Computer-aided design, synthesis and biological characterization of novel inhibitors for PKMYT1

Structural and energetic insights into the selective inhibition of PKMYT1 against WEE1

Protein kinase, membrane-associated tyrosine/threonine 1 (PKMYT1), a member of the WEE family and responsible for the regulation of CDK1 phosphorylation, has been considered a promising therapeutic target for cancer therapy. However, the highly structural conservation of the ATP-binding sites of the WEE family poses a challenge to the design of selective inhibitors for PKMYT1. Here, molecular docking, multiple microsecond-length molecular dynamics (MD) simulations and end-point free energy calculations were performed to uncover the molecular mechanism of the binding selectivity of RP-6306 toward PKMYT1 over its highly homologous kinase WEE1. The binding specificity of RP-6306 reported in previous experimental bioassays was clarified by MD simulations and binding free energy calculations. Further, the binding free energy prediction indicated that the binding selectivity of RP-6306 largely derived from the difference in the protein-ligand electrostatic interactions. The per-residue free energy decomposition suggested that the non-conserved gatekeeper residue in the hinge domain of PKMYT1/WEE1, Thr187/Asn376, is the critical factor responsible for the binding selectivity of RP-6306 toward PKMYT1. In addition, a water-mediated hydrogen bond was formed between RP-6306 and Gly191 at the hinge domain in the PKMYT1/RP-6306 complex, which was absent in the WEE1/RP-6306 complex. This study is expected to offer useful information for the design of more potent and selective PKMYT1 inhibitors.Communicated by Ramaswamy H. Sarma.

Myt1 kinase inhibitors - Insight into structural features, offering potential frameworks

The cell cycle includes two checkpoint arrests allowing to repair of damaged DNA. Many cancer cell lines exhibit weak G1 checkpoint mechanisms relying significantly more on the G2 checkpoint than do healthy cells. Inhibition of Myt1 kinase (PKMYT1), a forgotten member of the Wee family, cyclin-dependent kinase 1 (Cdk1) inhibitory kinase, target for G2 checkpoint abrogation, whose inhibition forces cells into premature unchecked mitosis resulting in cell death, is a promising concept for anticancer therapy. There are not many inhibitors of this emerging, potentially clinically important kinase. Herein, the valuable insight into structural features and binding mechanisms of diaminopyrimidines, aminoquinolines, quinazolines, pyrido[2,3-d]pyrimidines, pyrazolo[3,4-d]pyrimidines, and pyrrolo[2,3-b]quinoxalines, as well as finally made a general scheme of fragmented structures of Myt1 inhibitors with the enzyme, offer potential frameworks useful for future directions, for further chemical optimizations, in the discovery and the design of novel effective structures, potential therapeutics.

KinomeMETA: meta-learning enhanced kinome-wide polypharmacology profiling

Kinase inhibitors are crucial in cancer treatment, but drug resistance and side effects hinder the development of effective drugs. To address these challenges, it is essential to analyze the polypharmacology of kinase inhibitor and identify compound with high selectivity profile. This study presents KinomeMETA, a framework for profiling the activity of small molecule kinase inhibitors across a panel of 661 kinases. By training a meta-learner based on a graph neural network and fine-tuning it to create kinase-specific learners, KinomeMETA outperforms benchmark multi-task models and other kinase profiling models. It provides higher accuracy for understudied kinases with limited known data and broader coverage of kinase types, including important mutant kinases. Case studies on the discovery of new scaffold inhibitors for membrane-associated tyrosine- and threonine-specific cdc2-inhibitory kinase and selective inhibitors for fibroblast growth factor receptors demonstrate the role of KinomeMETA in virtual screening and kinome-wide activity profiling. Overall, KinomeMETA has the potential to accelerate kinase drug discovery by more effectively exploring the kinase polypharmacology landscape.

