Mutations in Disordered Regions Can Cause Disease by Creating Dileucine Motifs.

Many disease-causing missense mutations affect intrinsically disordered regions (IDRs) of proteins, but the molecular mechanism of their pathogenicity is enigmatic. Here, we employ a peptide-based proteomic screen to investigate the impact of mutations in IDRs on protein-protein interactions. We find that mutations in disordered cytosolic regions of three transmembrane proteins (GLUT1, ITPR1, and CACNA1H) lead to an increased clathrin binding. All three mutations create dileucine motifs known to mediate clathrin-dependent trafficking. Follow-up experiments on GLUT1 (SLC2A1), the glucose transporter causative of GLUT1 deficiency syndrome, revealed that the mutated protein mislocalizes to intracellular compartments. Mutant GLUT1 interacts with adaptor proteins (APs) in vitro, and knocking down AP-2 reverts the cellular mislocalization and restores glucose transport. A systematic analysis of other known disease-causing variants revealed a significant and specific overrepresentation of gained dileucine motifs in structurally disordered cytosolic domains of transmembrane proteins. Thus, several mutations in disordered regions appear to cause "dileucineopathies."

Strigolactones promote flowering by inducing the miR319-LA-SFT module in tomato.

Strigolactones are a class of phytohormones with various functions in plant development, stress responses, and in the interaction with (micro)organisms in the rhizosphere. While their effects on vegetative development are well studied, little is known about their role in reproduction. We investigated the effects of genetic and chemical modification of strigolactone levels on the timing and intensity of flowering in tomato (Solanum lycopersicum L.) and the molecular mechanisms underlying such effects. Results showed that strigolactone levels in the shoot, whether endogenous or exogenous, correlate inversely with the time of anthesis and directly with the number of flowers and the transcript levels of the florigen-encoding gene SINGLE FLOWER TRUSS (SFT) in the leaves. Transcript quantifications coupled with metabolite analyses demonstrated that strigolactones promote flowering in tomato by inducing the activation of the microRNA319-LANCEOLATE module in leaves. This, in turn, decreases gibberellin content and increases the transcription of SFT. Several other floral markers and morpho-anatomical features of developmental progression are induced in the apical meristems upon treatment with strigolactones, affecting floral transition and, more markedly, flower development. Thus, strigolactones promote meristem maturation and flower development via the induction of SFT both before and after floral transition, and their effects are blocked in plants expressing a miR319-resistant version of LANCEOLATE. Our study positions strigolactones in the context of the flowering regulation network in a model crop species.

Pioneering bioinformatics with agent-based modelling: an innovative protocol to accurately forecast skin or respiratory allergic reactions to chemical sensitizers.

The assessment of the allergenic potential of chemicals, crucial for ensuring public health safety, faces challenges in accuracy and raises ethical concerns due to reliance on animal testing. This paper presents a novel bioinformatic protocol designed to address the critical challenge of predicting immune responses to chemical sensitizers without the use of animal testing. The core innovation lies in the integration of advanced bioinformatics tools, including the Universal Immune System Simulator (UISS), which models detailed immune system dynamics. By leveraging data from structural predictions and docking simulations, our approach provides a more accurate and ethical method for chemical safety evaluations, especially in distinguishing between skin and respiratory sensitizers. Our approach integrates a comprehensive eight-step process, beginning with the meticulous collection of chemical and protein data from databases like PubChem and the Protein Data Bank. Following data acquisition, structural predictions are performed using cutting-edge tools such as AlphaFold to model proteins whose structures have not been previously elucidated. This structural information is then utilized in subsequent docking simulations, leveraging both ligand-protein and protein-protein interactions to predict how chemical compounds may trigger immune responses. The core novelty of our method lies in the application of UISS-an advanced agent-based modelling system that simulates detailed immune system dynamics. By inputting the results from earlier stages, including docking scores and potential epitope identifications, UISS meticulously forecasts the type and severity of immune responses, distinguishing between Th1-mediated skin and Th2-mediated respiratory allergic reactions. This ability to predict distinct immune pathways is a crucial advance over current methods, which often cannot differentiate between the sensitization mechanisms. To validate the accuracy and robustness of our approach, we applied the protocol to well-known sensitizers: 2,4-dinitrochlorobenzene for skin allergies and trimellitic anhydride for respiratory allergies. The results clearly demonstrate the protocol's ability to differentiate between these distinct immune responses, underscoring its potential for replacing traditional animal-based testing methods. The results not only support the potential of our method to replace animal testing in chemical safety assessments but also highlight its role in enhancing the understanding of chemical-induced immune reactions. Through this innovative integration of computational biology and immunological modelling, our protocol offers a transformative approach to toxicological evaluations, increasing the reliability of safety assessments.

