Biology subjects

Tufail, A.

Publications and source records attributed to Tufail, A..

10 recordsLinked to original sources

bioRxiv2025

Unlocking Antiviral Potentials of Traditional Plants: A Multi-Method Computational Study against Human Metapneumovirus (HMPV)

Human metapneumovirus (HMPV) remains a critical challenge in respiratory healthcare, particularly due to the lack of targeted antiviral therapies and vaccines. This study employs an integrative computational framework to identify and evaluate the antiviral potential of nature-based compounds derived from traditional medicinal plants. A suite of advanced methodologies, including virtual screening, molecular docking, molecular dynamics (MD) simulations, density functional theory (DFT) calculations, pharmacophore modeling, and ADMET profiling, was utilized to comprehensively analyze candidate compounds. Among the tested compounds, Glycyrrhizin exhibited exceptional properties, with a binding energy of -65.4 kcal/mol, eight stabilizing hydrogen bonds, and remarkable dynamic stability (RMSD 1.3 [A]). Similarly, Withaferin A demonstrated a binding energy of -63.7 kcal/mol and high pharmacokinetic potential. Quantum-level analyses revealed favorable electronic properties, while ADMET profiling confirmed the compounds safety and drug-like characteristics. These findings underscore the potential of traditional phytochemicals to serve as lead candidates in antiviral drug development. This research bridges the gap between traditional medicine and modern computational techniques, paving the way for innovative and efficient therapeutic strategies against HMPV.

bioinformatics↗

bioRxiv2025

Exploring FDA-Approved Antiviral Drugs for Human Metapneumovirus Treatment: Integrative Computational Insights

This study leverages advanced computational methodologies to identify potential antiviral therapies targeting human metapneumovirus (HMPV), focusing on FDA-approved antiviral drugs and control compounds. A comprehensive computational framework, encompassing virtual screening, molecular docking, molecular dynamics (MD) simulations, density functional theory (DFT) analysis, and ADMET profiling, was employed. Key findings highlight Remdesivir and Peramivir as the most promising candidates, with superior binding energies (-9.5 kcal/mol and - 9.2 kcal/mol, respectively), stable interaction profiles, and robust pharmacological properties. Molecular dynamics revealed exceptional stability for Remdesivir, with the lowest RMSD (0.20 nm), and pharmacophore analysis emphasized its strong hydrogen bonding and hydrophobic interactions. ADMET profiling confirmed their high bioavailability (85% {+/-} 3 for Remdesivir) and low toxicity, positioning these drugs for repurposing against HMPV. This integrative study underscores the potential of computational tools in streamlining drug discovery and advancing therapeutic interventions.

bioinformatics↗

bioRxiv2025

Repurposing Metal-Based Therapeutics for Human Metapneumovirus (HMPV): An Integrative Computational Approach

Human metapneumovirus (HMPV) poses a significant global health challenge, with limited therapeutic options available. This study employs a comprehensive computational framework to repurpose metal-based drugs as potential HMPV inhibitors. A library of compounds was systematically evaluated using virtual screening, high-precision molecular docking, molecular dynamics (MD) simulations, density functional theory (DFT) calculations, molecular electrostatic potential (MESP) mapping, and pharmacophore modeling. Key candidates, including Auranofin, Silver Sulfadiazine, and Gallium Nitrate, demonstrated high binding affinities ({Delta}Gbinding: -68.5 to -62.7 kcal/mol) and favorable stability metrics (RMSD: 2.1-2.4 [A]). ADME-toxicity (ADMET) profiling highlighted Auranofins robust bioavailability (80%) and extended half-life (8.5 hours), while Ribavirin and Favipiravir emerged as safe controls with minimal toxicity. Quantum chemical analyses reinforced the compounds electronic stability and reactivity. This integrative study provides a promising avenue for repurposing existing therapeutics, bridging computational insights with translational potential to combat HMPV.

bioinformatics↗

bioRxiv2025

Harnessing Computational Insights to Identify Potent Inhibitors for Human Metapneumovirus (HMPV): A Synergistic Approach with Natural Compounds