The SwissSimilarity 2021 Web Tool: Novel Chemical Libraries and Additional Methods for an Enhanced Ligand-Based Virtual Screening Experience

Hit finding, scaffold hopping, and structure–activity relationship studies are important tasks in rational drug discovery. Implementation of these tasks strongly depends on the availability of compounds similar to a known bioactive molecule. SwissSimilarity is a web tool for low-to-high-throughput virtual screening of multiple chemical libraries to find molecules similar to a compound of interest. According to the similarity principle, the output list of molecules generated by SwissSimilarity is expected to be enriched in compounds that are likely to share common protein targets with the query molecule and that can, therefore, be acquired and tested experimentally in priority. Compound libraries available for screening using SwissSimilarity include approved drugs, clinical candidates, known bioactive molecules, commercially available and synthetically accessible compounds. The first version of SwissSimilarity launched in 2015 made use of various 2D and 3D molecular descriptors, including path-based FP2 fingerprints and ElectroShape vectors. However, during the last few years, new fingerprinting methods for molecular description have been developed or have become popular. Here we would like to announce the launch of the new version of the SwissSimilarity web tool, which features additional 2D and 3D methods for estimation of molecular similarity: extended-connectivity, MinHash, 2D pharmacophore, extended reduced graph, and extended 3D fingerprints. Moreover, it is now possible to screen for molecular structures having the same scaffold as the query compound. Additionally, all compound libraries available for screening in SwissSimilarity have been updated, and several new ones have been added to the list. Finally, the interface of the website has been comprehensively rebuilt to provide a better user experience. The new version of SwissSimilarity is freely available starting from December 2021.

The QSAR Paradigm in Fragment-Based Drug Discovery: From the Virtual Generation of Target Inhibitors to Multi-Scale Modeling

Fragment-Based Drug Design (FBDD) has established itself as a promising approach in modern drug discovery, accelerating and improving lead optimization, while playing a crucial role in diminishing the high attrition rates at all stages in the drug development process. On the other hand, FBDD has benefited from the application of computational methodologies, where the models derived from the Quantitative Structure-Activity Relationships (QSAR) have become consolidated tools. This mini-review focuses on the evolution and main applications of the QSAR paradigm in the context of FBDD in the last five years. This report places particular emphasis on the QSAR models derived from fragment-based topological approaches to extract physicochemical and/or structural information, allowing to design potentially novel mono- or multi-target inhibitors from relatively large and heterogeneous databases. Here, we also discuss the need to apply multi-scale modeling, to exemplify how different datasets based on target inhibition can be simultaneously integrated and predicted together with other relevant endpoints such as the biological activity against non-biomolecular targets, as well as in vitro and in vivo toxicity and pharmacokinetic properties. In this context, seminal papers are briefly analyzed. As huge amounts of data continue to accumulate in the domains of the chemical, biological and biomedical sciences, it has become clear that drug discovery must be viewed as a multi-scale optimization process. An ideal multi-scale approach should integrate diverse chemical and biological data and also serve as a knowledge generator, enabling the design of potentially optimal chemicals that may become therapeutic agents.

Binding Free Energy (BFE) Calculations and Quantitative Structure-Activity Relationship (QSAR) Analysis of Schistosoma mansoni Histone Deacetylase 8 (smHDAC8) Inhibitors

Histone-modifying proteins have been identified as promising targets to treat several diseases including cancer and parasitic ailments. In silico methods have been incorporated within a variety of drug discovery programs to facilitate the identification and development of novel lead compounds. In this study, we explore the binding modes of a series of benzhydroxamates derivatives developed as histone deacetylase inhibitors of Schistosoma mansoni histone deacetylase (smHDAC) using molecular docking and binding free energy (BFE) calculations. The developed docking protocol was able to correctly reproduce the experimentally established binding modes of resolved smHDAC8–inhibitor complexes. However, as has been reported in former studies, the obtained docking scores weakly correlate with the experimentally determined activity of the studied inhibitors. Thus, the obtained docking poses were refined and rescored using the Amber software. From the computed protein–inhibitor BFE, different quantitative structure–activity relationship (QSAR) models could be developed and validated using several cross-validation techniques. Some of the generated QSAR models with good correlation could explain up to ~73% variance in activity within the studied training set molecules. The best performing models were subsequently tested on an external test set of newly designed and synthesized analogs. In vitro testing showed a good correlation between the predicted and experimentally observed IC₅₀ values. Thus, the generated models can be considered as interesting tools for the identification of novel smHDAC8 inhibitors.

PKMYT1 Promotes Gastric Cancer Cell Proliferation and Apoptosis Resistance

Background

Abnormal expression of protein kinase membrane associated tyrosine/threonine 1 (PKMYT1) is closely associated with multiple types of cancers. In the present study, we examined the roles of PKMYT1 in gastric cancer (GC) progression.

