Description Predicting the effect that a mutation would have on protein function is the overall top ...
Description Predicting the effect that a mutation would have on protein function is the overall topic . Only hypothesis and introduction will be written 4 attachments Slide 1 of 4 attachment_1 attachment_1 attachment_2 attachment_2 attachment_3 attachment_3 attachment_4 attachment_4 UNFORMATTED ATTACHMENT PREVIEW Make your Mutant Lab BSC3466L Lab 2 - Developing a Hypothesis for Your Mutant Design In this activity, each team of students will design a mutant enzyme by replacing one wild type amino acid for another amino acid of your choosing. Based on your mutation’s structural features, a comparison to previously published data, and taking an evolutionary context into account, you will predict the function of your mutant enzyme. Learning Objectives ? Use available data and conceptual understanding of protein structure to select amino acid substitutions in the BglB protein for subsequent analysis and build hypotheses relating these amino acid substitutions to catalytic activity, substrate binding, and thermodynamic stability of BglB. ? Design oligonucleotides that will be used to introduce selected amino acid substitutions into the BglB protein. Getting started When you are creating a mutant, you should be aware of the following: Naming Mutants should be named by standard convention, e.g., H243W. This translates as: "at amino acid #243, the wild type histidine is changed to tryptophan.” Novelty Verify that your selected mutant has not been previously characterized, if that is what you want. Alternatively, you can choose to repeat a previous one. You can find mutants that have previously been characterized by browsing the D2D CURE website (“Control/Command” + “F”). The D2D CURE website will allow you to see expression data results that you can consider when you compare your intended mutation to previously done work. The D2D CURE website is a work in progress but contains most of tested mutants yet. So, while novelty is always exciting, do not feel too much pressure to make a novel mutant. Find something you are really interested and that you want to test. We definitely see the value in replication, especially across institutions. If there is a mutation that you are very excited about and you want to test it, you are free to do so. Mutants uploaded to the D2D CURE website: https://www.d2dcure.com/data/?protein=BglB Make your Mutant Lab BSC3466L Developing a Hypothesis: A Three-Pronged Approach When developing a hypothesis, three approaches that can be considered are: 1. The comparative approach 2. The theoretical approach 3. Evolutionary approach These approaches are not mutually exclusive (nor are they the only approaches that exist). You are encouraged to consider all approaches by developing different hypotheses using each approach and later comparing them. Optimally, your comparison will generate ideas that are in agreement, thereby increasing the robustness of your hypothesis. If these approaches produce hypotheses that are in conflict, further consideration is needed. The evolutionary approach take-home assignment was intended to provide you with a “big picture” of BglB’s history and how it varies across species. As you go through the different approaches, you will be presented with different questions that you should be thinking about. Allow these questions to guide you as you design your mutant. You may change directions a few times, and that is okay. The Comparative Approach The comparative approach allows you to assess your mutant design in relation to published findings. Carlin et al. (2017), linked below, reported the characterization on over 100 mutants (Figure 2). Carlin, D. A., Caster, R. W., Wang, X., Betzenderfer, S. A., Chen, C. X., Duong, V. M., ... & Kim, N. (2016). Kinetic characterization of 100 glycoside hydrolase mutants enables the discovery of structural features correlated with kinetic constants. PloS one, 11(1), e0147596. You may also refer to the D2D network website, https://d2dcure.com/data/?protein=BglB, which reports characterization data generated by other students working on this project. In reviewing the published data compared to your mutant design, consider the following: ? Are you making changes at a residue site that’s been mutated before? ? Do you see the mutation you are considering making (e.g, E ? A) done at a different site? Perhaps at various sites? If at various sites, how do the expression and kinetics data compare for the same amino acid replacement made at these different sites? How can any of these data inform the prediction you make about the effect of your mutation? Make your Mutant Lab BSC3466L Notes on interpreting Figure 2 from Carlin et al. (2017) and D2D CURE. 1. Expression—did this mutant produce a detectable quantity of our BglB enzyme at all? This data is based on the quantification of protein at A280 and SDS-PAGE analyses. If the protein does not express, you cannot collect data on the effects of the mutation on the enzyme’s kinetics or thermostability. 