Biophysics 204B: Methods in Macromolecular Structure
Winter 2023 Syllabus
Course Title: Methods in Macromolecular Structure
Course Format: 6 hours of lecture/group work per week in class, substantial group work outside of class hours
Location and Date/Hours: Monday, Tuesday, Wednesday - 9AM-11AM in Genentech Hall 227
Prerequisites: All incoming first year BP and CCB graduate students are required to enroll in this course.
Grading: Letter grade
Textbook: None. Lab protocols and course materials will be available in class or online
Instructors: John Gross, Aashish Manglik, James Fraser, Klim Verba
TAs:
- Radhika.Dalal@ucsf.edu
- Catherine.Kuhn@ucsf.edu
- Estelle.Ronayne@ucsf.edu
- Maxwell.Tucker@ucsf.edu
Lecturers/Facilitators:
James Fraser, Klim Verba, John Gross, Yifan Cheng, Aashish Manglik, Robert Stroud, Tom Goddard, Tanja Kortemme, Lisa Eshun-Wilson
Background:
Fluency in multiple biophysical methods is often critical for answering mechanistic questions. Traditionally, students are exposed to the fundamentals of multiple techniques through lectures that cover the theory prior to exposure, for some, in analysis or data collection during lab rotations. However, this structure means that only students that rotate in specific labs gain hands-on-exposure, which could limit adventurous experiments in future years. To train the next generation of biophysicists at UCSF, we have decided to alter this traditional structure by creating “Macromolecular Methods”, a class that places emphasis on playing with data. Based on our experiences designing the project-based class Physical Underpinnings of Biological Systems, aka PUBS!, which used deep sequencing to assay the function of a comprehensive set of point mutants to introduce principles of high-throughput interrogation of biological functions, we have designed Macromolecular Methods to be a team-based class where students develop their own analysis of real data that, in non-pandemic years, they have collected.
Course Description:
This is a team-based class where students work in small groups develop their own analysis of real data. Statistical aspects of rigor and reproducibility in structural biology will be emphasized throughout lectures, journal club presentations, and hands-on activities. The website for the 2017, 2018, 2019, 2020 editions are available online.
Ethics: This course is more than a training experience; it is an active research project whose results will be published to the broader scientific community. The community must be able to understand our work, replicate it, and have confidence in its findings. We must therefore ensure the integrity of the information we disseminate. To do so, it is essential that students perform and document their experiments and analyses as faithfully as possible. Mistakes and oversights are normal and to be expected, but they must not be ignored, concealed, or disguised. In addition, to merit authorship, students must contribute to three aspects of the project: intellectual conception or interpretation of the methods or data, technical execution of the experiments and/or analyses, and documentation or dissemination of the results. We fully expect that by actively participating in the course and working toward the course objectives, all students will merit authorship.
Respect: This course is built around an open research project performed in teams. Successful completion of the course objectives will require that students work together effectively, so please respect the time and effort of your classmates and instructors. Moreover, as part of the research process, we will consider and debate a variety of ideas and approaches; however, we must not allow our position on a particular idea or argument to compromise our respect for its author. We therefore expect course participants to give all instructors and students, regardless of academic or personal background, their complete professional respect; anything less will not be tolerated.
Accommodations for students with disabilities: The Graduate Division embraces all students, including students with documented disabilities. UCSF is committed to providing all students equal access to all of its programs, services, and activities. Student Disability Services (SDS) is the campus office that works with students who have disabilities to determine and coordinate reasonable accommodations. Students who have, or think they may have, a disability are invited to contact SDS (StudentDisability@ucsf.edu); or 415-476-6595) for a confidential discussion and to review the process for requesting accommodations in classroom and clinical settings. More information is available online at http://sds.ucsf.edu. Accommodations are never retroactive; therefore students are encouraged to register with Student Disability Services (http://sds.ucsf.edu/) as soon as they begin their programs. UCSF encourages students to engage in support seeking behavior via all of the resources available through Student Life, for consistent support and access to their programs.