Human metapneumovirus (HMPV), a leading cause of acute lower respiratory tract infections, has emerged as a global health challenge due to its high prevalence, particularly among children, the elderly, and immunocompromised individuals. Despite its significant impact, no targeted antivirals or vaccines are available. This study employs a comprehensive computational pipeline to identify and evaluate potential inhibitors of the HMPV matrix protein (PDB: 5WB0). Natural compounds such as epigallocatechingallate (EGCG), rutin, and quercetin, along with control drugs, were screened for their therapeutic potential.Virtual screening identified EGCG (-9.1 kcal/mol), rutin (-9.0 kcal/mol), and quercetin (-8.8 kcal/mol) as top binders, surpassing standard drugs like ribavirin (-8.9 kcal/mol). Molecular docking revealed stable binding interactions, including hydrogen bonding with residues Arg143 and Glu186. Molecular dynamics (MD) simulations over a 1000 ns trajectory confirmed the stability of these complexes, with EGCG displaying the lowest RMSD (2.1 [A]) and consistent hydrogen bonding throughout the simulation. Density Functional Theory (DFT) calculations highlighted favorable electronic properties, with EGCG showing a low band gap (3.29 eV) and high dipole moment (3.12 D), indicative of strong reactivity and binding potential. ADMET profiling revealed excellent oral bioavailability for EGCG (84%) and quercetin (88%), with minimal toxicity risks. The Molecular Electrostatic Potential (MESP) mapping identified highly reactive regions on the molecular surface, correlating with nucleophilic and electrophilic binding capabilities. The findings position EGCG, rutin, and quercetin as promising candidates for HMPV therapy, providing a strong foundation for further experimental validation and preclinical development.

bioinformatics↗

bioRxiv2024

Disconnection Between Microvascular Damage and Neurodegeneration in Early Diabetic Retinopathy

AimDiabetic retinopathy (DR) is a common complication of diabetes mellitus and can result in vision loss. Early clinically diagnosed signs of DR are linked to vascular damage, impacting on the neural retina typically at later stages. However, vascular changes and potential effects on neural cells before clinical diagnosis of DR are less understood. MethodsTo learn more about the earliest stages of DR we studied postmortem retina from diabetic donors who did not have clinical DR. Histological phenotyping and quantitative analysis were carried out on retina from 14 donors (3 controls, 10 diabetics, and 1 DR case) to examine capillary loss in the deeper vascular plexus (DVP) and the superficial vascular plexus (SVP) of the retinal vasculature and to study effects on the neural retina. ResultThe advanced DR case exhibited profound vascular and neural damage as expected, whereas none of the ten randomly selected diabetic donors had any DR signs that would have been diagnosed clinically. Within that group, two showed very minor capillary dropout in the SVP, whilst in the remaining diabetic cases the SVP was indistinguishable from the controls. In contrast, over half of the diabetic retinas showed capillary dropout in the DVP and increased capillary diameter. Furthermore, a pan retinal loss of inner nuclear layer cells was observed in those diabetics with capillary dropout compared to the controls (p<0.05), but there was no local spatial correlation between neural cell loss and capillary dropout. ConclusionsOur study has established a novel histological biomarker for diabetes related tissue damage at the earliest stages of DR in human postmortem retina, which appears to be common in people with diabetes before DR can be clinically diagnosed. Furthermore, the spatial mismatch between local capillary dropout and the diffuse neural loss in the INL suggests that at this very early stage of DR, microvascular loss may not causally be directly connected to neurodegeneration and that diabetes may affect the two readouts independently. RESEARCH IN CONTEXTWhat is already known about this subject? O_LIEarly DR is currently clinically defined by visible microvascular changes. C_LIO_LITests of retinal function in people with diabetes imply neuroretinal impairments in early DR. C_LIO_LIClinical imaging in people with diabetes suggests reduced perfusion in the deep retinal vasculature plexus. C_LI What is the key question? (one bullet point only; formatted as a question) O_LIHow does retinal microvascular damage relate to neuronal damage? C_LI What are the new findings? O_LIWe have developed a sensitive histological biomarker for microvascular damage in postmortem retinal tissue. C_LIO_LIEarly vascular changes in the deeper plexus occur in diabetes even in the absence of manifest DR. C_LIO_LINeurodegenerative changes are distributed throughout the retina in diabetes and do not spatially correlate with microvascular nonperfusion. C_LI How might this impact on clinical practice in the foreseeable future? O_LIDeeper plexus perfusion can be a useful early biomarker to assess DR. C_LI

