Abstracts Keynote & Plenary

2. Göteborg University, Department of Medical Biochemistry and Cell Biology, Medicinaregatan 9A,
Box 440, SE-40530, Göteborg, Sweden
3. Laboratory for Molecular and Computational
Genomics, Department of Chemistry, Laboratory for
Genetics, University of Wisconsin-Madison Biotechnology Center, University of Wisconsin-Madison,
425 Henry Mall, Madison, Wisconsin 53706
Phone: 978-380-7287 Fax: 978-921-1350 Email:
xus@neb.com
BspQI is a thermostable Type IIS restriction endonuclease (REase)
with the recognition sequence 5’
GCTCTTC N1/N4 3’. Here we report the cloning and expression of the bspQIR gene for the BspQI
restriction enzyme in E. coli. Alanine scanning of the BspQI charged residues identified a number of
DNA nicking variants. After sampling combinations of different amino acid substitutions, an Nt.BspQI
triple mutant (E172A/E248A/E255K) was constructed with predominantly top-strand DNA nicking
activity. Furthermore, a triple mutant of BspQI (Nb.BspQI, N235A/K331A/R428A) was engineered to
create a bottom-strand nicking enzyme. In addition, we demonstrated the application of Nt.BspQI in
optical mapping of single DNA molecules. Nt or Nb.BspQI-nicked dsDNA can be further digested by
E. coli exonuclease III to create ssDNA for downstream applications. BspQI contains two potential
catalytic sites: a top-strand catalytic site (Ct) with a D-H-N-K motif found in the HNH endonuclease
family and a bottom-strand catalytic site (Cb) with three scattered Glu residues. BlastP analysis of
proteins in Genbank indicated a putative restriction enzyme with significant amino acid sequence
identity to BspQI from the sequenced bacterial genome Croceibacter atlanticus HTCC2559. This
restriction gene was amplified by PCR and cloned into a T7 expression vector. Restriction mapping
and run-off DNA sequencing of digested products from the partially purified enzyme indicated that it is
an EarI isoschizomer with 6-bp recognition, which we named CatHI (CTCTTC N1/N4).
PO-029
Prediction of Protein Binding Sites with Incremental Convex Hull Algorithm
Jing He and Dong-Qing Wei
Department of Bioinformatics and Biostatistics, College of Life Sciences and Biotechnology, Shanghai
otein surface[1,2].
re
re,
Wang and Dong-Qing, Wei*, “Role of Structural Bioinformatics and TCM databases in
2.Ch hou, Dong-Qing Wei *
Jiaotong University, 800 Dongchuan Road, Minhang District, Shanghai, China
The most potential protein binding sites are some pocket-shaped regions on the pr
Connolly, Brady and Stouten presented a mathematical solution by calculating the positions of a sphe
of given radii tangential to three protein atoms whose radii are not necessarily equal[3]. However, this
algorithm requires O(N
, “Molecular
4
) computational times. As N is the number of protein atoms, it takes extremely
long time for a protein of decent size. An incremental convex hull scheme is introduced to ameliorate
this algorithm. Suppose each convex hull is a three-contacting sphere, one adds protein atoms once at a
time to update the hull similar to incremental algorithm. The computational cost can be reduced to
O(N 2
) as estimated, which is much more efficient compared with the original algorithm. Furthermo
the catalytic features of the enzymes, as well as, the ligand-receptor complex information from the
PDB databank will be used to further improve the precision of prediction.
References:
1. Jing-Fang
Pharmacogenomics”, Pharmacogenomics, 10, Issue 10 (2009).
eng-Cheng Zhang, Jing-Fang Wang, Jing-Yi Yan, Kuo-Chen C
Modeling of CYP Proteins and Its Implication for Personal Drug Design”, in Automation in Genomics
and Proteomics: An Engineering Case-Based Approach Eds Gil Alterovitz, Roseann Benson, Marco
Ramoni,John Wiley, 2009(ISBN: 978-0-470-72723-2).