Antiviral drug acyclovir exhibits antitumor activity via targeting βTrCP1: Molecular docking and dynamics simulation study

Remission of HPV-Related Diseases by Antivirals for Herpesvirus: Clinical Cases and a Literature Review

Epidemiological studies have shown that HPV-related diseases are the most prevalent sexually transmitted infections. In this context, this report will present various clinical cases demonstrating the effectiveness of Acyclovir (ACV) or its prodrug Valaciclovir (VCV), both acyclic guanosine analogs commonly used for the treatment of HHV-1 and HHV-2, for the treatment of HPV-related diseases. The report shows the remission of five cases of penile condyloma and a case of remission in a woman affected by cervical and vaginal condylomas and a vulvar giant condyloma acuminate of Buschke and Lowenstein. The literature review shows that ACV is effective in treating skin warts when administered orally, topically, and intralesionally, suggesting its therapeutic potential in other diseases associated with HPV. ACV was also used successfully as an adjuvant therapy for juvenile and adult forms of laryngeal papillomatosis, also known as recurrent respiratory papillomatosis, prolonging the patient's symptom-free periods. Although the prevention of HPV infections is certainly achieved with the HPV vaccine, ACV and VCV have shown to be effective even against genotypes not included in the current vaccine and can be helpful for those problematic clinical cases involving unvaccinated individuals, immunocompromised patients, people who live with HIV, or non-responders to the vaccine. We and others concluded that randomized clinical trials are necessary to determine the efficacy of ACV and VCV for HPV-related diseases.

Beta-Transducin Repeats-Containing Proteins as an Anticancer Target

Beta-transducin repeat-containing proteins (β-TrCPs) are E3-ubiquitin-ligase-recognizing substrates and regulate proteasomal degradation. The degradation of β-TrCPs' substrates is tightly controlled by various external and internal signaling and confers diverse cellular processes, including cell cycle progression, apoptosis, and DNA damage response. In addition, β-TrCPs function to regulate transcriptional activity and stabilize a set of substrates by distinct mechanisms. Despite the association of β-TrCPs with tumorigenesis and tumor progression, studies on the mechanisms of the regulation of β-TrCPs' activity have been limited. In this review, we studied publications on the regulation of β-TrCPs themselves and analyzed the knowledge gaps to understand and modulate β-TrCPs' activity in the future.

The effects of Acyclovir administration to NCI-H1975 non-small cell lung cancer cells

The biochemical mechanisms by which the antiviral drug Acyclovir (ACV) may induce anticancer effects even without detecting human herpesviruses (HHVs) are still poorly understood. Herein, we investigated for the first time how NCI-H1975 non-small cell lung cancer cells responded in vitro to ACV administration by exploring mitochondrial damage and apoptosis induction. We confirmed ACV ability to cause the inhibition of cancer cell growth even without detecting intracellular HHVs; the drug also significantly inhibited the colony formation capacity of NCI-H1975 cells. Cell cycle analysis revealed an increase of the sub-G1 hypodiploid peak after ACV treatment; the activation of caspase-3 and the presence of DNA laddering sustained the capacity of the drug to induce apoptotic cell death. Regarding mitochondrial toxicity, a reduction of mitochondrial membrane potential, altered mitochondrial size and shape, and mtDNA damage were found after ACV administration. Furthermore, an increment of intracellular reactive oxygen species levels as well as the upregulation of NudT3 involved in DNA repair mechanisms were observed. Altogether, these findings suggest that mitochondria may be possible initial targets and/or sites of ACV cytotoxicity within cancer cells in the absence of intracellular HHVs.

Application of Machine Learning Approaches for the Design and Study of Anticancer Drugs

BACKGROUND

Globally the number of cancer patients and deaths are continuing to increase yearly, and cancer has, therefore, become one of the world's highest causes of morbidity and mortality. In recent years, the study of anticancer drugs has become one of the most popular medical topics.

OBJECTIVE

In this review, in order to study the application of machine learning in predicting anticancer drugs activity, some machine learning approaches such as Linear Discriminant Analysis (LDA), Principal components analysis (PCA), Support Vector Machine (SVM), Random forest (RF), k-Nearest Neighbor (kNN), and Naïve Bayes (NB) were selected, and the examples of their applications in anticancer drugs design are listed.

