2025

Permanent URI for this collectionhttps://dl.bhu.ac.in/bhuir/handle/123456789/62057

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Discovery of Novel PTP1B Inhibitors by High-throughput Virtual Screening
(Bentham Science Publishers, 2025) Abhijit Debnath; Anjna Rani; Rupa Mazumder; Avijit Mazumder; Rajesh Kumar Singh; Shalini Sharma; Shikha Srivastava; Hema Chaudhary; Rashmi Mishra; Navneet Khurana; Jahanvi Sanchitra; Sk Ashif Jan
Aim: To Discover novel PTP1B inhibitors by high-throughput virtual screening Background: Type 2 Diabetes is a significant global health concern. According to projections, the estimated number of individuals affected by the condition will reach 578 million by the year 2030 and is expected to further increase to 700 million deaths by 2045. Protein Tyrosine Phosphatase 1B is an enzymatic protein that has a negative regulatory effect on the pathways involved in insulin signaling. This regulatory action ultimately results in the development of insulin resistance and the subsequent elevation of glucose levels in the bloodstream. The proper functioning of insulin signaling is essential for maintaining glucose homeostasis, whereas the disruption of insulin signaling can result in the development of type 2 diabetes. Consequently, we sought to utilize PTP1B as a drug target in this investigation. Objective: The purpose of our study was to identify novel PTP1B inhibitors as a potential treatment for managing type 2 diabetes. Methods: To discover potent PTP1B inhibitors, we have screened the Maybridge HitDiscover database by SBVS. Top hits have been passed based on various drug-likeness rules, toxicity predictions, ADME assessment, Consensus Molecular docking, DFT, and 300 ns MD Simulations. Results: Two compounds have been identified with strong binding affinity at the active site of PTP1B along with drug-like properties, efficient ADME, low toxicity, and high stability. Conclusion: The identified molecules could potentially manage T2DM effectively by inhibiting PTP1B, providing a promising avenue for therapeutic strategies. © 2024 Bentham Science Publishers.
Application of Neutrosophic Stratified Ranked Set Sampling: An Efficient Sampling Technique in the Estimation of Average Relative Humidity in USA
(American Scientific Publishing Group (ASPG), 2025) Vishwajeet Singh; Rajesh Kumar Singh; Anamika Kumari
The study examined the shortcomings of conventional statistical techniques in managing unclear or ambiguous data and emphasized the necessity of implementing neutrosophic statistical techniques as a more enhanced remedy. Advanced techniques like neutrosophic statistics (NS) were developed since traditional statistical methods are unable to handle the uncertainty present in ambiguous data. In order to tackle this problem, the study suggested an innovative and novel sampling method called "neutrosophic stratified ranked set sampling (NSRSS)" in addition to specialized neutrosophic estimators for precisely predicting the population mean in the proximity of uncertainty. This novel strategy adjusted ranked set sampling (RSS) techniques to allow the special features of neutrosophic data. Furthermore, the study improved the precision of estimating the population mean in uncertain situations by introducing neutrosophic estimators that use subsidiary information inside the structure of stratified ranked set sampling (SRSS). The work provided theoretical insights into the performance of these estimators by presenting comprehensive formulations of bias and mean squared error (MSE). To illustrate the efficacy of the suggested techniques, the study includes simulation studies, numerical examples conducted using the computer language R. Evaluations utilizing MSE, and percentage relative efficiency (PRE) demonstrated the higher accuracy of the suggested estimators over conventional alternatives. The findings demonstrated the NSRSS's applicability, particularly for predicting population means in situations where heterogeneity and uncertainty are prevalent. Furthermore, it was demonstrated that the estimators and technique produced interval-based findings, which provided a more accurate depiction of the uncertainty related to population parameters. The reliability of the estimators in estimating population means was greatly improved by this interval estimation in combination with a lower MSE. A significant vacuum in the field of statistical research is filled by the study's introduction of estimators and a customized sampling approach made especially for neutrosophic data. This research significantly advances statistical theory and practice by extending traditional statistical approaches to efficiently handle ambiguous data, especially for applications where exact data is few, heterogeneous, or uncertain. The empirical validation through numerical illustrations and simulations conducted in R further solidifies the practicality and robustness of the proposed techniques, reinforcing their applicability to real-world scenarios. © 2025, American Scientific Publishing Group (ASPG). All rights reserved.
