Molecular modeling simulation studies reveal new potential inhibitors against HPV E6 protein

Recent update on the development of HPV16 inhibitors for cervical cancer

Persistent infection with human papillomavirus (HPV) can lead to cervical cancer (CC), which is the fourth most commonly diagnosed cancer in women globally. In this review, we have explained the HPV genome and the development of CC. Additionally, we summarized recently discovered small molecules that act as inhibitors of HPV-16. These molecules were identified through experimental and in-silico studies aimed at preventing or treating CC. HPV-16 and HPV-18 are the most common subtypes of HPV that cause CC globally. E6 oncoprotein of HPV-16 is considered the primary cause of CC progression. Therefore, E6 is the most focused targeted protein for developing specific and novel therapeutic inhibitors to treat HPV-related cancers. In recent years, various HPV inhibitors have been identified by means of experimental and in-silico studies. In addition, artificial intelligence-based medical diagnostic tools have grown more popular as they are capable of screening and diagnosing HPV-related cancer.

Virtual Screening, Molecular Docking and Molecular Dynamics Simulation of Bioactive Compounds from Various Indonesian Medicinal Plants as Potential Inhibitors of Human Papillomavirus Type 16 E6 Protein in Cervical Cancer Development

Infection of keratinocytes by high-risk human papillomavirus (HPV) strains, notably HPV16, is responsible for the onset of cervical cancer. The E6 protein serves as a pivotal oncoprotein implicated in the progression of cancer. We utilised a virtual screening method to identify bioactive compounds in a variety of commonly used medicinal plants in Indonesia. All the top five compounds bind to a single binding site on the E6 major hydrophobic groove, which corresponds to the binding site for the E6AP and IRF3's LxxLL motifs. They are expected to function as competitive inhibitors, inhibiting the development of the E6-E6AP and E6-IRF3 complexes, which limit p53 degradation and therefore cell proliferation, thus preserving the innate immune response to HPV16 infection. Asarinin and thiazolo[3,2-a]benzimidazole-3(2H)-one,2-(2-fluorobenzylideno)-7,8-dimethyl were predicted to be the most effective compounds in this research owing to their strong affinity for and persistent interactions with the E6 major hydrophobic groove, particularly in comparison to pharmacological controls.

Structure-based virtual screening and drug repurposing studies indicate potential inhibitors of bovine papillomavirus E6 oncoprotein

Bovine papillomavirus type 1 (BPV1) is an oncogenic virus that causes lesions and cancer in infected cattle. Despite being one of the most studied genotypes in the family and occurring in herds worldwide, there are currently no vaccines or drugs for its control. The viral E6 oncoprotein plays a crucial role in infection by this virus, making it a promising target for the development of new therapies. In this regard, we integrated structure-based virtual screening approaches, drug repositioning, and molecular dynamics to identify approved drugs with the potential to inhibit BPV1 E6. Our results reveal that Lumacaftor and MK-3207 are promising candidates for controlling BPV1 infection. The findings of this study may contribute to the development of E6 oncoprotein blockers in an accelerated and cost-effective manner.

Human papillomavirus-16 E6-positive cervical cancer attenuated by potent 2-(4-biphenylyl)-N-(1-ethyl-4-piperidinyl) acetamide second-generation analogs with improved binding affinity

Human papillomavirus (HPV) infection, particularly HPV16, is a major contributor to the development of cervical cancer. Given the urgent need for novel therapeutic strategies targeting HPV-associated cancers, this study focuses on characterizing second-generation analogs of a lead compound, as a potential inhibitor of HPV16-E6. Protein-ligand docking, Gibbs binding free energy estimation, and molecular dynamics simulations were conducted. HPV16-infected SiHa and CaSki cell lines were used. MTT (3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide) assay for proliferation and flow cytometry for target inhibition and apoptosis were employed. Computational and cell proliferation analyses revealed that modifications to E6-855, particularly in the piperidinyl group, enhanced binding affinities against HPV16-E6, with E6-272 demonstrating superior binding properties. Molecular dynamics simulations confirmed the stable binding of E6-272 to HPV16-E6, supported by favorable binding energy estimates. E6-272 inhibited the proliferation of SiHa and CaSki cells with GI50 values of 32.56 and 62.09 nM, respectively. The compound reduced HPV16-E6-positive population, while inducing the early and late phase apoptosis in these cells. Structural alterations at the piperidinyl group of E6-855 identified E6-272 as a promising inhibitor of HPV16-E6 with improved efficacy against HPV16-E6. Further experimental validation of E6-272 and its analogs warrant to advance its clinical utility in combating HPV-associated cancers.

