed non-oncology drugs for clinical cancer management and classify these candidates into their proposed administration for either mono- or drug combination therapy. We also summarize approaches used for drug repurposing and discuss the main barriers to its uptake.

Structure-Based Drug Design for Tuberculosis: Challenges Still Ahead

Structure-based and computer-aided drug design approaches are commonly considered to have been successful in the fields of cancer and antiviral drug discovery but not as much for antibacterial drug development. The search for novel anti-tuberculosis agents is indeed an emblematic example of this trend. Although huge efforts, by consortiums and groups worldwide, dramatically increased the structural coverage of the Mycobacterium tuberculosis proteome, the vast majority of candidate drugs included in clinical trials during the last decade were issued from phenotypic screenings on whole mycobacterial cells. We developed here three selected case studies, i.e., the serine/threonine (Ser/Thr) kinases—protein kinase (Pkn) B and PknG, considered as very promising targets for a long time, and the DNA gyrase of M. tuberculosis, a well-known, pharmacologically validated target. We illustrated some of the challenges that rational, target-based drug discovery programs in tuberculosis (TB) still have to face, and, finally, discussed the perspectives opened by the recent, methodological developments in structural biology and integrative techniques.

The protein kinase MAP3K19 phosphorylates MAP2Ks and thereby activates ERK and JNK kinases and increases viability of KRAS-mutant lung cancer cells

Identifying additional mitogen-activated protein kinase (MAPK) pathway regulators is invaluable in aiding our understanding of the complex signaling networks that regulate cellular processes, including cell proliferation and survival. Here, using in vitro kinase assays and by expressing WT or kinase-dead MAPK kinase kinase 19 (MAP3K19) in the HEK293T cell line and assessing activation of the extracellular signal-regulated kinase (ERK) and JUN N-terminal kinase (JNK) signaling pathways, we defined MAP3K19 as a novel regulator of MAPK signaling. We also observed that overexpression of WT MAP3K19 activates both the ERK and JNK pathways in a panel of cancer cell lines. Furthermore, MAP3K19 sustained ERK pathway activation in the presence of inhibitors targeting the RAF proto-oncogene Ser/Thr protein kinase (RAF) and MAPK/ERK kinase, indicating that MAP3K19 activates ERK via a RAF-independent mechanism. Findings from in vitro and in-cell kinase assays demonstrate that MAP3K19 is a kinase that directly phosphorylates both MAPK/ERK kinase (MEK) and MAPK kinase 7 (MKK7). Results from an short-hairpin RNA screen indicated that MAP3K19 is essential for maintaining survival in KRAS-mutant cancers; therefore, we depleted or inhibited MAP3K19 in KRAS-mutant cancer cell lines and observed that this reduces viability and decreases ERK and JNK pathway activation. In summary, our results reveal that MAP3K19 directly activates the ERK and JNK cascades and highlight a role for this kinase in maintaining survival of KRAS-mutant lung cancer cells.

Identification of molecular targets for the targeted treatment of gastric cancer using dasatinib

Gastric cancer (GC) remains the third leading cause of cancer-related death despite several improvements in targeted therapy. There is therefore an urgent need to investigate new treatment strategies, including the identification of novel biomarkers for patient stratification. In this study, we evaluated the effect of FDA-approved kinase inhibitors on GC. Through a combination of cell growth, migration and invasion assays, we identified dasatinib as an efficient inhibitor of GC proliferation. Mass-spectrometry-based selectivity profiling and subsequent knockdown experiments identified members of the SRC family of kinases including SRC, FRK, LYN and YES, as well as other kinases such as DDR1, ABL2, SIK2, RIPK2, EPHA2, and EPHB2 as dasatinib targets. The expression levels of the identified kinases were investigated on RNA and protein level in 200 classified tumor samples from patients, who had undergone gastrectomy, but had received no treatment. Levels of FRK, DDR1 and SRC expression on both mRNA and protein level were significantly higher in metastatic patient samples regardless of the tumor stage, while expression levels of SIK2 correlated with tumor size. Collectively, our data suggest dasatinib for treatment of GC based on its unique property, inhibiting a small number of key kinases (SRC, FRK, DDR1 and SIK2), highly expressed in GC patients.

Antipsychotic agent pimozide promotes reversible proliferative suppression by inducing cellular quiescence in liver cancer

The antipsychotic drug pimozide has been found to exhibit anticancer effects. Previously, it was demonstrated that pimozide inhibits hepatocellular carcinoma (HCC) cell growth, but its pharmacodynamic characteristics remain unclear. The aim of the present study was to investigate the reversibility and mechanism of the ability of pimozide to inhibit cell proliferation in liver cancer. Cell viability was determined by Cell Counting Kit‑8 and colony formation assay. The cell cycle distribution was analyzed by flow cytometry with Ki‑67 and PI staining. ROS production of HCC cells was detected with DCFH‑DA and inhibited with NAC treatment. Western blot assay was performed to detect the expression of related signaling molecules in HCC cells. Our results showed that pimozide promoted G0/G1 phase arrest in HCC cell lines without significant cell death. Its anti‑proliferative effects on HCC cells were reversible, consistent with involvement of cell quiescence and reactive oxygen species (ROS) production. Pimozide enhanced inhibition of HCC cell proliferation by sorafenib. In conclusion, elucidation of pimozide's reversible proliferation inhibition in liver cancer and additive activity with a well‑established anticancer drug warrants further exploration of the potential of pimozide as an adjuvant anticancer therapy.