Methods

We examined the expression status of PKMYT1 in GC tissues and cell lines. Meanwhile, short hairpin RNA (shRNA) was used to inhibit the endogenous expression of PKMYT1 in GC cells. Then we analyzed the effect of PKMYT1 on the malignant biological behavior of GC cells by in vitro and in vivo experiments.

Results

The findings showed high PKMYT1 expressions in GC tissues as well as a positive correlation between PKMYT1 expression and prognosis of patients with GC. Additional findings also revealed that PKMYT1 silencing significantly enhanced apoptosis and inhibited GC cell proliferation. In vivo, the silence of PKMYT1 inhibits tumor growth. Further analysis showed that the increase in PKMYT1 expressions led to malignant biological behavior through activation of the MAPK signaling pathway.

Conclusion

Our data suggested that PKMYT1 promotes cell proliferation and apoptosis resistance in GC cells by activating the MAPK signaling pathway, making it a potential therapeutic target for GC.

Virtual screening web servers: designing chemical probes and drug candidates in the cyberspace

The interplay between life sciences and advancing technology drives a continuous cycle of chemical data growth; these data are most often stored in open or partially open databases. In parallel, many different types of algorithms are being developed to manipulate these chemical objects and associated bioactivity data. Virtual screening methods are among the most popular computational approaches in pharmaceutical research. Today, user-friendly web-based tools are available to help scientists perform virtual screening experiments. This article provides an overview of internet resources enabling and supporting chemical biology and early drug discovery with a main emphasis on web servers dedicated to virtual ligand screening and small-molecule docking. This survey first introduces some key concepts and then presents recent and easily accessible virtual screening and related target-fishing tools as well as briefly discusses case studies enabled by some of these web services. Notwithstanding further improvements, already available web-based tools not only contribute to the design of bioactive molecules and assist drug repositioning but also help to generate new ideas and explore different hypotheses in a timely fashion while contributing to teaching in the field of drug development.

In silico Methods for Design of Kinase Inhibitors as Anticancer Drugs

Rational drug design implies usage of molecular modeling techniques such as pharmacophore modeling, molecular dynamics, virtual screening, and molecular docking to explain the activity of biomolecules, define molecular determinants for interaction with the drug target, and design more efficient drug candidates. Kinases play an essential role in cell function and therefore are extensively studied targets in drug design and discovery. Kinase inhibitors are clinically very important and widely used antineoplastic drugs. In this review, computational methods used in rational drug design of kinase inhibitors are discussed and compared, considering some representative case studies.

Systematic screening for potential therapeutic targets in osteosarcoma through a kinome-wide CRISPR-Cas9 library

Objective: Osteosarcoma is the most common primary malignant bone tumor. However, the survival of patients with osteosarcoma has remained unchanged during the past 30 years, owing to a lack of efficient therapeutic targets.

Methods: We constructed a kinome-targeting CRISPR-Cas9 library containing 507 kinases and 100 nontargeting controls and screened the potential kinase targets in osteosarcoma. The CRISPR screening sequencing data were analyzed with the Model-based Analysis of Genome-wide CRISPR/Cas9 Knockout (MAGeCK) Python package. The functional data were applied in the 143B cell line through lenti-CRISPR-mediated gene knockout. The clinical significance of kinases in the survival of patients with osteosarcoma was analyzed in the R2: Genomics Analysis and Visualization Platform.

Results: We identified 53 potential kinase targets in osteosarcoma. Among these targets, we analyzed 3 kinases, TRRAP, PKMYT1, and TP53RK, to validate their oncogenic functions in osteosarcoma. PKMYT1 and TP53RK showed higher expression in osteosarcoma than in normal bone tissue, whereas TRRAP showed no significant difference. High expression of all 3 kinases was associated with relatively poor prognosis in patients with osteosarcoma.

Conclusions: Our results not only offer potential therapeutic kinase targets in osteosarcoma but also provide a paradigm for functional genetic screening by using a CRISPR-Cas9 library, including target design, library construction, screening workflow, data analysis, and functional validation. This method may also be useful in potentially accelerating drug discovery for other cancer types.

