Nalin Goonesekere
Professor - Biochemistry, Bioinformatics, Structural Biology
283 McCollum Science Hall
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Nalin Goonesekere
Professor - Biochemistry, Bioinformatics, Structural Biology
B.Sc. University of Colombo, Sri Lanka.
Ph.D. Princeton University.
Research Fellow - National Cancer Institute, Bethesda
The dawn of the 21st century can be characterized as the golden era in biochemistry, as much as the dawn of the 20th century was the golden era for physics. In 2003, we witnessed the complete sequencing of human DNA (genome) and we now have access to many mammalian, plant and microbial genomes. An important scientific challenge for the 21st century is interpreting the vast amounts of DNA sequence data that has become available. Understanding the DNA sequence information is critical in converting this information into tangible benefits to humankind - whether it be new protein targets for drugs, or perhaps more efficient enzymes for use in biotechnology. Research conducted in our laboratory focuses on the broad problem of interpreting DNA sequence data to obtain biologically meaningful information.
Early detection of Pancreatic Cancer – Identification of Biomarkers
Pancreatic cancer (PC) is a highly lethal cancer, with a 5-year survival rate of less than 5%. Thus, even though the incidence of breast cancer is estimated to be 5 times greater than PC, the annual death rates of PC and breast cancer are actually comparable. In nearly 95% of PC patients there is neither an associated family history nor specific symptoms at the early stages of PC when the disease can be effectively treated by surgical resection. PC can also display a high biological aggressiveness, and a high resistance to current therapeutics. There are two fundamental ways by which the high mortality of PC can be reduced. One is to develop biomarkers for the early detection of PC and the second is to identify new targets in PC, against whom therapeutics can be developed. Research in our laboratory focuses on contributing to both these efforts, through a combination of computation analysis and laboratory experimentation.
Identification of Disease-causing (virulence) Genes in the Corn Pathogen Fusarium verticillioides
Members of the genus Fusarium are economically important plant pathogens, that cause billions of dollars of damage each year worldwide. Fusarium verticillioides is known to cause destructive diseases in a wide variety of agriculturally important crops including corn, wheat and potato. In corn, it causes the disease knows as stalk rots. In this project, we focus on identifying and characterizing proteins associated with infectivity or virulence. An analysis of the newly-sequenced genome of F. verticillioides has revealed candidate virulence genes. We are now employing recombinant DNA techniques to evaluate these assignments in the laboratory.
Predicting the Function of Proteins
Another area of interest is in using bioinformatics tools developed by us, and others, to predict the function of proteins that are, as yet, not annotated, using just the information from the protein sequence. We have been focusing our attention on a set of protein sequences from the well-known database Pfam. These sequences belong to Pfam families known as ‘Domains of Unknown Function’ (DUF). Since Pfam is used extensively in annotating protein sequence data from genomes such as the human genome, determining the functions of DUFs will directly assist current efforts to decode sequences from genomes.
1. Schutt, C.E., Myslik, J.C., Rozycki, M.D., Goonesekere, N.C.W. and Lindberg, U. (1993) The Structure of profilin:actin at 2.55 angstrom resolution Nature 365 810.
2. Zeppezauer, E. S. C., Goonesekere, N.C.W., Rozycki, M.D., Myslik, J.C., Dauter, Z., Lindberg, U. and Schutt, C.E. (1994) The structure of profilin at 2.0 angstrom resolution J Mol Biol 240 459.
3. Goonesekere, N.C.W., Gunasekera, M.B. and Fernandopulle, N. (1999) Use of DNA typing For Criminal Casework in Sri Lanka. Proceedings of the 10th International Symposium on Human Identification Promega Corporation,Wisconsin, U.S.A.
4. Tiedemann, R., Kurt, F., Goonesekere, N.C.W., Gunasekera, M.B., and Ratnasooriya, W.D. (1999) A simulation study on the viability of Sri Lankan elephant populations. Folia Zoologica 48 (supp. 1): 95-104.
5. Fernandopulle, N., Gunasekera, M.B. and Goonesekere, N.C.W. (2002) Population genetics of eight STR loci from Sri Lanka. Forensic Science International 126 1 93.