A multi-step and multi-scale bioinformatic protocol to investigate potential SARS-CoV-2 vaccine targets.

The COVID-19 pandemic has highlighted the need to come out with quick interventional solutions that can now be obtained through the application of different bioinformatics software to actively improve the success rate. Technological advances in fields such as computer modeling and simulation are enriching the discovery, development, assessment and monitoring for better prevention, diagnosis, treatment and scientific evidence generation of specific therapeutic strategies. The combined use of both molecular prediction tools and computer simulation in the development or regulatory evaluation of a medical intervention, are making the difference to better predict the efficacy and safety of new vaccines. An integrated bioinformatics pipeline that merges the prediction power of different software that act at different scales for evaluating the elicited response of human immune system against every pathogen is proposed. As a working example, we applied this problem solving protocol to predict the cross-reactivity of pre-existing vaccination interventions against SARS-CoV-2.

Late-stage Functionalization using a Popular Titrating Agent: Aryl-Chlorides and -Fluorides Activation by the Diphenylacetic Acid Dianion.

Aryl-chlorides and -fluorides are common building blocks, but their use in synthesis is limited by the high stability of their Ar-X bonds. The generation of aryl radicals via activation of strong Ar-X bonds is possible through the irradiation of tailor-made organic anions, which become reductants stronger than lithium metal. We report that the combination of visible light with the cheap diphenylacetic acid dianion is an even better tool, showing excellent activity across a variety of complex substrates and providing opportunities for late-stage drug modification. Ar-X bonds are chemoselectively activated in the presence of more easily reducible functions, such as Alk-Cl ones and carbonyl groups. These results pave the way to original synthetic strategies that would be otherwise considered impossible.

Cardio-oncology rehabilitation: are we ready?

Cardio-oncology rehabilitation (CORE) is not only an essential component of cancer rehabilitation but also a pillar of preventive cardio-oncology. Cardio-oncology rehabilitation is a comprehensive model based on a multitargeted approach and its efficacy has been widely documented; when compared with an 'exercise only' programme, comprehensive CORE demonstrates a better outcome. It involves nutritional counselling, psychological support, and cardiovascular (CV) risk assessment, and it is directed to a very demanding population with a heavy burden of CV diseases driven by physical inactivity, cancer therapy-induced metabolic derangements, and cancer therapy-related CV toxicities. Despite its usefulness, CORE is still underused in cancer patients and we are still at the dawning of remote models of rehabilitation (tele-rehabilitation). Not all CORE is created equally: a careful screening procedure to identify patients who will benefit the most from CORE and a multidisciplinary customized approach are mandatory to achieve a better outcome for cancer survivors throughout their cancer journey. The aim of this paper is to provide an updated review of CORE not only for cardiologists dealing with this peculiar population of patients but also for oncologists, primary care providers, patients, and caregivers. This multidisciplinary team should help cancer patients to maintain a healthy and active life before, during, and after cancer treatment, in order to improve quality of life and to fight health inequities.

Beyond the state of the art of reverse vaccinology: predicting vaccine efficacy with the universal immune system simulator for influenza.

When it was first introduced in 2000, reverse vaccinology was defined as an in silico approach that begins with the pathogen's genomic sequence. It concludes with a list of potential proteins with a possible, but not necessarily, list of peptide candidates that need to be experimentally confirmed for vaccine production. During the subsequent years, reverse vaccinology has dramatically changed: now it consists of a large number of bioinformatics tools and processes, namely subtractive proteomics, computational vaccinology, immunoinformatics, and in silico related procedures. However, the state of the art of reverse vaccinology still misses the ability to predict the efficacy of the proposed vaccine formulation. Here, we describe how to fill the gap by introducing an advanced immune system simulator that tests the efficacy of a vaccine formulation against the disease for which it has been designed. As a working example, we entirely apply this advanced reverse vaccinology approach to design and predict the efficacy of a potential vaccine formulation against influenza H5N1. Climate change and melting glaciers are critical due to reactivating frozen viruses and emerging new pandemics. H5N1 is one of the potential strains present in icy lakes that can raise a pandemic. Investigating structural antigen protein is the most profitable therapeutic pipeline to generate an effective vaccine against H5N1. In particular, we designed a multi-epitope vaccine based on predicted epitopes of hemagglutinin and neuraminidase proteins that potentially trigger B-cells, CD4, and CD8 T-cell immune responses. Antigenicity and toxicity of all predicted CTL, Helper T-lymphocytes, and B-cells epitopes were evaluated, and both antigenic and non-allergenic epitopes were selected. From the perspective of advanced reverse vaccinology, the Universal Immune System Simulator, an in silico trial computational framework, was applied to estimate vaccine efficacy using a cohort of 100 digital patients.

