Browsing by Author "Waqar Hussain"

Now showing 1 - 7 of 7
  • No Thumbnail Available
    Item
    Automated fingerprint identification system
    (UMT.Lahore, 2016) Waqar Hussain; Taimour Munawar; Muhammad Shahzaib Shahid; Muhammad Masood
    abstract not available
  • Thumbnail Image
    Item
    Computational exploration of antiviral activity of phytochemicals against ns2b/ns3 proteases from dengue virus
    (Turkish Journal of Biochemistry, 2018) Nouman Rasool; Aisha Ashraf; Muneeba Waseem; Waqar Hussain; Sajid
    Background: Dengue fever has emerged as a serious threat in Pakistan in the last few years with high morbidity rates and substantial mortality. In the present study, NS2B/NS3 protease from four dengue virus (DENV) serotypes have been targeted using 2350 phytochemicals from various medicinal plants. Material and methods: The phytochemicals were subjected to docking against NS2B/NS3 proteases using AutoDock Vina focusing the binding site, and the binding energies were determined to screen the effectively docked phytochemicals. Pharmacological properties were also analyzed for all the phytochemicals using PreADMET web server. Results: Binding affinities ranged from −4.0 to –9.8 kcal/mol and a threshold of −9.0 kcal/mol was applied for screening compounds. A total of 18 phytochemicals are screened for passing all evaluation criteria of a drug in which three were for DENV1-NS2B/NS3, five for DENV2-NS2B/NS3, six for DENV3-NS2B/NS3 and four for DENV4-NS2B/NS3. Erycristagallin and Osajin from Erythrina variegate, PapraineA from Fumaria indica and Aloe-Emodin from Aloe vera are the most potent inhibitors of NS2B/NS3 protease from DENV1, DENV2, DENV3 and DENV4, having binding affinities of −9.6 kcal/ mol, −9.6 kcal/mol, −9.6 kcal/mol and −9.2 kcal/mol, respectively. Conclusion: The effective drug-like properties of all 18 phytochemicals demonstrate the inhibition potential against dengue virus replication in human beings.
  • Thumbnail Image
    Item
    In silico targeting of non-structural 4b protein from dengue virus 4 with spiropyrazolopyridone: study of molecular dynamics simulation, admet and virtual screening
    (VirusDisease, 2018) Waqar Hussain; Iqra Qaddir; Sajid Mahmood; Nouman Rasool
    Dengue fever is one of the most prevalent disease in tropical and sub-tropical regions of the world. According to the World Health Organisation (WHO), approximately 3.5 billion people have been affected with dengue fever. Four serotypes of dengue virus (DENV) i.e. DENV1, DENV2, DENV3 and DENV4 have up to 65% genetic variations among themselves. dengue virus 4 (DENV4) was first reported from Amazonas, Brazil and is spreading perilously due to lack of awareness of preventive measures, as it is the least targeted serotype. In this study, non-structural protein 4B of dengue virus 4 (DENV4NS4B) is computationally characterised and simulations are performed including solvation, energy minimizations and neutralisation for the refinement of predicted model of the protein. The spiropyrazolopyridone is considered as an effective drug against NS4B of DENV2, therefore, a total of 91 different analogues of spiropyrazolopyridone are used to analyse their inhibitory action against DENV4NS4B. These compounds are docked at the binding site with various binding affinities, representing their efficacy to block the binding pocket of the protein. Pharmacological and pharmacokinetic assessment performed on these inhibitors shows that these are suitable candidates to be used as a drug against the dengue fever. Among all these 91 compounds, Analogue-I and Analogue-II are analysed to be the most effective inhibitor having potential to be used as drugs against dengue virus.
  • Thumbnail Image
    Item
    Probing the pharmacological parameters, molecular docking and quantum computations of plant derived compounds exhibiting strong inhibitory potential against ns5 from zika virus
    (Brazilian Archives of Biology and Technology, 2018) Nouman Rasool; Amir Jalal; Adnan Amjad; Waqar Hussain
    Zika virus (ZIKV) is known for microcephaly and neurological disease in humans and the nonstructural proteins of ZIKV play a fundamental role in the viral replication. Among the seven nonstructural proteins, NS5 is the most conserved and largest protein. Two major functional domains of NS5 i.e. methyltransferase (MTase) and RNAdependent RNA polymerase (RdRp) are imperative for the virus life cycle and survival. The present study explicates the inhibitory action of phytochemicals from medicinal plants against NS5 from ZIKV, leading to the identification of potential inhibitors. The crystal structure of the protein is retrieved from RCSB protein data bank. A total of 2035 phytochemicals from 505 various medicinal plants are analysed for their pharmacological properties and pharmacokinetics. Compounds having effective drug-likeness are docked against the protein and further analysed using density functional theory approach. Among the 2035 phytochemicals, 13 are selected as potential inhibitors against MTase having high binding affinities and 17 compounds are selected for RdRp. HOMO and LUMO energies are calculated for the docked compounds within and outside binding pockets of MTase and RdRp, adapting the B3LYP hybrid exchange-correlation functional with def2-SV(P) basis set. Physicochemical properties such as ionization energy, electronic chemical potential, electronegativity, electron affinity, molecular softness, molecular hardness and electrophilicity index have also been analysed for selected phytochemicals. Based upon the results, it is concluded that the selected phytochemicals are highly competent to impede the replication of the virus by inhibiting the ZIKV-NS5.