6. Vandebona, H., Goonesekere, N.C.W., Ratnasooriya, W.D., Alahakoon, J. and Gunasekera, M.B. (2002) The establishment of paternity of elephants born in captivity in Pinnawela Elephant Orphanage, Sri Lanka, by DNA fingerprinting. International Zoo Yearbook 39.
7. Vandebona, H., Goonesekere, N.C.W., Tiedemann, R., Ratnasooriya, W.D., and Gunasekera, M.B. (2002) Sequence variation at two mitochondrial genes in the Asian elephant (Elephas maximus) population in Sri Lanka. Mam Biol 67 4 193.
8. Mapatuna, Y., Gunasekera, M.B., Ratnasooriya W.D., Goonesekere, N.C.W. & Bates P.J.J. (2002) Unravelling the taxonomic status of the Genus Cynopterus (Chiroptera:Pteropodidae) in Sri Lanka by multivariate morphometrics and mitochondrial DNA sequence analysis Mam Biol67: 321.
10. Goonesekere, N.C.W. and Lee B. (2004) Frequency of gaps observed in a structurally aligned protein pair database suggest a simple gap penalty function Nucleic Acids Research 32 9 2838.
11. De Silva, A.P., de Silva, S.S.K., Goonesekere, N.C.W. (2007) Gunaratne, H.Q.N, Lynch, P.L.M, Nesbitt, K.R., Patuwathavithana, S.T., Ramyalal, N.L.D.S. Analog Parallel Processing of Molecular Sensory Information. J Am Chem Soc 129: 3050.
12. Goonesekere, N.C.W. and Lee B. (2008) Context-specific substitution matrices and their use in the detection of protein homologs. Proteins: Struct Fun and Bioinformatics 71: 910.
13. Goonesekere, N.C.W., Beaudry, S. and Tasovski, I. (2009) Towards establishing the molecular function of Pfam domain DUF294 by sequence analysis and homology modeling On JBioinformatics. 11 (1): 125
14. Goonesekere, N.C.W. (2009) Evaluating the efficacy of a structure-derived amino acid substitution matrix in detecting protein homologs by BLAST and PSI-BLAST. Adv Appl in Bioinformatics and Chemistry, 2009: 2 71.
15. Goonesekere, N.C.W., Shipely, K. and O’Connor, K. (2010) The challenge of annotating protein sequences: The tale of eight domains of unknown function in Pfam. Comp. Biol. Chem., 2010: 34 210.
16. Shen, R., Goonesekere, N.C.W. and Guda, C. (2012) Mining functional subgraphs from cancer protein-protein interaction networks, BMC Systems Biology 2012, 6(Supp 3):S2.
17. Goonesekere, N.C.W., Wang, X., *Ludwig, L. and Guda, C. (2014) A Meta Analysis of Pancreatic Microarray Datasets Yields New Targets as Cancer Genes and Biomarkers, PLoS ONE 9(4): e93046. doi:10.1371/journal.pone.0093046.
18. Smith, A., Poole, L., Dhanwada, K. and Goonesekere, N.C.W. (2016) "Identification of Candidate Biomarkers and Cancer Genes AHNAK2 and EPPK1 in Pancreatic Cancer" Brit. J. Med. Med. Rep. 18(8): 1-8.
19. Goonesekere, N.C.W., *Andersen, W., *Smith A. and Wang X. (2018) “Identification of genes highly downregulated in pancreatic cancer through a meta-analysis of microarray datasets: implications for discovery of novel tumor-suppressor genes and therapeutic targets”. J. Cancer. Res. Clin. Oncol. 144(2):309-320.
20. Bricker B., Goonesekere, N.C.W., Bayles, D., Olsen, S. and Vrentas, C. (2020) “A Genome Sequence Analysis of the RB51 Strain of Brucella abortus in the Context of Its Vaccine Properties”. Genes, Genomes and Genetics 10(4):1175-1181.
21. *Heinzman, Z., *Schmidt, C., Sliwinski, M.K. and Goonesekere, N.C.W. (2021) “The Case for GNMT as a Biomarker and Therapeutic Target in Pancreatic Cancer”. Pharmaceuticals 14, 209.