RESULTS

Machine learning contributes a lot to anticancer drugs design and helps researchers by saving time and is cost effective. However, it can only be an assisting tool for drug design.

CONCLUSION

This paper introduces the application of machine learning approaches in anticancer drug design. Many examples of success in identification and prediction in the area of anticancer drugs activity prediction are discussed, and the anticancer drugs research is still in active progress. Moreover, the merits of some web servers related to anticancer drugs are mentioned.

Structural basis of βTrCP1-associated GLI3 processing

Controlled ubiquitin-mediated protein degradation is essential for various cellular processes. GLI family regulates the transcriptional events of the sonic hedgehog pathway genes that are implicated in almost one fourth of human tumors. GLI3 phosphorylation by Ser/Thr kinases is a primary factor for their transcriptional activity that incurs the formation of both GLI3 repressor and activator forms. GLI3 processing is triggered in an ubiquitin-dependent manner via SCF^βTrCP1 complex; however, structural characterization, mode of action based on sequence of phosphorylation signatures and induced conformational readjustments remain elusive. Here, through structural analysis and molecular dynamics simulation assays, we explored comparative binding pattern of GLI3 phosphopeptides against βTrCP1. A comprehensive and thorough analysis demarcated GLI3 presence in the binding cleft shared by inter-bladed binding grooves of β-propeller. Our results revealed the involvement of all seven WD40 repeats of βTrCP1 in GLI3 interaction. Conversely, GLI3 phosphorylation pattern at primary protein kinase A (PKA) sites and secondary casein kinase 1 (CK1) or glycogen synthase kinase 3 (GSK3) sites was carefully evaluated. Our results indicated that GLI3 processing depends on the 19 phosphorylation sites (849, 852, 855, 856, 860, 861, 864, 865, 868, 872, 873, 876, 877, 880, 899, 903, 906, 907 and 910 positions) by a cascade of PKA, GSK3β and CSKI kinases. The presence of a sequential phosphorylation in the binding induction of GLI3 and βTrCP1 may be a hallmark to authenticate GLI3 processing. We speculate that mechanistic information of the individual residual contributions through structure-guided approaches may be pivotal for the rational design of specific and more potent inhibitors against activated GLI3 with a special emphasis on the anticancer activity.

Structural basis for renal cancer by the dynamics of pVHL-dependent JADE1 stabilization and β-catenin regulation

Renal cancer is the major cause of mortality due to abnormal functioning of von Hippel-Lindau (pVHL) and Jade Family PHD Finger 1 (JADE1) complex. E3 ubiquitin ligase JADE1 is stabilized by pVHL interaction through its plant homeodomains (PHDs). JADE1 acts as a renal tumor suppressor that promotes the ubiquitination and degradation of β-catenin by inhibiting canonical WNT signalling. Current study focuses on the structural characterization of reported missense mutations in pVHL through in silico approaches. The predicted 3-dimensional structures of pVHL^WT, pVHL^Y98H, pVHL^Y112H, pVHL^L118P and pVHL^R167W were subjected to binding analysis against JADE1 through molecular docking and simulation assays. In all cases, JADE1 binding was observed at the β-domain, except pVHL^L118P that exhibited binding with JADE1 through its α-domain. Our results signify that JADE1 stabilization is induced by pVHL α-domain, while β-domain is required for JADE1 binding. pVHL binding was mediated through β1 and β2-strands against the concave surface of the JADE1-PHD domain. The pVHL-JADE1 complex was evaluated to scrutinize the β-catenin-binding interface, which suggested the contribution of both α and β-domains of pVHL in β-catenin binding. The eleven-residue (Tyr30-Thr40) β-catenin segment exhibited association in a bipartite manner with pVHL-JADE1 complex. The presented model depicts a pVHL-JADE1 interface for the cooperative regulation of β-catenin binding. We propose that reduced JADE1 stabilization in case of pVHL^L118P and pVHL^R167W may correlate with the increased activity of β-catenin that may lead to renal cancer through β-catenin de-repression. Overall, β-catenin targeting mechanism coupled with the structural knowledge of JADE1-pVHL complex will provide better understanding of renal cancer pathogenesis.