Computational Biology and Bioinformatics Lab

Centre for AI Driven Drug Discovery at Macao Polytechnic University

Welcome to CBBio@MPU! We are dedicated to advancing computational biology to deepen our understanding of biomolecular systems and to enable discovery across the health and life sciences. By integrating biological insight with AI-driven methods, we address challenging questions at the interface of computation and biology.

In drug discovery, our research spans method development for peptide and small-molecule drug discovery and property prediction, from target identification, lead discovery to (bio)synthesis prediction. Current projects focus on antimicrobial peptides (AMPs), anticancer peptides (ACPs), antioxidant peptides (AOPs), bacterial targets (TxSS), and cancer targets (TROP2 and HER2).

In health sciences, we work on medical imaging diagnosis, with a particular focus on infectious diseases, as well as spatial gene expression prediction from histopathological images for cancer research.

Keywords: 人工智能藥物與多肽發現;蛋白質語言模型;生物醫學知識圖譜;生物催化/計算酶學;分子建模與化學資訊學;醫學影像分析. AI-Driven Drug and Peptide Discovery; Protein Language Models; Biomedical Knowledge Graphs; Biocatalysis / Computational Enzymology; Molecular Modeling and Cheminformatics; Medical Image Analysis

Explore our app portal (https://app.cbbio.online). Some program source codes can be downloaded from our GitHub page or SourceForge page.

Join us!!! PhD admission 2026/2027 (Admission period: 15 Oct 2025 to 15 May 2026) 「中文版」

Latest News

澳门理工大学招收人工智能药物发现博士生

我们現正招募 2026/2027 年秋季入学的博士生。申请受理直至 2027年 5月15日。 Shirley Siu 澳门理工大学(MPU)人工智能驱动药物发现中心(AIDD)的团队正在招收2026/2027年秋季入学的博士生。我们是一支充满活力的研究团队,致力于人工智能和药物发现交叉领域的前沿研究。我们开发并应用人工智能方法和计算化学技术来解决药物发现过程中的复杂问题。硏究项目包括靶标识别、蛋白质-配体和蛋白质-肽结合预测、虚拟筛选以及生物分子和化合物的活性和功能预测。 我们诚邀充满热情和动力的博士生参与以下创新项目: 肽生物活性预测、发现与设计开发机器学习和深度学习方法,预测和设计具有治疗潜力的肽类药物——抗菌、抗癌、抗氧化、毒素和抗毒素。 靶向特异性肽生成模型推进定制化生成式人工智能模型,用于设计靶向特定蛋白质和疾病通路的肽类药物。 通过人工智能驱动的药物发现 (AIDD) 和计算机辅助药物设计 (CADD) 发现小分子抑制剂应用人工智能和计算化学工具识别和优化新型小分子疗法。 大型语言模型和代理生物医学数据管理利用文献挖掘和自然语言处理,自动提取和管理生物医学知识,加速发现疾病的分子机制及药物再利用。 使用综合计算方法研究与疾病相关的分子机制,特别是微生物耐药性、癌症进展和衰老。 资格: 具备严谨的科学态度、团队合作精神、良好的沟通能力、积极乐观的态度 拥有计算化学/生物学/物理学、生物信息学或密切相关领域的硕士学位 也欢迎具有药学和生命科学背景、具备肽合成和实验技能、并且热衷于学习人工智能的学生! 熟悉AI编程 具有分子建模或模拟经验優先 良好的英语口语和写作能力 全额奖学金澳门币20,000元/月,上限3年 半额奖学金澳门币10,000元/月,上限3年 期间:通常为 3-4 年 课程将在澳门及横琴校区上课。 申请截止:招生采取滚动录取政策,最后申请日期為2027年5月15日(参见招生网站) 询问:有意者请电郵 shirleysiu@mpu.edu.mo(请提供意向书、简历、成绩单和代表性出版物) 课程和入学信息: PhD programme in AI Driven Drug discovery Key dates 学费 University admission page 內地考生專頁 Academic regulations for PhD students

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PhD Positions in AI Driven Drug Discovery (2026/2027 intake)

We are admitting new PhDs for the 2026/2027 cohort. Official application is until 15 May 2027. 🚀 PhD Recruitment: Computational Biology & AI-Driven Drug Discovery 🚀 Join our research team exploring the intersection of AI, computational biology, and drug discovery. We invite passionate and motivated PhD candidates to work on innovative projects including: Peptide Bioactivity…

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Advancing AI for Protein-Peptide Interaction Prediction

Protein-peptide interactions are central to many biological processes, but the scarcity of experimental data makes their prediction challenging. In our latest work, Xinke Zhan led the development of PepInter, a deep learning framework that leverages pretrained protein language models and large-scale structural pretraining to learn interaction-aware representations, achieving strong results across multiple benchmarks. We’re excited…

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