pathology↗

bioRxiv2022

A SOD1-dependent mitotic DNA damage checkpoint

In the event of DNA damage, the cell cycle can be slowed or halted to allow for DNA repair. The mechanisms by which this occurs are well-characterised in interphase, although the mechanisms underpinning mitosis slowing in response to damage are unclear. Canonical checkpoints and DNA repair pathways are largely repressed in mitosis, and whilst there is some level of mitotic DNA synthesis and repair, the bulk of DNA damage is processed for post-mitotic repair. How the decision is made between mitotic DNA repair and post-mitotic DNA repair is not known. We have identified the antioxidant enzyme Superoxide Dismutase 1 (SOD1) as an essential factor mediating delayed mitotic progression in response to DNA damage and replication stress. Cells depleted of SOD1 no longer exhibit DNA damage dependent mitotic delay, and display increased levels of damaged centromeres and mitotic defects. Whilst reactive oxygen species (ROS)-inducing agents also lead to SOD1-dependent mitotic delay, intracellular ROS levels do not correlate with mitotic arrest. SOD1 appears to play an important role in DNA repair in interphase and is recruited to the nucleus in response to DNA damage. In addition to control of mitotic progression in response to genotoxic stress, SOD1 also plays a major role in mitotic DNA synthesis. SOD- depleted cells show reduced levels of mitotic EdU incorporation in response to either replication stress or DNA breaks, seemingly in tandem with Rad51 andSOD1-depletion induced mitotic progression in the presence of DNA breaks is Rad52-dependent. We suggest that there are two responses to DNA breaks in mitosis; either arrest and mitotic repair or progression and post-mitotic repair; and these two pathways exist in a fine balance, controlled by a signaling cascade involving SOD1.

molecular biology↗

bioRxiv2019

The Moorfields AMD Database Report 2 - Fellow Eye Involvement with Neovascular Age-related Macular Degeneration

Background/AimsNeovascular age-related macular degeneration (nAMD) is frequently bilateral, and previous reports on fellow eyes have assumed sequential treatment after a period of treatment of the first eye only. The aim of our study was to analyse baseline characteristics and visual acuity (VA) outcomes of fellow eye involvement with nAMD, specifically differentiating between sequential and non-sequential (due to macular scarring in the first eye) anti-vascular endothelial growth factor treatment and timelines for fellow eye involvement.\n\nMethodsRetrospective, electronic medical record database study of the Moorfields AMD database of 8174 eyes/120,756 single entries with data extracted between October 21, 2008 and August 9, 2018. The dataset for analysis consisted of 1180 sequential, 413 nonsequential, and 1110 unilateral eyes.\n\nResultsMean VA of sequentially treated fellow eyes at baseline was significantly higher (62{+/-}13), VA gain over two years lower (0.65{+/-}14), and proportion of eyes with good VA ([≥]20/40 or 70 letters) higher (46%) than the respective first eyes (baseline VA 54{+/-}16, VA gain at two years 5.6{+/-}15, percentage of eyes with good VA 38%). Non-sequential fellow eyes showed baseline characteristics and VA outcomes similar to first eyes. Fellow eye involvement rate was 32% at two years, and median time interval to fellow eye involvement was 71 (IQR 27-147) weeks.\n\nConclusionThis reports shows sequentially treated nAMD fellow eyes have better baseline and final VA than non-sequentially treated eyes after 2 years of treatment. Sequentially treated eyes also had a greater proportion with good VA after 2 years of treatment.\n\nPRECISDepending on age, fellow eye involvement occurs in 32% of patients with neovascular AMD by two years. Fellow eyes generally maintain better vision, except in cases where late-stage disease in the first eye was untreated.