  • Thumbnail Image
    Item
    Sequence-Based Prediction of Multiple Lipid Modification Sites in Proteins by Integration of Pseaac and Statistical Moments
    (University of Management & Technology, 2018) Waqar Hussain
    Lipid modification of a protein, which can be co-translational or post-translational, is known for regulation of various physiological factors, such as protein-membrane interactions, protein-protein interactions, protein stabilization and enzymatic functionality. Due to the association of these lipid modification sites with various diseases, its timely prediction can help in diagnosing and controlling the associated fatal diseases. Here, we present a method for prediction of multiple lipid modification sites, in which we have incorporated PseAAC with statistical moments for the prediction. The aim of this study is to propose a new and more accurate predictor for lipid modification sites, based on the 5-step rule, to make it easier for the experimental scientists getting desired results. A benchmark dataset of 893 positive and 1093 negative samples for NMyristoylG-PseAAC, 90 positive and 100 negative samples for SFarnesylC-PseAAC, 74 positive and 100 negative samples for SGeranylgeranylC-PseAAC, and 436 positive and 500 negative samples for SPalmitoylC -PseAAC, is collected and used in this study. For feature vector, various position and composition relative features along with the statistical moments are calculated. Later on, a back propagation neural network is trained using feature vectors and scaled conjugate gradient descent with adaptive learning is used as an optimizer. Self-consistency testing and 10-fold cross-validation are performed to evaluate the performance of predictors, using accuracy metrics. For self-consistency testing of NMyristoylG-PseAAC, 96.93% Acc, 97.09% Sp, 96.80% Sn and 0.94 MCC is observed, whereas, for 10-fold cross validation 94.41% Acc, 94.06% Sp, 94.70% Sn and 0.89 MCC is observed. For self-consistency testing of SFarnesylC-PseAAC, 95.79% Acc, 96.67% Sp, 95.00% Sn and 0.92 MCC is observed, whereas, for 10-fold cross validation 93.68% Acc, 95.56% Sp, 92.00% Sn and 0.87 MCC is observed. For self-consistency testing of SGeranylgeranylC-PseAAC, 95.91% Acc, 95.77% Sp, 96.00% Sn and 0.92 MCC is observed, whereas, for 10-fold cross validation 92.98% Acc, 92.96% Sp, 93.00% Sn and 0.86 MCC is observed. For self-consistency testing of SPalmitoylC-PseAAC, 98.08% Acc, 98.62% Sp, 97.60% Sn and 0.96 MCC is observed, whereas, for 10-fold cross validation 94.66% Acc, 96.79% Sp, 92.80% Sn and 0.89 MCC is observed. Thus the proposed predictor can help in predicting the targeted lipid modification sites in an efficient and accurate way.
  • Thumbnail Image
    Item
    Stability of a compact star and exotic matter
    (UMT Lahore, 2025-05-02) Waqar Hussain
    We explore how density inhomogeneities and dissipation influence the final outcome of a self-gravitating sphere's collapse. Using a perturbative approach to the thermodynamic variables and gravitational potentials, which is initially a type of Krori-Barua approach we track the collapse process starting from an initially static, shear-free perfect fluid sphere. As the core collapses, it dissipates energy through a radial heat flux, while the surrounding spacetime is filled with a mix of null energy and an anisotropic string distribution. Over time, this dynamical process transitions into a shear-like regime, influenced by both the heat flux and density fluctuations. Our findings show that the anisotropy caused by the strings drives the stellar fluid toward instability, with this effect further amplified by the density inhomogeneities. A notable and new aspect of this collapse scenario is the delay in the formation of the event horizon.
  • Thumbnail Image
    Item
    Structural and quantum mechanical computations to elucidate the altered binding mechanism of metal and drug with pyrazinamidase from mycobacterium tuberculosis due to mutagenicity
    (ournal of Molecular Graphics and Modelling, 2018) Nouman Rasool; Saima Iftikhar; Waqar Hussain
    Pyrazinamide is known to be the most effective treatment against tuberculosis disease and is known to have bacteriostatic action. By targeting the bacterial spores, this drug reduces the chances for the progression of the infection in organisms. In recent years, increased instances of the drug resistance of bacterial strains are reported. Pyrazinamidase, activator for pyrazinamide, leads to resistance against the drug due to mutagenicity across the world. The present study aimed at the quantum mechanistic analysis of mutations in pyrazinamidase to gain insights into the mechanism of this enzyme. Quantum mechanical calculations were performed to analyse the effect of mutations at the metal coordination site using ORCA software program. Moreover, conformational changes in PZase binding cavity has also been analysed due to mutations of binding pocket residues using CASTp server. In order to elucidate the behaviour of the mutant pyrazinamidase, docking of PZA in the binding pocket of PZase was performed using AutoDock Vina. Analysis of results revealed that iron showed weak binding with the metal coordination site of the mutant proteins due to alteration in electron transfer mechanism. The binding cavity of the mutant PZase has undergone major conformational changes as the volume of pocket increased due to bulky R-chains of mutated amino acids. These conformational changes lead to weak binding of the drug at binding cavity of PZase and reduce the drug activation mechanism leading to increased drug resistance in the bacterial strains.