Deciphering the prognostic landscape of triple-negative breast cancer: A focus on immune-related hub genes and therapeutic implications.

Triple-negative breast cancer (TNBC), known for its hostile nature and limited treatment modalities, has spurred researchers to explore novel approaches for enhancing clinical outcomes. Here, the study aimed to analyze transcriptomics data to identify immune-related hub genes associated with TNBC that might serve as prognostic biomarkers. Initially, we determined genes that were differentially expressed between TNBC and normal tissues by integrating microarray and RNA sequencing data.

Deciphering early responsive signature genes in rice blast disease: an integrated temporal transcriptomic study.

Rice blast disease, caused by Magnaporthe oryzae, reigns as the top-most cereal killer, jeopardizing global food security. This necessitates the timely scouting of pathogen stress-responsive genes during the early infection stages. Thus, we integrated time-series microarray (GSE95394) and RNA-Seq (GSE131641) datasets to decipher rice transcriptome responses at 12- and 24-h post-infection (Hpi).

Histological validation of in-vivo larvicidal efficacy of marine Streptomyces sp. RD06 secondary metabolites against filariasis causing Culex quinquefasciatus and statistical media optimization for larvicidal derivatives production.

Mosquito-borne disease pandemics, such as the Zika virus and chikungunya, have escalated cognizance of how critical it is to implement proficient mosquito vector control measures. The prevention of Culicidae is becoming more difficult these days because of the expeditious imminence of synthetic pesticide resistance and the universal expansion of tremendously invasive mosquito vectors. The present study highlights the insecticidal and larvicidal efficacy of the prospective novel actinobacterium derived from the marine Streptomyces sp.

Transcriptome profiling and metabolic pathway analysis towards reliable biomarker discovery in early-stage lung cancer.

Earlier diagnosis of lung cancer is crucial for reducing mortality and morbidity in high-risk patients. Liquid biopsy is a critical technique for detecting the cancer earlier and tracking the treatment outcomes. However, noninvasive biomarkers are desperately needed due to the lack of therapeutic sensitivity and early-stage diagnosis.

In-silico bioprospecting of secondary metabolites from endophytic spp. against , a cereal killer fungus.

Unlabelled: Rice blast disease, caused by , is the most devastating cereal killer worldwide. Note that melanin pigment is an essential factor of virulence, thus fungicides interfering with melanin biosynthesizing enzymes would reduce the pathogenicity. Scytalone dehydratase (SDH) is the key target for commercial fungicides, like carpropamid, due to its role in the dehydration reaction of the fungal melanin pathway.

Exploring the potential of laccase for endosulfan and chlorophacinone degradation: insights from molecular docking and molecular dynamics simulations.

Pesticides are widely used in agriculture but at the same time, a majority of them are known to cause serious harm to health and the environment. In the recent past, laccases have been reported as key enzymes having the ability to degrade pollutants by converting them into less toxic forms. In this investigation, laccase from polyextremophilic bacterium C-125 was analyzed for its structural, physicochemical, and functional characterization using in approaches.

A multitier virtual screening of antagonists targeting PD-1/PD-L1 interface for the management of triple-negative breast cancer.

Immunotherapies are promising therapeutic options for the management of triple-negative breast cancer because of its high mutation rate and genomic instability. Of note, the blockade of the immune checkpoint protein PD-1 and its ligand PD-L1 has been proven to be an efficient and potent strategy to combat triple-negative breast cancer. To date, various anti-PD-1/anti-PD-L1 antibodies have been approved.

Sequential virtual screening collaborated with machine-learning strategies for the discovery of precise medicine against non-small cell lung cancer.

Dysregulation of MAPK pathway receptors are crucial in causing uncontrolled cell proliferation in many cancer types including non-small cell lung cancer. Due to the complications in targeting the upstream components, MEK is an appealing target to diminish this pathway activity. Hence, we have aimed to discover potent MEK inhibitors by integrating virtual screening and machine learning-based strategies.