epidemiology↗

bioRxiv2019

In-Silico Analysis of nsSNPs Associated with CYP11B2 Gene

CYP11B2 gene is located over the upper layer of the kidney. It produces aldosterone synthase enzyme and thereby has an essential role to balance salt and mineral level in the body. A mutation in this gene can deregulate the production of aldosterone hormone in the body which may lead to many diseases including hypertension and cardiac diseases. To control the excess production of this aldosterone an inhibitor \"Fadrozole\" is being used which is associated with an active site cavity of CYP11B2. This study has been divided into two parts. In the first part, the four computational tools (SIFT, Polyphen-2, I-Mutant, ConSurf) were used to identify 29 deleterious SNPs out of 1600 CYP11B2 SNPs. In the second part, five residues (R448G, R141P, W260R, F130S, and F445S) were identified in the active site cavity (out of 29 deleterious CYP11B2 SNPs) at the distance of 5A{degrees}. Binding free energy calculation as well as Dynamics simulation techniques were applied to determine the effect of these mutations on the CYP11B2-Fadrozole compound. The results showed that Fadrozole binding with CYP11B2 became stronger which proved the efficiency of this drug inhibitor with these highly damaging mutations. Our study will be useful for selecting the high priority CYP11B2 mutations, which could be further, investigated in this gene-associated study, for better understanding of the structural and functional aspects of the observed (CYP11B2) protein.

bioinformatics↗

bioRxiv2018

One and Two Year Visual Outcomes from the Moorfields AMD Database - an Open Science Resource for the Study of Neovascular Age-related Macular Degeneration

ObjectivesTo analyse treatment outcomes and share clinical data from a large, single-center, well-curated database (8174 eyes / 6664 patients with 120,756 single entries) of patients with neovascular age related macular degeneration (AMD) treated with anti-vascular endothelial growth factor (VEGF). By making our depersonalised raw data openly available, we aim to stimulate further research in AMD, as well as setting a precedent for future work in this area.\n\nSettingRetrospective, comparative, non-randomised electronic medical record (EMR) database cohort study of the UK Moorfields AMD database with data extracted between 2008 and 2018.\n\nParticipants3357 eyes/patients (61% female). Extraction criteria were [≥] 1 ranibizumab or aflibercept injection, entry of \"AMD\" in the diagnosis field of the EMR, and a minimum of one year of follow-up. Exclusion criteria were unknown date of first injection and treatment outside of routine clinical care at Moorfields before the first recorded injection in the database.\n\nMain outcome measuresPrimary outcome measure was change in VA at one and two years from baseline as measured in Early Treatment Diabetic Retinopathy Study (ETDRS) letters. Secondary outcomes were the number of injections and predictive factors for VA gain.\n\nResultsMean VA gain at one-year and two years were +5.5{+/-}0.5 and +4.9{+/-}0.68 letters respectively. Fifty-four percent of eyes gained [≥]5 letters at two years, 63% had stable VA ({+/-}[≤]14 letters), forty-four percent of eyes maintained good VA ([≥]70 letters). Patients received a mean of 7.7{+/-}0.06 injections during year one and 13.0{+/-}0.2 injections over two years.\n\nYounger age, lower baseline VA, and more injections were associated with higher VA gain at two years.\n\nConclusionThis study benchmarks high quality EMR study results of real life AMD treatment and promotes open science in clinical AMD research by making the underlying data publicly available.\n\nStrengths and limitations of this study- Large sample size, retrospective, single centre, electronic medical record database study\n- High quality real life data\n- Open science approach with sharing of depersonalised raw data

epidemiology↗

bioRxiv2018

Generating perfusion maps from structural optical coherence tomography with artificial intelligence

Despite advances in artificial intelligence (AI), its application in medical imaging has been burdened and limited by expert-generated labels. We used images from optical coherence tomography angiography (OCTA), a relatively new imaging modality that measures retinal blood flow, to train an AI algorithm to generate flow maps from standard optical coherence tomography (OCT) images, exceeding the ability and bypassing the need for expert labeling. Deep learning was able to infer flow from single structural OCT images with similar fidelity to OCTA and significantly better than expert clinicians (P < 0.00001). Our model allows generating flow maps from large volumes of previously collected OCT data in existing clinical trials and clinical practice. This finding demonstrates a novel application of AI to medical imaging, whereby subtle regularities between different modalities are used to image the same body part and AI is used to generate detailed inferences of tissue function from structure imaging.

neuroscience↗