Biology subjects

Ramakrishnan, P.

Publications and source records attributed to Ramakrishnan, P..

8 recordsLinked to original sources

bioRxiv2026

MicroRNA-146a Deficiency Protects NOD Mice from Autoimmune Diabetes by Enhancing c-Rel-Dependent Regulatory T Cell Function

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by T-cell mediated destruction of pancreatic islet {beta}-cells with genetic, environmental, and molecular triggers involved in disease pathogenesis. Patients with T1D have elevated serum levels of microRNA146a (miR146a). Polymorphisms in the miR146a gene that result in reduced expression of miR146a are associated with protection from T1D. We studied physiological regulators of miR146a expression and found that both hyperglycemia and elevated O-GlcNAcylation increased miR146a expression in T cells. Peripheral blood mononuclear cells (PBMCs) from T1D patients showed increased miR146a and O-GlcNAc transferase (OGT) expression, suggesting increased O-GlcNAcylation may promote miR146a expression in T1D patients. To determine the genetic and developmental role of miR146a in T1D, we generated miR146a-knockout (KO) non-obese diabetic (NOD) mice and found that absence of miR146a significantly protected NOD mice from spontaneous autoimmune diabetes. While we found no impact of miR146a knockout on general hematopoietic parameters and immune cell populations, remarkably, immune cell infiltration into the pancreas was significantly attenuated. Protection from autoimmune diabetes in miR146a-KO NOD mice was associated with increased regulatory T (Treg) cells in the spleen and pancreatic lymph node. Mechanistically, absence of miR146a increased NF-{kappa}B c-Rel expression in Treg cells and enhanced c-Rel binding at the Forkhead box protein P3 (FOXP3) promoter, which positively regulated Treg cell development and suppressor function, offering protection from T1D in miR146a-KO NOD mice. Our findings reveal miR146a as a key regulator of Treg cell-mediated immune tolerance through controlling NF-{kappa}B c-Rel-dependent FOXP3 expression and suggest targeting miR146a as a potential strategy to restore peripheral tolerance in T1D.

immunology↗

bioRxiv2026

Amylo-Pipe: an integrated web server for mechanistic and kinetic prediction of protein and peptide aggregation

Protein aggregation is central to amyloid-related disorders and remains a major developability challenge for protein therapeutics. Over the past two decades, significant advances have been made to predict aggregation-prone regions (APRs) and estimate aggregation propensity in proteins and peptides. In contrast, the prediction of aggregation kinetics has received relatively less attention due to the limited availability and heterogeneity of experimental data. Consequently, aggregation propensities from APR prediction algorithms were widely accepted as a means to predict relative changes in the aggregation kinetics of proteins and mutants. Previous studies have demonstrated, using large-scale datasets, that aggregation propensity shows a weak or inconsistent correlation with aggregation kinetics. In the present study, we have integrated complementary state-of-the-art mechanistic and kinetic prediction tools for protein aggregation into a unified, user-friendly web framework entitled "Amylo-Pipe". Amylo-Pipe also implements practical features that are especially useful for protein engineering, such as gatekeeper-residue mutational scanning to support the design of aggregation-resistant variants. By consolidating multiple prediction tasks in a single interface, Amylo-Pipe enables a more comprehensive assessment of aggregation behavior than APR-only workflows. The web server is freely accessible at: https://web.iitm.ac.in/bioinfo2/amylopipe/.

bioinformatics↗

bioRxiv2026

Targeting WNK1 Releases Differentiation Block in Acute Myeloid Leukemia

Impaired differentiation is a hallmark of Acute Myeloid Leukemia (AML). Current differentiation therapies benefit only a small subset of AML patients, leaving a substantial gap in care for other subtypes. Identifying novel molecular drivers of maturation arrest is critical to expand differentiation induction to a broader range of AML patients. This study addresses this unmet clinical need, by identifying With-no-Lysine(K) kinase 1 (WNK1) as a novel regulator of AML differentiation arrest. We show that WNK1 expression and activity are elevated in AML patients. WNK1 inhibition induced differentiation accompanied by decreased growth and survival of AML cell lines and patient cells. It also inhibited self-renewal of AML patient cells in vitro and elicited significant anti-tumor activity in vivo in mouse models. Mechanistically, WNK1 inhibition derepressed the MEK-ERK-C/EBP{beta} signaling axis and increased the expression of myeloid differentiation genes. Our findings reveal a novel role of WNK1 in promoting AML through differentiation arrest, posing WNK1 inhibition as a potential approach for AML differentiation therapy.

cancer biology↗

bioRxiv2025

YAbS: The Antibody Society's antibody therapeutics database

Therapeutic antibodies have gained prominence in recent years due to their precision in targeting specific diseases. As these molecules become increasingly essential in modern medicine, comprehensive data tracking and analysis are critical for advancing research and ensuring successful clinical outcomes. YAbS, The Antibody Societys Antibody Therapeutics Database, serves as a vital resource for monitoring the development and clinical progress of therapeutic antibodies. The database catalogues detailed information on over 2,900 commercially sponsored investigational antibody candidates that have entered clinical study since 2000, as well as all approved antibody therapeutics. Data for the late-stage clinical pipeline and antibody therapeutics in regulatory review or approved (over 450 molecules) are openly accessible (https://db.antibodysociety.org). Antibody-related information includes molecular format, targeted antigen, current development status, indications studied, and the clinical development timeline of the antibodies, as well as the geographical region of company sponsors. Furthermore, the database supports in-depth industry trends analysis, facilitating the identification of innovative developments and the assessment of success rates within the field. This resource is continually updated and refined, providing invaluable insights to researchers, clinicians, and industry professionals engaged in antibody therapeutics development.