Targeting Undruggable Proteins: The siRNA Revolution Beyond Small Molecules - Advances, Challenges, and Future Prospects in Therapeutic Innovation
(Bentham Science Publishers, 2025) Sk Ashif Jan; Abhijit Debnath; Rajesh Kumar Singh; Pankaj Kumar Tyagi; S. K. Singh; Anil Kumar Singh
The field of drug discovery has long been challenged by the existence of “undruggable” proteins - targets that have resisted traditional small molecule approaches due to their structural or functional characteristics. This review explores the revolutionary potential of small interfering RNA (siRNA) technology in addressing these elusive targets, marking a paradigm shift in therapeutic development. We discuss the historical development of siRNA technology and its unique mechanism of action, which allows for the silencing of virtually any gene, including those coding for proteins previously deemed undruggable. The review provides a comprehensive analysis of the challenges in targeting undruggable proteins and how siRNA approaches are overcoming these obstacles. We examine several case studies of undruggable targets being successfully addressed by siRNA, including oncogenic proteins like KRAS and c-Myc, transcription factors such as NF-κB and STAT3, and proteins involved in complex protein-protein interactions. The article delves into the latest advances in siRNA design, delivery systems, and targeting strategies, highlighting innovations that enhance specificity and reduce off-target effects. We also discuss the challenges facing siRNA therapeutics, including delivery obstacles, potential immune responses, and regulatory considerations. The review concludes with an exploration of future directions, including combination therapies, personalized medicine approaches, and emerging technologies that complement siRNA strategies. By providing a thorough examination of the advances, challenges, and prospects of using siRNA to target undruggable proteins, this review underscores the transformative potential of this technology in expanding the landscape of therapeutic targets and ushering in a new era of precision medicine. © 2025 Bentham Science Publishers.
miRNA-Targeted Vaccines: A Promising Approach for Viral Attenuation and Immunogenicity Enhancement
(Bentham Science Publishers, 2025) Abhijit Debnath; Rupa Mazumder; Avijit Mazumder; Soumya Tripathi; Arpita Dua; Rajesh Kumar Singh; Saloni Mangal; Jahanvi Sanchitra; Pratibha Pandey; Biplab Pal; Hema Chaudhary; Parul Sharma; Shikha Srivastava
MicroRNAs (miRNAs) have emerged as a significant tool in the realm of vaccinology, offering novel approaches to vaccine development. This study investigates the potential of miRNAs in the development of advanced vaccines, with an emphasis on how they regulate immune response and control viral replication. We go over the molecular features of miRNAs, such as their capacity to direct post-transcriptional regulation toward mRNAs, hence regulating the expression of genes in diverse tissues and cells. This property is harnessed to develop live attenuated vaccines that are tissue-specific, enhancing safety and immunogenicity. The review highlights recent advancements in using miRNA-targeted vaccines against viruses like influenza, poliovirus, and tick-borne encephalitis virus, demonstrating their attenuated replication in specific tissues while retaining immunogenicity. We also explored the function of miRNAs in the biology of cancer, highlighting their potential to develop cancer vaccines through targeting miRNAs that are overexpressed in tumor cells. The difficulties in developing miRNA vaccines are also covered in this work, including delivery, stability, off-target effects, and the requirement for individualized cancer treatment plans. We wrap off by discussing the potential of miRNA vaccines and highlighting how they will influence the development of vaccination techniques for cancer and infectious diseases in the future. © 2025 Bentham Science Publishers.
Challenges and Progress of Orphan Drug Development for Rare Diseases
(Bentham Science Publishers, 2025) Abhijit Debnath; Rupa Mazumder; Avijit Mazumder; Pankaj Kumar Tyagi; Rajesh Kumar Singh
Rare diseases, defined as conditions affecting fewer than 200,000 people in the United States or less than 1 in 2,000 people in Europe, pose significant challenges for healthcare systems and pharmaceutical research. This comprehensive review examines the evolving landscape of orphan drug development, analyzing scientific, economic, and regulatory challenges while highlighting recent technological breakthroughs and innovative approaches. We explore how artificial intelligence, next-generation sequencing, and personalized medicine are revolutionizing rare disease research and treatment development. The review details key advances in therapeutic approaches, including gene therapy, cell-based treatments, and drug repurposing strategies, which have led to breakthrough treatments for previously untreatable conditions. We analyze the impact of international collaborations, such as the International Rare Diseases Research Consortium, and discuss how regulatory frameworks worldwide have evolved to accelerate orphan drug development. The paper highlights the growing market for orphan drugs, projected to reach $242 billion by 2024 while examining the complex challenges of ensuring treatment accessibility and economic sustainability. We assess innovative clinical trial designs, patient registry development, and emerging strategies in personalized medicine that are transforming the field. Despite notable advancements, significant gaps remain in diagnosis, treatment accessibility, and sustainable funding for rare disease research. The review concludes by proposing specific actions for enhancing international collaboration, improving patient registries, and aligning incentives to address the unmet medical needs of rare disease patients, emphasizing the critical role of continued public-private partnerships and technological innovation in advancing orphan drug development. © 2025 Bentham Science Publishers.
