Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis.
Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available.



To fully comprehend the diverse functions of a protein, it is essential to understand the functionality of individual residues. Current methods are highly dependent on evolutionary sequence conservation, which is usually limited by sampling size. Sequence conservation-based methods are further confounded by structural constraints and multifunctionality of proteins. Here we present a method that can systematically identify and annotate functional residues of a given protein. We used a high-throughput functional profiling platform to identify essential residues. Coupling it with homologous-structure comparison, we were able to annotate multiple functions of proteins. We demonstrated the method with the PB1 protein of influenza A virus and identified novel functional residues in addition to its canonical function as an RNA-dependent RNA polymerase. Not limited to virology, this method is generally applicable to other proteins that can be functionally selected and about which homologous-structure information is available.
Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, California, USA.|Cancer Institute, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, ZJU-UCLA Joint Center for Medical Education and Research, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Yushen
Y
Du
Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, California, USA.|Molecular Biology Institute, University of California Los Angeles, Los Angeles, California, USA.
Nicholas C
NC
Wu
Department of Neurology, University of California Los Angeles, Los Angeles, California, USA.
Lin
L
Jiang
Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, California, USA.|Molecular Biology Institute, University of California Los Angeles, Los Angeles, California, USA.
Tianhao
T
Zhang
Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, California, USA.
Danyang
D
Gong
Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, California, USA.
Sara
S
Shu
Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, California, USA.
Ting-Ting
TT
Wu
Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, California, USA rsun@mednet.ucla.edu.|Cancer Institute, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, ZJU-UCLA Joint Center for Medical Education and Research, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.|Molecular Biology Institute, University of California Los Angeles, Los Angeles, California, USA.
Ren
R
Sun
D000596:Amino Acids / Q000235:genetics* / Q000378:metabolism*; D004252:DNA Mutational Analysis; D066289:Data Curation; D059014:High-Throughput Nucleotide Sequencing; D009980:Influenza A virus / Q000201:enzymology* / Q000502:physiology*; D008958:Models, Molecular; D011487:Protein Conformation; D021382:Protein Sorting Signals; D021381:Protein Transport; D014764:Viral Proteins / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism*; D014779:Virus Replication
D000596:Amino Acids; D021382:Protein Sorting Signals; D014764:Viral Proteins; C077346:influenza virus polymerase basic protein 1