Structure of the p53 degradation complex from HPV16

Human papillomavirus (HPV) is a significant contributor to the global cancer burden, and its carcinogenic activity is facilitated in part by the HPV early protein 6 (E6), which interacts with the E3-ligase E6AP, also known as UBE3A, to promote degradation of the tumor suppressor, p53. In this study, we present a single-particle cryoEM structure of the full-length E6AP protein in complex with HPV16 E6 (16E6) and p53, determined at a resolution of ~3.3 Å. Our structure reveals extensive protein-protein interactions between 16E6 and E6AP, explaining their picomolar binding affinity. These findings shed light on the molecular basis of the ternary complex, which has been pursued as a potential therapeutic target for HPV-driven cervical, anal, and oropharyngeal cancers over the last two decades. Understanding the structural and mechanistic underpinnings of this complex is crucial for developing effective therapies to combat HPV-induced cancers. Our findings may help to explain why previous attempts to disrupt this complex have failed to generate therapeutic modalities and suggest that current strategies should be reevaluated.

Computational exploration of FOXM1 inhibitors for glioblastoma: an integrated virtual screening and molecular dynamics simulation study

In this study, a comprehensive investigation of a set of phytochemicals to identify potential inhibitors for the Forkhead box protein M1 (FOXM1) was conducted. FOXM1 is overexpressed in glioblastoma (GBM) cells and plays a crucial role in cell cycle progression, proliferation, and invasion. FOXM1 inhibitors have shown promising results in preclinical studies, and ongoing clinical trials are assessing their efficacy in GBM patients. However, there are limited studies on the identification of novel compounds against this attractive therapeutic target. To address this, the NPACT database containing 1,574 phytochemicals was used, employing a hierarchical multistep docking approach, followed by an estimation of relative binding free energy. By fixing user-defined XP-dock and MM-GBSA cut-off scores of -6.096 and -37.881 kcal/mol, the chemical space was further narrowed. Through exhaustive analysis of molecular binding interactions and various pharmacokinetics profiles, we identified four compounds, namely NPACT00002, NPACT01454, NPACT00856, and NPACT01417, as potential FOXM1 inhibitors. To assess the stability of protein-ligand binding in dynamic conditions, 100 ns Molecular dynamics (MD) simulations studies were performed. Furthermore, Molecular mechanics with generalized Born and surface area solvation (MM-GBSA) based binding free energy estimations of the entire simulation trajectories revealed a strong binding affinity of all identified compounds towards FOXM1, surpassing that of the control drug Troglitazone. Based on extensively studied multistep docking approaches, we propose that these molecules hold promise as FOXM1 inhibitors for potential therapeutic applications in GBM. However, experimental validation will be necessary to confirm their efficacy as targeted therapies.

Finding potential inhibitors for Main protease (Mpro) of SARS-CoV-2 through virtual screening and MD simulation studies

SARS-CoV-2 is a highly hazardous species that can infect people with Covid-19 disease, dramatically increasing mortality rates worldwide. Plenty of researches have been done to find drugs or inhibitors, with this study aiming to identify an inhibitor within the ChEMBL database using computational approaches. From the ChEMBL library, 19,43,048 compounds which are known type of small compounds and proteins were downloaded and docked with the Main protease (Mpro). After performing compound screening using Lipinski's rule, Qikprop analysis following with virtual Screening, Induced Fit Docking (IFD) and MM-GBSA analysis with the Glide and Prime modules of Schrödinger, the best complex was subjected to MD simulation with Desmond. According to the docking results, small protein 2,371,668 and compound 1,090,395 were docked with Main protease with -12.6, -12.0 kcal/mol dock score and interacted with the functional site residues His 41 and Cys 145, as well as the binding site residues Thr 26, Phe 140, Asn 142, Gly 143, Glu 166, and Gln 189. Complex structures were shown to be steadier by the MD simulation study because both the ligands heavy atoms and the protein Cα atoms' RMSD values fell within acceptable ranges. As a result, this research suggests that the molecule CHEMBL2371668 and the compound CHEMBL1090395 may inhibit the activity of Main protease, and the usefulness of these molecules will be examined further through experimental research.

