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Trinity College Dublin

Personal Information
Name Fares, Mario Ali
Main Department Genetics
College Title Assistant Professor
E-mail faresm@tcd.ie
College Tel +353 1 896 3521
 
Membership of Professional Institutions, Associations, Societies
Details Date From Date To
I'm member of the Societe of the International Society for Computational Biology 01-June-2007 to date
Associate Editor in: Research Journal of Microbiology and Open Journal of Informatics
 
Awards and Honours
Award Date
MSc 1998
PhD 2002
FulBright Fellowship 2002
President of Ireland Young Researcher Award 2004
 
Languages
Language Skill Reading Skill Writing Skill Speaking
Arabic Fluent Fluent Fluent
English Fluent Fluent Fluent
Spanish Fluent Fluent Fluent
 
Research Interests
Biocomputing Biological Sciences Computational Biology EVOLUTION
EVOLUTION RATE Evolution Evolutionary Biology Genetics
Genomes, Genomics Molecular Biology Stress Response, Neuroanatomy Structural Biology
Symbiosis
 
Research Projects
Project title Correlating LBA, adaptive evolution and expression at the genome level
Summary
Funding Agency SFI
Programme Basic Research Grant
Type of Project Basic
Date from 2004
Date to 2007
Person Months 36


Project title Computational and Biomedical analysis of heat-shock proteins (Hsp): Optimisation of protein function and putative drug targets
Summary
Funding Agency SFI
Programme PIYRA
Type of Project Biomedical
Date from 2004
Date to 2009
Person Months 60


Project title Computational analysis of inter- and intra-molecular covariation in key cellular proteins
Summary Intra- and inter-molecular interactions are important aspects in the understanding of the flow of chemical information through the cell. For example, the interaction between Toll-like receptors with their ligands, or between dendritic-cell (DC) receptors and Heat-shock proteins (HSPs) are essential points in the immune system defence. The last decade has witnessed an enormous increase in our understanding of the role of protein-protein interaction in cell viability. In fact, dozens of studies have shown that the interaction between Hsps with antigenic peptides as well as with receptors from antigen presenting cells (APC) are essential for the immune response to take place. Furthermore, Hsp90 establishes very complex protein-interaction networks to regulate cell growth and differentiation. The success of inter-protein interactions depends on the stability of the intra-molecular interactions. Studying both types of interactions is hence a must in specific biological systems, such the immune defence, to predict the relative importance of the different protein-protein interactions. To date, protein-protein interactions have been determined using two-hybrid systems or have been predicted by very simplistic computational tools. The underlying objective of this project is to predict proteins and peptide regions that may be key in maintaining the stability of cell differentiation pathways, and immune response induction using a computational approach. The specific objectives of the project are: a) Development of a mathematical approach to highlight interacting peptide regions in proteins and to predict interaction between two proteins b) Computational implementation of the new method to detect peptide-peptide interactions c) Study of the protein-protein interaction patterns in three main systems, including: c.1) Interaction between HSPs and the immune response c.2) Interaction between immune cell receptors and antigenic peptides c.3) Definition of key HSPs-protein interactions for the maturation of steroid hormone receptors In order to define the relative importance of intra-molecular interacting regions for the protein function, we will conduct neural network and selective constraints analyses. The first approach applies neural networks to the analysis of sequence alignments and permits the identification or prediction of the functional or the structural importance of specific amino acid sites. The second approach uses the information stored in the evolutionary history of proteins isolated from different taxonomically related organisms and highlights peptide regions that have contributed to the improvement of the protein function under certain environmental conditions (such as oxidative stress, or viral infections). To find specific HSP client proteins in other organisms for the evolutionary analyses we will perform Hidden Markov Model (HMM) based searches of proteins in complete genomes. It is our objective to screen the recently sequenced genome of the chicken Gallus gallus in order to find possible client proteins for Hsp90, Hsp70 or Grp94 that may be involved in the immune response. We estimate a total of 12 possible eukaryotic genomes that can be screened for orthologous sequences of HSPs and client proteins. With this number of sequences we will have enough information as to conduct reliable results on predicting protein-protein interactions in specific cellular pathways.
Funding Agency Science Foundation Ireland
Programme UREKA
Type of Project Biomedical (basic)
Date from 2005
Date to 2005
Person Months 3


