Identification of PPA1 inhibitor candidates for potential repurposing in cancer medicine

Inorganic pyrophosphatase 1 (PPA1) is pivotal to cellular metabolism as it facilitates the hydrolysis of PPi-a by-product of various metabolic processes that influence cell growth and differentiation. Overexpression of PPA1 enzyme has been linked to diminished patient survival and was shown to influence tumor cell dynamics, thereby positioning it as a potential therapy target for a variety of cancers including colorectal cancer, diffuse large B-cell lymphoma, and lung adenocarcinoma. Despite this therapeutic promise, there are no known inhibitors of PPA1 as of today. In this study, we searched for potential PPA1 inhibitors using a molecular docking screen of 30 470 compounds with a history of clinical trials and/or US Food and Drug Administration approval. We specifically targeted the active pocket that coincides with the established catalytic domain. Our screen identified promising hits, which we further subjected to ADMET (absorption, distribution, metabolism, excretion, and toxicity) filtering. Subsequent molecular dynamics (MD) analyses were conducted on devazepide, quinotolast, and tarazepide-the three substances that successfully navigated all filters. MD analyses reinforced the stability of the protein-ligand complexes and confirmed ligand binding, as substantiated by our root mean square deviation, radius of gyration and secondary structures of proteins analyses. Furthermore, Molecular Mechanics Poisson-Boltzmann Surface Area calculations post-MD identified devazepide and quinotolast as showing higher binding affinities; being supported by principal component analysis, free energy landscape, and dynamic cross-correlation matrix results. Overall, our study reveals devazepide and quinotolast as potential candidates for PPA1 inhibition which could be considered for repurposing studies that need further experimental validation. These results not only reveal a potential for clinical repurposing for PPA1 inhibition but they also offer valuable insights into the development of future compounds for targeting the crucial PPA1 enzyme.

In silico drug screen reveals potential competitive MTHFR inhibitors for clinical repurposing

MTHFR (Methylenetetrahydrofolate reductase) is a pivotal enzyme involved in one-carbon metabolism, which is critical for the proliferation of cancer cells. In line with this, published literature showed that MTHFR knockdown caused impaired growth of multiple types of cancer cells. Moreover, higher MTHFR expression levels were linked to shorter overall survival in hepatocellular carcinoma, adrenocortical carcinoma, and low-grade glioma, bringing the need to design MTHFR inhibitors as a possible treatment option. No competitive inhibitors of MTHFR have been reported as of today. This study aimed to identify potential competitive MTHFR inhibitor candidates using an in silico drug screen. A total of 30470 molecules containing biogenic compounds, FDA-approved drugs, and those in clinical trials were screened against the catalytic pocket of MTHFR in the presence and absence of cofactors. Binding energy and ADMET analysis revealed that Vilanterol (β2-adrenergic agonist), Selexipag (prostacyclin receptor agonist), and Ramipril Diketopiperazine (ACE inhibitor) are potential competitive inhibitors of MTHFR. Molecular dynamics analyses and MM-PBSA calculations with these compounds particularly revealed the amino acids between 285-290 for ligand binding and highlighted Vilanterol as the strongest candidate for MTHFR inhibition. Our results could guide the development of novel MTHFR inhibitor compounds, which could be inspired by the drugs brought into the spotlight here. More importantly, these potential candidates could be quhickly tested as a repurposing strategy in pre-clinical and clinical studies of the cancers mentioned above.Communicated by Ramaswamy H. Sarma.

Comparative molecular dynamics analyses on PIK3CA hotspot mutations with PI3Kα specific inhibitors and ATP

PI3K pathway is heavily emphasized in cancer where PIK3CA, which encodes for the p110α subunit of PI3Kα, presents itself as the second most common mutated gene. A lot of effort has been put in developing PI3K inhibitors, opening promising avenues for the treatment of cancer. Among these, PI3Kα specific inhibitor alpelisib was approved by FDA for breast cancer and other α-isoform specific inhibitors such as inavolisib and serabelisib reached clinical trials. However, the mode of action of these inhibitors on mutated PI3Kα and how they interact with mutant structures has not been fully elucidated yet. In this study, we are revealing the calculated interactions and binding affinities of these inhibitors within the context of PIK3CA hotspot mutations (E542K, E545K and H1047R) by employing molecular dynamics (MD) simulations. We performed principal component analysis to understand the motions of the protein complex during our simulations and also checked the correlated motions of all amino acids. Binding affinity calculations with MM-PBSA confirmed the consistent binding of alpelisib across mutations and revealed relatively higher affinities for inavolisib towards wild-type and H1047R mutant structures in comparison to other inhibitors. On the other hand, E542K mutation significantly impaired the interaction of inavolisib and serabelisib with PI3Kα. We also investigated the structural relationship of the natural ligand ATP with PI3Kα, and interestingly realized a significant reduction in binding affinity for the mutants, with potentially unexpected implications on the mechanisms that render these mutations oncogenic. Moreover, correlated motions of all residues were generally higher for ATP except the H1047R mutation which exhibited a distinguishable reduction. The results presented here could be guiding for pre-clinical and clinical studies of personalized medicine where individual mutations are a strong consideration point.