Pharmacophore based virtual screening for identification of effective inhibitors to combat HPV 16 E6 driven cervical cancer

Targeting HPV16 E6 has emerged as an effective drug target for the treatment/management of cervical cancer. We utilized pharmacophore-based virtual screening, molecular docking, absorption, distribution, metabolism and excretion (ADME) prediction, and molecular dynamics simulation approach for identifying potential inhibitors of HPV16 E6. Initially, we generated a ligand-based pharmacophore model based on the features of four known HPV16 E6 inhibitors (CA24, CA25, CA26, and CA27) via the PHASE module implanted in the Schrödinger suite. We constructed four-point pharmacophore features viz., three hydrogen bond acceptors (A) and one aromatic ring (R). The common pharmacophore feature further employed as a query for virtual screening against the ASINEX database via Schrödinger suite. The pharmacophore-based virtual screening filtered out top 2000 hits, based on the fitness score. We then applied the high throughput virtual screening (HTVS), standard precision (SP) and extra precision (XP). 1000 compounds were obtained from HTVS docking. Based on the glide score, they were further filtered to 500 hits by employing docking in standard precision mode. Finally, the best four hits and a negative molecule were identified using docking in XP mode. The four lead compounds and a negative molecule were then further subjected to ADME profile prediction by engaging Qikprop module. The ADME properties of the four lead molecules indicate good pharmacokinetic (PK) properties rather than the negative molecule. The binding stability of the HPV16 E6-hit complexes were investigated at a different time scale (100 ns) by using the desmond package and the results were examined using Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) and it revealed the stability of the protein-ligand complex throughout the simulation. Key residues, CYS 51 and GLN 107, also play a crucial role in enhancing the stability of the protein-ligand complex during the simulation. Furthermore, the binding free energy of the HPV16 E6-leads complexes was analyzed by prime which revealed that the ΔGbind coulomb and ΔGbind vdW interactions are crucially contributes to the binding affinity. In order to validate the computational findings, the efficacy of benzoimidazole and benzotriazole were ascertained for regulating ME180 cervical cancer cell survival, migration and ability to release MMP-2.

Targeting of HPV E6 at the binding sites to the host-cell E6AP, p53, and the endoplasmic reticulum-resident chaperone, GRP78

Background: Human papillomavirus (HPV) represents an etiological factor for many cancer types, especially cervical cancer. Its oncoprotein E6 sheds drug designers who aim to stop its cellular protein associations, such as p53 and E6AP. Recently, it was discovered that the host-cell chaperone glucose-regulated protein 78 (GRP78) plays a crucial function in HPV infectivity by association with the viral E6 and E7 proteins. Therefore, we aimed to test small molecules inhibitor that could contradict the association between E6 and cellular factors E6AP, GRP78, and p53. Methods: In this study, molecular docking protocol was elaborated to test 115 small molecule compounds against the three binding sites of HPV E6 to the host-cell proteins; E6AP, p53, and GRP78. After that, molecular dynamics simulation and free energy calculations were performed on the best three complexes. Results: The results reveal the potency of 18 compounds against the HPV E6 at different binding sites, which give lower free energies than paclitaxel (positive control). The best two compounds, hypericin, and anabsinthin, could bind effectively and stably during the 100 ns MD simulation period to HPV E6. The calculated average free energies for hypericin and anabsinthin are -18.76 and -14.40 kcal/mol, respectively. They formed stable complexes with the three binding sites by forming hydrophobic contacts. The key residues that stabilize the two ligands in HPV E6 binding sites are V31, Y32, V62, and Y70 (E6AP), P13, C16, T22, I23 and A46 (p53), and M1, V31, L50, L67, and Q107 (GRP78). Conclusions: The best two compounds, hypericin, and anabsinthin, are potential candidates against HPV E6 at the host-cell factors binding sites, hence could block the oncoprotein activity of E6 in infected cells. Further experimental validation is yet to be performed and suggested as future work.Communicated by Ramaswamy H. Sarma.

