Dr Nick Furnham PhD
- Nick Furnham's Contacts
- Keppel Street
- WC1E 7HT
- T: 2953
Nick Furnham's Background
Nicholas joined the School as an independent investigator supported by a MRC Strategic Skill Fellowship in Methodology Research.
His research is focused on developing new computational methods to predict the function of proteins in infectious disease related genomes by:
- bringing together relationships between protein sequences and their molecular structures, putting them into an evolutionary context as well as establishing measures of similarity between the functions of these proteins.
- using the data captured to develop a new method to predict the function of proteins by defining rules bases on the systematic analysis of cases where changes in function occur between related proteins and determining the features of that change.
The methods will be applied to specific problems in factious disease research, for example addressing the function of key enzymes involved in new drug treatments for Chagas disease with the aim of providing a better understanding of drug-resistance mechanisms. Another example of application is to add value to the results of high-throughput drug screens against schistosomes.
This furthers his post-doctoral research in the group of Prof. Dame Janet Thornton at the European Bioinformatics Institute (an outstation of the European Molecular Biology Laboratory), his PhD under the supervision of Prof. Sir Tom Blundell in the Biochemistry Department at Cambridge University and his original undergraduate training at King’s College London in Biological Science where he specialised in parasitology.
Nick Furnham's Affiliation
Nick Furnham's Research
The recent revolution in high throughput DNA sequencing, started by the Human Genome Project, has led to large collections of data on a diverse set of organisms. This notably includes the parasitic, bacterial and viral agents that cause infectious diseases, as well as the organisms that are responsible for disease transmission. The emergence of this data offers new and exciting opportunities to understand these disease-causing agents and to develop novel therapeutics.
An outstanding and challenging problem is to understand the functions of the proteins encoded by these genomes. Time and resources limit the number whose function can be experimentally determined; therefore methods for predicting function are of paramount importance. Moreover, new methods are required when applied to infectious diseases due to the complex relationships between the host organism and the disease causing agent. The best method for achieving this is using a multidisciplinary approach interfacing biology, chemistry and computer science techniques.
My research is focused on developing new computational methods to predict the function of protein in infectious disease related genomes and to apply them to specific problems in infectious disease research.
- Drug discovery and development
- Drug resistance
- Molecular biology
Disease and Health Conditions
- African trypanosomiasis
- Chagas Disease
- Infectious disease
- 3D Structure
- Antiprotozoal Drug Discovery
- Drug Screening
- Infectious Diseases
- Information Science
- Interdisciplinary research
- Neglected Diseases
- R statistical language
- Trypansoma cruzi
- host virus interactions
- molecualr biology
- research and analysis
- structural biology
New functional families (FunFams) in CATH to improve the mapping of conserved functional sites to 3D structures.
Sillitoe, I. ; Cuff, A.L. ; Dessailly, B.H. ; Dawson, N.L. ; Furnham, N. ; Lee, D. ; Lees, J.G. ; Lewis, T.E. ; Studer, R.A. ; Rentzsch, R. ; Yeats, C. ; Thornton, J.M. ; Orengo, C.A. ;
Nucleic Acids Res, 2013; 41(Database issue):D490-8
FunTree: a resource for exploring the functional evolution of structurally defined enzyme superfamilies.
Furnham, N. ; Sillitoe, I. ; Holliday, G.L. ; Cuff, A.L. ; Rahman, S.A. ; Laskowski, R.A. ; Orengo, C.A. ; Thornton, J.M. ;
Nucleic Acids Res, 2012; 40(Database issue):D776-82
Exploring the evolution of novel enzyme functions within structurally defined protein superfamilies.
Furnham, N. ; Sillitoe, I. ; Holliday, G.L. ; Cuff, A.L. ; Laskowski, R.A. ; Orengo, C.A. ; Thornton, J.M. ;
PLoS Comput Biol, 2012; 8(3):e1002403
Current challenges in genome annotation through structural biology and bioinformatics.
Furnham, N. ; de Beer, T.A. ; Thornton, J.M. ;
Curr Opin Struct Biol, 2012; 22(5):594-601
Missing in action: enzyme functional annotations in biological databases.
Furnham, N. ; Garavelli, J.S. ; Apweiler, R. ; Thornton, J.M. ;
Nat Chem Biol, 2009; 5(8):521-5
Assembly and channel opening in a bacterial drug efflux machine.
Bavro, V.N. ; Pietras, Z. ; Furnham, N. ; Pérez-Cano, L. ; Fernández-Recio, J. ; Pei, X.Y. ; Misra, R. ; Luisi, B. ;
Mol Cell, 2008; 30(1):114-21
Is one solution good enough?
Furnham, N. ; Blundell, T.L. ; DePristo, M.A. ; Terwilliger, T.C. ;
Nat Struct Mol Biol, 2006; 13(3):184-5; discussion 185
Knowledge-based real-space explorations for low-resolution structure determination.
Furnham, N. ; Doré, A.S. ; Chirgadze, D.Y. ; de Bakker, P.I. ; Depristo, M.A. ; Blundell, T.L. ;
Structure, 2006; 14(8):1313-20
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