In the Classroom edited by
Molecular Modeling Exercises and Experiments
Ronald Starkey University of Wisconsin–Green Bay Green Bay, WI 54311-7001
Exploring the Structure–Function Relationship of Macromolecules at the Undergraduate Level Belinda Pastrana-Rios Department of Chemistry, University of Puerto Rico–Mayagüez Campus, Mayagüez, Puerto Rico 00681-9019;
[email protected] Traditionally, classroom learning is a relatively passive experience for students who receive input from instructors but are rarely given the opportunity to fulfill their potential as active learners. The advanced undergraduate laboratory described here is the first course in Puerto Rico to successfully bridge the gap between passive and active learning in the classroom by introducing a number of innovative techniques. Recent advances in genome sequencing efforts require students to address biological problems by understanding the interrelationships between sequence, structure, and function. This is best achieved with the aid of computational methods in structural biology (1, 2). The biochemistry laboratory course was revised, introducing undergraduate students to structure–sequencing technology, while giving the students a hands-on, active-learning experience. The course demonstrates how this approach can provide incremental information for understanding protein function. The interdisciplinary approach gives the undergraduate students the necessary knowledge, expertise, and problem-solving skills to become effective scientists in the field of biochemistry and the growing fields of structural biology and functional genomics. The Molecular Modeling and Visualization Center in the Department of Chemistry at the University of Puerto Rico–Mayagüez Campus is equipped with eight Silicon
Graphics model 02 workstations, one Octane, four crystal eyes, and Internet 2. The Center is well equipped for small groups of students and for 3D-visualization activities (using liquid crystal glasses), which are key elements of the learning experience (Figure 1). Accelrys Insight II, Builder, Biopolymer, Homology, Discover, CHARMm, GCG modules, and BLAST (from NCBI) software programs are available to the students. Accelrys programs are used for molecular modeling and energy minimization routines using Silicon Graphics Workstations. Educational Methods The course is offered to biology, biotechnology, chemistry, and microbiology undergraduate majors. Students learn the value of computational resources in a basic research environment by performing a variety of tasks, such as using the Internet for remote database searches, and performing basic sequence analysis, multiple sequence alignment, and the visualization of the macromolecule. This laboratory course is not limited to the study of proteins and peptides, but also includes DNA, RNA, and the protein or peptide complexes thereof. In addition the course involves an introduction to protein crystallography, Fourier transform infrared (FT-IR) spectroscopy of biological molecules, and nuclear magnetic
Figure 1. (Left) The laboratory consists of nine fully-networked workstations: eight model O2, one Octane (server), and Insight II suite from Accelrys. (Right) An undergraduate student visualizing a DNA-peptide complex while running a minimization routine using stereographic view.
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student
molecular modeling programs
database search
group presentation
portfolio
biochemistry biophysics biology bioinformatics problem-solving, written, and oral skills; independent learning; student development
graduate school
Figure 2. Schematic representation of different facets of the biochemistry laboratory course, QUIM 5074.