Evaluation of anticancer activity of Gmelina asiatica leaves, in-vitro and in-silico studies

Cervical cancer poses a major threat to women's health worldwide, constituting the fourth most prevalent cancer among the female population. High-risk variants of human papillomavirus (HPV) with its oncogenic proteins are a necessary cause of cervical cancer. Due to the resistance of cancer cells to the current treatment, there is a need for new medicines with new strategies to treat cervical cancer. Gmelina asiatica Linn. is a medicinal plant with various traditional uses and biological activities. Its anticancer potential against breast cancer and lymphoma has been demonstrated in the literature. In view of this, our study aims to investigate the anticancer activity of Gmelina asiatica leaves against cervical cancer. Various extracts of Gmelina asiatica leaves were prepared by soxhletation and maceration methods. The cytotoxic activity of the extracts was evaluated through in-vitro studies against SiHa cell line using MTT assay and fluorescence imaging. The most potent extract (GAME) phytochemical profile was analysed by UHPLC-HRMS. Further, in-silico studies were performed on its phytoconstituents against E6 oncoprotein, and the DFT studies were conducted on the active component to assess the physicochemical properties. In-vitro studies revealed that methanolic extract (GAME) showed the highest inhibition on the SiHa cell line compared to the other extracts and the control (p < 0.0001). In-silico studies indicated high affinity with stable interaction of the compound 5 (JC5ABDR) at E6 binding sites. This study revealed the importance of Gmelina asiatica plant as a potential source of anticancer molecules with a specific mode of action against cervical cancer.Communicated by Ramaswamy H. Sarma.

Anticancer Potential of Hydroxychavicol Derived from Piper betle L: An in Silico and Cytotoxicity Study

Piper betle L. is a popular medicinal plant in Asia, and extracts of the plant leaf are used for several therapeutics. It is known for its rich source of phenolic compounds, including hydroxychavicol. Hydroxychavicol is an allylbenzene that has gained much attention due to its anticancer properties. The current study quantified and purified hydroxychavicol from P. betle L. and predicted its anticancer competence through in silico and cytotoxicity studies. Leaf samples of 22 P. betle L. accessions from different locations of Tamil Nadu, India, were analyzed using reverse phase-high performance liquid chromatography for quantification of hydroxychavicol. The highest quantity of hydroxychavicol was obtained from the accession BV22 (89.2%). Chemical absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis of hydroxychavicol using SwissADME satisfied the physicochemical property guidelines of Lipinski's Rule of Five, ensuring its drug-likeness behavior. Molecular docking studies confirmed the interaction of hydroxychavicol with all 16 tested cancer targets. In Vitro MTT assay of hydroxychavicol in bone cancer cell lines (MG63) also demonstrated the anticancer competency, indicating the requirement to formulate the molecule as a drug in treating various types of cancers.

Taxifolin and Lucidin as Potential E6 Protein Inhibitors: p53 Function Re-Establishment and Apoptosis Induction in Cervical Cancer Cells

Simple Summary

Human papillomavirus (HPV)-related cancers continue to be a major medical concern, and there exists an urgent need to improve the current therapeutic approaches by combining strategies or proposing new compounds to offer more specific and less invasive treatments. The aim of this work was to discover potential inhibitors of the E6/E6AP/p53 complex formation. We started this work with an initial in silico approach including molecular docking and molecular dynamics simulations, and these tools allowed us to select potential inhibitors, using E6 protein as a target. In addition, we found that lucidin and taxifolin were able to selectively decrease the viability of HPV-positive cells to re-establish p53 protein levels and to induce apoptosis. These findings represent a promising starting point for the development of anti-HPV drugs.

