NMR of proteins (and all things regular…)

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Presentation transcript:

NMR of proteins (and all things regular…) Now we have more or less all the major techniques used in the determination of coupling networks (chemical structure) and distances (conformation). We’ll see how these are used in the study of macromolecular structure and conformational preferences, particularly of peptides. We will try to cover in two or three classes the main aspects of something for which several books exist. There are certain things that I want to bring up before going into any detail: 1) The data obtained is not better or worst than X-ray. It gives a different picture, which can be considered complementary. Also, it is considerably faster than X-ray. 2) One of the reasons it is faster is because we don’t need the crystals. This has a two-fold advantage. First, we don’t need to spend the time growing them, and second, we can do it even if the stuff does not crystallize (small flexible peptides, polysaccharides, etc.). 3) It gives the 3D structure in water, which is the solvent in which most biological reactions take place (enzymes and drugs interact in water). 4) It gives information on the dynamics of the molecule. It is not a static picture.

A brief review of protein structure Before we go into how we determine the structure of a protein from NMR, we need to review briefly the chemical and three- dimensional structure of peptides. Peptides are composed of only ~ 20 amino acids. This makes life a lot simpler… The chemical structure of the protein is the sequence of amino acids forming it. We always write it from the NH2 end to the COOH end: This is called the primary structure. We see clearly that in between each AA we have C=O groups. Thus, the spin system of each AA is isolated from all the others. For this reason, the spectrum of a protein is basically the superposition of the spectra of the isolated amino acids. However, the small deviations from this indicate a defined (not random) structure and allow us to study them by NMR… H O A 2 Ha H O residue N N N N A 1 Ha H O A 3 Ha H peptide group

A brief review of protein structure (continued) The way in which the amino acids in the peptide chain arrange locally is called the secondary structure. Some of the most common elements of secondary structure are the a-helix and the b-sheet (parallel or anti-parallel): Another important element of secondary structure is the b-turn, which allows the polypeptide chain to reverse its direction:

The very basics of NMR of proteins Finally, the tertiary structure is how the whole thing packs (or not) in solution - How all the elements of secondary structure come together. The first thing we need to know is were do the peaks of an amino acid show up in the 1H spectrum: Since they are all very close, after we go pass 3 or 4 amino acids we need to do 2D spectroscopy to spread out the signals enough to resolve them. As we said before, there are no connections between different AAs: we cannot tell which one is which. One of the requirements in NMR structure determination is knowledge of the primary structure of the peptide chain. Now, in order to determine the structure we need to assign an amino acid in the chain to signals in the spectrum. This is the first step in the NMR study. water Aromatic Imines Amides HCa HCb, g, d, ... 10 9 8 7 6 5 4 3 2 1 0

Spin system assignments. To do this we rely on the 1D (if the molecule is small enough), COSY and TOCSY spectra. Last time we saw how a whole spin system is easily identified in a TOCSY. In peptides, there will be an isolated line for each amino acid starting from the NH that will go all the way down to the side chain protons. The only exceptions are Phe, Tyr, Trp, and His (and some others I don’t remember) in which part of the side chain is separated by a quaternary or carbonyl carbon. We can either assign all the spin systems to a particular amino acid (good), or do only part of them due to spectral overlap (bad). If this happens, we may have to go to higher dimensions or fully labeled protein (next class…). In any case, once all possible spins systems are identified, we have to tie them together and identify the relative position of the signals in the primary structure. There are two ways of doing this. One is the sequential assignment approach, and the other one the main-chain directed approach. Both rely on the fact that there will be characteristic NOE cross-peaks for protons of residue i to (i + 1) and (i - 1).

Characteristic NOE patterns. The easiest to identify are interesidue and sequential NOE, cross-peaks, which are NOEs among protons of the same residue and from a residue to protons of the (i + 1) and (i - 1) residues: Apart from those, regular secondary structure will have regular NOE patterns. For a-helices and b-sheets we have: daa dNN daN H O A 2 Ha H O N N N N A 1 Ha H O Ha H A 3 dNb, dNg, … daa dab, dag, … da(i)N(j) i+4 i+3 C N dab(i, i+3) daN(i, i+3) dNN(i, i+3) daN (i, i+4) i+2 N da(i)a(j) C i+1 C N dN(i)N(j) i N C i-1