resonance (NMR). A summary of the course activities is shown in Figure 2. Description of the Biochemistry Laboratory Course This course is structured such that the students work in pairs during the first half of the course. The purpose is to encourage peer–peer learning processes during the students’ first exposure to the software. An initial project is assigned that has a low degree of difficulty but helps the students review their knowledge of basic protein chemistry and stimulates their creativity. This project involves the design of a peptide, taking into consideration the biochemical characteristics of the 20 amino acids. This spurs discussion among students regarding the hydrophobicity imparted throughout
the peptide or the ionic interactions students would like to observe within a peptide. The students are then asked to decide what types of structural motifs or overall secondary structure this peptide should have. This process is carried out in a traditional manner. A brief description of the operating system and Insight II software is followed by a multimedia presentation of the Biopolymer and Builder programs. A round of questions and answers is carried out, followed by a hands-on approach to visualizing students’ customized peptides. Students who participated in this activity were fully engaged in all aspects of the chemistry involved in a peptide; for example, they were looking for hydrogen bond interactions, π–π interactions among stacked aromatic residues (tyrosine, phenylalanine, tryptophan), or ionic interactions among aspartates and lysines. The students’ first exposure reveals how they applied their knowledge to a visual three-dimensional image and thus had an active role in their learning experience. A Web page (3) was created to provide students instructional and hands-on information. In this course, the instructor is a facilitator and the students formulate their own questions. By integrating biology, chemistry, and technology, the undergraduate students venture into the world of structural biology. Students visualize and, thus, better understand the kinds of interactions that govern protein structures. Students relate those governing principles to material that is typically presented in a more passive manner in a traditional lecture class. However, in this setting the students apply knowledge and develop critical thinking. This laboratory uses a hands-on approach focused primarily on basic sequence analysis and the use of the Internet for searching databases, such as GenBank (4), EMBL (5), DDBJ (6), and PDB (7) while using Genetic Computer Group (GCG), Basic local Alignment Search Tool (BLAST), and pairwise and multiple sequence alignment (Psi and Phi Blast) (8). This database searching is combined with an introduction to X-ray crystallography and how data is reported in protein database format (PDB). Students learn how to download X-ray or NMR coordinates of proteins. Molecular modeling, homology, and energy minimization routines are used to study proteins or
Figure 3. Exploring hemagglutinin (HA) as a virulent factor. This project was carried out by Edgardo Sanabria and Yasmine ValentínVega (microbiology majors) during their junior and senior year, respectively. They studied the proposed mechanism of binding of HA to cause fusion between the viral membrane and the host membrane (red blood cell).
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macromolecules of interest (9–13). The students also get hands-on experience in the areas of molecular spectroscopy and NMR spectroscopy.
Protein Structure and Homology Weak chemical interactions that govern protein interactions, such as hydrogen bonding, ionic, and hydrophobic interactions, are examined by looking at close contacts and binding pockets (Figure 3). In this way students apply what they learned in class (biochemistry course). The students learn to measure dihedral angles and distances and create templates by which searches on databases can be made. They learn to distinguish conserved amino acid sequences, as well as point mutations that define specificity and affinity. In this manner the students learn to evaluate enzymes that catalyze the same reaction and rationalize differences in the kinetics based on the proposed mechanisms. The students are then required to write about their findings and explain their results based on the models generated. They use those results, along with other projects done throughout the semester, to create their work portfolios. Each portfolio records the students’ individual development throughout the semester. Examples of the models generated by past students and excerpts from portfolios can be observed on the University Web page (3). Student Presentations Students end this project with a 25-minute presentation to the class and invited guests. They summarize relevant
information about a protein followed by a discussion of their findings using the Biopolymer or Homology programs.
Nucleic Acid Polymers This individual project is straightforward and, after working with proteins, is relatively simple. The students are asked to build several different types of DNA and RNA polymers and measure the width, overall length, and groove size and then compare them. They are also taught how to search for and download a particular nucleic acid polymer using the nucleotide databank (14). Energy Minimization Activity This activity, which is included if time allows, is an introduction to the potential energy of a molecule and how it is related to structure. It is a hands-on activity. Students use the peptide they modeled in their first project and minimize its energy using Steepest Descent. Final Project This individual project is the students’ most creative and challenging activity. The students choose a macromolecule and search appropriate references, formulate questions, and use the available resources. The project’s degree of depth is solely dependent on the student’s capacity to work independently (Figure 4). Short discussions with each student are carried out to ensure that he or she remains focused and to share knowledge and experience on an as-needed basis only.
Figure 4. TBP or the TATA-box Binding protein. This project was carried out by Samuel Henández (chemistry major) during his junior year. He studied docking of the TBP with DNA (TATA sequence). The residues that reportedly are interacting within the minor groove are Lys and Arg by H-bonding and by electrostatic interactions with the phosphate backbone of the DNA, Leu participates in hydrophobic interactions, and Phe interact by π-stacking.
