Structure-Based Approaches for Protein-Protein Interaction Prediction Using Machine Learning and Deep Learning.

Protein-Protein Interaction (PPI) prediction plays a pivotal role in understanding cellular processes and uncovering molecular mechanisms underlying health and disease. Structure-based PPI prediction has emerged as a robust alternative to sequence-based methods, offering greater biological accuracy by integrating three-dimensional spatial and biochemical features. This work summarizes the recent advances in computational approaches leveraging protein structure information for PPI prediction, focusing on machine learning (ML) and deep learning (DL) techniques.

Computational Evidence for Bisartan Arginine Blockers as Next-Generation Pan-Antiviral Therapeutics Targeting SARS-CoV-2, Influenza, and Respiratory Syncytial Viruses.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza, and respiratory syncytial virus (RSV) are significant global health threats. The need for low-cost, easily synthesized oral drugs for rapid deployment during outbreaks is crucial. Broad-spectrum therapeutics, or pan-antivirals, are designed to target multiple viral pathogens simultaneously by focusing on shared molecular features, such as common metal cofactors or conserved residues in viral catalytic domains.

Zinc and its binding proteins: essential roles and therapeutic potential.

Zinc is an essential micronutrient that participates in a multitude of cellular and biochemical processes. It is indispensable for normal growth and the maintenance of physiological functions. As one of the most significant trace elements in the body, zinc fulfills three primary biological roles: catalytic, structural, and regulatory.

New insights into the oxidative and cytogenotoxic effects of Tetraglyme on human peripheral blood cells.

The present study investigated the oxidative and cytogenotoxic potential of Tetraethylene glycol dimethyl ether (known as Tetraglyme) on healthy human peripheral blood lymphocytes, widely used as an in vitro model for assessing the human health risk posed by different chemical compounds. In a first step, Nuclear Magnetic Resonance (H NMR) spectroscopy, and Ultra-High Performance Liquid Chromatography-Mass Spectrometry (UHPLC-MS) were employed to estimate Tetraglyme's stability under a wide range of pH values (4-12), and thus to identify potential by-products. Thereafter, isolated lymphocytes were treated with different concentrations of Tetraglyme (0.

Density functional theory and enzyme studies support interactions between angiotensin receptor blockers and angiotensin converting enzyme-2: Relevance to coronavirus 2019.

The binding affinities and interactions between eight drug candidates, both commercially available (candesartan; losartan; losartan carboxylic acid; nirmatrelvir; telmisartan) and newly synthesized benzimidazole-N-biphenyltetrazole (ACC519T), benzimidazole bis-N,N'-biphenyltetrazole (ACC519T(2) and 4-butyl-N,N-bis([2-(2H-tetrazol-5-yl)biphenyl-4-yl]) methyl (BV6), and the active site of angiotensin-converting enzyme-2 (ACE2) were evaluated for their potential as inhibitors against SARS-CoV-2 and regulators of ACE2 function through Density Functional Theory methodology and enzyme activity assays, respectively. Notably, telmisartan and ACC519T(2) exhibited pronounced binding affinities, forming strong interactions with ACE2's active center, favorably accepting proton from the guanidinium group of arginine273. The ordering of candidates by binding affinity and reactivity descriptors, emerged as telmisartan > ACC519T(2) > candesartan > ACC519T > losartan carboxylic acid > BV6 > losartan > nirmatrelvir.