2. ?TM: This is a measure of the enzyme’s thermostability (how well it can withstand increasing temperatures). TM is the temperature at which half of the enzymes were denatured. ?TM compares how the mutant performed compared to the wild type. Thus, more negative values indicate reduced thermostability, relative to wild type. 3. ?Kcat/KM: Kcat, the catalytic constant (or turnover number), describes how many molecules of substrate can be converted to product each second per single active site of enzyme. Higher values of Kcat are favorable. KM is the Michaelis constant which represents how much substrate is needed to get to half of the maximum velocity (V max/2) of the reaction (related to the affinity of the enzyme for the substrate). Lower KM means less substrate is needed to reach a certain reaction rate. The ratio Kcat/KM therefore indicates the catalytic efficiency. ?Kcat/KM compares the catalytic efficiency of a mutant to that of the wild type. Thus, more negative values indicate reduced catalytic efficiency, relative to wild type. The Theoretical Approach The theoretical approach uses data generated by the Foldit Modeling functions to evaluate the mutant’s local interactions that are summarized in the local score. You can see the local score of any residue by selecting it and hitting “Tab”. Consider the following: ? How do the properties (e.g., hydrophobic/hydrophilic, large/small, etc.) of your mutant amino acid interact with the other local amino acids? Are these interactions different from those of the wild type amino acid? How about any broken or new hydrogen bonds? ? What local scores are produced by your mutant amino acid? How do they compare to the local scores observed in the wild type? ? How might these modeled interactions deter or enhance substrate binding? Can you provide an explanation for this prediction? Notes on interpreting the local score in Foldit 1. In the same manner that a lower (more negative) Foldit Energy is indicative of higher stability, a lower local score (both overall and for specific factors) is considered more favorable from an energy-based perspective. There are different factors that all Make your Mutant Lab BSC3466L contribute to the overall score, detailed below. If the score for any of these is 0 (zero), it will not be displayed. 2. Clashing: Clashes occur when atoms are spaced too closely together, resulting in their electron clouds repelling each other and destabilization of the protein. 3. Packing: A measure of the extent that atoms are surrounded by other atoms. Poorly packed proteins will have voids (empty spaces), which are energetically unfavorable. 4. Hiding: Based on hydrophobicity. Hydrophobic side chains should point inward and hydrophilic side chains should point outward. 5. Backbone: Reflection of how the backbone is modeled, affected by the dihedral angles. 6. Sidechain: Compares the shape of the sidechain to the shape of the backbone. This is an exception where a more negative score is worse, because it indicates that a configuration is rare and thus less likely to occur in nature. 7. Disulfides: Depicts quality of a disulfide bridge, shown only for cysteines. 8. Ideality: A measure of how closely bond lengths, angles, and dihedral angles are to ideal values. 9. Bonding: Based on hydrogen bonds between the residue and others. 10. Pairwise: Reflects the electrostatic energy between charged but unbonded atoms within a certain vicinity of one another. At the end of the manual, you can find the structure of all amino acids as well as the Venn diagram of their physicochemical properties. Notes and Helpful Tips: Interpreting Total Protein Scores When considering changes in the energy score, the variations in energy described below refer to the change in energy score between the wild type and the mutation you just modeled. ? A total energy that is more negative, i.e., < 0 (relative to the wildtype), represents an increase in stability. ? A total energy change that is more positive, i.e., between 0 and +2 (relative to the wildtype), is okay if the clash score (fa_rep) is < 1. ? A total energy between +2 and +5 is iffy (in terms of likelihood of protein expression); however, it can work if you think the Rosetta picture of the protein is missing an enabling feature, such as increased formation of hydrogen bonds. ? A total energy between +5 and +10 is