Author ORCID Identifier


Date of Graduation


Document Type

Thesis (MS)

Program Affiliation

Biomedical Sciences

Degree Name

Masters of Science (MS)

Advisor/Committee Chair

Alemayehu Gorfe

Committee Member

Jeffrey Chang

Committee Member

Xiaodong Cheng

Committee Member

Vasanthi Jayaraman

Committee Member

Shuxing Zhang

Committee Member

Michael Zhu


The development of efficient tools for allosteric ligand binding site identification in potential drug targets is an important step for computational drug design. Ligand binding specificity analysis (LIBSA) is one of the protocols that utilize filtering algorithms to assess the propensity of a site on a target structure or structures to bind a ligand. However, LIBSA requires expert skills to be properly executed. Thus, a Web interface, LBPI (Ligand Binding Pocket Identification) has been developed using Django, a Python-based web framework. A Python Wrapper has also been developed to streamline pre-existing algorithms of LIBSA. The Wrapper helps in the preparation of files, execution of individual programs and generation of appropriate results. LBPI provides an ideal platform for making complex binding site identification protocols readily available for non-expert users to submit jobs and monitor the results. The goal of LBPI is to integrate available algorithms in a systematic way and make it easily available for both experts and non-experts.


LBPI, Web Interface, Computational Pipeline, Wrapper, LIBSA, Python, Django, Platform, Integrate, Availability



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