Publications by authors named "Pritish Kumar Varadwaj"

Article Synopsis
  • A comparative genomic analysis helps identify genetic variations and evolutionary relationships among microorganisms, which is important for understanding traits like pathogenicity and antibiotic resistance, as well as their ecological roles in agriculture.
  • The study specifically examined two Bacillus strains known for promoting plant growth in apple trees, revealing key genetic features that contribute to their survival and adaptation.
  • Findings include the discovery of mobile genetic elements and genomic islands, indicating that horizontal gene transfer plays a role in these bacteria's diversity and ability to thrive in different environments.
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Curcumin, a biphenolic substance derived from turmeric (), offers a number of health-beneficial effects, including anti-inflammatory, cardiovascular protection, anti-cancerous, and anti-angiogenic. By interacting with the PPARγ (Peroxisome Proliferator-Activated Receptor-γ), curcumin inhibits NF-κB. These biological outcomes seem to be the outcome of NF-κB inhibition mediated by curcumin.

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Treatment of triple-negative breast cancer (TNBC) is very challenging as only few therapeutic options are available, including chemotherapy. Thus, a constant search for new and effective approaches of therapy that could potentially fight against TNBC and mitigate side effects is "turn-on". Recently, multitarget therapy has come up with huge possibilities, and it may possibly be useful to overcome several concurrent challenges in cancer therapy.

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Radiation resistance is one of the major problems in the treatment of small cell lung cancer (SCLC). Most of these patients are given radiation as first-line treatment and it was observed that the initial response in these patients is very good. However, they show relapse in a few months which is also associated with resistance to treatment.

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Article Synopsis
  • The study tackles the complex relationship between molecular structure and odor perception, highlighting challenges due to vague odor descriptors.
  • Recent advancements in machine learning (ML), particularly with the XGBoost model, have enabled more accurate predictions of odors from molecular structures.
  • The developed model achieved over 99% precision and sensitivity in predicting seven basic smells, outperforming other recent models and offering insights into the structure-odor relationship.
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In this study, we investigated whether zerumbone (ZBN), ellagic acid (ELA) and quercetin (QCT), the plant-derived components, can modulate the role of COX-3 or cytokines liable in arthritic disorder. Initially, the effect of ZBN, ELA, and QCT on inflammatory process was investigated using in-vitro models. In-silico docking and molecular dynamics study of these molecules with respective targets also corroborate with in-vitro studies.

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Oral Squamous Cell Carcinoma (OSCC) accounts for more than 90% of all kinds of oral neoplasms that develop in the oral cavity. It is a type of malignancy that shows high morbidity and recurrence rate, but data on the disease's target genes and biomarkers is still insufficient. In this study, studies have been performed to find out the novel target genes and their potential therapeutic inhibitors for the effective and efficient treatment of OSCC.

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Unlabelled: The article has been withdrawn at the request of the author. Bentham Science apologizes to the readers of the journal for any inconvenience this may have caused. The Bentham Editorial Policy on Article Withdrawal can be found at https://benthamscience.

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Multi-target therapies have been considered one of the viable options to overcome the challenges to eradicate intrinsic and acquired drug-resistant cancer cells. While to increase the efficacy of therapeutics, the use of a single drug against multiple structurally similar sites, which noncommittedly modulate several vital cellular pathways proposed as a potential alternative to a 'single drug single target'. Besides, it reduces the usage of a number of drugs and their side effects.

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The presence of ERG gene fusion; from developing prostatic intraepithelial neoplasia (PIN) lesions to hormone resistant high grade prostate cancer (PCa) dictates disease progression, altered androgen metabolism, proliferation and metastasis. ERG driven transcriptional landscape may provide pro-tumorigenic cues in overcoming various strains like hypoxia, nutrient deprivation, inflammation and oxidative stress. However, insights on the androgen independent regulation and function of ERG during stress are limited.

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PER1 and PER2 are among the class A β-lactamase enzymes, which have evolved clinically to form antibiotic resistance and have significantly expanded their spectrum of activity. Hence, there is a need to study the clinical mutation responsible for such β-lactamase mediated antibiotic resistance. Alterations in catalytic centre and Ω-loop structure could be the cause of antibiotic resistance in these β-lactamase enzymes.