Transcriptome Analysis Points to BES1 as a Transducer of Strigolactone Effects on Drought Memory in Arabidopsis thaliana.

Strigolactones (SLs) are carotenoid-derived phytohormones governing a wide range of physiological processes, including drought-associated stomatal closure. We have previously shown in tomato that SLs regulate the so-called after-effect of drought, whereby stomatal conductance is not completely restored for some time during recovery after a drought spell, irrespective of the water potential. To ease the elucidation of its molecular underpinnings, we investigated whether this SL effect is conserved in Arabidopsis thaliana by contrasting the physiological performances of the wild-type with SL-depleted (more axillary growth 4, max4) and insensitive (dwarf 14, d14) mutants in a drought and recovery protocol. Physiological analyses showed that SLs are important to achieve a complete after-effect in A. thaliana, while transcriptome results suggested that the SL-dependent modulation of drought responses extends to a large subset (about 4/5) of genes displaying memory transcription patterns. Among these, we show that the activation of over 30 genes related to abscisic acid metabolism and signaling strongly depends on SL signaling. Furthermore, by using promoter-enrichment tools, we identified putative cis- and trans-acting factors that may be important in the SL-dependent and SL-independent regulation of genes during drought and recovery. Finally, in order to test the accuracy of our bioinformatic prediction, we confirmed one of the most promising transcription factor candidates mediating SL signaling effects on transcriptional drought memory-BRI-EMS SUPPRESSOR1 (BES1). Our findings reveal that SLs are master regulators of Arabidopsis transcriptional memory upon drought and that this role is partially mediated by the BES1 transcription factor.

Strigolactones promote the localization of the ABA exporter ABCG25 at the plasma membrane in root epidermal cells of Arabidopsis thaliana.

The phytohormones strigolactones crosstalk with abscisic acid (ABA) in acclimation to osmotic stress, as ascertained in leaves. However, our knowledge about underground tissues is limited, and lacking in Arabidopsis: whether strigolactones affect ABA transport across plasma membranes has never been addressed. We evaluated the effect of strigolactones on the localization of ATP BINDING CASSETTE G25 (ABCG25), an ABA exporter in Arabidopsis thaliana. Wild-type, strigolactone-insensitive, and strigolactone-depleted seedlings expressing a green fluorescent protein:ABCG25 construct were treated with ABA or strigolactones, and green fluorescent protein was quantified by confocal microscopy in different subcellular compartments of epidermal root cells. We show that strigolactones promote the localization of an ABA transporter at the plasma membrane by enhancing its endosomal recycling. Genotypes altered in strigolactone synthesis or perception are not impaired in ABCG25 recycling promotion by ABA, which acts downstream or independent of strigolactones in this respect. Additionally, we confirm that osmotic stress decreases strigolactone synthesis in A. thaliana root cells, and that this decrease may support local ABA retention under low water availability by allowing ABCG25 internalization. Thus, we propose a new mechanism for ABA homeostasis regulation in the context of osmotic stress acclimation: the fine-tuning by strigolactones of ABCG25 localization in root cells.

Combining ß-Carotene with 5-FU via Polymeric Nanoparticles as a Novel Therapeutic Strategy to Overcome uL3-Mediated Chemoresistance in p53-Deleted Colorectal Cancer Cells.

Colorectal cancer (CRC) is one of the leading causes of cancer-related death worldwide. Despite recent therapeutic advancements, resistance to 5-fluorouracil (5-FU) remains a major obstacle to the successful treatment of this disease. We have previously identified the ribosomal protein uL3 as a key player in the cell response to 5-FU, and loss of uL3 is associated with 5-FU chemoresistance. Natural products, like carotenoids, have shown the ability to enhance cancer cell response to drugs and may provide a safer choice to defeat chemoresistance in cancer. Transcriptome analysis of a cohort of 594 colorectal patients revealed a correlation between uL3 expression and both progression-free survival and response to treatment. RNA-Seq data from uL3-silenced CRC cells demonstrated that a low uL3 transcriptional state was associated with an increased expression of specific ATP-binding cassette (ABC) genes. Using two-dimensional (2D) and three-dimensional (3D) models of 5-FU-resistant CRC cells stably silenced for uL3, we investigated the effect of a novel therapeutic strategy by combining ß-carotene and 5-FU using nanoparticles (NPs) as a drug delivery system. Our results indicated that the combined treatment might overcome 5-FU chemoresistance, inducing cell cycle arrest in the G2/M phase and apoptosis. Furthermore, the combined treatment significantly reduced the expression levels of analyzed ABC genes. In conclusion, our findings suggest that ß-carotene combined with 5-FU may be a more effective therapeutic approach for treating CRC cells with low levels of uL3.

