Whether we call it predicting or folding, the problem is the same one. Given the primary structure of a protein, how do we find, theoretically (that is, no X-rays) what the tertiary structure is?

Why do we want to predict protein structure ?

• With many genomes completely sequenced, we now have the sequences of thousands of proteins that have not yet been isolated and characterized

• Isolation, purification, crystallization, and X-ray diffraction represent an extremely slow way to learn the structures and functions of these proteins

• Being able to predict complete structure and function from primary sequence data would greatly simplify the task of interpreting the genome

• Further, if we can predict structure, we should be able to design structure

In a recent review of the state of the art, Baker [Science, 2005, 310, 638] makes the point that prediction and design are complementary processes, and employ essentially the same methodology.

Predicting Secondary Structure is relatively easy. For example:

• b-strands tend to have one face hydrophobic, one hydrophilic
  • Since side chains alternate up and down, hydrophobic side chains of period 2 tend to indicate b-strand

• Helices tend to have one hemisphere hydrophobic, one hydrophilic
  • Hydrophobic side chains of period 4 tend to indicate helix

For greater accuracy we need:

• A look-up table of the tendencies of amino acids to appear in various kinds of structure

• Some kind of weighting function, like a PAM or BLOSUM matrix, to deal with how to penalize "wrong" amino acids and reward "right" ones

Results tend to be right 70-75% of the time.

For an example of this and other prediction methodologies, I have used the sequence of the amyloid precursor protein (APP), one of the proteolysis products of which is the Alzheimer's amyloid protein:

MLPGLALLLLAAWTARALEVPTDGNAGLLAEPQIAMFCGRLNMHMNVQNGKWDSDPSGTKT
CIDTKEGILQYCQEVYPELQITNVVEANQPVTIQNWCKRGRKQCKTHPHFVIPYRCLVGEFVSD
ALLVPDKCKFLHQERMDVCETHLHWHTVAKETCSEKSTNLHDYGMLLPCGIDKFRGVEFVCC
PLAEESDNVDSADAEEDDSDVWWGGADTDYADGSEDKVVEVAEEEEVAEVEEEEADDDE
DDEDGDEVEEEAEEPYEEATERTTSIATTTTTTTESVEEVVREVCSEQAETGPCRAMISRWYF
DVTEGKCAPFFYGGCGGNRNNFDTEEYCMAVCGSAMSQSLLKTTQEPLARDPVKLPTTAAST
PDAVDKYLETPGDENEHAHFQKAKERLEAKHRERMSQVMREWEEAERQAKNLPKADKKAVI
QHFQEKVESLEQEAANERQQLVETHMARVEAMLNDRRRLALENYITALQAVPPRPRHV
FNMLKKYVRAEQKDRQHTLKHFEHVRMVDPKKAAQIRSQVMTHLRVIYERMNQSLSLLYNVPA
VAEEIQDEVDELLQKEQNYSDDVLANMISEPRISYGNDALMPSLTETKTTVELLPVNGEFSLDDLQ
PWHSFGADSVPANTENEVEPVDARPAADRGLTTRPGSGLTNIKTEEISEVKMDAEFRHDSGYEV
HHQKLVFFAEDVGSNKGAIIGLMVGGVVIATVIVITLVMLKKKQYTSIHHGVVEVDAAVTPEERHLS
KMQQNGYENPTYKFFEQMQN

Submitted to the PsiPred server (link on the main page), this brought the result by email:

PsiPred Prediction

Going after tertiary structure is MUCH more difficult.

The difficult is related to the overall protein folding problem.

Levinthal's Paradox [J. Chim. Phys., 1968, 85, 44] suggests that given the size of the conformation space available to a protein of any significant size, finding a particular conformation starting from any other conformation could take longer than the age of the Universe.

Consider a polypeptide with 100 amino acid residues, and two equally possible conformations per residue

• The number of possible conformations is then of the order of 10¹³⁰

• Assume an interconversion time for conformations of the order of 10^-12 seconds (which is too short by several orders of magnitude)

• Then, it will take 10¹⁰ years to sample all the conformations, proceeding randomly

Hence, simply searching the conformation space of a protein for the "best" tertiary structure is futile, even with a supercomputer.

Several methodologies have been developed for dealing with this problem.

We will take a brief look at:

• Homology (comparative) modeling

• Ab initio predictions of secondary and tertiary structure

• Designing new proteins

Comparative Modeling consists of four steps:

• Find a known structure (a template) related to the sequence to be modeled

• Align the new sequence with the template

• Build a model

• Assess the quality of the model

Two general methodologies are used for finding the template:

• Sequence comparison (e.g., Psi-BLAST) with proteins of known structure
  • Models fall off substantially in accuracy below about 30% sequence identity

  • The identity must be distributed in blocks throughout the length of the protein