Commitment to Diversity, Equity and Inclusion: The course instructors and teaching assistants value the contributions, ideas and perspective of all students. It is our intent that students from diverse backgrounds be well-served by this course, that students’ learning needs be addressed both in and out of class, and that the diversity that the students bring to this class be viewed as a resource, strength and benefit. It is our intent to present materials and activities that are respectful of diversity: gender identity, sexuality, disability, age, socioeconomic status, ethnicity, race, nationality, religion, and culture. However, we also acknowledge that many of the literature examples used in this course were authored in an environment that marginalized many groups. Integrating a diverse set of experiences is important for a more comprehensive understanding of science and we strive towards that goal. Although the instructors are committed to continuous improvement of our practices and our learning environment, we value input from students and your suggestions are encouraged and appreciated. Please let the course director or program leadership know ways to improve the effectiveness of the course for you personally, or for other students or student groups. (modeled after CCB and Brown University’s Diversity & Inclusion Syllabus Statements)
2022 schedule
TEAM ASSIGNMENTS
- 1: Radhika.Dalal@ucsf.edu
- Dani Rodea
- David Byun
- Haley Ogasawara
- Jeffrey Zheng
- Jonathan Borowsky
- Kelmen Low
- 2: Catherine.Kuhn@ucsf.edu
- Asa Kalish
- Catherine Shin
- Kamyar Yazdani
- Kevin Delgado-Cunningham
- Nicholas Freitas
- Yisheng Zheng
- 3: Estelle.Ronayne@ucsf.edu
- Angelika Arada
- Giovanni Aviles
- Harry Wu
- Henry Scott
- Isiac Orr
- Kevin Choi
- 4: Maxwell.Tucker@ucsf.edu
- Alex Long
- Colton Sanders
- Joseph Pepe
- Matthew Lyons
- Tracy Lou
- David Larwood
Jan 9-11 - Class intro
Monday January 9
- Welcome: structure of the class, zoom vs. in person norms, teams and work-together recommendations, auditing, relationship to Macro mini-quals, final writeups for this class (JF)
- FFT 101 (JF)
- Waves: amplitude/intensity, phase, frequency/wavelength (and in multiple dimensions: direction/index)
- How to sum sine waves together: weights/amplitude - can make any periodic function!
- Intuitively decomposing a complex function into sine waves (Fourier transform!)
- Resolution: start thinking about 3D objects like an X-ray or EM map, building intuition of more waves measured giving higher resolution
- Building up the MTZ (index = frequency and direction, amplitude/intensity, phase) and the concept of Nyquist frequency (why pixel size, changing values across pixels, and maximum resolution are related in EM)
- interactive website used in class for demo
- sin wave grapher
- another cool fourier thing
- The technique in a few minutes with reference to the importance of the Fourier Transform!
- JF Xray crystallography
- KV CryoEM
- JG NMR
Tuesday January 10
- Followups from first class:
- Why structural biology/Intro to Pchem (JG)
- BEAMLINE trip Feb 16th
- software check:
- coot
- phenix
- ccp4 (for dials, xia2)
- chimerax
- pymol
- EMAN2
- NMRBox signup
- TEAM 1 to negative stain with KV
Wednesday January 11
Jan 17-24 - CryoEM - Lectures Yifan Cheng, Tutorials Klim Verba
Monday January 16
MLK DAY - HOLIDAY
Tuesday January 17
Wednesday January 18
10-11: Intro to data processing by TAs after short intro by KV
- TEAM 2 to negative stain with KV?