Abstract

Cervical cancer is the fourth leading cause of death in women worldwide, with 99% of cases associated with a human papillomavirus (HPV) infection. Given that HPV prophylactic vaccines do not exert a therapeutic effect in individuals previously infected, have low coverage of all HPV types, and have poor accessibility in developing countries, it is unlikely that HPV-associated cancers will be eradicated in the coming years. Therefore, there is an emerging need for the development of anti-HPV drugs. Considering HPV E6’s oncogenic role, this protein has been proposed as a relevant target for cancer treatment. In the present work, we employed in silico tools to discover potential E6 inhibitors, as well as biochemical and cellular assays to understand the action of selected compounds in HPV-positive cells (Caski and HeLa) vs. HPV-negative (C33A) and non-carcinogenic (NHEK) cell lines. In fact, by molecular docking and molecular dynamics simulations, we found three phenolic compounds able to dock in the E6AP binding pocket of the E6 protein. In particular, lucidin and taxifolin were able to inhibit E6-mediated p53 degradation, selectively reduce the viability, and induce apoptosis in HPV-positive cells. Altogether, our data can be relevant for discovering promising leads for the development of specific anti-HPV drugs.

Deciphering the mechanisms of HPV E6 mutations in the destabilization of E6/E6AP/p53 complex

In epithelial tumors, oncoprotein E6 binds with the ubiquitin ligase E6AP to form E6/E6AP heterodimer; then this heterodimer recruits p53 to form E6/E6AP/p53 heterotrimer and induces p53 degradation. Recent experiments demonstrated that three E6 single-site mutants (F47R, R102A, and L50E) can inhibit the E6/E6AP/p53 heterotrimer formation and rescue p53 from the degradation pathway. However, the molecular mechanism underlying mutation-induced heterotrimer inhibition remains largely elusive. Herein, we performed extensive molecular dynamics simulations (totally ∼13 μs) on both heterodimer and heterotrimer to elucidate at an atomic level how each p53-degradation-defective HPV16 E6 mutant reduces the structural stabilities of the two complexes. Our simulations reveal that the three E6 mutations destabilize the structure of E6/E6AP/p53 complex through distinct mechanisms. Although F47R^E6 mutation has no effect on the structure of E6/E6AP heterodimer, it results in an electrostatic repulsion between R47^E6 and R290^p53, which is unfavorable for E6-p53 binding. R102A^E6 mutation destabilizes the structure of E6/E6AP heterodimer and significantly disrupts hydrophobic and cation-π interactions between F47^E6 and E286^p53/L298^p53/R290^p53. L50E^E6 mutation impairs both E6 interdomain interactions (especially F47-K108 cation-π interaction) and E6-E6AP intermolecular interactions important for the stabilization of E6/E6AP heterodimer. This study identifies the intra- and intermolecular interactions crucial for the complex stability, which may provide mechanistic insights into the inhibition of complex formation by the three HPV16 E6 mutations.

Integration of Molecular Docking Analysis and Molecular Dynamics Simulations for Studying Food Proteins and Bioactive Peptides

In silico tools, such as molecular docking, are widely applied to study interactions and binding affinity of biological activity of proteins and peptides. However, restricted sampling of both ligand and receptor conformations and use of approximated scoring functions can produce results that do not correlate with actual experimental binding affinities. Molecular dynamics simulations (MDS) can provide valuable information in deciphering functional mechanisms of proteins/peptides and other biomolecules, overcoming the rigid sampling limitations in docking analysis. This review will discuss the information related to the traditional use of in silico models, such as molecular docking, and its application for studying food proteins and bioactive peptides, followed by an in-depth introduction to the theory of MDS and description of why these molecular simulation techniques are important in the theoretical prediction of structural and functional dynamics of food proteins and bioactive peptides. Applications, limitations, and future prospects of MDS will also be discussed.

Machine learning prediction of antiviral-HPV protein interactions for anti-HPV pharmacotherapy

Persistent infection with high-risk types Human Papillomavirus could cause diseases including cervical cancers and oropharyngeal cancers. Nonetheless, so far there is no effective pharmacotherapy for treating the infection from high-risk HPV types, and hence it remains to be a severe threat to the health of female. Based on drug repositioning strategy, we trained and benchmarked multiple machine learning models so as to predict potential effective antiviral drugs for HPV infection in this work. Through optimizing models, measuring models' predictive performance using 182 pairs of antiviral-target interaction dataset which were all approved by the United States Food and Drug Administration, and benchmarking different models' predictive performance, we identified the optimized Support Vector Machine and K-Nearest Neighbor classifier with high precision score were the best two predictors (0.80 and 0.85 respectively) amongst classifiers of Support Vector Machine, Random forest, Adaboost, Naïve Bayes, K-Nearest Neighbors, and Logistic regression classifier. We applied these two predictors together and successfully predicted 57 pairs of antiviral-HPV protein interactions from 864 pairs of antiviral-HPV protein associations. Our work provided good drug candidates for anti-HPV drug discovery. So far as we know, we are the first one to conduct such HPV-oriented computational drug repositioning study.