Design and In Silico Validation of a Novel MZF-1-Based Multi-Epitope Vaccine to Combat Metastatic Triple Negative Breast Cancer.

Immunotherapy is emerging as a potential therapeutic strategy for triple negative breast cancer (TNBC) owing to the immunogenic landscape of its tumor microenvironment. Interestingly, peptide-based cancer vaccines have garnered a lot of attention as one of the most promising cancer immunotherapy regimens. Thus, the present study intended to design a novel, efficacious peptide-based vaccine against TNBC targeting myeloid zinc finger 1 (MZF1), a transcription factor that has been described as an oncogenic inducer of TNBC metastasis.

Machine learning driven drug repurposing strategy for identification of potential RET inhibitors against non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) remains the leading cause of mortality and morbidity worldwide accounting about 85% of total lung cancer cases. The receptor REarranged during Transfection (RET) plays an important role by ligand independent activation of kinase domain resulting in carcinogenesis. Presently, the treatment for RET driven NSCLC is limited to multiple kinase inhibitors.

In Silico Design and Investigation of Novel Thiazetidine Derivatives as Potent Inhibitors of PrpR in Mycobacterium tuberculosis.

Tuberculosis is one of the most life-threatening acute infectious diseases diagnosed in humans. In the present investigation, a series of 16 new disubstituted 1,3-thiazetidines derivatives is designed, and investigated via various in silico methods for their potential as anti-tubercular agent by evaluating their ability to block the active site of PrpR transcription factor protein of Mycobacterium tuberculosis. The efficacy of the molecules was initially assessed with the help of AutoDock Vina algorithm.

Exploration of natural product database for the identification of potent inhibitor against IDH2 mutational variants for glioma therapy.

Mutation in isocitrate dehydrogenase 2 (mIDH2) is an oncogenic driver prevalently reported in various cancer types including gliomas. To date, enasidenib is the only FDA-approved drug widely used as a mIDH2 (R140Q) inhibitor. However, dose-limiting toxicity and modest brain penetrating capability restrict its use as a plausible mIDH2 inhibitor.

Bioherbicides for sustainable barnyard grass management in paddy field: an in-silico perspective.

Paddy () yield is greatly influenced by the insidious presence of rice-mimicking weed, widely known as barnyard grass. This study explores the promising natural ACCase inhibitors that could enhance paddy yield by controlling weeds. A total of 2828 natural compounds were examined using diverse computational techniques.

Forecasting determinants of recurrence in lung cancer patients exploiting various machine learning models.

Lung cancer recurrence seems to be the most leading cause of death as well as deterioration of lifespan. Proper assessment of the probability of recurrence in early-stage lung cancer is necessary to push up the treatment progress. We therefore employed machine-learning technologies to forecast post-operative recurrence risks using 174 lung cancer patient records.

Computational biophysics approach towards the discovery of multi-kinase blockers for the management of MAPK pathway dysregulation.

The MAPK pathway is important in human lung cancer and is improperly activated in a substantial proportion through number of ways. Strategies on dual-targeting RAF and MEK are an alternative option to diminish the limitations in this pathway inhibition. Hence, we implemented parallel pharmacophore screening of 11,808 DrugBank compounds against RAF and MEK.

molecular modelling, MM/GBSA binding free energy and molecular dynamics simulation study of novel pyrido fused imidazo[4,5-]quinolines as potential anti-tumor agents.

With an alarming increase in the number of cancer patients and a variety of tumors, it is high time for intensive investigation on more efficient and potent anti-tumor agents. Though numerous agents have enriched the literature, still there exist challenges, with the availability of different targets and possible cross-reactivity. Herein we have chosen the phosphoinositide 3-kinase (PI3K) as the target of interest and investigated the potential of pyrido fused imidazo[4,5-]quinoline derivatives to bind strongly to the active site, thereby inhibiting the progression of various types of tumors.

Envelope Glycoprotein based multi-epitope vaccine against a co-infection of Human Herpesvirus 5 and Human Herpesvirus 6 using in silico strategies.

