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Computational Microscopy: Revealing Molecular Mechanisms in Plants Using Molecular Dynamics
Simulations - Teaching Guide Jiangyan Feng+, Jiming Chen+, Balaji Selvam+ and Diwakar Shukla*
Department of Chemical & Biomolecular Engineering, Plant Biology, University of Illinois at Urbana-Champaign.
+These authors contributed equally to this work.
Overview Molecular dynamics (MD) simulations provide a detailed view of biological pro- cesses at the atomic level. It has been successfully applied to predict protein struc- tures, dynamics, functions and for design of drugs. Despite the increasing amount of sequence and structural information, very little is known about protein dynamics, which governs protein functions. This teaching tool introduces the MD simulations to the plant community. It contains six sections that aim to answer following questions about molecular simulations: (i) Why use MD? (ii) What is the future of MD in plant biology? (iii) What are the basic principles of MD (iv) What are some key achievements of MD (v) How has MD been applied to plant proteins? (vi) How can MD simulations and experiments be integrated? This teaching tool also includes two tutorials on how to run MD simulations using QwikMD software and how to analyze MD simulations using Visual Molecular Dynamics (VMD) software.
Use of this Material This teaching tool is appropriate for use with a plant molecular biology course for upper level undergraduates. Prior knowledge of basic protein structure and function is helpful, but not required as this teaching tool includes material on basics of protein structure. Basic knowledge of physics (i.e. a high school or freshman level physics class) is useful for a full grasp of the section on the inner workings of MD. Remaining sections assume early undergraduate-level biology background. The lecture slides should take approximately 4-6 hours of lecture time to go through.
Tutorial Use: In addition to the lecture material, we have included hands-on tutori- als to guide students through setting up, running, and analyzing MD data. “Tutorial 0: Installing Required Software” contains instructions on how to download nec- essary software on Windows, Mac and Linux platforms. “Tutorial 1: Preparing and Running a Simulation” shows students how to prepare and run a molecular dynamics simulation using the QwikMD software. Finally, “Tutorial 2: Watching a Protein in Action” shows students how to analyze MD data that we provide. Together, these two tutorials are intended to demonstrate the process of performing an MD study, from system preparation to analysis of results. Tutorials 1 and 2 are independent and thus can be performed in any order. For students with prior knowledge of molecular biology and protein structure, we recommend working through Tutorial 1 before Tutorial 2 to mimic an actual workflow of an MD study. For students with less prior knowledge of molecular biology and protein structure, we recommend working through Tutorial 2 before Tutorial 1. This will allow students gain some familiarity with looking at protein structures prior to setting
up their own simulations. The estimated time requirement for tutorials are ∼15 minutes for Tutorial 0, 1 hour setup for Tutorial 1 plus 3-4 hours of run time, and 1.5 hours for Tutorial 2. Due to the required amount of time for each tutorial, we recommend that students work on them individually or in small groups outside of class time.
Learning Objectives By the end of this lesson the student should be able to understand:
1. Why use molecular dynamics (MD) simulations?
2. What is all-atom MD?
3. How does MD work and what is the protocol to setup a MD simulation?
4. How can MD complement the study of plant proteins?
5. What is the advantage of integrating MD and experiments?
6. How can we engineer plant proteins using MD?
7. How can MD make an impact in the future of plant biology?
8. How do we run MD simulations using QwikMD?
9. How do we analyze MD output using VMD?
Study/exam Questions (understanding and comprehension) Quiz 1: Why use molecular dynamics (MD) simulations?
1. What are amino acids and how do they form proteins?
2. What is the central dogma of life?
3. Why do proteins function like machines?
4. What are the limitations of experiments?
5. Why do we need MD to complement experiments?
6. How are proteins made, and how do you classify levels of protein structure?
7. Why do we study plant proteins?
Quiz 2: Future of MD in plant biology
1. How can MD simulations help solve global issues?
2. List two projects that are aimed at engineering high yield crops.
Quiz 3: All-atom MD: The computational microscope
1. What is the principle behind MD and why do we need MD?
2. How does MD calculate forces and how the data is stored?
3. What kind of information do we get from MD?
4. How do we setup a MD simulation and why the starting structure important for MD?
5. How do we solve a protein structure and where can you find solved protein structures?
6. List some classical MD programs.
7. How can you gain biological insights of proteins using MD data?
8. What are advantages and limitations of MD?
9. Why do we use QwikMD and what is the best feature of QwikMD?
10. How do you visualize proteins and MD trajectory data?
Quiz 4: Scientific successes of MD
1. Discuss the evolution of MD
2. Name three scientists involved in discovery and development of MD methods and their contributions.
3. What are the timescales of biologically relevant protein dynamics?
4. How can MD scaling be increased using supercomputers?
5. List some of the protein folding simulations performed by different research groups. How well do they match with experiments?
6. Why do proteins adopt different shape and structure?
7. What is a ligand and what is the importance of ligands in terms of protein function?
Quiz 5: Applications of MD to plant proteins
1. How will MD complement the experimental study of plant proteins?
2. What are the plant proteins studied using MD?
3. Describe the functions of the above proteins.
Quiz 6: Complement MD and experiments
1. What is the relationship between simulations and experiments?
2. What is the advantage of combining experiments and simulations in terms of understanding complex functional dynamics of plant proteins?
3. List one example of simulation guided experimental design.
4. List one example of experiment guided MD simulation.
Discussion Questions (engagement and connections) Part 1: Why use molecular dynamics (MD) simulations?
1. How amino acids are classified based on their properties?
2. What are essential and nonessential amino acids?
3. How are amino acids linked together to form a long chain?
4. Why are plant protein MD studies largely under-developed compared to human proteins targets?
5. Explain how MD is a successful complement to experimental studies.
Part 2: All-atom MD: The computational microscope
1. What are the common experimental techniques to solve protein structures?
2. What are the inputs needed for MD?
3. How can we obtain biological insights from MD results?
4. How do we setup a MD simulation using QwikMD?
5. How do we analyze MD output using VMD?
Part 3: Scientific successes of MD
1. What are the example applications of MD?
2. Does protein size limit MD simulations?
Part 4: Applications of MD to plant proteins
1. Describe the advantages of using MD to study plant proteins?
2. List the recent MD studies on plant proteins.
Part 5: Complement MD and experiments
1. List the recent publications that combine MD and experiments.
2. What are remaining challenges in combining simulation and experiments?
Part 6: Future of MD in plant biology How can MD help solve the future challenges in plant biology?
Lecture Synopsis Why use molecular dynamics (MD) simulations? (3-19) For more details, see Lecture Notes, sections 1 and 3 Proteins are essential biological molecules that perform various physiological func- tions in animals and plants. They are synthesized from DNA, transcribed to RNA and translated to protein. Amino acids are bonded together as a polypeptide to make a long chain of protein. Later, the protein is folded to perform a desired function. Proteins are small and the three-dimensional structures of these molecules are obtained using experimental techniques such as X-ray crystallography, Cryo- electon microscopy (Cryo-EM) and Nuclear Magnetic Resonance (NMR). Proteins are dynamic entities in nature and adapt shapes frequently to perform various func- tions. Therefore, it is extremely difficult to understand the molecular mechanism of protein functions from one single static structure.
The need for Molecular Dynamics simulations in plant biology (20-27) For more details, see Lecture Notes, section 2 Climate change and global warming pose a major threat to current agriculture procedure. The projected global population and future food demands shows that we need to double to crop productivity by 2050. Drought threatens agricultural production and severely hits the crop yield. Additionally, extensive use of fertilizers to increase the crop production results in environmental pollution. The multiscale modeling might help