Tuberculosis incidence in foreign-born people residing in European countries in 2020.

BackgroundEuropean-specific policies for tuberculosis (TB) elimination require identification of key populations that benefit from TB screening.AimWe aimed to identify groups of foreign-born individuals residing in European countries that benefit most from targeted TB prevention screening.MethodsThe Tuberculosis Network European Trials group collected, by cross-sectional survey, numbers of foreign-born TB patients residing in European Union (EU) countries, Iceland, Norway, Switzerland and the United Kingdom (UK) in 2020 from the 10 highest ranked countries of origin in terms of TB cases in each country of residence. Tuberculosis incidence rates (IRs) in countries of residence were compared with countries of origin.ResultsData on 9,116 foreign-born TB patients in 30 countries of residence were collected. Main countries of origin were Eritrea, India, Pakistan, Morocco, Romania and Somalia. Tuberculosis IRs were highest in patients of Eritrean and Somali origin in Greece and Malta (both > 1,000/100,000) and lowest among Ukrainian patients in Poland (3.6/100,000). They were mainly lower in countries of residence than countries of origin. However, IRs among Eritreans and Somalis in Greece and Malta were five times higher than in Eritrea and Somalia. Similarly, IRs among Eritreans in Germany, the Netherlands and the UK were four times higher than in Eritrea.ConclusionsCountry of origin TB IR is an insufficient indicator when targeting foreign-born populations for active case finding or TB prevention policies in the countries covered here. Elimination strategies should be informed by regularly collected country-specific data to address rapidly changing epidemiology and associated risks.

Novel Molecular Mechanisms Underlying Tumorigenesis and Innovative Therapeutic Approaches for Cancer-Fighting.

Remarkable advances have been made in cancer therapy; however, the high degree of cellular heterogeneity observed during cancer progression is the major driver in the development of resistant phenotypes upon treatment administration [...].

In silico design of recombinant multi-epitope vaccine against influenza A virus.

BACKGROUND: Influenza A virus is one of the leading causes of annual mortality. The emerging of novel escape variants of the influenza A virus is still a considerable challenge in the annual process of vaccine production. The evolution of vaccines ranks among the most critical successes in medicine and has eradicated numerous infectious diseases. Recently, multi-epitope vaccines, which are based on the selection of epitopes, have been increasingly investigated. RESULTS: This study utilized an immunoinformatic approach to design a recombinant multi-epitope vaccine based on a highly conserved epitope of hemagglutinin, neuraminidase, and membrane matrix proteins with fewer changes or mutate over time. The potential B cells, cytotoxic T lymphocytes (CTL), and CD4 T cell epitopes were identified. The recombinant multi-epitope vaccine was designed using specific linkers and a proper adjuvant. Moreover, some bioinformatics online servers and datasets were used to evaluate the immunogenicity and chemical properties of selected epitopes. In addition, Universal Immune System Simulator (UISS) in silico trial computational framework was run after influenza exposure and recombinant multi-epitope vaccine administration, showing a good immune response in terms of immunoglobulins of class G (IgG), T Helper 1 cells (TH1), epithelial cells (EP) and interferon gamma (IFN-g) levels. Furthermore, after a reverse translation (i.e., convertion of amino acid sequence to nucleotide one) and codon optimization phase, the optimized sequence was placed between the two EcoRV/MscI restriction sites in the PET32a+ vector. CONCLUSIONS: The proposed "Recombinant multi-epitope vaccine" was predicted with unique and acceptable immunological properties. This recombinant multi-epitope vaccine can be successfully expressed in the prokaryotic system and accepted for immunogenicity studies against the influenza virus at the in silico level. The multi-epitope vaccine was then tested with the Universal Immune System Simulator (UISS) in silico trial platform. It revealed slight immune protection against the influenza virus, shedding the light that a multistep bioinformatics approach including molecular and cellular level is mandatory to avoid inappropriate vaccine efficacy predictions.