The Human Betaherpesviruses HHV-5 and HHV-6 are quite inimical in immunocompromised hosts individually. A co-infection of both has been surmised to be far more disastrous. This can be attributed to a synergetic effect of their combined pathologies.

Designing a novel SOX9 based multi-epitope vaccine to combat metastatic triple-negative breast cancer using immunoinformatics approach.

Immunotherapies are a promising treatment option especially for the management of TNBC owing to its higher levels of tumour-associated antigens together with higher mutational load. Of note, the administration of preventive vaccines in the early stage of the cancer holds promise for effective disease management. Therefore, the present study aimed to develop a novel multi-epitope peptide-based vaccination against TNBC employing SOX9, which has recently been recognized as a key regulator of TNBC metastasis.

New sulphonamide-peptide hybrid molecules as potential PBP 2a ligands and methicillin resistant actives.

Penicillin binding protein 2a (PbP 2a) expression accounts for the insusceptibility of methicillin-resistant (MRSA) to -lactam antibiotics. Here we employed computational strategies to challenge PbP 2a with series of fifty-five 'ala-ala' and 'ala-pro' sulphonamide-dipeptides. Binding stability of two compounds (labeled: and ) with theoretical in nM and µM ranges, for PbP 2a active and allosteric sites respectively, were investigated using molecular dynamics simulations.

Computational studies reveal potential dolichyl-phosphate N-acetylglucosaminephosphotransferase inhibitors amidst existing drugs.

Dolichyl-phosphate N-acetylglucosaminephosphotransferase (dpagt1) inhibition is reported to kill tumor cells whose growth progression requires increased branching of N-linked glycans. Available dpagt1 inhibitors are grossly limited and are faced with problems of heamolytic effect and aqueous solubility thereby necessitating the search for new, safe and effective dpagt1 inhibitors. We employed computational methods to screen a dataset of ∼1300 FDA approved drugs in order to obtain theoretical dpagt1 inhibitors which could be repurposed as chemotherapeutic drugs.

Fragment-based virtual screening discovers potential new Plasmodium PI4KIIIβ ligands.

Type III beta phosphatidylinositol 4-kinase (PI4KIIIβ) is the only clinically validated drug target in Plasmodium kinases and therefore a critical target in developing novel drugs for malaria. Current PI4KIIIβ inhibitors have solubility and off-target problems. Here we set out to identify new Plasmodium PI4K ligands that could serve as leads for the development of new antimalarial drugs by building a PPI4K homology model since there was no available three-dimensional structure of PfPI4K and virtually screened a small library of ~ 22 000 fragments against it.

Identification of novel inhibitors for Prp protein of Mycobacterium tuberculosis by structure based drug design, and molecular dynamics simulations.

In this study, we assess the effective inhibition of a series of thiazolidine derivatives (1a-1q) were adopting structure-based drug design. Thiazolidine is a five-membered ring structure with thioether and amino groups at positions 1 and 3. Although, thiazolidine may bind to a wide range of protein targets, it is a major heterocyclic core in medicinal chemistry.

In Silico Screening of Available Drugs Targeting Non-Small Cell Lung Cancer Targets: A Drug Repurposing Approach.

The RAS-RAF-MEK-ERK pathway plays a key role in malevolent cell progression in many tumors. The high structural complexity in the upstream kinases limits the treatment progress. Thus, MEK inhibition is a promising strategy since it is easy to inhibit and is a gatekeeper for the many malignant effects of its downstream effector.

Drug repurposing combined with MM/PBSA based validation strategies towards MEK inhibitors screening.

Emergence of oncogenic mutations in the MAPK pathway gaining more impact in the recent years. Importantly, MEK is a core element of this pathway as it is easy to inhibit and is a gatekeeper of multiple malignancies. Therefore, we performed strategy to screen repurposed candidate for MEK protein using a library of 11,808 compounds from different clusters in the DrugBank database.