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Date: Thu Sep 11 05:52:34 2008
Subject: 08.09.11 PhD positions in Computational Drug Design at the Italian Institute of Technology
PhD Studentships available at Italian Institute of Technology

submission deadline October 3, 2008

The Universita' degli Studi di Genova (www.unige.it) and the Italian 
Institute of Technology (www.iit.it) have made an agreement for a 
3-year PhD School in Robotics, Neurosciences, Nanotechnologies and 
Drug Discovery. 

The Italian Institute of Technology (IIT) is a research institution in 
Italy that after the start-up phase is currently almost complete. 
The fellowships assigned by IIT to the University of Genova are part 
of the start-up strategy of the Institute and have the specific goal 
of forming the first generation of IITs research fellows. 
Following the start of the Research Labs in the IITs Headquarters in 
Genova Morego (Italy) and the appointment of the first scientists, this 
years research topics are proposed by the Research Directors and their 
senior collaborators.  The candidates are asked to prepare a research 
project of their choice with explicit reference to the Theme proposed. 
The soundness of the project will be part of the evaluation process and 
will be considered preferential for the choice of the individual 
scientific theme that will be made jointly by the tutor and the candidate.

This years school activities will start in January 2009.

The Drug Discovery and Development department (directed by Prof. Daniele 
Piomelli) offers 6 PhD studentships concerning the field of COMPUTATIONAL
DRUG DESIGN. 


The corresponding Theme follows:


Theme 6.1: Modeling of membrane proteins
Tutor: Dr. Andrea Cavalli
N. available positions: 2

Nearly one-third of all genes in various organisms encode for 
membrane-associated proteins that play a fundamental role in life 
processes. In this respect, it is not surprising that membrane proteins 
also represent validated and innovative targets for the discovery of new 
drug candidates. Modeling of membrane proteins can provide new insights 
into structural features and functional mechanisms of such biological 
machines, and in turn open up new avenues to the discovery of small 
organic molecules able to modulate the biological functions regulated 
by these target proteins. The PhD student will use computational tools 
to study two main families of membrane proteins, G-protein-coupled 
receptors and ion channels. Homology modeling techniques (when required), 
molecular dynamics simulations, and molecular docking experiments will
be carried out aimed at both obtaining new mechanistic insights into the 
members of these families, and designing new modulators for selected 
membrane proteins.


Theme 6.2: Design of disruptors of protein-protein interactions 
Tutor: Dr. Giovanni Bottegoni - Dr. Matteo Masetti
N. available positions: 2

Interactions between proteins are at the heart of the cellular machinery, 
and designing molecules able to interfere with protein-protein interactions
is an important challenge. However, detailed insights into the protein 
binding properties as well as efficient screening platforms are needed to 
identify small organic molecules able to disrupt interactions between 
proteins. In this respect, computational tools can be of a great help as 
they can be exploited to both disclose the molecular determinants of 
protein-protein interactions, and identify new chemical entities able to 
prevent the formation of and/or to disrupt protein-protein complexes. 
In detail, the PhD student will apply docking tools to predict the 
structure of protein-protein complexes and identify small organic 
molecules able to interfere with such complexes. Molecular dynamics 
simulations and/or metadynamics will also be used to sample the 
conformational space of the proteins involved in complex formation and 
identify conformations responsible for protein-protein interactions.


Theme 6.3: Data mining and virtual screening of compound libraries
Tutor: Dr. Walter Rocchia
N. available positions: 2

Large libraries of chemical compounds reflect the exponentially growing 
data-enrichment in drug discovery that trends towards fully automated 
solutions to study structure-activity relationships of molecules vs. 
their biological counterparts. The first step is the construction of 
databases (chemical libraries) of non-redundant compounds that can be then
exploited for virtual screening experiments. In detail, the PhD student 
will apply computer science to construct a database of compounds either 
commercially or non-commercially available, which will be provided by 
national and international collaborators. The database will be then 
extended into a three-dimensional compound library containing low-energy 
conformations of all available molecules. All compounds will be finally 
screened against selected molecular targets (and/or pharmacophore models) 
to identify new lead candidates able to modulate the activity of a target 
protein.


For further details concerning the research project, please visit the 
following url: http://www.iit.it/doctoral_school and/or contact: 
andrea.cavalli_+_iit.it
Please visit the following url: http://www.iit.it/doctoral_school 
and/or contact: andrea.cavalli_+_iit.it
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