Faculty Publications

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Scholarly Publications by Integral Academia

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    Computational Studies of Thiosemicarbazone-Based Metal Complexes and Their Biological Applications
    (MDPI, 2026) Kulsum Hashmi, Satya, Priya Mishra, Ekhlakh Veg, Tahmeena Khan, Seema Joshi
    Thiosemicarbazones are known for their versatile coordination behavior and wide-ranging applications in the field of materials science, catalysis, and medicinal chemistry. Several investigations have reported on the biological potential of transition metal complexes of TSCs. In addition, the structural, electronic, and reactive properties of these complexes are explored through computational studies using molecular docking and density functional theory (DFT). Such investigations not only support the interpretation of experimental results but also influence synthetic design by predicting the structural behavior of the complexes. In this study, we explore the computational studies of thiosemicarbazone metal complexes along with their biological activities.
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    A Brief Review on the Exploration of Nanocomposites and Their Properties Through Computational Methods for Biological Activity Evaluation
    (MDPI, 2025) Nashra Fatima,Ekhlakh Veg, Tahmeena Khan
    This brief review examines the application of various computational approaches to investigate the physicochemical and interfacial properties of nanocomposite systems. Density functional theory (DFT), a quantum-mechanical technique, examines the fundamental properties of nanomaterials. Molecular docking studies have also been explored to show how different biological macromolecules can interact and bind with the nanoparticles (NPs’) surface, along with the molecular dynamics (MDs) simulations, which further strengthen the docking findings. Furthermore, nanotoxicology, a comparatively less explored field, has also been introduced, providing an insight into the interactions between nanomaterials and the environment and biological systems, including the harmful consequences.
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    Novel drug design and bioinformatics: an introduction
    (De Gruyter, 2021) Mohammad Kalim Ahmad Khan ,Salman Akhtar
    In the current era of high-throughput technology, where enormous amounts of biological data are generated day by day via various sequencing projects, thereby the staggering volume of biological targets deciphered. The discovery of new chemical entities and bioisosteres of relatively low molecular weight has been gaining high momentum in the pharmacopoeia, and traditional combinatorial design wherein chemical structure is used as an initial template for enhancing efficacy pharmacokinetic selectivity properties. Once the compound is identified, it undergoes ADMET filtration to ensure whether it has toxic and mutagenic properties or not. If the compound has no toxicity and mutagenicity is either considered a potential lead molecule. Understanding the mechanism of lead molecules with various biological targets is imperative to advance related functions for drug discovery and development. Notwithstanding, a tedious and costly process, taking around 10–15 years and costing around $4 billion, cascaded approached of Bioinformatics and Computational biology viz., structure-based drug design (SBDD) and cognate ligand-based drug design (LBDD) respectively rely on the availability of 3D structure of target biomacromolecules and vice versa has made this process easy and approachable. SBDD encompasses homology modelling, ligand docking, fragment-based drug design and molecular dynamics, while LBDD deals with pharmacophore mapping, QSAR, and similarity search. All the computational methods discussed herein, whether for target identification or novel ligand discovery, continuously evolve and facilitate cost-effective and reliable outcomes in an era of overwhelming data.