5 papers
Persistent Sheaf Laplacian Analysis of Protein Stability and Solubility Changes upon Mutation
Yiming Ren, Junjie Wee, Xi Chen +2
Genetic mutations frequently disrupt protein structure, stability, and solubility, acting as primary drivers for a wide spectrum of diseases. Despite the critical importance of the…
Predicting Protein-Nucleic Acid Flexibility Using Persistent Sheaf Laplacians
Nicole Hayes, Ekaterina Merkurjev, Guo-Wei Wei
Understanding the flexibility of protein-nucleic acid complexes, often characterized by atomic B-factors, is essential for elucidating their structure, dynamics, and functions, suc…
Persistent Sheaf Laplacian Analysis of Protein Flexibility
Nicole Hayes, Xiaoqi Wei, Hongsong Feng +2
Protein flexibility, measured by the B-factor or Debye-Waller factor, is essential for protein functions such as structural support, enzyme activity, cellular communication, and mo…
Persistent Directed Flag Laplacian (PDFL)-Based Machine Learning for Protein-Ligand Binding Affinity Prediction
Mushal Zia, Benjamin Jones, Hongsong Feng +1
Directionality in molecular and biomolecular networks plays a significant role in the accurate represention of the complex, dynamic, and asymmetrical nature of interactions present…
Multiscale differential geometry learning for protein flexibility analysis
Hongsong Feng, Jeffrey Y. Zhao, Guo-Wei Wei
Protein flexibility is crucial for understanding protein structures, functions, and dynamics, and it can be measured through experimental methods such as X-ray crystallography. The…