Potential of E3 Ubiquitin Ligases in Cancer Immunity: Opportunities and Challenges

Cancer immunotherapies, including immune checkpoint inhibitors and immune pathway–targeted therapies, are promising clinical strategies for treating cancer. However, drug resistance and adverse reactions remain the main challenges for immunotherapy management. The future direction of immunotherapy is mainly to reduce side effects and improve the treatment response rate by finding new targets and new methods of combination therapy. Ubiquitination plays a crucial role in regulating the degradation of immune checkpoints and the activation of immune-related pathways. Some drugs that target E3 ubiquitin ligases have exhibited beneficial effects in preclinical and clinical antitumor treatments. In this review, we discuss mechanisms through which E3 ligases regulate tumor immune checkpoints and immune-related pathways as well as the opportunities and challenges for integrating E3 ligases targeting drugs into cancer immunotherapy.

Recent Developments in Free Energy Calculations for Drug Discovery

The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry.

Drug repurposing against SARS-CoV-2 receptor binding domain using ensemble-based virtual screening and molecular dynamics simulations

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused worldwide pandemic and is responsible for millions of worldwide deaths due to -a respiratory disease known as COVID-19. In the search for a cure of COVID-19, drug repurposing is a fast and cost-effective approach to identify anti-COVID-19 drugs from existing drugs. The receptor binding domain (RBD) of the SARS-CoV-2 spike protein has been a main target for drug designs to block spike protein binding to ACE2 proteins. In this study, we probed the conformational plasticity of the RBD using long molecular dynamics (MD) simulations, from which, representative conformations were identified using clustering analysis. Three simulated conformations and the original crystal structure were used to screen FDA approved drugs (2466 drugs) against the predicted binding site at the ACE2-RBD interface, leading to 18 drugs with top docking scores. Notably, 16 out of the 18 drugs were obtained from the simulated conformations, while the crystal structure suggests poor binding. The binding stability of the 18 drugs were further investigated using MD simulations. Encouragingly, 6 drugs exhibited stable binding with RBD at the ACE2-RBD interface and 3 of them (gonadorelin, fondaparinux and atorvastatin) showed significantly enhanced binding after the MD simulations. Our study shows that flexibility modeling of SARS-CoV-2 RBD using MD simulation is of great help in identifying novel agents which might block the interaction between human ACE2 and the SARS-CoV-2 RBD for inhibiting the virus infection.

In Silico Approaches: A Way to Unveil Novel Therapeutic Drugs for Cervical Cancer Management

Cervical cancer (CC) is the fourth most common pathology in women worldwide and presents a high impact in developing countries due to limited financial resources as well as difficulties in monitoring and access to health services. Human papillomavirus (HPV) is the leading cause of CC, and despite the approval of prophylactic vaccines, there is no effective treatment for patients with pre-existing infections or HPV-induced carcinomas. High-risk (HR) HPV E6 and E7 oncoproteins are considered biomarkers in CC progression. Since the E6 structure was resolved, it has been one of the most studied targets to develop novel and specific therapeutics to treat/manage CC. Therefore, several small molecules (plant-derived or synthetic compounds) have been reported as blockers/inhibitors of E6 oncoprotein action, and computational-aided methods have been of high relevance in their discovery and development. In silico approaches have become a powerful tool for reducing the time and cost of the drug development process. Thus, this review will depict small molecules that are already being explored as HR HPV E6 protein blockers and in silico approaches to the design of novel therapeutics for managing CC. Besides, future perspectives in CC therapy will be briefly discussed.

