Search for: All records

Prediction of surface topography in milling usually requires complex kinematics and dynamics modeling of the milling process, plus solving physical models of surface generation is a daunting task. This paper presents a multimodal data-driven machine learning (ML) method to predict milled surface topography. The proposed method predicts the height map of the surface topography by fusing process parameters and in-process acoustic information as model inputs. This method has been validated by comparing the predicted surface topography with the measured data. 

The thioamide is a versatile replacement of the peptide backbone with altered hydrogen bonding and conformational preferences, as well the ability participate in energy and electron transfer processes. Semi-synthetic incorporation of a thioamide into a protein can be used to study protein folding or protein/protein interactions using these properties. Semi-synthesis also provides the opportunity to study the role of thioamides in natural proteins. Here we outline the semi-synthesis of a model protein, the B1 domain of protein G (GB1) with a thioamide at the N-terminus or the C-terminus. The thioamide is synthetically incorporated into a fragment by solid-phase peptide synthesis, whereas the remainder of the protein is recombinantly expressed. Then, the two fragments are joined by native chemical ligation. The explicit protocol for GB1 synthesis is accompanied by examples of applications with GB1 and other proteins in structural biology and protein misfolding studies.