Present studies include small projects emphasizing the use of bioinformatics to study protein function.  The common premise is the analysis of evolutionary similarities between proteins' structure and function. In additional to the scientific objective of finding relationships between proteins and gaining new insight into their biological roles, the projects aim to engage undergraduate students in intellectually challenging work. Through these activities, students find the opportunity to utilize their knowledge, understand molecular and cellular processes, enhance their analytical and communication skills, and participate in construction of biological models with hands-on experience.

My previous studies have been based on analysis of inter-species sequence relationships to decipher regions on proteins that have remained conserved during evolution.  These regions can be detected in the form of sequence homology, common motifs, structural domains, amino acid composition and propensity.  Proteins with such similarities are likely to share expression patterns, process functions, subcellular location or protein-protein interaction properties. I have exploited these concept in nucleic acid hybridization-based methods, including identifying and capturing target genes and detection and quantification of gene expression, among others (Ref).

I later extended the approach to study protein function by using structure modeling in combination with analysis of molecular binding and reaction chemistry.  With this approach, I apply sequence alignment to cluster short amino acid strings from analogous and homologous proteins to identify representative groups of amino acids that correspond to structural and functional determinants.  Such determinants are useful for inferring molecular interaction models; they can be exploited using homology modeling and virtual screening.  A recent applications of this work involve identification of functional sites that may occur on proteins in the absence of massive 3-dimensional structure similarity. This line of work has implications not only for inferring the catalytic activity of enzymes but also for understanding metabolic pathway evolution.   Another application of the approach involves probing structural determinants on the lepidopteron insect cadherin BTR1.  BTR1 mediates the lethal action of the Bacillus thuringiensis (Bt) Cry toxins. Along with the cadherin structure modules, the ectodomain of BTR1 contains regions with structural mimicry that may have evolutionary potential for other type of cell adhesion interactions (Ref).

1.  Protein sequence domains representing structural and functional determinants of enzymes’ active sites are descriptors of physico-chemical composition associated with their catalytic activity.  Therefore, it is hypothesized that proteins sharing such physico-chemical descriptors may have reaction chemistry relatedness even though they may fold into completely different 3-dimentional structures. To test this hypothesis, we integrate comparative modeling of protein three-dimensional structures with phylogenetic profiling to find catalytic site similarity between proteins working in alternative metabolic processes, particularly in microbial enzymes supporting anaplerotic pathways.

2.  Gene ontologies and conceptual clustering methods are useful in exploring gene-phenotype associations.  The approach considers that knowledge of the biological role of genes and proteins in one organism can often be transferred to other organisms.  Therefore, disconnected pieces of information that describe proteins’ molecular function, cellular location and biological process can be correlated using semantic-based bioinformatics tools to find plausible connections and develop and/or support hypotheses.  In one application of this approach, we reasoned a potential mechanistic relationship between folate transport and neural tube closure defects by using gene ontologies.  A broader implication of this line of work is to address the challenge in integration of information in gene/protein databases and translating to practical applications.  The integrative and translational aspect of information re-use can facilitate applications critical to biomedical research and healthcare industry, including personalized medical treatments, pharmaceutical drug repositioning, and medical informatics.

3.  Network theory is a powerful approach to study organization principles of cellular components. Network models can help us understand the nature of fundamental connectivity in biological pathways. It is hypothesized that stability, viability and agility of cells are dependent on the compatibility between interacting components.  The interactions occur in a flexible network topology involving power law.  Critical disruptions and/or incompatibilities may cause large-scale collapse, or loss of cellular viability.  The project aims to examine this conjecture conceptually and establish a model by using matrix analysis of a simple toy network. This model can be used to address the theoretical properties of a network consisting of a set of interactions between select proteins, which have ontological relationships in terms of biochemical function, process involvement and cellular location. The approach is centered on the definition of a network, which considers any collection of units potentially interacting as a system. Subtraction of certain components or addition of new components as well as perturbing changes in the existing components may alter the connectivity and accessibility in biological networks, resulting in variable outcomes.  Applications of this approach include understanding evolutionary principles of protein interactions and correlating physical and functional attributes of cellular components to biological processes, such as metabolic pathways.  Finding unique characteristics of component connectivity and gaining insight into emergence of cellular responses that are caused by disturbed component interactions, for instance, when microbial toxins exploit host molecules, can help us understand the basis of cellular organization in physiological and pathophysiological conditions.