scientific communication and education↗

bioRxiv2023

Molecular Property Diagnostic Suite for COVID-19 (MPDSCOVID-19): An open access disease specific drug discovery portal

Computational drug discovery is intrinsically interdisciplinary and has to deal with the multifarious factors which are often dependent on the type of disease. Molecular Property Diagnostic Suite (MPDS) is a Galaxy based web portal which was conceived and developed as a disease specific web portal, originally developed for tuberculosis (MPDSTB). As specific computational tools are often required for a given disease, developing a disease specific web portal is highly desirable. This paper emphasises on the development of the customised web portal for COVID-19 infection and is referred to as MPDSCOVID-19. Expectedly, the MPDS suites of programs have modules which are essentially independent of a given disease, whereas some modules are specific to a particular disease. In the MPDSCOVID-19 portal, there are modules which are specific to COVID-19, and these are clubbed in SARS-COV-2 disease library. Further, the new additions and/or significant improvements were made to the disease independent modules, besides the addition of tools from galaxy toolshed. This manuscript provides a latest update on the disease independent modules of MPDS after almost 6 years, as well as provide the contemporary information and tool-shed necessary to engage in the drug discovery research of COVID-19. The disease independent modules include file format converter and descriptor calculation under the data processing module; QSAR, pharmacophore, scaffold analysis, active site analysis, docking, screening, drug repurposing tool, virtual screening, visualisation, sequence alignment, phylogenetic analysis under the data analysis module; and various machine learning packages, algorithms and in-house developed machine learning antiviral prediction model are available. The MPDS suite of programs are expected to bring a paradigm shift in computational drug discovery, especially in the academic community, guided through a transparent and open innovation approach. The MPDSCOVID-19 can be accessed at http://mpds.neist.res.in:8085.

bioinformatics↗

bioRxiv2023

Functional profiling of the sequence stockpile: a review and assessment of in silico prediction tools

In silico functional annotation of proteins is crucial to narrowing the sequencing-accelerated gap in our understanding of protein activities. Numerous function annotation methods exist, and their ranks have been growing, particularly so with the recent deep learning-based developments. However, it is unclear if these tools are truly predictive. As we are not aware of any methods that can identify new terms in functional ontologies, we ask if they can, at least, identify molecular functions of new protein sequences that are non-homologous to or far-removed from known protein families. Here, we explore the potential and limitations of the existing methods in predicting molecular functions of thousands of such orphan proteins. Lacking the ground truth functional annotations, we transformed the assessment of function prediction into evaluation of functional similarity of orphan siblings, i.e. pairs of proteins that likely share function, but that are unlike any of the currently functionally annotated sequences. Notably, our approach transcends the limitations of functional annotation vocabularies and provides a platform to compare different methods without the need for mapping terms across ontologies. We find that most existing methods are limited to identifying functional similarity of homologous sequences and are thus descriptive, rather than predictive of function. Curiously, despite their seemingly unlimited by-homology scope, novel deep learning methods also remain far from capturing functional signal encoded in protein sequence. We believe that our work will inspire the development of a new generation of methods that push our knowledge boundaries and promote exploration and discovery in the molecular function domain.

bioinformatics↗

bioRxiv2021

NF-kB c-Rel is dispensable for the development but is required for the cytotoxic function of NK cells

Natural Killer (NK) cells are cytotoxic lymphocytes critical to the innate immune system. We found that germline deficiency of NF-kB c-Rel results in a marked decrease in cytotoxic function of NK cells, both in vitro and in vivo, with no significant differences in the stages of NK cell development. We found that c-Rel binds to the promoters of perforin and granzyme B, two key proteins required for NK cytotoxicity, and controls their transactivation. We generated a NK cell specific c-Rel conditional knockout to study NK cell intrinsic role of c-Rel and found that both global and conditional c-Rel deficiency leads to decreased perforin and granzyme B expression and thereby cytotoxic function. We also confirmed the role of c-Rel in perforin and granzyme B expression in human NK cells. c-Rel reconstitution rescued perforin and granzyme B expressions in c-Rel deficient NK cells and restored their cytotoxic function. Our results show a previously unknown role of c-Rel in transcriptional regulation of perforin and granzyme B expressions and control of NK cell cytotoxic function.

immunology↗

bioRxiv2021

Molecular dynamics simulations and functional studies reveal that hBD-2 binds SARS-CoV-2 spike RBD and blocks viral entry into ACE2 expressing cells

New approaches to complement vaccination are needed to combat the spread of SARS-CoV-2 and stop COVID-19 related deaths and long-term medical complications. Human beta defensin 2 (hBD-2) is a naturally occurring epithelial cell derived host defense peptide that has antiviral properties. Our comprehensive in-silico studies demonstrate that hBD-2 binds the site on the CoV-2-RBD that docks with the ACE2 receptor. Biophysical and biochemical assays confirm that hBD-2 indeed binds to the CoV-2-receptor binding domain (RBD) (KD [~] 300 nM), preventing it from binding to ACE2 expressing cells. Importantly, hBD-2 shows specificity by blocking CoV-2/spike pseudoviral infection, but not VSV-G mediated infection, of ACE2 expressing human cells with an IC50 of 2.4{+/-} 0.1 M. These promising findings offer opportunities to develop hBD-2 and/or its derivatives and mimetics to safely and effectively use as novel agents to prevent SARS-CoV-2 infection.

biochemistry↗