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Predicting antibody structures and antibody-antigen complexes using AlphaFold

Microscopic beauty is hiding in common kitchen ingredients - even vanillin flavoring can be turned into mesmerizing artwork by crystallizing the vanillin and examining it under a polarizing microscope. Wang and Pang explore this hidden beauty by determining the optimal conditions to grow crystalline vanillin films and by creating computer simulations of chemical interactions between vanillin molecules.

Here, seeking to address the growing threat of multidrug-resistant bacteria (MDR). the authors used in silico virtual screening to target MDR Pseudomonas aeruginosa. They considered a key protein in its biosynthesis and virtually screened 20,000 candidates and 30 derivatives of brequinar. In the end, they identified a possible candidate with the highest degree of potential to inhibit the pathogen's lipid A synthesis.

With molecular energy being an integral element to the study of molecules and molecular interactions, computational methods to determine molecular energy are used for the preservation of time and resources. However, these computational methods have high demand for computer resources, limiting their widespread feasibility. The authors of this study employed machine learning to address this disadvantage, utilizing neural networks trained on different representations of molecules to predict molecular properties without the requirement of computationally-intensive processing. In their findings, the authors determined the Feedforward Neural Network, trained by two separate models, as capable of predicting molecular energy with limited prediction error.

Here, through protein-ligand docking, the authors investigated the effect of the interaction of emodin with serine/threonine kinases, a subclass of kinases that is overexpressed in many cancers, which is implicated in phosphorylation cascades. Through molecular dynamics theyfound that emodin forms favorable interactions with chitosan and chitosan PEG (polyethylene glycol) copolymers, which could aid in loading drugs into nanoparticles (NPs) for targeted delivery to cancerous tissue. Both polymers demonstrated reasonable entrapment efficiencies, which encourages experimental exploration of emodin through targeted drug delivery vehicles and their anticancer activity.

In this study, the authors investigate the antibacterial efficacy of penicillin G and its analogs amoxicillin, carbenicillin, piperacillin, cloxacillin, and ampicillin, against four species of bacteria. Results showed that all six penicillin-type antibiotics inhibit Staphylococcus epidermidis, Escherichia coli, and Neisseria sicca with varying degrees of efficacy but exhibited no inhibition against Bacillus cereus. Penicillin G had the greatest broad-spectrum antibacterial activity with a high radius of inhibition against S. epidermidis, E. coli, and N. sicca.

This article investigates differences in gene expression in the brains of patients with and without Parkinson's disease. The authors identify a crucial transcriptional regulator may be a relevant target for future therapeutic treatment for Parkinson's disease.

DegS is an integral inner membrane protein in E. coli that helps break down misfolded proteins. When it is mutated, there is a large increase in the production of outer membrane vesicles (OMVs), which are thought to play a role in pathogenesis. This study used mutant strains of uropathogenic E. coli (UPEC) to characterize the role of DegS and OMVs on UPEC virulence.

Kalirin is a guanine nucleotide exchange factor (GEF) for the GTPase RAC1, linked to schizophrenia and Alzheimer’s Disease. It plays a crucial role in synaptic plasticity by regulating dendritic spine formation and actin cytoskeleton remodeling, which are essential for creating new synapses. Authors developed two novel compounds targeting kalirin, confirming that predictive modeling can indicate biological activity.

Here, recognizing the important role of bacterial biofilms in many life-threatening chronic infections, the authors investigated the effectiveness of a combination treatment on biofilms composed of up to three different common species within the lungs of cystic fibrosis patients with computational analysis. They found that a triple cocktail therapy targeting three different signaling pathways has significant potential as both a treatment and prophylaxis.