Conformational plasticity of RNA for target recognition as revealed by the 2.15 Å crystal structure of a human IgG–aptamer complex

Aptamers are short single-stranded nucleic acids with high affinity to target molecules and are applicable to therapeutics and diagnostics. Regardless of an increasing number of reported aptamers, the structural basis of the interaction of RNA aptamer with proteins is poorly understood. Here, we determined the 2.15 Å crystal structure of the Fc fragment of human IgG1 (hFc1) complexed with an anti-Fc RNA aptamer. The aptamer adopts a characteristic structure fit to hFc1 that is stabilized by a calcium ion, and the binding activity of the aptamer can be controlled many times by calcium chelation and addition. Importantly, the aptamer–hFc1 interaction involves mainly van der Waals contacts and hydrogen bonds rather than electrostatic forces, in contrast to other known aptamer–protein complexes. Moreover, the aptamer–hFc1 interaction involves human IgG-specific amino acids, rendering the aptamer specific to human IgGs, and not crossreactive to other species IgGs. Hence, the aptamer is a potent alternative for protein A affinity purification of Fc-fusion proteins and therapeutic antibodies. These results demonstrate, from a structural viewpoint, that conformational plasticity and selectivity of an RNA aptamer is achieved by multiple interactions other than electrostatic forces, which is applicable to many protein targets of low or no affinity to nucleic acids

Higher-order spike triggered analysis of neural oscillators.

For the purpose of elucidating the neural coding process based on the neural excitability mechanism, researchers have recently investigated the relationship between neural dynamics and the spike triggered stimulus ensemble (STE). Ermentrout et al. analytically derived the relational equation between the phase response curve (PRC) and the spike triggered average (STA). The STA is the first cumulant of the STE. However, in order to understand the neural function as the encoder more explicitly, it is necessary to elucidate the relationship between the PRC and higher-order cumulants of the STE. In this paper, we give a general formulation to relate the PRC and the nth moment of the STE. By using this formulation, we derive a relational equation between the PRC and the spike triggered covariance (STC), which is the covariance of the STE. We show the effectiveness of the relational equation through numerical simulations and use the equation to identify the feature space of the rat hippocampal CA1 pyramidal neurons from their PRCs. Our result suggests that the hippocampal CA1 pyramidal neurons oscillating in the theta frequency range are commonly sensitive to inputs composed of theta and gamma frequency components