Project title A new method to detect functionally and structurally important regions in proteins.
Summary One of the most important aspects in the study of proteins is the determination of the effect that mutations have on their function. If the protein is involved in a key pathway for cell viability, the study of these mutations become rather crucial for the clarification of the main effects on that pathway. Dozens of studies have focused on the analyses of the effect of mutations on protein function by conducting either serial deletion of peptide regions that have some indication of functionality, by directed mutagenesis, or by combination of both. Even though these experimental procedures have been useful for underlying functionally important regions in proteins, the aposteriori examination of randomly induced changes in proteins is subject to several drawbacks. In fact, these procedures are useful in the case of apriori knowledge of the functional importance of the peptide region. Moreover, linear examination of protein sequences is poorly realistic since protein function is determined by the protein folding and conformational changes rather than by the linear combination of its amino acids. Very few computational attempts have been made during the last years to decipher the main constraints on the protein mutability. Among them, neural network analyses have become one of the most successfully used methods to predict the functional or structural importance of specific protein amino acid sites. These methods rely on the assumption that important protein regions should be very conserved along their evolutionary history and are hence not allowed to fix amino acid mutations. Comparison thus of the protein sequence isolated from different organisms could underline regions that can be important for the protein to keep its proper function. The second assumption made by these methods is that conserved regions that are predicted to be exposed in the protein surface may have a functional importance because of its accessibility to other proteins in the medium. Alternatively, if the conserved region is predicted as buried in the protein, its role is more likely to be structural. One of the main problems of these methods is that they do not take into account the time since the divergence between the organisms from which the protein has been sequenced. These methods are also prone to error when the divergence time between the organisms compared is too high. The underlying objective of this project is to develop a sensitive and precise mathematical approach to determine structurally and functionally important regions in proteins. In order to achieve this objective we will address the following goals: a) Development and computational implementation of the mathematical framework to detect functional or structurally important protein regions b) Test the sensitivity of the method by the analysis of functionally mapped proteins c) Use the secondary structure information to evaluate the structural importance of the key regions detected by the method d) Apply the method to important proteins, such as the heat-shock protein 90, to resolve some controversies regarding the determination of functional regions for protein interaction and cofactor binding The computational work will be completed with the study of the evolution of the protein regions detected to be important and by defining their role in keeping the functional fitness of the protein in specific organisms or groups of organisms.
Funding Agency Science Foundation Ireland
Programme UREKA
Type of Project Basic
Date from 2005
Date to 2005
Person Months 3


Project title A multi-disciplinary approach to unravel biological factors responsible for cell viability
Summary The underlying objective of the STARs project is to decipher the main cofactors and intra-molecular regions determining the coordinated function of heat-shock proteins (Hsps) 70 and 90 Kda. These ATPase proteins are molecular chaperones responsible for the folding and degradation of proteins, stabilisation of steroid hormone receptors, cell-cycle regulation and induction of the immune system. Both proteins work in a coordinated way and need from the help of several cofactors. The pattern of interaction between the different cofactors and Hsps has to be still elucidated. Moreover, Complex intra-molecular interactions between the different domains within Hsp90 have been proposed, although the importance of these interactions for Hsp90 ability to bind partially folded peptides or to bind and hydrolyse ATP is poorly understood. In order to shed some light on these issues, we are going to conduct a computational-experimental approach that will include the following steps: a) Use recently developed software in our laboratory to determine regions that co-evolve within and between the above-mentioned proteins. b) Determine the importance of these regions for the function of the proteins as ATPases and Folding machines by studying their covariation with their essential cofactors. c) Define the importance of these regions from the evolutionary perspective through neural-network and selective constraints analyses. d) Conduct directed mutagenesis in the laboratory of Dr. Gary Jones to test the relative importance of each region for the function of the Hsps individually as well as in coordination with other molecules in the cell.
Funding Agency Science Foundation Ireland
Programme STARs
Type of Project Basic
Date from 2005
Date to 2005
Person Months 3


More Research Projects>>>
 
Publications and Other Research Outputs
Peer Reviewed
David McNally and Mario A. Fares, In silico identification of functional divergence between the multiple groEL gene paralogs in Chlamydiae, BMC Evolutionary Biology, 22, 2007, p1-13
Notes: [PubMed ID: 17519003]
TARA - Full Text  DOI
Mario A. Fares and Edward C. Holmes, A revised evolutionary history of Hepatitis B virus (HBV). , Journal of Molecular Evolution , 54, 2002, p807 - 814
Mario A. Fares, Andrés Moya, Cristina Escarmís Eric Baranowski, Esteban Domingo and Eladio Barrio, Evidence for positive selection in the capsid protein-coding region of the foot-and-mouth disease virus (FMDV) subjected to experimental passage regimens, Molecular Biology and Evolution, 18, 2001, p10 - 21
Ignacio Marín; Mario A. Fares; Fernando González-Candelas; Eladio Barrio and Andrés Moya, Detecting changes in the functional constraints of paralogous genes, Journal of Molecular Evolution , 52, 2000, p17 - 28
Mario A. Fares, Eladio Barrio, Nelsson Becerra, Cristina Escarmís, Esteban Domingo and Andrés Moya, The foot-and-mouth disease virus as a model in experimental phylogenetics, International Microbiology, 1, 1998, p311 - 318
More Publications and Other Research Outputs >>>
 

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Last Updated:01-SEP-2014