Model verification tools: a computational framework for verification assessment of mechanistic agent-based models.

BACKGROUND: Nowadays, the inception of computer modeling and simulation in life science is a matter of fact. This is one of the reasons why regulatory authorities are open in considering in silico trials evidence for the assessment of safeness and efficacy of medicinal products. In this context, mechanistic Agent-Based Models are increasingly used. Unfortunately, there is still a lack of consensus in the verification assessment of Agent-Based Models for regulatory approval needs. VV&UQ is an ASME standard specifically suited for the verification, validation, and uncertainty quantification of medical devices. However, it can also be adapted for the verification assessment of in silico trials for medicinal products. RESULTS: Here, we propose a set of automatic tools for the mechanistic Agent-Based Model verification assessment. As a working example, we applied the verification framework to an Agent-Based Model in silico trial used in the COVID-19 context. CONCLUSIONS: Using the described verification computational workflow allows researchers and practitioners to easily perform verification steps to prove Agent-Based Models robustness and correctness that provide strong evidence for further regulatory requirements.

Evaluation of word embedding models to extract and predict surgical data in breast cancer.

BACKGROUND: Decisions in healthcare usually rely on the goodness and completeness of data that could be coupled with heuristics to improve the decision process itself. However, this is often an incomplete process. Structured interviews denominated Delphi surveys investigate experts' opinions and solve by consensus complex matters like those underlying surgical decision-making. Natural Language Processing (NLP) is a field of study that combines computer science, artificial intelligence, and linguistics. NLP can then be used as a valuable help in building a correct context in surgical data, contributing to the amelioration of surgical decision-making. RESULTS: We applied NLP coupled with machine learning approaches to predict the context (words) owning high accuracy from the words nearest to Delphi surveys, used as input. CONCLUSIONS: The proposed methodology has increased the usefulness of Delphi surveys favoring the extraction of keywords that can represent a specific clinical context. It permits the characterization of the clinical context suggesting words for the evaluation process of the data.

PETAL: a Python tool for deep analysis of biological pathways.

SUMMARY: Although several bioinformatics tools have been developed to examine signaling pathways, little attention has been given to ever long-distance crosstalk mechanisms. Here, we developed PETAL, a Python tool that automatically explores and detects the most relevant nodes within a KEGG pathway, scanning and performing an in-depth search. PETAL can contribute to discovering novel therapeutic targets or biomarkers that are potentially hidden and not considered in the network under study. AVAILABILITYAND IMPLEMENTATION: PETAL is a freely available open-source software. It runs on all platforms that support Python3. The user manual and source code are accessible from https://github.com/Pex2892/PETAL.

Trans-anal minimally invasive surgery (TAMIS) versus trans-anal endoscopic microsurgery (TEM): a comparative case-control matched-pairs analysis.

AIM: Since its introduction, transanal endoscopic microsurgery (TEM) has become the treatment of choice for rectal benign lesions not amenable to flexible endoscopic excision and for early rectal cancer. Disposable soft devices as the Trans-anal Minimally Invasive Surgery (TAMIS) are a valid alternative to non-disposable rigid trans-anal endoscopic microsurgery (TEM) platforms. The aim of the present study is to compare TEM and TAMIS in terms of incidence of R1 resection and lesion fragmentation which were combined in a composite outcome called quality resection. Perioperative complication and operative time were also investigated. METHODS: A total of 132 patients were eligible for this study of whom 63 (47.7%) underwent TAMIS and 69 (52.3%) underwent TEM. Patients were extracted for from a prospective maintained database and groups resulted homogenous after matching using propensity score in terms of size of the lesion, height from the anal verge, position within the rectal lumen, preoperative histology, neoadjuvant treatment. A multivariate logistic and linear regression analysis was carried out using those variables that have significant independent relationship with the quality of surgical resection and operative time. RESULTS: The incidence of R0 resection and lesion fragmentation was similar between groups. No differences were found in terms of perioperative complication. TAMIS was associated with less setup time and less operative time compared with TEM. Variables influencing quality resection at the multivariate analysis were larger lesion (> 5 cm) and ≥ T2 stage. Variables influencing operative time were surgical procedure (TEM vs TAMIS), height from the anal verge and size of the lesion. CONCLUSION: The present study shows that TEM and TAMIS are equally effective in terms of quality of local excision and perioperative complication. TAMIS resulted less operative time consuming compared to TEM.

Structural properties and anticoagulant/cytotoxic activities of heterochiral enantiomeric thrombin binding aptamer (TBA) derivatives.

