Drug repurposing against galectin-3 using simulation-based studies

The protein galectin, which binds to carbohydrates and is involved in a number of therapeutic processes including cell proliferation, inflammatory responses, apoptosis, etc., has been discovered as a potential therapeutic target. Galectin-3 is a stable biomarker that exhibits both increased and decreased expression in a variety of illnesses and infections, regardless of sex, age, or body mass index. The goal of the current study is to apply bioinformatics techniques to examine the possibility of cardiovascular medications to inhibit Galectin-3-related biological activities. Unsupervised clustering techniques, molecular docking, and guided molecular dynamics (MD) simulation were used to create a computational pipeline that was used to screen potential chemical compounds from a library of chemical compounds with related molecular fingerprints. Utilizing input factors such as gene expression, mode of action, and chemical descriptors, clustering enables prioritization of medicinal molecules. Twenty-four compounds were screened and repurposed against Galectin-3 utilizing molecular docking as part of the cluster-facilitated virtual screening technique. The polar interactions that Arg144, Glu184, Arg162, His158, and Asn174 have with Bufalin, Cymarin, and Ouabalin have the highest binding affinities, according to docking studies. Studies using MD simulations confirm the tested compounds' ability to inhibit Galectin-3. Galactin-3 targeted experimental and in vivo animal model-based validation studies using Bufalin, Cymarin, and Ouabalin are also necessary.Communicated by Ramaswamy H. Sarma.

Evaluating critical success factors in implementing E-learning system using multi-criteria decision-making

Learning using the Internet or training through E-Learning is growing rapidly and is increasingly favored over the traditional methods of learning and teaching. This radical shift is directly linked to the revolution in digital computer technology. The revolution propelled by innovation in computer technology has widened the scope of E-Learning and teaching, whereby the process of exchanging information has been made simple, transparent, and effective. The E-Learning system depends on different success factors from diverse points of view such as system, support from the institution, instructor, and student. Thus, the effect of critical success factors (CSFs) on the E-Learning system must be critically analyzed to make it more effective and successful. This current paper employed the analytic hierarchy process (AHP) with group decision-making (GDM) and Fuzzy AHP (FAHP) to study the diversified factors from different dimensions of the web-based E-Learning system. The present paper quantified the CSFs along with its dimensions. Five different dimensions and 25 factors associated with the web-based E-Learning system were revealed through the literature review and were analyzed further. Furthermore, the influence of each factor was derived successfully. Knowing the impact of each E-Learning factor will help stakeholders to construct education policies, manage the E-Learning system, perform asset management, and keep pace with global changes in knowledge acquisition and management.