- other teams work on data processing tutorial with TAs
Thursday January 19
- TEAM 3 to negative stain with KV (outside of class time)
Monday January 23
- TEAM 4 to negative stain with KV
- Cryo show and tell, teams 1 and 2
- other teams work on data processing when not at microscope
Tuesday January 24
- Cryo show and tell, teams 3 and 4
- other teams work on data processing when not at microscope
- rigor and reproducibility - lecture by Klim Verba
Reading on rigor and reproducibility in EM:
Jan 25-Feb 6 - NMR - Lectures John Gross
Wednesday January 25
Monday January 30
- process 15N HSQC and 13C HSQC data with teams (Allie Born and John Gross)
Tuesday January 31
Wednesday Feb 1
Monday Feb 6
Lecture 5 from John Gross, Measuring ns-ps dynamics in proteins
- process mNb6:RBD 15N and 13C HSQC spectra, overlay with mNb6. Cross-peak bookkeeping with teams (Allie Born and John Gross)
How to setup and process HSQCs on the 800 MHz spectrometer
Materials for TA Office Hours
Reading on rigor and reproducibility in NMR:
Feb 7-8 - Computational Approaches and Community Building in Structural Biology
Tuesday February 7
Lecture from Tanja Kortemme - AlphaFold and RosettaFold
Wednesday February 8
Lecture from Lisa Eshun-Wilson - Her recent structural biology work and building Diversity, Equity, and Inclusion in structural biology
Feb 13-22 X-ray Crystallography - Lectures Bob Stroud, Tutorials James Fraser
Monday February 13
9-1030: Lecture 1 from Bob Stroud
- What is the system?
- Examine diffraction data in adxv
-
Tuesday February 14
9-10:30: Lecture 2 from Bob Stroud
- Use xia2 to process diffraction data
- Understand various metrics for data reduction
- What do we have at the end? MTZ files!
- XRayView Download
Wednesday February 15
9-10:30: Lecture 3 from Bob Stroud
10:30-11:30: Facility tour with Violla Bassim
Thursday February 16 - BEAMLINE TRIP!!!
Monday February 20 - PRESIDENTS DAY
Tuesday February 21
- File formats and contents
- MTZ file format
- PDB file as text
- Refinement as minimizing Fo-Fc residual
- Where do the phases come from?
- Molecular replacement
- Iterative phase improvement
- ASU vs. unit cell vs. monomer
- 2Fo-Fc map
- Fo-Fc map
- Iterative phase improvement affects density everywhere
- R-free
- B-factors
- The curse of high resolution!!!
- Model building
- Fixing stuff in real space
- Real space vs. reciprocal space refinment
- Prior knowledge (chemistry/physics) vs. Data in minimizing residual
- Water placement in Phenix or Coot
- Alternative conformations and partial occupancy
- conformational vs. compositional heterogeneity
- Team 1+2
- Team 3+4
- Alternative conformations of loops
- Occupancy refinement
- A/B conformations
- mutually exclusive
Wednesday February 22
Reading on rigor and reproducibility in Crystallography:
Final write up due: one per team - Feb 27
- EM: which of the 12 sequences/structure is your sample? Explain how you processed your data and identified which one it is? How can you quantify whether you are correct?
- Piezo1
- Spliceosome
- HSP104
- Cas9
- GroEL
- E. Coli Ribosome
- 20S Proteosome
- LKB1-StradA-Mo25 complex
- TRPV1
- Glutamine Synthetase
- SARS-CoV-2 Spike
- BRAF:MEK:14-3-3 Complex
- X-ray: Introduce the problem you are trying to answer. Give a summary of data processing and refinement statistics (Table 1 type information). Provide results and interpretation of the ligand modeling excercise. How does the density in the binding site compare across your datasets? What roadblocks did you encounter, what did you try, how would you ideally model this? If you were successful in modeling the data, how did you quantify your data (presence/absence/occupancy of ligands)? If you weren’t successful, what is your interpretation? What conclusions can you draw about the forces driving ligand binding at the atomistic level? What would you do next?
- NMR: What is the NMR evidence that the nano bodies are undergoing conformational exchange in solution? Is the conformational change local or global? (Hint: where do the isoleucines in Nb6 and mNb6 map onto the structure?). Can you infer any differences between the dynamics of ancestral and mature Nb6 based on the NMR data? How does binding to Spike RBD change the dynamics? You may simply use the 13C HSQC on ILVMA labelled nanobodies to answer these questions though there is complementary information in the 15N HSQC spectra you may call on to support.
Supplemental material and tutorial videos