Peptides are ubiquitous and important biomolecules that self-assemble into diverse structures. Although extensive research has explored the effects of chemical composition and exterior conditions on self-assembly, a systematic study consolidating the...
Identification of intrinsically disordered regions (IDRs) in proteins is essential for understanding fundamental cellular processes. The IDRs can be divided into long disordered regions (LDRs) and short disordered regions (SDRs) according to their le...
The CRISPR-Cas system, an adaptive immune mechanism found in bacteria and archaea, has evolved into a promising genomic editing tool, with various types of Cas proteins playing a crucial role. In this study, we developed a set of strategies for minin...
With the advantage of extensive coverage, predicted spectral libraries are becoming an attractive alternative in proteomic data analysis. As a popular false discovery rate estimation method, target decoy search has been adopted in library search work...
The UniProt database is a valuable resource for biocatalyst discovery, yet predicting enzymatic functions remains challenging, especially for low-similarity sequences. Identifying superior enzymes with enhanced catalytic properties is even harder. To...
BACKGROUND: Association and cooperation among structural domains play an important role in protein function and drug design. Despite remarkable advancements in highly accurate single-domain protein structure prediction through the collaborative effor...
Proceedings of the National Academy of Sciences of the United States of America
40314982
Understanding the effects of missense mutations or single amino acid variants (SAVs) on protein function is crucial for elucidating the molecular basis of diseases/disorders and designing rational therapies. We introduce here , a machine learning too...
Protein science : a publication of the Protein Society
40260988
Deep learning methods have played an increasingly pivotal role in advancing side-chain packing and mutation effect prediction (ΔΔG) for protein complexes. Although these two tasks are inherently closely related, they are typically treated separately ...
MOTIVATION: Understanding the protein sequence-function relationship is essential for advancing protein biology and engineering. However, <1% of known protein sequences have human-verified functions. While deep-learning methods have demonstrated prom...
Protein-DNA interactions play a crucial role in cellular biology, essential for maintaining life processes and regulating cellular functions. We propose a method called iProtDNA-SMOTE, which utilizes non-equilibrium graph neural networks along with p...