Current Signal Transduction Therapy - Volume 18, Issue 3, 2023

Background: Depression is one of the leading causes of disability around the globe. In the early years of depression, it is hypothesized that neurotransmitters have a major or dominant role in depression pathophysiology. The roles of different parts of the brain and neurotransmitters have emerged at different intervals of time, and various hypotheses beyond monoamines have arisen. In this review, numerous theories that have been proposed in the last 60 years are covered based on the literature.Methodology: This review was prepared with literature and data presented from different databases including PubMed, Frontier in Pharmacology, Elsevier, Journal of Depression and Anxiety, etc.Results: The different hypotheses of depression have been presented in different eras. Each hypothesis of depression tries to explore different aspects of depression, which shifts the pathogenesis of depression approaches towards bio-molecule and genetic roles.Conclusion: The pathophysiology of depression is very complex. None of the hypotheses alone can explain the pathophysiology of depression. All of these hypotheses are interconnected with each other. Through these hypotheses, it can be concluded that neuro-inflammation can be the base of depression and by reducing this factor we can overcome this problem.

Background: When analyzing multivariate data, it can be challenging to quantify and pinpoint relationships between a collection of consistent characteristics. Reliable computational prediction of cancer patient's response to treatment based on their clinical and molecular profiles is essential in this era of precision medicine. This is essential in helping doctors choose the least contaminated and most potent restorative therapies that are now available. Better patient monitoring and selection are now possible in clinical trials.Methods: This research proposes a novel robust model to aid in the diagnosis of various cancers induced by biomarker proteins (Protein Kinase B, MAPK, and mammalian Target of Rapamycin). Later, various medications (Perifosine, Wortmannin, and Rapamycin) were proposed to cure cancer. Various studies were carried out to obtain all of the results, which aid in the identification of various types of cancer. The drugs mentioned in this essay help to ward off cancer. Scaling and normalization were carried out using parallel coordinates plots and correlation tests, respectively. The boosted tree method and kNN with multiple distance approaches were also used to generate a solid model. The medical diagnosis system was enhanced by training the boosted tree technique to identify various tumors. A robust model was validated by predicting various values that were displayed against the observed value and agreed with the advised strategy to locate biomarkers to show the value of our method.Results: The results show that the predicted and observed values agree with each other, especially for MAPK pathways. The observed correlation coefficient (r²) is 0.9847 without intercept and 0.9849 with intercept. The precise computational prediction of the reaction of cancer patients to treatment based on the patient's clinical and molecular profiles is vital in the period of exactitude medicine.Conclusion: A robust model was validated by predicting the different values that were plotted with the observed value, which agrees with the results of the proposed technique to uncover biomarkers and shows the effectiveness of our technique.

Background: High or abnormal blood sugar levels are the hallmark of diabetes mellitus (DM), a metabolic disorder that will be one of the major causes of mortality in 2021. SGLT2 inhibitors have recently shown beneficial effects in the treatment of diabetes by reducing hyperglycemia and glucosuria.Objective: Molecular docking and ADMET studies of Schiff base- based 1, 3, 4-thiadiazole scaffold as SGLT2 inhibitors.Methods: Chem draw Ultra 16.0 software was used to draw the structures of newly designed molecules of Schiff base-based 1, 3, 4-thiadiazole, which were then translated into 3D structures. For the molecular docking study, AutoDock Vina 1.5.6 software was employed. Lazar in silico and Swiss ADME predictors were used to calculate in silico ADMET characteristics.Results: We have designed 111 novel Schiff base-based 1, 3, 4-thiadiazole derivatives as SGLT2 inhibitors. A total of 10 compounds from the thiadiazole series were found to have higher binding affinity to the SGLT2 protein than dapagliflozin. SSS 56 had the best docking scores and binding affinities, with -10.4 Kcal/mol, respectively. In silico ADMET parameters demonstrated that the best binding compounds were found to be non-carcinogenic with LogP = 2.53-4.02.Conclusion: Novel Schiff base-based 1, 3, 4-thiadiazole were designed and binding affinity was assessed against SGLT2 protein, which resulted in a new lead molecule with a maximal binding affinity and estimated to be noncarcinogenic with an optimal partition coefficient (iLogP = 2.53- 4.02).

Epilepsy is a neurological disorder characterized by spontaneously occurring seizures known for several decades. Despite the availability of current anti-epileptic drugs, including Phenytoin, Valproate, Carbamazepine, Lamotrigine, Gabapentin, Vigabatrin, etc., a considerable 30% of the epileptic population are drug-resistant to the available conventional medications. This suggests a need to find new drug therapy for the management of epilepsy. Moreover, prolonged use of a single drug or monotherapy can also lead to therapeutic failure owing to the inability of a single drug to exert the desired anti-epileptic effect. Hence, on the basis of the knowledge and understanding regarding the existing targets, novel agents having the ability to show therapeutic effects should be studied and investigated further. This article emphasizes the need to investigate and repurpose drug molecules for the management of epilepsy. The review elaborates on the potential targets, including Glutamate, EAAT (Excitatory nucleotide) Channel and mTOR (Mammalian Target of Rapamycin) pathway. Moreover, the discussion on the EAAT (Excitatory Amino Acid Transporters), RAS (Renin Angiotensin System), NHE (Na+/H+ exchangers), HCN (Hyperpolarization-activated cyclic nucleotide) targets and treatment approach has been supported by literature that sheds light on evidence which is validated via suitable preclinical and clinical studies.

Cervical cancer is ranked as the fourth most frequently diagnosed cancer and the fourth leading cause of cancer-related deaths among females. Cervical cancer is a complex disease influenced by various genetic, epigenetic, and environmental factors. While treatment options such as radiotherapy, chemotherapy, and hormonal therapy exist, the prognosis remains poor due to high rates of distant and lymphatic metastasis. Recent research has shed light on the role of non-coding RNAs (ncRNAs) in cervical cancer development, with circular RNAs (circRNAs) emerging as a potentially significant regulator of cellular processes. Through targeting miRNAs/mRNAs, circRNAs can impact cell growth and invasion in cervical cancer cells, making them a promising biomarker for diagnosis and treatment. This review provides an overview of the functional roles of circRNAs in the context of cervical cancer.