Research projects

The following research projects are of my interest and I am currently working or involved with.

• Project title: Identification, Molecular and Proteomic Characterisation of food allergens, further profiling for allergomic,  genomic and bioinformatic analysis.

Background: About 8% of the population is subjected to food allergens which involved only a small group of protein families. More than 90 percent of acute systemic reactions to food are caused by the eight foods: in children are from eggs, milk, soy, wheat, or peanuts, and in adults are from crustaceans, tree nuts, peanuts, or fish.
Aim: The aim of the study is the molecular and proteomic characterization of food allergens, further profiling for allergomic,  genomic and bioinformatic analysis.

Methods: Optimisation of new protocols and novel methodologies for designing proteomic experiments, (ii) proteomic sample preparation including protein extraction, purification and modification using digestion and other bio-chemical processes, (iii) mass spectrometric data acquisition, (iv) data analysis and (v) generation of results- three-dimensional modeling using best-practice methods and pipelines. Functional characterization of yet uncharacterized proteins would be performed.  

Possible outcome: 

• Project title: Chemical profiling and identification of the total therapeutic constituents in medicinally used natural products based on High performance liquid chromatography coupled with mass spectroscopy.

Background: Natural products largely from medicinal plants are mostly the source of modern day pharmaceutical lead compounds. Most lead compounds work by binding to various sites on proteins, and little is known about the structures of the proteins. Therefore, medicinally used plants are extensively searched for lead chemopreventive drug discovery. However, broad chemical profiling of therapeutic constituents from commonly used medicinal plants is not predominantly known.
Aim and Methods: This study attempts to broadly profile the bio-active therapeutic constituents from medicinal plants widely used in traditional and complementary medicine using High performance liquid chromatography coupled with mass spectroscopy (HPLC/MS), the most widely applied technique to the quality control and chemical profiling.

Possible outcome: Crude data from HPLC/MS profiles of medicinal plant extracts would be scrutinized using databases of earlier reported studies, multidimensional structure databases and network pharmacology as well as checked for inter-genus variations of constituents by studying pharmacophylogeny. The outcome of the study might facilitate further bioactivity guided identification, isolation and repurposing of therapeutic agents for treatment, explain the therapeutic potential, synergism, antagonism and protein binding of bio-constituents. Furthermore, the results will open up the possibility of discovery of new drugs applying molecular docking, molecular dynamic simulation, machine learning and artificial-intelligence (AI) programs more quickly and cheaply.

• Project title: Bioactivity guided chemical and biological evaluation of medicinal plants for lead molecule identification and therapeutic development.

Background: A lead compound in drug discovery is a chemical compound that has pharmacological or biological activity likely to be therapeutically useful. Therefore, medicinally used plants that are reputed for specific diseases are extensively searched for drug target in drug discovery. However, broad chemical and biological profiling of therapeutic constituents from commonly used medicinal plants is not predominantly known.
Aim and Methods: This study attempts to broadly profile the bio-active therapeutic constituents from medicinal plants widely used in traditional and complementary medicine, aiming to answer these key questions using standard chromatographic techniques as well as evaluate their activities using suitable in vivo model organisms of human health and disease or in vitro simulated environment or in silico computational modelling and/or molecular modelling as the main approaches. Ultimately, the research aims to elucidate biological mechanisms unique in the healing diseases, and guide the design of new therapeutic components and tools.

Possible outcome: Crude data from HPLC/MS profiles of medicinal plant extracts would be scrutinized using databases of earlier reported studies, multidimensional structure databases and network pharmacology as well as checked for inter-genus variations of constituents by studying pharmacophylogeny. The outcome of the study might facilitate further bioactivity guided identification, isolation and repurposing of therapeutic agents for treatment, explain the therapeutic potential, synergism, antagonism and protein binding of bio-constituents. Furthermore, the results will open up the possibility of discovery of new drugs applying molecular docking, molecular dynamic simulation, machine learning and artificial-intelligence (AI) programs more quickly and cheaply.