Prediction of peptide secondary structure is challenging because of complex molecular interactions, sequence-specific behavior, and environmental factors. Traditional design strategies, based on hydrophobicity and structural propensity, can be biased...
Peptides can serve as building blocks for supramolecular materials because of their unique ability to self-assemble, offering potential applications in drug delivery, tissue engineering, and nanotechnology. In this review, we describe peptide self-as...
Journal of chemical information and modeling
Jun 9, 2025
Understanding the binding interactions within protein-peptide complexes is crucial for elucidating key physicochemical phenomena in biological systems. Among the outcomes of these interactions, biomolecular condensates have recently emerged as vital ...
Journal of chemical information and modeling
Jun 9, 2025
(MAB) infections pose a significant treatment challenge due to their intrinsic resistance to antibiotics, requiring prolonged multidrug regimens with limited success and frequent relapses. tRNA (m1G37) methyltransferase (TrmD), an enzyme essential f...
Identifying detectable peptides, known as flyers, is key in mass spectrometry-based proteomics. Peptide detectability is strongly related to peptide sequences and their resulting physicochemical properties. Moreover, the high variability in MS data c...
International journal of biological macromolecules
Jun 1, 2025
Recent advances in machine learning have revolutionized molecular design; however, a gap remains in integrating generative models with physics-based simulations to develop functional modulators, such as stable peptides, for challenging targets like t...
Protein science : a publication of the Protein Society
Jun 1, 2025
Accurate identification of angiotensin-I-converting enzyme (ACE) inhibitory peptides is essential for understanding the primary factor regulating the renin-angiotensin system and guiding the development of new drug candidates. Given the inherent chal...
Accurate prediction of protein-peptide complex structures plays a critical role in structure-based drug design, including antibody design. Most peptide-docking benchmark studies were conducted using crystal structures of protein-peptide complexes; as...
Cancer engineering for tumor normalization offers a promising therapeutic strategy to reverse malignant cells and their supportive tumor microenvironment into a more benign state. Herein, an artificial intelligence (AI) approach was developed using m...
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