Some novel sine-type estimators for finite population mean utilizing known auxiliary information
(Springer Science and Business Media B.V., 2025) Rajesh Kumar Singh; Anamika Kumari; Shivam Dubey; Shobh Nath Tiwari
In sampling, the population mean estimate is essential because it offers a clear snapshot of the population’s average, helping with analysis and informed choices in areas such as environmental science, economics, and public health. To improve the efficiency and accuracy of estimators in estimating unknown population parameters, auxiliary information is often utilized, which typically results in reduced mean squared error (MSE) and increased percentage relative efficiency (PRE). In this paper, we modified conventional estimators and introduced some novel sine-type estimators, along with proposing a new exponential-cum-sine-type estimator to enhance finite population mean estimation with auxiliary data under simple random sampling. We compute the bias and MSE of the proposed estimator by applying first-order approximation techniques. The effectiveness and practical utility of the newly proposed estimator are validated using both real-world datasets and simulation studies. The proposed estimator proves to be consistently more efficient than both the sample mean and several competing sine-type estimators (ratio, product, regression, etc.) analyzed in this research. The results are summarized and followed by an analysis of the estimator’s practical applicability in real-world scenarios. The improved efficiency and reliability of the proposed estimator highlight its practical relevance in real-world data analysis. Its applicability across different domains underscores its potential as a robust tool for finite population mean estimation using auxiliary information. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.
Advancements of Glucose Monitoring Biosensor: Current State, Generations of Technological Progress and Innovation Dynamics
(Bentham Science Publishers, 2025) Arpita Dua; Abhijit Debnath; Kunal Kumar; Rupa Mazumder; Avijit Mazumder; Rajesh Kumar Singh; Saloni Mangal; Jahanvi Sanchitra; Fahad Khan; Soumya Tripathi; Sukriti Vishwas; Hema Chaudhary; Parul Sharma; Shikha Srivastava
Glucose monitoring is essential for managing diabetes, and continuous glucose monitoring biosensors can offer real-time monitoring with little invasiveness. However, challenges remain in improving sensor accuracy, selectivity, and overall performance. This article aims to review current trends and recent advancements in glucose-monitoring biosensors while evaluating their benefits and limitations for diabetes monitoring. An analysis of current literature on transdermal glucose sensors was conducted, focusing on detection techniques, novel nanomaterials, and integrated sensor systems. Recent research has led to advancements in electrochemical, optical, electromagnetic, and sonochemical sensors for transdermal glucose detection. The use of novel nanomaterials and integrated sensor designs has improved sensitivity, selectivity, and accuracy. However, issues like calibration requirements, motion artifacts, and skin irritation persist. Transdermal glucose sensors show promise for non-invasive, convenient diabetes monitoring but require further enhancements to address limitations in accuracy, reliability, and biocompatibility. Continued research and innovation focusing on sensor materials, designs, and surface chemistry is needed to optimize biosensor performance and utility. The study offers a comprehensive analysis of the present status of technological advancement and highlights areas that need more research. © 2025 Bentham Science Publishers.
Estimation of population mean using ranked set sampling in the presence of non-response error with numerical illustration and simulation study
(Springer Science and Business Media B.V., 2025) Anamika Kumari; Prayas Sharma; Rajesh Kumar Singh
This paper develops innovative estimators based on ranked set sampling (RSS) for estimating the population mean in the presence of non-response (NR) errors, utilizing auxiliary information. RSS is shown to be a more efficient alternative to simple random sampling (SRS), particularly under non-response conditions. The proposed estimators are evaluated against existing ratio, regression, and exponential estimators using bias, mean squared error (MSE), and percent relative efficiency (PRE). Results from empirical analysis and simulation studies demonstrate that the RSS-based estimators achieve lower MSE and higher PRE, thereby outperforming conventional methods. The study highlights the practical advantages of RSS in survey sampling and contributes to improving the robustness and accuracy of estimators under non-response error scenarios, while also suggesting directions for future research. © The Author(s) 2025.
