Cryo-electron microscopy (cryo-EM) single-particle analysis is a revolutionary imaging technique to resolve and visualize biomacromolecules. Image alignment in cryo-EM is an important and basic step to improve the precision of the image distance calculation. However, it is a very challenging task due to high noise and low signal-to-noise ratio. Therefore, we propose a new deep unsupervised difference learning (UDL) strategy with novel pseudo-label guided learning network architecture and apply it to pair-wise image alignment in cryo-EM. The training framework is fully unsupervised. Furthermore, a variant of UDL called joint UDL (JUDL), is also proposed, which is capable of utilizing the similarity information of the whole dataset and thus further increase the alignment precision. Assessments on both real-world and synthetic cryo-EM single-particle image datasets suggest the new unsupervised joint alignment method can achieve more accurate alignment results. Our method is highly efficient by taking advantages of GPU devices. The source code of our methods is publicly available at "http://www.csbio.sjtu.edu.cn/bioinf/JointUDL/" for academic use.

Ramachandran plots, which describe protein structures by plotting the dihedral angle pairs of the backbone on a two-dimensional plane, have played an important role in structural biology over the past few decades. However, despite continued discovery of new protein structures to date, the Ramachandran plot is still constructed by only a small number of data points, and further it cannot reflect the steric information of proteins. Here, we investigated the secondary structure of proteins in terms of static and dynamic characteristics. As for static feature, the Ramachandran plot was revisited for the dataset consisting of 9,148 non-redundant high-resolution protein structures released in the protein data bank until April 1, 2022. By calculating amino acid propensities, it was found that the proportion of secondary structures with respect to residue depth is directly related to their hydrophobicity. As for dynamic feature, normal mode analysis (NMA) based on an elastic network model (ENM) was carried out for the dataset using our KOSMOS web server (http://bioengineering.skku.ac.kr/kosmos/). All ENM-based NMA results were stored in the KOSMOS database, allowing researchers to use them in various ways. In this process, it was commonly found that high B-factors appeared at the edge of the alpha helix region, which was elucidated by introducing residue depth. In addition, by investigating the change in dihedral angle, it was possible to quantitatively survey the contribution of structural change of protein on the Ramachandran plot. In conclusion, our statistical analysis of protein characteristics will provide insight into a range of protein structural studies.

O-Glycosylation of hydroxylysine (Hyl) in collagen occurs at an early stage of biosynthesis before the triple-helix has formed. This simple post-translational modification (PTM) of lysine by either a galactosyl or glucosylgalactosyl moiety is highly conserved in collagens and depends on the species, type of tissue and the collagen amino acid sequence. The structural/functional reason why only specific lysines are modified is poorly understood, and has led to increased efforts to map the sites of PTMs on collagen sequences from different species and to ascertain their potential role in vivo. To investigate this, we purified collagen type I (Col1) from the skins of four animals, then used mass spectrometry and proteomic techniques to identify lysines that were oxidised, galactosylated, glucosylgalactosylated, or glycated in its mature sequence. We found 18 out of the 38 lysines in collagen type Iα1, (Col1A1) and 7 of the 30 lysines in collagen type Iα2 (Col1A2) were glycosylated. Six of these modifications had not been reported before, and included a lysine involved in crosslinking collagen molecules. A Fourier transform analysis of the positions of the glycosylated hydroxylysines showed they display a regular axial distribution with the same d-period observed in collagen fibrils. The significance of this finding in terms of the assembly of collagen molecules into fibrils and of potential restrictions on the growth of the collagen fibrils is discussed.