Proteins are key players in cellular pathways and interactions between them play main role in wide range of process in cells such as cellular motion, signal transduction and transport. Furthermore, information and knowledge about protein-protein interactions and constructing of protein interaction graph has very important role in understanding of biological process. Since protein-protein interaction information can define function of a protein through position of that protein in a protein web, further such information have key role in supporting of biological researches. Akin to the complete sequencing of genomes, complete descriptions of interactomes is a fundamental step towards a deeper understanding of biological process. Experimental detection of protein-protein interactions include CO-IP, TAP-MS, Y2H but these METHODS limited by time consuming, high cost and have more false positives. COMPUTATIONAL analysis of PPI networks is increasingly becoming a mandatory tool to understand the functions of unexplored proteins. Thus in silico METHODS which include sequence-based approaches, structure-based approaches, chromosome proximity, phylogenetic tree, phylogenetic profile and gene fusion approaches were developed. Also a variety of web server have been developed to prediction the interactions that have been detected by experimental approach such as: STRING, PRISM, Mirror tree, InterpreTS and struct2net. Recent developments have also led to the construction of networks having all the protein-protein interactions using COMPUTATIONAL METHODS for signaling pathways and protein complex identification in specific diseases. In this review, we discuss about in silico METHODS in prediction of PPI that is important field in protein research.

Topology optimization has emerged as a critical tool in engineering design, enabling the creation of highly efficient and innovative structures across various industries. This review provides a comprehensive synthesis of the current state of topology optimization, focusing on its COMPUTATIONAL METHODS and practical applications in engineering design. The article discusses the foundational role of the Finite Element Method (FEM) in topology optimization and explores the distinctions between gradient-based and gradient-free optimization METHODS. It also delves into recent advancements in multi-scale and multi-physics topology optimization, which represent the cutting edge of research in this field. The practical applications of topology optimization are examined in detail, with specific focus on its impact in aerospace, automotive, civil, and biomedical engineering, as well as in the energy sector. The review highlights how topology optimization has revolutionized design practices by reducing material usage, enhancing structural performance, and enabling the development of innovative solutions across diverse engineering challenges. Finally, the article identifies key areas for future research, including the integration of topology optimization with emerging manufacturing technologies and the development of more efficient COMPUTATIONAL METHODS. This review serves as a valuable resource for researchers and practitioners, providing insights into both the current applications and the future potential of topology optimization in engineering design.

Normodyne is the brand name of Labetalol. It has medicinal importance and well known antihypertensive drug and is given to patients with severe hypertension conditions. It is the two-fold alpha and beta-adrenergic antagonism and has dissimilar physiological effects in acute conditions of high blood pressure. Various techniques were used to elaborate on the qualitative behavior of this drug. In the present work, Cyclic Voltammetry (CV) is used to determine the qualitative characteristics of Labetalol. The Glassy Carbon Electrode (GCE) is used as a working and Calomel as a reference electrode with supporting electrolyte (0. 1M NaOH) at 30±, 1oC. In the case of GCE, a single anodic peak is observed which indicates that this drug showed an irreversible process with the transfer of one electron in the selected medium. In addition, different electrochemical parameters are also calculated including, Anodic peak current (Ipa), Anodic peak potential (Epa), half peak potential (Ep/2), differential peak potential Δ, Ep = (Epa –,Ep/2), transfer coefficient (α, ), diffusion coefficient (D), formal potential (Eo), heterogeneous rate constant (Ko), and Gibbs free energy (Δ, G). Furthermore, the adsorption process is also studied. For comparative study, COMPUTATIONAL METHODS are employed for finding HOMO-LUMO energies and vibrational frequencies of the Labetalol molecule. Both METHODS, electrochemical and COMPUTATIONAL are in good agreement and validate the irreversible oxidation of Labetalol. This study has not been reported before and it is useful for the pharmaceutical industry.

In this work, molecular docking was performed to evaluate the anticancer activities of cannabidiol on various targeted proteins. Interactions and significant binding energy prove that cannabidiol can be synthesized and tested as a potent drug that treats all types of human cancer safely. The data obtained highlight the key amino acids involved in the ligand/protein interactions and show that the designed cannabidiol-bound complexes exhibited the best confirmation in the binding site. In addition, a DFT optimization of the geometry and orbital frontier analysis was performed to describe the chemical reactivity of the studied molecule. A pharmacokinetic and bioavailability study in the body was performed by ADMET proprietes. The results of the molecular docking indicate that cannabinol can tested as a potent drug to treat human cancer, given its interactions and significant binding energy up to -8,6 kcal/mol with FAAH protein.