Developing interactive computer programs that simulate separations processes encountered in biochemistry and proteomics.
My name is Dr. Paul A. Craig and I am a Professor of Biochemistry and Bioinformatics at the Rochester Institute of Technology located in Rochester, New York. I am also the Department Head for the School of Chemistry and Materials Science in the College of Science at RIT.
My research involves developing interactive computer programs that simulate separations processes encountered in biochemistry and proteomics. To date we have developed simulations of ion exchange chromatography, one dimensional electrophoresis and two dimensional electrophoresis.
Moltimate is a tool from the BASIL project that can be used to compare 3D protein structures with a library of enzyme active sites, to predict whether the query structure (often a protein of unknown function) aligns with an enzyme of known function. Students use alignment results from Moltimate, in combination results from BLAST, Pfam, and Dali to predict functions for protein structures which are currently unannotated.
A team of four software engineering students at RIT (George Herde, Shannon McIntosh, Joshua Miller and Steven Teplica) completed their senior capstone project with Herbert Berntstein and Paul Craig. They created Moltimate, a web application that performs similar alignments to those that have been determined by ProMOL, which was also developed by students at RIT and Dowling College. The advantage of Moltimate is that it is a web application that can be used from any web browser.
BASIL is an acronym for Biochemistry Authentic Scientific Inquiry Lab. In the BASIL curriculum, our aim is to get students to transition from thinking like students to thinking like scientists. Students will analyze proteins with known structure but unknown function using computational analyses and wet-lab techniques. BASIL is designed for undergraduate biochemistry lab courses, but can be adapted to first year (or even high school) settings, as well as upper-level undergraduate or graduate coursework. It is targeted to students in biology, biochemistry, chemistry, or related majors. Further details about the BASIL biochemistry consortium can be found on the BASIL blog.
The curriculum is flexible and can be adapted to match the available facilities, the strengths of the instructor and the learning goals of a course and institution. These lessons are often used as part of upper-level laboratory coursework with at least one semester of biochemistry as a pre-requisite or co-requisite. The lab has been designed for classes ranging from 10-24 students (working in teams of two or three) per lab section.
Electro2D-Tandem MS is a simulation of two-dimensional electrophoresis (2DE) - tandem mass spectroscopy (tandem MS), a tool that is used to separate and identify proteins from complex mixtures. This program was created entirely by students from programs in chemistry and computer science at RIT and is written in Java. Three notable contributors are Janine Garnham, who wrote the initial code for protein separation by 2DE; Jill Zapoticznyj, who started from Janine's code to build the graphical user interface for the simulation, and Amanda Fisher, who updated the code to make it work on any operating system and then integrated the protein separation by 2DE with Tandem Mass Spectrometry, which performs protein sequencing that can be used for protein identification and bioinformatics searching.
All scientists need to learn computer scripting/coding skills to remain competitive. Most undergraduate programs do not include coding skills in coursework for biology or chemistry majors, yet we hear of a need for basic coding skills from graduates who enter industry and those who go on to graduate school. During the spring of 2021, I worked with Jessica Nash at the Molecular Sciences Software Institute (MolSSI) to develop a Python scripting workshop. My goal is to introduce scientists from all professional levels (undergraduate, graduate, post-doc, faculty member, industrial scientist) to the use of Python programming in Jupyter notebooks, thereby enabling them to start taking advantage of computational power and flexibility that far exceeds data analysis and display tools found in Microsoft Excel and Apple Numbers.
The workshop includes the following modules: Introduction, File Parsing, Processing Multiple Files and Writing Files, Working with Pandas, Linear Regression, Creating Plots in Jupyter Notebooks, and Nonlinear Regression.