unlikely to express the protein. ? Energies >+10 are very unlikely to be expressed, but this data can also be important. Do not worry about the total protein score too much as long as it is no more than 5 Rosetta Energy Units higher than wild type. If the score is more than 5 Rosetta Energy Units higher than wild type, you may have reason to worry but that does not always have to be the case. Use your Make your Mutant Lab BSC3466L knowledge about the physicochemical properties of amino acids, the interactions/bonds they can form, the local structure of the area you are working in, and the level of conservation at an evolutionary level to guide you in making your decision. You may design a mutant that has an energy score >+10 than that of the wild type and all of the information that you have access to can indicate to you that this protein should express (perhaps it’s still quite similar to the wild type). For example, we created the mutation V275I with a final energy of -1065.855. It expressed and we were able to get functional data from the mutant. So use your instincts as a budding biochemist! Don’t be afraid to give something a try as long as you can back it up with a good reason. The Evolutionary Approach The evolutionary approach takes homologous sequences and compares them to one another. The degree of conservation or variability at a site can provide meaningful insight about a residue’s role in maintaining local or global structural contacts and overall protein function. Oftentimes, a residue that is conserved across many species can be assumed to be functionally relevant due to the selective pressures that are preventing mutations at that site. Sites with lower selective pressures are able to accumulate mutations more freely if function is not significantly impaired (no negative functional consequence = the mutation cannot be selected against). Consider the following: ? Which residues are conserved? Which residues are more variable? Where are they found in the protein structure? How might the functional consequences at a conserved site differ from the functional consequences at a variable site? ? Are there sites that fluctuate between only a few amino acids (e.g. always valine or isoleucine)? If so, do those residues have any physicochemical properties in common (i.e., the amino acid varies but the property is conserved)? Alternatively, do those residues display different physicochemical properties? Developing a Hypothesis: Putting it all Together After considering the many approaches that have been presented to you. You are now ready to construct your hypothesis. A hypothesis differs from a prediction. With a prediction, you are stating what you expected to observe at the end of an experiment. A prediction becomes a hypothesis when you provide a potential explanation or mechanism to justify why you expect to observe specific results. As such, hypotheses incorporate previously made observations and known data. You are not only addressing what you think will be the functional consequence of the mutation you are choosing to engineer, but why you think that will be the case. Make your Mutant Lab BSC3466L To draft your hypothesis, answer the following questions with your partner, and use the answers to formulate a coherent hypothesis which you will submit with the second part of the assignment that was given out last lab. If done correctly, your hypothesis will be roughly a paragraph long. ? What are the physicochemical properties of the wild type amino acid that you are mutating? What are the physicochemical properties of the amino acid you have selected to replace the wild type? How do they compare to one another? Consider also the physicochemical properties of residues that neighbor the one you are mutating. ? Where in the 3D structure of the protein is the amino acid that you are mutating located? Is there anything significant about this region? Here, significance can be relative to protein function as well as the goals you have for the mutation that you are engineering. ? Is your residue located in a secondary structure element? If so, which one? ? NOTE: Methionine, Alanine, Leucine, Glutamic acid, and Lysine (“MALEK”) have especially high alpha helical propensities. Prolines and glycines often disrupt alpha helices. Tyrosine, Phenylalanine, Tryptophan (aromatics , “YFW”), and Threonine, Valine, Isoleucine (beta-branched, “TRI”) have high beta sheet propensities. Prolines may be found in beta sheets, but often in the edge strands (as opposed to a middle strand). ? Does your mutation disrupt any previously existing bonds? Does it create any new bonds or interactions of interest (hydrogen bonds, disulfide bridges, etc)? ? From the multiple sequence