Identifying host defense peptides (HDPs) that are effective against drug-resistant infections is challenging due to their vast sequence space. Artificial intelligence (AI)-guided design can accelerate HDP discovery, but it traditionally requires larg...
We use a combination of Brownian dynamics (BD) simulation results and deep learning (DL) strategies for the rapid identification of large structural changes caused by missense mutations in intrinsically disordered proteins (IDPs). We used ∼6500 IDP s...
Natural topological proteins exhibit unique properties including enhanced stability, controlled quaternary structures, and dynamic switching properties, highlighting topology as a unique dimension in protein engineering. Although artificial design an...
Advancements in polymer chemistry have enabled the design of macromolecular structures with tailored properties for diverse applications. Reversible addition-fragmentation chain-transfer (RAFT) polymerization is a controlled technique for precise pol...
Glycosylation is a valuable tool for modulating protein solubility; however, the lack of reliable research strategies has impeded efficient progress in understanding and applying this modification. This study aimed to bridge this gap by investigating...
This Perspective outlines recent progress and future directions for using machine learning (ML), a data-driven method, to address critical questions in the design, synthesis, processing, and characterization of . The achievement of these tasks requir...
The inherent hydrolytic reactivity of polyesters renders them excellent candidates for a variety of biomedical applications. Incorporating ionic groups further expands their potential impact, encompassing charge-dependent function such as deoxyribonu...