Abstract

Molecular docking is a computational technique often used in drug design due to its ability to predict ligand binding potential, conformation, and location for a given drug target. Docking as a screening tool also comes at a greatly reduced cost compared to wet bench work. Despite its usefulness, molecular docking is often inaccessible to novice users, as to perform molecular docking, most programs require at least a basic knowledge of command line and computer programming for both installation and utilization. Additionally, tutorials for the most popular programs tend to be inflexible, instructing how to bind predetermined molecules to a specified receptor and requiring the use of other programs and tools to download and prepare structures outside of the docking software. To increase access to molecular docking, basil_dock utilizes a series of easy-to-use Jupyter notebooks that do not assume user familiarity with molecular docking procedures, scripting, or command line usage. The series includes three notebooks that were created to reflect different steps in the molecular docking process: (1) the preparation of ligand and protein files prior to docking, (2) the docking of ligands to a protein receptor, and (3) analysis of docking scores to determine how differences in ligands can affect protein-ligand binding. The notebooks encourage flexibility and customization in exploring docking procedures and systems, as well as teaching users the basis behind molecular docking without having to leave the environment to obtain information and materials from other applications. In addition to the series of Jupyter notebooks, a graphical user interface for basil_dock has been created using Streamlit for ease of access. Separated into eight distinct pages, the Streamlit application translates the Jupyter notebooks into a webpage that can be installed and accessed locally or through the Streamlit Community Cloud. For all versions of basil_dock, accessibility and customizability remain at the forefront of program, aiming to provide the means to understand and perform molecular docking to all who wish to do so.

Library of Congress Subject Headings

Molecules--Models; Drugs--Computer-aided design; Drugs--Design; Proteins--Structure--Computer simulation; Ligands (Biochemistry)

Publication Date

12-4-2025

Document Type

Thesis

Student Type

Graduate

Degree Name

Bioinformatics (MS)

Department, Program, or Center

Thomas H. Gosnell School of Life Sciences

College

College of Science

Advisor

Paul Craig

Advisor/Committee Member

Gregory Babbitt

Advisor/Committee Member

Feng Cui

Campus

RIT – Main Campus

Plan Codes

BIOINFO-MS

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