A multitask deep-learning method for predicting membrane associations and secondary structures of proteins. J. Proteome Res., (20)8:4089--4100, American Chemical Society (ACS), August 2021. [PUMA: convolutional deep learning; long memory multitask networks; neural prediction prediction; secondary short-term structure topic_lifescience topology transmembrane]
RosettaCM for antibodies with very long HCDR3s and low template availability. Proteins, (89)11:1458--1472, Wiley, November 2021. [PUMA: Rosetta; antibody; benchmark; homology loop modeling; prediction; structure topic_lifescience]
Modeling of protein conformational changes with Rosetta guided by limited experimental data. Structure, (30)8:1157--1168.e3, Elsevier BV, August 2022. [PUMA: EPR Rosetta; biology; changes; conformational dynamics; integrative modeling; molecular protein refinement spectroscopy; structural structure topic_lifescience]
Sparse pseudocontact shift NMR data obtained from a non-canonical amino acid-linked lanthanide tag improves integral membrane protein structure prediction. J. Biomol. NMR, (77)3:69--82, June 2023. [PUMA: (IMPs); (PCSs); (ncAAs); Click Integral Non-canonical Pseudocontact Rosetta; Structure acids amino chemistry; membrane prediction proteins shifts topic_lifescience]
Benchmarking AlphaFold2 on peptide structure prediction. Structure, (31)1:111--119.e2, Elsevier BV, January 2023. [PUMA: AlphaFold2; benchmark; bonds; disulfide folding; pLDDT; peptides; prediction protein structure topic_lifescience]
Biasing AlphaFold2 to predict GPCRs and kinases with user-defined functional or structural properties. Front. Mol. Biosci., (10):1121962, February 2023. [PUMA: (G-protein-coupled AlphaFold; GPCRs function; kinases; prediction protein receptors); structure topic_lifescience]