Innovation and Technology

Prof. Yao Zhongping
Associate Head and Professor, Department of Applied Biology and Chemical Technology

We are an interdisciplinary team specializing in mass spectrometry (MS), analytical chemistry, chemical biology and multi-omics. We develop and apply MS-based approaches to address fundamental and applied problems in various fields, including chemistry, biology, medicine, food science and information science.

Our current research interests include:

Molecular Data Storage
We are developing amino acid sequences for data storage that offer high density and long storage time compared to conventional and emerging methods. By assigning different amino acids to represent various bit combinations, we can translate bit sequences of digital information into amino acid sequences that can be synthesized as peptides or expressed as proteins for storage. During data retrieval, the data-bearing peptides/proteins are sequenced, and the acquired amino acid sequences are converted back into digital combinations based on prior assignments, ultimately decoding the original data. We have successfully stored text and audio information in peptides and retrieved them via LC-MS/MS sequencing. We are also exploring data storage with proteins, including storage in organisms such as bacteria and plants. Our research links data storage with peptide synthesis, protein engineering and proteomics, creating new possibilities for these fields.

Conformational Dynamics of Proteins and Protein Interactions
We employ techniques such as hydrogen/deuterium exchange MS, native MS, ion mobility MS, and molecular dynamics simulations to study the conformational dynamics of proteins and their interactions, which are challenging to obtain using conventional methods. Current projects include investigating the conformational dynamics of β-lactamases and their interactions with antibiotics and inhibitors, as well as studying SARS-CoV-2 proteins and their interactions with ACE-2, antibodies and inhibitors.

Molecular Assembly and Recognition
MS is rapid, sensitive, and provides a gas-phase environment free from the interferences of solvents or other species, making it an ideal tool for understanding the intrinsic properties of molecular assembly and recognition. We utilize tandem MS, ion mobility MS, and molecular modeling to investigate how biomolecules assemble, particularly in coordination with metal ions, how chiral recognition of fundamental molecules is induced and propagated, and to develop new methods for differentiating isomers, including the chiral recognition of drugs.

Mechanistic Study and Biomarker Discovery in Diseases and Biological Processes
We apply proteomics, metabolomics and lipidomics approaches to investigate biological and clinical samples, aiming to understand fundamental biological processes and discover disease biomarkers. For example, in collaboration with Prof. Yusong Guo, a research team in cell biology at the Hong Kong University of Science and Technology, we have utilized MS-based proteomics to systematically reveal how cargo proteins are sorted into vesicles for transport.

Food Safety
We develop and apply MS techniques for the authentication of edible oils, wines, and herbal medicines. Our ongoing efforts in quality assurance for edible oils include the development of a MALDI-MS-based method for rapid analysis and screening of gutter oils, the creation of a spectral database for classifying edible oils, and methods for the rapid quantitation of blended oils. We have also collaborated with the HKSAR Government to establish guidelines for using frying oil in Hong Kong, which have been announced for implementation.

基於質譜的跨學科研究

姚鍾平教授
應用生物及化學科技學系副系主任及教授

我們的跨學科團隊專注於質譜（MS）、分析化學、化學生物學及多組學的研究。我們開發和應用基于質譜的方法來解決化學、生物學、醫學、食品科學及資訊科學等領域的基础與應用問題。

我們目前的研究興趣包括：

分子數據存儲
我們正在開發用於數據存儲的氨基酸序列。與傳統及其他新興方法相比，這種序列具有更高的儲存密度及更長的儲存期限。通過指定不同的氨基酸代表不同的位元組合，便可將數字信息的位元序列轉換為氨基酸序列，而這些序列可被合成或表達為多肽或蛋白質進行數據存儲。在取回數據時，對承載數據的肽或蛋白質進行測序，並根據先前的指定將獲取的氨基酸序列轉換為位元組合，最後再進行解碼得到原來的數據。我們已成功將一些文本和音訊資料存儲在多肽中，並通過LC-MS/MS測序成功將其讀回，並正研究如何用蛋白質進行數據存儲，包括將數據存儲在細菌和植物等物種之中。我們的研究將數據存儲與多肽合成、蛋白質工程及蛋白質組學聯繫起來，為這些領域創造了新的可能性。

蛋白質動態構象與蛋白質相互作用
我們運用氫/氘交換質譜、原态質譜、離子遷移質譜及分子動態模擬等技術，來研究蛋白質動態構象及蛋白質之間的相互作用，這些信息往往難以通過傳統技術得到。目前，正在進行中的項目包括研究β-內酰胺酶的動態構象及其與抗生素和抑制劑的相互作用，以及SARS-CoV-2蛋白質與ACE-2、抗體及抑制劑的相互作用等。

分子組裝與識別
質譜技術快速、靈敏，並能提供不受溶劑或其他物質干擾的氣相環境，是獲取分子組裝與識別內在特性的理想工具。我們正在使用串聯質譜、離子遷移質譜及分子建模來了解，生物分子（特别是在金屬離子協調下）如何進行組裝，基本分子的手性識別如何被誘導及傳播，並開發新的區分異構體的方法，包括藥物的手性識別。

疾病與生物運作機制研究與尋找生物標記物
我們致力採用蛋白質組學、代謝組學及脂質組學技術來研究生物與臨床樣本，以了解生物學中的基本運作機制並尋找疾病的生物標記物。例如，通過與香港科技大學的細胞生物學研究團隊郭玉松教授合作，我們得以利用基於質譜的蛋白質組學系統地揭示了運送蛋白如何被分揀進入囊泡進行運輸。

食品安全
我們致力應用並開發質譜技術來為食用油、葡萄酒及草藥等食品進行鑑定。例如，我們一直尋找方法確保食用油的質量，包括根據MALDI-MS開發出食用油快速分析方法及地溝油篩查方法，建立食用油的質譜數據庫，並開發了快速定量分析調和油的方法。我們還與香港特區政府合作，制定了香港油炸用油的使用指引，並已在香港公佈執行。