Unit:
Department of Informatics and TelecommunicationsΠληροφορική
Supervisors info:
Ιωάννης Εμίρης, Καθηγητής, Τμήμα Πληροφορικής και Τηλεπικοινωνιών, Εθνικό και Καποδιστριακό Πανεπιστήμιο Αθηνών
Ευαγγελία Χρυσίνα, Κύρια Ερευνήτρια, IXB-EIE
Original Title:
Clustering approaches for extracting structural determinants of enzyme active sites that dictate ligand binding
Translated title:
Clustering approaches for extracting structural determinants of enzyme active sites that dictate ligand binding
Summary:
The study of enzyme binding sites is a very important process which can be very arduous
since it requires a lot of experimental work.This is why we need to use informatics and
computational tools which could speed up the process. The focus of this thesis is to
propose workflows by which we can depict the structure of an enzyme’s active site by
using computational methods and exploiting geometrical features of the enzyme. The
enzyme of glycogen prosphorylase (GP), a validated target for the design of therapeutic
agents for the treatment of type 2 diabetes, was selected as use case. With the aim
to create a glove representation of the active site of GP, all possible conformations of the
active site were artificially generated and clustered, taking into account the rotamers of the
individual residues that form this site. The results obtained give new structural insights on
a subsite of the catalytic site of GP that may be further exploited for the structurebased
design of improved therapeutic agents accelerating the drug discovery process.
Main subject category:
Technology - Computer science
Keywords:
Active site, pocket, clustering, alpha shape, rotamers, enzyme, glycogen phosphorylase, ligand, superposition, protein-ligand interaction
