Compared to proteomics, computational platforms for glycoproteomics is at an early stage and many researchers rely on the manual interpretation of large data sets to gain structural insights into the glycoproteome. Over the last few years there has been a steady increase in the availability of bioinformatics tools for processing and annotating glycoproteomics data sets. This mini-review describes advances in the development of algorithms and software applications and their applications. Furthermore, an update on structural and analytical databases is presented with a focus on those resources still actively maintained by the community, and how these resources are now being integrated into glycoproteomics pipelines to improve data interpretation.

Glycoprotein drugs have a remarkable structural complexity among biopharmaceuticals. The main reason for this is the diversity and complexity of their glycans. We have become able to prepare, in high-purity and large quantities, glycans which are extremely difficult to artificially control with posttranslational modification. We have also established a method of adding uniform glycans to arbitrary positions. These technologies make it possible to prepare homogeneous glycoproteins that are extremely difficult to prepare by expression. In addition, because glycans can be introduced to new arbitrary positions, appropriate design of the position, number, and structure of these sugar chains has made it possible to create next-generation biopharmaceuticals.

糖タンパク質性医薬品は、バイオ医薬品の中でも構造の複雑さが際立っている。要因は、糖鎖部分の多様性と複雑さである。我々は、翻訳後修飾で人為的制御が極めて困難な糖鎖部位を高純度・大量に調製できるようになった。さらに構造均一な糖鎖を任意の位置に付加する技術も構築した。これらの技術により、発現系での糖タンパク調製では極めて困難であった構造均一な糖タンパク調製が可能となった。また、新たな任意の位置への糖鎖導入も可能であるので、修飾位置とそれぞれの位置の糖鎖構造と糖鎖本数を適切に設計することで次世代型バイオ医薬品の創生も可能となった。