Sequential assignment In the sequential assignment approach, we try to tie spin systems by using sequential NOE connectivities (those from a residue to residues i + 1 or i - 1). The idea is to pick an amino acid whose signals are well resolved in the TOCSY, and then look in the NOESY for sequential NOE correlations from its protons to protons in other spin systems. These are usually the dNN, daN, and dbN correlations. At this point we also look for the dbd to establish the identity of aromatic amino acids, Asn, Arg, Gln, etc… After we found those, we go back to the TOCSY to identify to which amino acid those correlations belong. This protons will be in either the i + 1 or i - 1 residues. We do it until we run out of amino acids (when we get to the end of the peptide chain) or until we bump into a lot of overlapping signals. Since we may have different starting points (and directions), the method has a built-in way of proofing itself automatically. Yes, hundreds of folks have some sort of a computerized algorithm that should do this. Their reliability varies, and there is a lot of user intervention involved…

Sequential assignment (continued) We can see this with a simple diagram (sorry, could not find much good data among my stuff…). Say we are looking at four lines in a TOCSY spectrum that correspond to Ala, Asn , Gly and Leu. We also know that we have Ala-Leu-Gly in the peptide, but no other combination: In the TOCSY we see all the spins. The NOESY will have both intraresidue correlations ( ), as well as interesidue correlations ( ), which allows to find which residue is next to which. TOCSY NOESY HC HC Gly Gly Asn Asn Ala Ala Leu NH Leu NH

Main-chain directed approach This method was introduced by Wüthrich (the granddaddy of protein NMR). We’ve seen already that regular secondary structure has regular NOE patterns. What if instead of doing all the sequential assignments, which may belong in great part to regions which have no structure, we focus in finding these regular NOE patterns? This is exactly what we do. We actually look for cyclic NOE patterns, which are normally found in regular secondary structure. After we found these patterns, we try to match them with chunks of primary structure of our peptide. This method is not really easy to do by hand, but is ideal to implement into a computer searching algorithm: - First the program looks for a-helices (it looks for dab(i, i+3), daN(i, i+3), dNN(i, i+3), daN (i, i+4), etc…). - It eliminates all peaks used up by helical patterns and looks for b-sheets (stretches of connectivities from things that cannot be close in the sequence). - After eliminating these, it goes for loops and undefined regions.

Locating secondary and tertiary structure Although the main-chain directed approach already looks for secondary structure, all this was done mainly to identify the amino acids in the spectrum (assign spin systems). Now we really need to look for secondary/tertiary structure. If we used the main-chain directed approach, we have most of the work done (some people say 90 %), because all the regions of defined secondary structure (a-helices, b-sheets) have already been identified. If we’ve done the assignments sequentially, we will have most of the i to i + 1 and i - 1, or short-range NOEs. We only need to look for medium-range (> i + 2) and long-range (> i + 5) NOE cross-peaks. The amount and type of medium and long-range NOEs will obviously depend on the secondary and tertiary structure. We group the NOEs in tables, and assign them intensity values according to their intensity (cross-peak volume). As we saw before we take an internal reference (a CH2 in a Phe). Since in large molecules we can have many competing relaxation processes, we don’t give NOEs single values, but ranges. These are usually three, for strong, medium, and weak. Sometimes you’ll also see a very weak range. Next time we’ll see how these are converted to ‘distances’...

What the NOEs does and doesn’t mean So now we have everything: All spin systems identified, all their sequential, medium, and long range NOEs assigned, and their intensities measured. At this point (and very likely before this point also), we will have several conflicting cases in which we see a particular NOE but we don’t see others we think should be there. The reason is because the NOE not only depends on the distance between two protons, but also on the dynamics between them (that means how much one moves relative to the other). This is particularly important in peptides, because we have lots of side chain and backbone mobility. The most important ‘law’ from all this is that not seeing an NOE cross-peak does not mean that the protons are at a distance larger than 5 Å. Also, an NOE can arise from an average of populations of the peptide. We see something as medium (1.8 to 3.3 Å), when it is actually a mix of strong (1.8 - 2.7 Å) and no NOE: Real: Apparent: dij ~ 3 Å dij < 3 Å dij > 6 Å

Summary Next class Today we saw some of the parameters related to the structure of a polypeptide chain we can obtain from NMR: TOCSY, COSY - Used to identify spin systems (to tie signals in the spectrum with particular amino acids NOEs - Used both to finish-off the assignment of spin systems to amino acids from the primary sequence and, More importantly, NOEs give us approximate distances between protons from one amino acid to another. Next class Coupling constants. peptide backbone (f) and amino acid side chain (y) conformation Determination of structures from NMR data (brief intro to molecular modeling methods: Minimization, molecular dynamics, distance geometry, simulated annealing).