The thrombin binding aptamer (TBA) possesses promising antiproliferative properties. However, its development as an anticancer agent is drastically impaired by its concomitant anticoagulant activity. Therefore, suitable chemical modifications in the TBA sequence would be required in order to preserve its antiproliferative over anticoagulant activity. In this paper, we report structural investigations, based on circular dichroism (CD) and nuclear magnetic resonance spectroscopy (NMR), and biological evaluation of four pairs of enantiomeric heterochiral TBA analogues. The four TBA derivatives of the d-series are composed by d-residues except for one l-thymidine in the small TT loops, while their four enantiomers are composed by l-residues except for one d-thymidine in the same TT loop region. Apart from the left-handedness for the l-series TBA derivatives, CD and NMR measurements have shown that all TBA analogues are able to adopt the antiparallel, monomolecular, 'chair-like' G-quadruplex structure characteristic of the natural D-TBA. However, although all eight TBA derivatives are endowed with remarkable cytotoxic activities against colon and lung cancer cell lines, only TBA derivatives of the l-series show no anticoagulant activity and are considerably resistant in biological environments.

In silico clinical trials for relapsing-remitting multiple sclerosis with MS TreatSim.

BACKGROUND: The last few decades have seen the approval of many new treatment options for Relapsing-Remitting Multiple Sclerosis (RRMS), as well as advances in diagnostic methodology and criteria. These developments have greatly improved the available treatment options for today's Relapsing-Remitting Multiple Sclerosis patients. This increased availability of disease modifying treatments, however, has implications for clinical trial design in this therapeutic area. The availability of better diagnostics and more treatment options have not only contributed to progressively decreasing relapse rates in clinical trial populations but have also resulted in the evolution of control arms, as it is often no longer sufficient to show improvement from placebo. As a result, not only have clinical trials become longer and more expensive but comparing the results to those of "historical" trials has also become more difficult. METHODS: In order to aid design of clinical trials in RRMS, we have developed a simulator called MS TreatSim which can simulate the response of customizable, heterogeneous groups of patients to four common Relapsing-Remitting Multiple Sclerosis treatment options. MS TreatSim combines a mechanistic, agent-based model of the immune-based etiology of RRMS with a simulation framework for the generation and virtual trial simulation of populations of digital patients. RESULTS: In this study, the product was first applied to generate diverse populations of digital patients. Then we applied it to reproduce a phase III trial of natalizumab as published 15 years ago as a use case. Within the limitations of synthetic data availability, the results showed the potential of applying MS TreatSim to recreate the relapse rates of this historical trial of natalizumab. CONCLUSIONS: MS TreatSim's synergistic combination of a mechanistic model with a clinical trial simulation framework is a tool that may advance model-based clinical trial design.

Antiproliferative Effects of the Aptamer d(GGGT)4 and Its Analogues with an Abasic-Site Mimic Loop on Different Cancer Cells.

In this paper, we study the T30923 antiproliferative potential and the contribution of its loop residues in six different human cancer cell lines by preparing five T30923 variants using the single residue replacement approach of loop thymidine with an abasic site mimic (S). G-rich oligonucleotides (GRO) show interesting anticancer properties because of their capability to adopt G-quadruplex structures (G4s), such as the G4 HIV-1 integrase inhibitor T30923. Considering the multi-targeted effects of G4-aptamers and the limited number of cancer cell lines tested, particularly for T30923, it should be important to find a suitable tumor line, in addition to considering that the effects also strictly depend on G4s. CD, NMR and non-denaturating polyacrylamide gel electrophoresis data clearly show that all modified ODNs closely resemble the dimeric structure of parallel G4s' parent aptamer, keeping the resistance in biological environments substantially unchanged, as shown by nuclease stability assay. The antiproliferative effects of T30923 and its variants are tried in vitro by MTT assays, showing interesting cytotoxic activity, depending on time and dose, for all G4s, especially in MDA-MB-231 cells with a reduction in cell viability approximately up to 30%. Among all derivatives, QS12 results are the most promising, showing more pronounced cytotoxic effects both in MDA-MB-231 and Hela cells, with a decrease in cell viability from 70% to 60%. In summary, the single loop residue S substitution approach may be useful for designing antiproliferative G4s, considering that most of them, characterized by single residue loops, may be able to bind different targets in several cancer cell pathways. Generally, this approach could be of benefit by revealing some minimal functional structures, stimulating further studies aimed at the development of novel anticancer drugs.