AFM has developed into a powerful tool in structural biology, providing topographs of proteins under close-to-native conditions and featuring an outstanding signal/noise ratio. However, the imaging mechanism exhibits particularities: fast and slow scan axis represent two independent image acquisition axes. Additionally, unknown tip geometry and tip-sample interaction render the contrast transfer function nondefinable. Hence, the interpretation of AFM topographs remained difficult. How can noise and distortions present in AFM images be quantified? How does the number of molecule topographs merged influence the structural information provided by averages? What is the resolution of topographs? Here, we find that in high-resolution AFM topographs, many molecule images are only slightly disturbed by noise, distortions, and tip-sample interactions. To identify these high-quality particles, we propose a selection criterion based on the internal symmetry of the imaged protein. We introduce a novel feature-based resolution analysis and show that AFM topographs of different proteins contain structural information beginning at different resolution thresholds: 10 A (AqpZ), 12 A (AQP0), 13 A (AQP2), and 20 A (light-harvesting-complex-2). Importantly, we highlight that the best single-molecule images are more accurate molecular representations than ensemble averages, because averaging downsizes the z-dimension and "blurs" structural details.

This review is focused on methods for detecting small molecules and, in particular, the characterisation of their interaction with natural proteins (e.g. receptors, ion channels). Because there are intrinsic advantages to using label-free methods over labelled methods (e.g. fluorescence, radioactivity), this review only covers label-free techniques. We briefly discuss available techniques and their advantages and disadvantages, especially as related to investigating the interaction between small molecules and proteins. The reviewed techniques include well-known and widely used standard analytical methods (e.g. HPLC-MS, NMR, calorimetry, and X-ray diffraction), newer and more specialised analytical methods (e.g. biosensors), biological systems (e.g. cell lines and animal models), and in-silico approaches.

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