S-PLM: Structure-Aware Protein Language Model via Contrastive Learning Between Sequence and Structure.

Proteins play an essential role in various biological and engineering processes. Large protein language models (PLMs) present excellent potential to reshape protein research by accelerating the determination of protein functions and the design of proteins with the desired functions. The prediction and design capacity of PLMs relies on the representation gained from the protein sequences.

Human placental mesenchymal stromal cell-derived small extracellular vesicles as a treatment for severe COVID-19: A double-blind randomized controlled clinical trial.

The current study aimed to investigate the effects of human placental mesenchymal stromal cell-derived small extracellular vesicles (hPMSC-sEVs) as a treatment for COVID-19. This double-blind, randomized, controlled clinical trial was conducted on two groups of patients with COVID-19-associated acute respiratory distress syndrome. After randomization, the control group received standard treatment and placebo, and the intervention arm received standard treatment plus hPMSC-sEVs.

Machine learning-based approaches for ubiquitination site prediction in human proteins.

Protein ubiquitination is a critical post-translational modification (PTMs) involved in numerous cellular processes. Identifying ubiquitination sites (Ubi-sites) on proteins offers valuable insights into their function and regulatory mechanisms. Due to the cost- and time-consuming nature of traditional approaches for Ubi-site detection, there has been a growing interest in leveraging artificial intelligence for computer-aided Ubi-site prediction.

A Review of Machine Learning and Algorithmic Methods for Protein Phosphorylation Site Prediction.

Post-translational modifications (PTMs) have key roles in extending the functional diversity of proteins and, as a result, regulating diverse cellular processes in prokaryotic and eukaryotic organisms. Phosphorylation modification is a vital PTM that occurs in most proteins and plays a significant role in many biological processes. Disorders in the phosphorylation process lead to multiple diseases, including neurological disorders and cancers.

S-PLM: Structure-aware Protein Language Model via Contrastive Learning between Sequence and Structure.

Proteins play an essential role in various biological and engineering processes. Large protein language models (PLMs) present excellent potential to reshape protein research by accelerating the determination of protein function and the design of proteins with the desired functions. The prediction and design capacity of PLMs relies on the representation gained from the protein sequences.