Friday, November 11, 2016

Sagar Maheshwari named a regional finalist in the national Siemens Competition in Math, Science & Technology

Sagar Maheshwari 

Sagar Maheshwari has been named a regional finalist in the national Siemens Competition in Math, Science & Technology and his project has been named one of the top 30 individual high school research projects in the nation. 

Sagar is now preparing to present his research to a panel of esteemed judges at the Massachusetts Institute of Technology, vying for an all-expense paid trip to the final competition in Washington DC where $500,000 in college scholarships will be awarded, including two top prizes of $100,000.

The Siemens Competition, launched in 1999 by the Siemens Foundation, was established to increase access to higher education for students who are gifted in STEM and is based on the culture of innovation, research and educational support that is the hallmark of Siemens. This competition, administered by Discovery Education, seeks to recognize and hopefully build a strong pipeline for the nation’s most promising scientists, engineers and mathematicians.

Sagar is a senior at UHS and his interests in STEM started at an early age and was furthered along by his uncle.  Always interested in solving problems and driven by curiosity, Sagar demonstrated extraordinary drive and determination when he sought out a Harvard professor, to help him with his research.

Dr. Gil Alterovitz  is at the Harvard/MIT Health Sciences and Technology Division Children's Hospital Informatics Program (CHIP). He is also affiliated with the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT).  

Sagar (cold) contacted the professor, submitted his proposal, and earned a spot as a summer intern where he further developed his project titled "SiteKey: A Novel Binding Site Predictor for Ordered Proteins Interacting with Intrinsically Disordered Proteins." 

The project executive summary is below.  In short, the project crosses the disciplines of computer science and biology, (Bioinformatics) creating artificial intelligence to predict biological functions. This program could be useful in better understanding where cancer starts based on disordered protein structures.

Sagar is an extraordinary and exceptional Unionville High School student.  Sagar is thankful for the support of his family and his school.  He also mentioned the inspiration and support he received from alums Shashwat Kishore and Meghan Shea.


SiteKey: A Novel Binding Site Predictor for Ordered Proteins Interacting with Intrinsically Disordered Proteins 

EXECUTIVE SUMMARY Proteins are often considered the workhorses of human cells; they make up nearly all structures in the human body and take part in most biological processes. All proteins are composed of hundreds to thousands of individual units called amino acids, which form what is known as the protein sequence. 

For decades, scientists believed in the sequence-to-structure-to- function paradigm: the idea that the protein sequence determines a unique fixed protein structure, which determines the function and interactions of the protein. In the past decade and half, scientists discovered exceptions to this paradigm. There are proteins called intrinsically disordered proteins (IDPs) that have flexible structures, allowing them to bind to many other proteins. Unsurprisingly, IDPs have been associated with numerous diseases, including cancer. 

The goal of this project is to build an algorithm that can effectively identify and characterize binding sites on proteins interacting with IDPs, a previously unaccomplished task. To do so, an artificial intelligence method called machine learning is implemented in which the algorithm is able to autonomously train itself to perform the given task. 

The developed algorithm—SiteKey—is able to predict these binding sites with 88.4% accuracy, making it both reliable and biologically useful. Consequently, SiteKey holds great promise in advancing rational drug design by identifying binding sites that can be targeted to prevent major diseases, including cancer.