alignments you made, how conserved is the wild type amino acid at the site you are mutating? Is there conservation at that same for any physicochemical properties? How do the properties of your replacement amino acid compare? ? How does the final Foldit energy score compare to the initial energy score? ? Is there experimental data for a mutant similar to yours? What do those results indicate? ? Based on all of the above components, how do you think your mutation will affect catalytic efficiency? Enzyme turnover rate? Binding affinity? Thermal stability? Be sure to provide possible explanations. Foldit Figures As you are designing your mutant in Foldit, there are certain figures that you may want to generate and save (i.e. take a screenshot). Before mutation: 1. A screenshot of the residue you have chosen to mutate (wild type). Make sure the residue is selected (highlighted) and in clear view. You may want to try pressing Q or Shift + Q to orient and zoom in on your selected residue (no pop out window). Make your Mutant Lab BSC3466L 2. The same as above, but with the pop out window that contains additional information about your selected residue. You may toggle this window by pressing Tab. After mutation: 3. A screenshot of the residue after you’ve induced the mutation. Make sure the residue is selected (highlighted) and in clear view. You may want to try pressing Q or Shift + Q to orient and zoom in on your selected residue (no pop out window). 4. The same as above, but with the pop out window that contains additional information about your selected residue. You may toggle this window by pressing Tab. You may or may not want to use couple of these figures in your poster at the end of the semester. Therefore, you may choose to organize these screenshots in a PowerPoint or Word document. Your figures should be accompanied by a figure legend (caption) that describes what is being shown in the figure. You may choose to write 4 different figure legends, or you may choose to combine your 4 figures into one larger figure with components neatly labeled a, b, c, d. Imagine that you are trying to put something together for publication. This is a good opportunity to practice presenting your data the way a scientist would, since you are, in fact, now a scientist. For the legend, you may want to include the following information: ? What protein is this? From what organism? What’s the PDB id? ? What residue position is being shown/highlighted? ? What is the wild type amino acid? What is the mutated amino acid? ? What is the initial vs final energy? ? What do the different colors represent? Make your Mutant Lab BSC3466L The Oligo Order Process “Oligo” is short for “oligomer,” which is a technical term for a relatively short chain of polymers, such as nucleotides, saccharides, or peptides. In our case, the oligo will contain 33 nucleotides; it will span the region that codes for 11 amino acids, where the middle amino acid is an amino acid that will be changed. To mutate a protein, we will change the DNA sequence that codes for it (gene). The DNA oligo we will be ordering in this step encodes for the mutation you designed in the BglB gene. We order oligos through the biotech company, IDT technologies. This protocol will walk you through completing the order. Students can assist with sections (1) Identifying Oligo Sequences and (2) Organizing Mutant Names and Oligo Sequences. Obtaining Oligo Sequences with D2D CURE Application First, you will need to find the oligo sequence that encodes for your mutation. To do this, you will perform a quick search of an oligo database from the D2D Cure website. Navigate to the D2D Cure page: Oligo Search Type in the name of the enzyme variant using the format A123G. Remember that the first letter is the original amino acid residue at the given position, and the final letter is the new residue. Click “Search.” The website will provide a codon-optimized DNA 33-mer sequence to use as a primer, which you can copy and paste as needed. (This 33-mer codes for an 11-mer peptide with the modified residue at the center.) Students should submit their sequence information on the Google Form emailed by your instructor. Make your Mutant Lab BSC3466L Make your Mutant Lab BSC3466L ILVCA GMFYW HKREQ DNSTP XXXXX XXXXX XX... ...X. ..... ...XX XXXXX XXXXX ..XXX X.... ..... XXXXX ..... ..... ..... ....P ....X X.... ..... ..X.. XXX.. ..... ..... ..... ..... ..XXX X.... ..... ..... ..... XXX.. ..... ..... ..... ...X. X.... ..... ..... XXXX. X.... Hydrophobic Polar Small Proline Tiny Aliphatic Aromatic Positive Negative Charged Purchase answer to see full attachment Explanation & Answer: 5 Paragraphs User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.