Targeting the Ubiquitin-Proteasome System for Cancer Therapeutics by Small-Molecule Inhibitors

The ubiquitin-proteasome system (UPS) is a critical regulator of cellular protein levels and activity. It is, therefore, not surprising that its dysregulation is implicated in numerous human diseases, including many types of cancer. Moreover, since cancer cells exhibit increased rates of protein turnover, their heightened dependence on the UPS makes it an attractive target for inhibition via targeted therapeutics. Indeed, the clinical application of proteasome inhibitors in treatment of multiple myeloma has been very successful, stimulating the development of small-molecule inhibitors targeting other UPS components. On the other hand, while the discovery of potent and selective chemical compounds can be both challenging and time consuming, the area of targeted protein degradation through utilization of the UPS machinery has seen promising developments in recent years. The repertoire of proteolysis-targeting chimeras (PROTACs), which employ E3 ligases for the degradation of cancer-related proteins via the proteasome, continues to grow. In this review, we will provide a thorough overview of small-molecule UPS inhibitors and highlight advancements in the development of targeted protein degradation strategies for cancer therapeutics.

PPI Modulators of E6 as Potential Targeted Therapeutics for Cervical Cancer: Progress and Challenges in Targeting E6

Advanced cervical cancer is primarily managed using cytotoxic therapies, despite evidence of limited efficacy and known toxicity. There is a current lack of alternative therapeutics to treat the disease more effectively. As such, there have been more research endeavors to develop targeted therapies directed at oncogenic host cellular targets over the past 4 decades, but thus far, only marginal gains in survival have been realized. The E6 oncoprotein, a protein of human papillomavirus origin that functionally inactivates various cellular antitumor proteins through protein–protein interactions (PPIs), represents an alternative target and intriguing opportunity to identify novel and potentially effective therapies to treat cervical cancer. Published research has reported a number of peptide and small-molecule modulators targeting the PPIs of E6 in various cell-based models. However, the reported compounds have rarely been well characterized in animal or human subjects. This indicates that while notable progress has been made in targeting E6, more extensive research is needed to accelerate the optimization of leads. In this review, we summarize the current knowledge and understanding of specific E6 PPI inhibition, the progress and challenges being faced, and potential approaches that can be utilized to identify novel and potent PPI inhibitors for cervical cancer treatment.

The HECT E3 Ligase E6AP/UBE3A as a Therapeutic Target in Cancer and Neurological Disorders

The HECT (Homologous to the E6-AP Carboxyl Terminus)-family protein E6AP (E6-associated protein), encoded by the UBE3A gene, is a multifaceted ubiquitin ligase that controls diverse signaling pathways involved in cancer and neurological disorders. The oncogenic role of E6AP in papillomavirus-induced cancers is well known, with its action to trigger p53 degradation in complex with the E6 viral oncoprotein. However, the roles of E6AP in non-viral cancers remain poorly defined. It is well established that loss-of-function alterations of the UBE3A gene cause Angelman syndrome, a severe neurodevelopmental disorder with autosomal dominant inheritance modified by genomic imprinting on chromosome 15q. Moreover, excess dosage of the UBE3A gene markedly increases the penetrance of autism spectrum disorders, suggesting that the expression level of UBE3A must be regulated tightly within a physiologically tolerated range during brain development. In this review, current the knowledge about the substrates of E6AP-mediated ubiquitination and their functions in cancer and neurological disorders is discussed, alongside with the ongoing efforts to pharmacologically modulate this ubiquitin ligase as a promising therapeutic target.

Expression of the Long Noncoding RNA DINO in Human Papillomavirus-Positive Cervical Cancer Cells Reactivates the Dormant TP53 Tumor Suppressor through ATM/CHK2 Signaling

Functional restoration of the TP53 tumor suppressor holds great promise for anticancer therapy. Current strategies are focused on modulating TP53 regulatory proteins. Long noncoding RNAs (lncRNAs) have emerged as important regulators of TP53 as well as modulators of downstream tumor-suppressive transcriptional responses. Unlike many other cancer types, human papillomavirus (HPV)-positive cancer cells retain wild-type TP53 that is rendered dysfunctional by the viral E6 protein. We show that acute expression of the damage-induced long noncoding RNA, DINO, a known TP53 transcriptional target and functional modulator, causes TP53 reactivation in HPV-positive cervical cancer cells. This causes increased vulnerability to standard chemotherapeutics as well as biguanide compounds that cause metabolic stress. Hence, strategies that target DINO may be useful for restoring TP53 tumor suppressor activity in HPV-positive cancers and other tumor types that retain wild-type TP53.