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Introduction: After the outbreak from Wuhan City of China, COVID-19, caused by SARS-CoV-2, has become a pandemic worldwide in a very short span of time. The high transmission rate and pathogenicity of this virus have made COVID-19 a major public health concern globally. Basically, the emergence of SARS-CoV-2 is the third introduction of a highly infectious human epidemic coronavirus in the twenty-first century.

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Nearly 80% of human chronic infections are caused due to bacterial biofilm formation. This is the most leading cause for failure of medical implants resulting in high morbidity and mortality. In addition, biofilms are also known to cause serious problems in food industry.

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Small cell lung cancer (SCLC) is known for its rapid growth with high metastatic spread. Its treatment remains a major challenge for oncologists due to the high mutation rate and other clinical disadvantages. The survival rate of these patients is very poor but there is no significant progress over the last few decades in the treatment protocols.

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Cancer care has become a challenge with the current COVID-19 pandemic scenario. Specially, cancers like small cell lung cancers (SCLC) are difficult to treat even in the normal situation due to their rapid growth and early metastasis. For such patients, treatment can't be compromised and care must be taken to ensure their minimum exposure to the ongoing spread of COVID-19 infection.

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Since the first patient was detected in India in late February 2020, the SARS-CoV-II virus is playing havoc on India. After the first wave, India is now riding the second wave. As was in the case of European countries like Italy and the UK, the second wave is more contagious and at the time of writing this paper, the per day infection is as high as 400,000.

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Olfaction is a multi-stage process that initiates with the odorants entering the nose and terminates with the brain recognizing the odor associated with the odorant. In a very intricate way, the process incorporates various components functioning together and in synchronization. OlfactionBase is a free, open-access web server that aims to bring together knowledge about many aspects of the olfaction mechanism in one place.

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The disease COVID-19 caused by SARS-CoV-2 is the third highly infectious human Coronavirus epidemic in the 21 century due to its high transmission rate and quick evolution of its pathogenicity. Genomic studies indicate that it is zoonotic from bats. The COVID-19 has led to significant loss of lives and a tremendous economic decline in the world.

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Coronavirus disease 2019 (COVID-19) caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused a global pandemic. RNA-dependent RNA polymerase (RdRp) is the key component of the replication or transcription machinery of coronavirus. Therefore SARS-CoV-2-RdRp has been chosen as an important target for the development of antiviral drug(s).

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Finding the relationship between the structure of an odorant molecule and its associated smell has always been an extremely challenging task. The major limitation in establishing the structure-odor relation is the vague and ambiguous nature of the descriptor-labeling, especially when the sources of odorant molecules are different. With the advent of deep networks, data-driven approaches have been substantiated to achieve more accurate linkages between the chemical structure and its smell.

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Precise monitoring of the enzyme activity by a suitable modulator is one of the very fundamental aspects of drug designing that provides the opportunity to overcome the challenges of several diseases. Herein, inhibition of human Topoisomerase IIα enzyme which serves as a potential target site for several anti-cancer drugs is demonstrated by using ultra-small size gold nanoclusters (Au NCs) with the dimension comparable with size of the active site of the enzyme. Molecular dynamics simulation results demonstrate that the Au NCs strongly interact with the human Topo IIα enzyme at its active site or allosteric site depending on forms of enzyme.

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Aims: To develop a tool that can annotate subcellular localization of human proteins.

Background: With the progression of high throughput human proteomics projects, an enormous amount of protein sequence data has been discovered in the recent past. All these raw sequence data require precise mapping and annotation for their respective biological role and functional attributes.

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been responsible for the current global pandemic that has caused a death toll of >1.12 million worldwide and number continues to climb in several countries. Currently, there are neither specific antiviral drugs nor vaccines for the treatment and prevention of COVID-19.

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Computational approaches have been helpful in high throughput screening of drug libraries and designing ligands against receptors. Alzheimer's disease is a complex neurological disorder, which causes dementia. In this disease neurons are damaged due to formation of Amyloid-beta plaques and neurofibrillary tangles, which along with some other factors contributes to disease development and progression.

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Motifs are the evolutionarily conserved patterns which are reported to serve the crucial structural and functional role. Identification of motif patterns in a set of protein sequences has been a prime concern for researchers in computational biology. The discovery of such a protein motif using existing algorithms is purely based on the parameters derived from sequence composition and length.

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