Research Progress in Area 3 方向 ( 三 ) 課題進展 155 Abstract Biological systems have evolved a wide range of complex networks that perform all kinds of functions. In thisproject, deep learningapproaches will be performed to investigate protospacer adjacent motif (PAM) sequence identity in CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated) systems. Multiscale simulations will be conducted to unravel the delicate interactions and hierarchical structural features of interactions between phages and bacteria. Moreover, scaling relations will be formulated by including viral-host adaptations and symbiosis to establish an integrated picture of vent and seep biological processes for better understanding of bio-diversity. Research Activities and Progress • Identified key residues through statistical / direct coupling analysis (Fig. 1); • Searched for novel decalin-forming macrolides by genome mining; • Gained insights in evolution dynamics of coronavirus’ spike glycoproteins. Key Findings • Overall kinetic mechanism is elucidated in detail with specific steps involved in Cas9 activity (Fig. 2); • Several potential new decalin-forming macrolide biosynthetic gene clusters were identified through analyzing all available bacterial genomes. The most promising candidate is a biosynthetic gene clusters within the genome of Streptomyces tsukubaensis; • The evolution dynamic of coronavirus’ spike glycoproteins is investigated by analyzing protein sequences data with leading mutation patterns. The key mutation sites of future strains are outlined to guide antibody and vaccine development. Research Output Publication 0 Trained personnel 6 Quantitative Modeling of Eco-Genomics Prof. Haibin Su The Hong Kong University of Science and Technology Fig 1. a) residues that are critical in interaction between HNH domain and DNA strands. b) Statistical Coupling Analysis shows network of those residues. c) representation in 3D structure (to be submitted).
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