ملفوظات ِ سید اشرف جہانگیر سمنانی میں غزوات نبویہﷺکا جائزہ: The appraisal of Ghazwiat-e-Nabvi SAWW in the sermons of Syed Ashraf Jahangir Samnani)

Religious mystics especially commemorated the Seerat-e-Tayyaba in the Malfoozati dissertations because it is the theme of mysticism. The name of Syed Ashraf Jahangir Samnani is considered authentic and honourable among Sofis. His lectures are collected by Hazrat Nizam-ud-din Yamni. Argumentations on Seerah during Ghazwiat-e-Nabvi are not only characterized in the most epistemological and theosophical manner but also, it specifies the other aspects of Seerat-e-Tayyaba in the form of poetry and prose. Ghazwiat-e-Nabviah is the characteristic of Seerah that is collected in the books of Seerah by the name of ‘Maghazi’. It highlights the aspect of Seerat-e-Tayyab in the Ghazwiat-e-Nabavia being the highest excellence in publication of religion

In-silico prediction of TGF-β1 non-synonymous variants and their impact on binding affinity to Fresolimumab

TGF-β1 is a potent immunoregulatory cytokine that plays diverse roles in development, bone healing, fibrosis, and cancer. However, characterizing TGF-β1 gene variants is challenging because the structural and functional consequences of these variants are still undetermined. In this study, we aimed to perform an in-silico analysis of TGF-β1 non-synonymous variants and their pathogenic effects on the TGF-β1 protein. A total of 10,252 TGF-β1 SNPs were collected from the NCBI dbSNP database and in-silico tools (SIFT, PROVEAN, Mutation Taster, ClinVar, PolyPhen-2, CScape, MutPred, and ConSurf) were used. The in-silico predicted potential variants were further investigated for their binding to the TGF-β1 targeting drug “Fresolimumab”. Molecular docking was performed using HADDOCK and confirmed by PRODIGY and PDBsum. The in-silico analysis predicted four potential TGF-β1 nsSNPs: E47G in the LAP domain of the propeptide and I22T, L28F, and E35D in the mature TGF-β1 peptide. HADDOCK and molecular dynamics simulations revealed that the I22T and E35D variants have higher binding affinity for Fresolimumab as compared to the wild type and L28F variants. Molecular dynamics simulations (100 ns) and principal component analysis showed that TGF-β1 variants influenced the protein structure and caused variations in the internal dynamics of protein complexes with the antibody. Among them, the E35D variant significantly destabilized the TGF-β1 protein structure, resulting in rearrangement in the binding site and affecting the interactions with the Fresolimumab. This study identified four variants that can affect the TGF-β1 protein structure and result in functional consequences such as impaired response to Fresolimumab.: TGF-β1 is a potent immunoregulatory cytokine that plays diverse roles in development, bone healing, fibrosis, and cancer. However, characterizing TGF-β1 gene variants is challenging because the structural and functional consequences of these variants are still undetermined. In this study, we aimed to perform an in-silico analysis of TGF-β1 non-synonymous variants and their pathogenic effects on the TGF-β1 protein. A total of 10,252 TGF-β1 SNPs were collected from the NCBI dbSNP database and in-silico tools (SIFT, PROVEAN, Mutation Taster, ClinVar, PolyPhen-2, CScape, MutPred, and ConSurf) were used. The in-silico predicted potential variants were further investigated for their binding to the TGF-β1 targeting drug "Fresolimumab". Molecular docking was performed using HADDOCK and confirmed by PRODIGY and PDBsum. The in-silico analysis predicted four potential TGF-β1 nsSNPs: E47G in the LAP domain of the propeptide and I22T, L28F, and E35D in the mature TGF-β1 peptide. HADDOCK and molecular dynamics simulations revealed that the I22T and E35D variants have higher binding affinity for Fresolimumab as compared to the wild type and L28F variants. Molecular dynamics simulations (100 ns) and principal component analysis showed that TGF-β1 variants influenced the protein structure and caused variations in the internal dynamics of protein complexes with the antibody. Among them, the E35D variant significantly destabilized the TGF-β1 protein structure, resulting in rearrangement in the binding site and affecting the interactions with the Fresolimumab. This study identified four variants that can affect the TGF-β1 protein structure and result in functional consequences such as impaired response to Fresolimumab.Communicated by Ramaswamy H. Sarma

Impact of induced magnetic field on Darcy–Forchheimer nanofluid flows comprising carbon nanotubes with homogeneous-heterogeneous reactions

The appealing traits of carbon nanotubes (CNTs) encompassing mechanical and chemical steadiness, exceptional electrical and thermal conductivities, lightweight, and physiochemical reliability make them desired materials in engineering gadgets. Considering such stimulating characteristics of carbon nanotubes, our goal in the current study is to scrutinize the comparative analysis of Darcy–Forchheimer nanofluid flows containing CNTs of both types of multi and single-wall carbon nanotubes (MWCNTs, SWCNTs) immersed into two different base fluids over a stretched surface. The originality of the model being presented is the implementation of the induced magnetic field that triggers the electric conductivity of carbon nanotubes. Moreover, the envisioned model is also analyzed with homogeneous-heterogeneous (h-h) chemical reactions and heat source/sink. The second-order slip constraint is assumed at the boundary of the surface. The transmuted high-nonlinearity ordinary differential equations (ODEs) are attained from the governing set of equations via similarity transformations. The bvp4c scheme is engaged to get the numerical results. The influence of different parameters is depicted via graphs. For both CNTs, the rate of heat flux and the surface drag coefficient are calculated using tables. It is highlighted that an increase in liquid velocity is witnessed for a varied counts volume fraction of nanoparticles. Also, Single-wall water-based carbon nanotube fluid has comparatively stronger effects on concentration than the multi-walled carbon nanotubes in water-based liquid. The analysis also indicates that the rate of heat flux and the surface drag coefficient are augmented for both SWCNTs and MWCNTs for different physical parameters. The said model is also validated by comparing it with a published result