Repeat expression is linked to patient survival and exhibits single nucleotide variation in pancreatic cancer revealing LTR70:r.879A>G

Despite an overwhelming number of cancer literature reporting the links between patient survival and the expression levels of genes or mutations/single nucleotide variations (SNVs) on them, there is only limited information on repeat elements, which make at least half the human genome. Here, we analysed RNA-seq data obtained from primary pancreatic cancer tissues of 51 patients and revealed that two transposons, HERVI-int and X6A_LINE, showed an upregulation trend in the patients who lived shorter, along with 56 other potential repeats which were linked to survival. We also detected expressed single nucleotide variations (SNVs) on repeats, among which LTR70:r.879A>G stands out with the effect of its presence on this particular repeat's expression levels and a significant link to overall patient survival. Interestingly, the expression of LTR70:r.879A>G correlated with different cancer genes in comparison to its reference version highlighting the involvement of BRAF and Fumerate Hydratase with this expressed SNV. This is one of the first studies revealing possible links between repeat expression and survival in cancer and it warrants further research in this avenue.

TEffectR: an R package for studying the potential effects of transposable elements on gene expression with linear regression model

Introduction

Recent studies highlight the crucial regulatory roles of transposable elements (TEs) on proximal gene expression in distinct biological contexts such as disease and development. However, computational tools extracting potential TE -proximal gene expression associations from RNA-sequencing data are still missing.

Implementation

Herein, we developed a novel R package, using a linear regression model, for studying the potential influence of TE species on proximal gene expression from a given RNA-sequencing data set. Our R package, namely TEffectR, makes use of publicly available RepeatMasker TE and Ensembl gene annotations as well as several functions of other R-packages. It calculates total read counts of TEs from sorted and indexed genome aligned BAM files provided by the user, and determines statistically significant relations between TE expression and the transcription of nearby genes under diverse biological conditions.

Availability

TEffectR is freely available at https://github.com/karakulahg/TEffectR along with a handy tutorial as exemplified by the analysis of RNA-sequencing data including normal and tumour tissue specimens obtained from breast cancer patients.

Dysregulated expression of repetitive DNA in ER+/HER2- breast cancer

Limited studies on breast cancer indicated pathogenic changes in the expressions of some repeat elements. A global analysis was much needed within this context to distinguish the most significant repeats from more than a thousand repeat motifs. Utilising a previously presented RNA-seq dataset, we studied expression changes of all repeats in ER+/HER2- human breast tumour samples obtained from 22 patients in comparison to matched normal tissues. Fifty six (56) repeat subtypes including satellites and transposons were found to be differentially expressed and most of them were novel for breast cancer. HERVKC4-int and HERV1_LTRc, whose expressions correlated well with that of the estrogen receptor gene ESR1, were upregulated at the highest level. REP522 and D20S16 satellites were also significantly upregulated along with insignificant increases in the expressions of other satellites including HSATI and BSR/beta. Interestingly, expressions of REP522 and D20S16 correlated with many key breast cancer pathway (e.g. BRCA1, BRCA2, AKT1, MTOR, KRAS) and survival genes; possibly highlighting their importance in the carcinogenesis of breast. Additional differentially expressed elements such as L1P and various MER transposons also exhibited a similar pattern. Finally, our repeat enrichment analysis on the promoters of differentially expressed genes revealed further links between additional repeats and nearby genes.

Expression dynamics of repetitive DNA in early human embryonic development

BACKGROUND

The last decade witnessed a number of genome-wide studies on human pre-implantation, which mostly focused on genes and provided only limited information on repeats, excluding the satellites. Considering the fact that repeats constitute a large portion of our genome with reported links to human physiology and disease, a thorough understanding of their spatiotemporal regulation during human embryogenesis will give invaluable clues on chromatin dynamics across time and space. Therefore, we performed a detailed expression analysis of all repetitive DNA elements including the satellites across stages of human pre-implantation and embryonic stem cells.

RESULTS

We uncovered stage-specific expressions of more than a thousand repeat elements whose expressions fluctuated with a mild global decrease at the blastocyst stage. Most satellites were highly expressed at the 4-cell level and expressions of ACRO1 and D20S16 specifically peaked at this point. Whereas all members of the SVA elements were highly upregulated at 8-cell and morula stages, other transposons and small RNA repeats exhibited a high level of variation among their specific subtypes. Our repeat enrichment analysis in gene promoters coupled with expression correlations highlighted potential links between repeat expressions and nearby genes, emphasising mostly 8-cell and morula specific genes together with SVA_D, LTR5_Hs and LTR70 transposons. The DNA methylation analysis further complemented the understanding on the mechanistic aspects of the repeatome's regulation per se and revealed critical stages where DNA methylation levels are negatively correlating with repeat expression.

CONCLUSIONS

Taken together, our study shows that specific expression patterns are not exclusive to genes and long non-coding RNAs but the repeatome also exhibits an intriguingly dynamic pattern at the global scale. Repeats identified in this study; particularly satellites, which were historically associated with heterochromatin, and those with potential links to nearby gene expression provide valuable insights into the understanding of key events in genomic regulation and warrant further research in epigenetics, genomics and developmental biology.