Fragment-based drug design of nature-inspired compounds

Natural product (NP)-derived drugs can be extracts, biological macromolecules, or purified small molecule substances. Small molecule drugs can be originally purified from NPs, can represent semisynthetic molecules, natural fragments containing small molecules, or are fully synthetic molecules that mimic natural compounds. New semisynthetic NP-like drugs are entering the pharmaceutical market almost every year and reveal growing interests in the application of fragment-based approaches for NPs. Thus, several NP databases were constructed to be implemented in the fragment-based drug design (FBDD) workflows. FBDD has been established previously as an approach for hit identification and lead generation. Several biophysical and computational methods are used for fragment screening to identify potential hits. Once the fragments within the binding pocket of the protein are identified, they can be grown, linked, or merged to design more active compounds. This work discusses applications of NPs and NP scaffolds to FBDD. Moreover, it briefly reviews NP databases containing fragments and reports on case studies where the approach has been successfully applied for the design of antimalarial and anticancer drug candidates.

Application of the SwissDrugDesign Online Resources in Virtual Screening

SwissDrugDesign is an important initiative led by the Molecular Modeling Group of the SIB Swiss Institute of Bioinformatics. This project provides a collection of freely available online tools for computer-aided drug design. Some of these web-based methods, i.e., SwissSimilarity and SwissTargetPrediction, were especially developed to perform virtual screening, while others such as SwissADME, SwissDock, SwissParam and SwissBioisostere can find applications in related activities. The present review aims at providing a short description of these methods together with examples of their application in virtual screening, where SwissDrugDesign tools successfully supported the discovery of bioactive small molecules.

Overexpressed PKMYT1 promotes tumor progression and associates with poor survival in esophageal squamous cell carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is one of the most common malignant tumors worldwide and the 5-year overall survival rate remains poor. Protein kinase, membrane associated tyrosine/threonine (PKMYT1) is overexpressed in several cancers and participate in tumor progression. However, the mechanism of PKMYT1 in ESCC is unclear.

Purpose

The objective of our study was to demonstrate the the expression and role of PKMYT1 in ESCC.

Patients and methods

  We detected the expression of PKMYT1 in ESCC patients and analysed the correlation with overall survival time and disease-free survival time. Then we detected PKMYT1 expression in ESCC cell lines and immortalized human esophageal epithelial cell line. Down-regulated PKMYT1 was carried out in KYSE70 and KYSE450 cells to invetigate the mechanism of PKMYT1 in ESCC cells.

Results

PKMYT1 was up-regulated in tumor tissues and ESCC cell lines, and higher expression of PKMYT1 correlated with poorer overall survival in ESCC patients. Besides, in ESCC cell lines KYSE70 and KYSE450, knocking down PKMYT1 allowed more cells to skip G2/M checkpoint to complete mitosis, which promoted cell apoptosis, inhibited cell proliferation, and prevented the EMT phenotype in vitro. Meantime, we also observed that down-regulated PKMYT1 in ESCC cells suppressed AKT/mTOR signaling pathway. These results demonstrated PKMYT1 may act as an oncogene in ESCC.

Conclusion

PKMYT1 plays an crutial role in ESCC progression, downregulated PKMYT1 might inhibit the development of ESCC by AKT/mTOR signaling pathway, and might be a novel target in the treatment of ESCC.

Licochalcone B Extracted from Glycyrrhiza uralensis Fisch Induces Apoptotic Effects in Human Hepatoma Cell HepG2

The present study explored the molecular mechanism by which licochalcone B induces the cell cycle arrest and apoptosis in human hepatoma cell HepG2. Initial extraction and identification were performed by HPLC, UPLC-TOF-MS/MS, and NMR analysis, respectively. Licochalcone B inhibited the HepG2 growth with IC₅₀ (110.15 μM) after 24 h, caused morphological distortion, and seized the cell cycle in the G2/M phase (cell arrest in G2/M:43.1 ± 2.2% for 120 μM versus 23.7 ± 1.2% for control), as well as induced apoptosis and intracellular ROS generation. Furthermore, exposure to licochalcone B markedly affected the cell cycle (up/down regulation) at mRNA and protein levels. Apoptosis was induced through the activation of receptor-mediated and mitochondrial pathways. The inhibition of Caspase 8 and Caspase 9 proteins abolished the licochalcone B induced apoptosis. The present work suggested that licochalcone B may further be identified as a potent functional food component with specific health benefits.