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At the end of the semester, the student turns in a portfolio that includes a description of each project completed, as well as an analysis of the results, hardcopies of selected images, copies of referenced articles, an evaluation of themselves for each project, an evaluation of the overall course, and a brief one page autobiography. Outcome of This Learning Experience Since 1997, the spring course, QUIM 5074, has been offered five times to undergraduate students (juniors and seniors) using SGI workstations and Accelrys software. The students have diverse backgrounds (microbiology, biology, biotechnology, and chemistry). The course curriculum has required that 80% of the time be devoted to the use of molecular modeling software, database search, and student oral presentations. A nontraditional approach to student evaluation (portfolios) has been used. The portfolios are composed of projects carried out in the laboratory and reflect both the increasing degree of difficulty of each project and the development of each student as the semester progressed. Conclusion A course dedicated to bioinformatics, molecular modeling, and introduction to structural genomics is feasible at the undergraduate level as demonstrated in this article. The laboratory activities have a significant long-term impact on maintaining students’ interest in biology, chemistry, biochemistry, biophysics, and bioinformatics. In the future, the students will explore other databases for protein structure classification such as CATH (15, 16). Acknowledgments The author would like to express her appreciation to the Industrial Biotechnology program, the University of Puerto Rico for the financial support. Also, the NIH-COBRE grant I-P20-RR1 6439-01 for the funding that allowed the purchase of the new Insight II software from Accelrys, and the
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Howard Hughes Foundation for present funding for the continuation of the teaching licenses. Literature Cited 1. Cox, J. R. J. Chem. Educ. 2000, 77, 1424–1428. 2. Canning, D. R.; Cox, J. R. Chem. Educ. Res. Prac. Eur. 2001, 2, 109–122. 3. Course Web Page. http://www.uprm.edu/wquim/Q5074/ default.htm (accessed Mar 2004). 4. GenBank Database. http://www.ncbi.nlm.nih.gov/ (accessed Mar 2004). 5. EMBL Database. http://www.ebi.ac.uk/embl/ (accessed Mar 2004). 6. DDBJ Database. http://www.ddbj.nig.ac.jp/ (accessed Mar 2004). 7. Protein Data Bank. http://www.rcsb.org/pdb/ (accessed Mar 2004). 8. Barton, G. J. Protein Sequence Alignment and Database Scanning. In Protein Structure Prediction. A Practical Approach; Sternberg, M. J. E., Ed.; Oxford University Press: Oxford, U.K., 1996; pp 1–63. 9. Jone, D. T. Curr. Opin. Struc. Bio. 1997, 7, 377–387. 10. Sànchez, R.; Sali, A. Curr. Opin. Struc. Bio. 1997, 7, 206– 214. 11. Sali, A.; Potterton, L.; Yuan, F.; van Vlijmen, H.; Karplus, M. Prot. Struct. Funct. Genet. 1995, 23, 318–326. 12. Goodman, J. A. Chemical Applications of Molecular Modeling; Royal Society of Chemistry: Cambridge U.K., 1998. 13. Leach, A. R. Molecular Modeling Principles and Applications; Longmans: Essex, U.K., 1996. 14. Nucleic Acid Data Base. http://ndbserver.rutgers.edu/NDB (accessed Mar 2004). 15. Pearl, F. M. G.; Martin, N.; Bray, J. E.; Buchan, D. W. A.; Harrison, A. P.; Lee, D.; Reeves, G. A.; Shepherd, A. J.; Sillitoe, I.; Todd, A. E.; Thornton, J. M.; Orengo, C. A. Nucl. Acids Res. 2001, 29, 223–227. 16. Orengo, C. A.; Pearl, F. M. G.; Bray, J. E.; Todd, A. E.; Martin, A. C.; Lo Conte, L.; Thornton, J. M. Nucl. Acids Res. 1999, 27, 275–279.
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