Direct structural and dynamic characterization of protein conformers in solution is highly desirable but currently impractical. Herein, we developed a single molecule gold plasmonic nanopore system for observation of protein allostery, enabling us to monitor translocation dynamics and conformation transition of proteins by ion current detection and SERS spectrum measurement, respectively. Allosteric transition of calmodulin (CaM) was elaborately probed by the nanopore system. Two conformers of CaM were well-resolved at a single-molecule level using both the ion current blockage signal and the SERS spectra. The collected SERS spectra provided structural evidence to confirm the interaction between CaM and the gold plasmonic nanopore, which was responsible for the different translocation behaviors of the two conformers. SERS spectra revealed the amino acid residues involved in the conformational change of CaM upon calcium binding. The results demonstrated that the excellent spectral characterization furnishes a single-molecule nanopore technique with an advanced capability of direct structure analysis.

Allosteric mechanisms are commonly employed regulatory tools used by proteins to orchestrate complex biochemical processes and control communications in cells. The quantitative understanding and characterization of allosteric molecular events are among major challenges in modern biology and require integration of innovative computational experimental approaches to obtain atomistic-level knowledge of the allosteric states, interactions, and dynamic conformational landscapes. The growing body of computational and experimental studies empowered by emerging artificial intelligence (AI) technologies has opened up new paradigms for exploring and learning the universe of protein allostery from first principles. In this review we analyze recent developments in high-throughput deep mutational scanning of allosteric protein functions; applications and latest adaptations of Alpha-fold structural prediction methods for studies of protein dynamics and allostery; new frontiers in integrating machine learning and enhanced sampling techniques for characterization of allostery; and recent advances in structural biology approaches for studies of allosteric systems. We also highlight recent computational and experimental studies of the SARS-CoV-2 spike (S) proteins revealing an important and often hidden role of allosteric regulation driving functional conformational changes, binding interactions with the host receptor, and mutational escape mechanisms of S proteins which are critical for viral infection. We conclude with a summary and outlook of future directions suggesting that AI-augmented biophysical and computer simulation approaches are beginning to transform studies of protein allostery toward systematic characterization of allosteric landscapes, hidden allosteric states, and mechanisms which may bring about a new revolution in molecular biology and drug discovery.