Tumor cells overcome the cytostatic and cytotoxic restraints of TP53 tumor suppressor signaling through a variety of mechanisms. High-risk human papillomavirus (HPV)-positive tumor cells retain wild-type TP53 because the HPV E6/UBE3A ubiquitin ligase complex targets TP53 for proteasomal degradation. While restoration of TP53 in tumor cells holds great promise for cancer therapy, attempts to functionally restore the dormant TP53 tumor suppressor in HPV-positive cancer cells by inhibiting the HPV E6/UBE3A ubiquitin ligase complex have not yet been successful. The damage-induced long noncoding RNA, DINO (DINOL), is a TP53 transcriptional target that has been reported to bind to and stabilize TP53, thereby amplifying TP53 signaling. We show that HPV-positive cervical carcinoma cells contain low levels of DINO because of HPV E6/UBE3A-mediated TP53 degradation. Acute DINO expression overrides HPV16 E6/UBE3A-mediated TP53 degradation, causing TP53 stabilization and increased expression of TP53 transcriptional target genes. This causes a marked sensitization to chemotherapy agents and renders cells vulnerable to metabolic stress. Acute DINO expression in HPV-positive cervical cancer cells induces hallmarks of DNA damage response signaling, and TP53 activation involves ATM/CHK2 signaling. DINO upregulation in response to DNA damage is independent of ATM/CHK2 and can occur in cancer cells that express mutant TP53.

Is viral E6 oncoprotein a viable target? A critical analysis in the context of cervical cancer

An understanding of the pathology of cervical cancer (CC) mediated by E6/E7 oncoproteins of high-risk human papillomavirus (HPV) was developed by late 80's. But if we look at the present scenario, not a single drug could be developed to inhibit these oncoproteins and in turn, be used specifically for the treatment of CC. The readers are advised not to presume the "viability of E6 protein" as mentioned in the title relates to just druggability of E6. The viability aspect will cover almost everything a researcher should know to develop E6 inhibitors until the preclinical stage. Herein, we have analysed the achievements and shortcomings of the scientific community in the last four decades in targeting HPV E6 against CC. Role of all HPV proteins has been briefly described for better perspective with a little detailed discussion of the role of E6. We have reviewed the articles from 1985 onward, reporting in vitro inhibition of E6. Recently, many computational studies have reported potent E6 inhibitors and these have also been reviewed. Subsequently, a critical analysis has been reported to cover the in vitro assay protocols and in vivo models to develop E6 inhibitors. A paragraph has been devoted to the role of public policy to fight CC employing vaccines and whether the vaccine against HPV has quenched the zeal to develop drugs against it. The review concludes with the challenges and the way forward.

Integrated Computational Approaches and Tools forAllosteric Drug Discovery

Understanding molecular mechanisms underlying the complexity of allosteric regulationin proteins has attracted considerable attention in drug discovery due to the benefits and versatilityof allosteric modulators in providing desirable selectivity against protein targets while minimizingtoxicity and other side effects. The proliferation of novel computational approaches for predictingligand-protein interactions and binding using dynamic and network-centric perspectives has ledto new insights into allosteric mechanisms and facilitated computer-based discovery of allostericdrugs. Although no absolute method of experimental and in silico allosteric drug/site discoveryexists, current methods are still being improved. As such, the critical analysis and integration ofestablished approaches into robust, reproducible, and customizable computational pipelines withexperimental feedback could make allosteric drug discovery more efficient and reliable. In this article,we review computational approaches for allosteric drug discovery and discuss how these tools can beutilized to develop consensus workflows for in silico identification of allosteric sites and modulatorswith some applications to pathogen resistance and precision medicine. The emerging realization thatallosteric modulators can exploit distinct regulatory mechanisms and can provide access to targetedmodulation of protein activities could open opportunities for probing biological processes and insilico design of drug combinations with improved therapeutic indices and a broad range of activities.