Proteostasis Disturbances and Inflammation in Neurodegenerative Diseases
(Springer Science+Business Media, 2025) Shivani Malviya; Neha Arya; Rupali Yadav; Ashok V. Kumar; Rajesh Kumar Singh; Priyanka Vikas Kashyap
Proteostasis or protein homeostasis is the dynamic regulation of cellular protein to maintain the functional proteome of a cell. Proteostasis is regulated by a complex machinery regulating biogenesis, folding, trafficking, and degradation of proteins. Misfolded and damaged proteins are either degraded by ubiquitin-proteasome systems (UPS) or by autophagy. Dysregulation of proteostasis in the brain and central nervous system (CNS) can induce glial cells to produce inflammatory molecules, affecting proteostasis and thereby leading to neuroinflammation. Abnormalities in proteostasis and inflammation are key pathophysiological components of normal aging as well as neurodegenerative disorders (NDDs). Since neurons have a limited capacity for regeneration, proteostasis plays an essential role in maintaining cellular processes within the central nervous system. Therefore, an interplay between proteostasis and inflammation in the onset and progression of neurodegenerative diseases has emerged as a critical area of investigation. This chapter explores the intricate relationship between these two processes and their collective impact on the central nervous system. Furthermore, we provide a comprehensive review of how disruptions in proteostasis, leading to the accumulation of misfolded or aggregated proteins, can trigger an inflammatory response or, conversely, result in neuronal dysfunction. In addition, this chapter highlights the bidirectional relationship between inflammation and dysregulated proteostasis and how it may contribute to the clinical manifestations of various neurodegenerative disorders, including Parkinson’s disease (PD) and Alzheimer’s disease (AD). © 2025 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Genome-wide association studies identified novel SNPs associated with efficient biological nitrogen fixation in chickpea (Cicer arietinum L.)
(Frontiers Media SA, 2025) Chandana B. S; Rohit Kumar Mahto; Rajesh Kumar Singh; Ramachandra V; Khushboo K. Singh; S. S. Kushwah; Gera Roopa Lavanya; Himabindu Kudapa; Vinod Kumar Valluri; Anilkumar Vemula; Raju Ratan Yadav; L. B. Yadav; Hari Deo Upadhyaya; Aladdin Hamwieh; Rajendra A.J. Kumar
Chickpea (Cicer arietinum L.) is the second most important food legume crop, capable of converting atmospheric nitrogen (N2) into ammonia (NH3) in symbiotic association with Mesorhizobium cicero through a process called biological nitrogen fixation (BNF). BNF shows promise in effectively diminishing reliance on exogenous nitrogen applications, enhancing soil sustainability and productivity in pulse crops. Notably, there are limited studies on the molecular basis of root nodulation in chickpea. In order to identify new sources of highly nodulating genotypes and gain deep insights into genomic regions governing BNF, a diverse chickpea global germplasm collection (284) was evaluated for nodulation and yield traits in four different environments in an augmented randomized block design. The genotypes exhibited significant trait variation, encompassing all traits under study. Correlation analysis revealed a significant positive correlation of nodulation traits on yield within the chickpea population. The genotypes ICC 7390, ICC 15, ICC 8348, and ICC 2474 were identified as high nodulating across the locations. Genome-wide association studies (GWAS) identified noteworthy and stable marker–trait associations (MTAs) linked to the traits of interest. For the traits number of nodules (NON) and nodule fresh weight (NFW), 65 and 109 significant MTAs were identified, respectively. In addition, two SNPs, Ca1pos289.52482.1 and 6_33340878, identified in our earlier studies were validated by independent population studies, which are crucial in evaluating the accuracy and reliability of the projections. Subsequent analysis revealed that a substantial proportion of these MTAs were situated within intergenic regions, with the potential to modulate genes associated with the focal traits. The candidate genes identified could be converted to Kompetitive allele-specific PCR (KASP) markers and exploited in marker-assisted breeding, accentuating their impact on future chickpea breeding efforts. © © 2025 S, Mahto, Singh, V, Singh, Kushwah, Lavanya, Kudapa, Kumar Valluri, Vemula, Yadav, Yadav, Upadhyaya, Hamwieh and Kumar.

2025

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