Follow by Email

Thursday, May 19, 2011

Compugen: New Discovery Method for Drug Candidates That Interfere With Protein Conformations

Compugen today issued a press release (http://www.cgen.com/Content.aspx?Page=press_releases&NewsId=551), stating that it had developed a new method based upon in silico (by computer) prediction of previously unknown conformations of target proteins, facilitating the design of novel drug candidates:

"Compugen . . . announced today the development of a method to identify novel therapeutic candidates to interfere with disease associated protein conformations and protein-protein interactions. This new in silico method relies on the prediction of hidden conformations of the proteins of interest, which is the subject of a scientific paper to be published in the journal Bioinformatics . . . .

Proteins are dynamic entities and can adopt a series of different conformations. However, some of these conformations are “hidden”, since they are short-lived or difficult to study experimentally for other reasons. Since this dynamic property of proteins is important for their function in healthy and diseased states, a broad view of a protein’s conformational space is crucial in many aspects of drug discovery."

Okay, what does this mean? If you're waiting for me to tell you that it's not rocket science and readily understood by persons like myself, you're mistaken. This is rocket science. Moreover, if it wasn't rocket science, it wouldn't be worth contemplating, because, as I have often said, predictive, algorithm-driven biology, based upon the most advanced computer science, is necessary to give rise to the next generation of therapeutics.

So what can we poor laymen hope to understand from this announcement?

First, the perception of proteins and their relationship to disease continues to evolve. Although the link between proteins (e.g., in excessive quantities, in insufficient quantities) and diseased states has long been known, emphasis had been placed upon their static structures. Today, it is better understood that proteins twist, turn and fold within conformational boundaries, and some of these alternate structures cause disease.

More simply stated, proteins, for the purpose of drug development, are moving targets that can be extremely hard to hit.

And if you are seeking to cure, for example, various kinds of cancer, you are going to have to contend with these alternate states.

Compugen is now saying that it can even more accurately predict the various conformational changes in protein structure, including those that are short-lived. Moreover, as we have also learned from prior announcements, they believe that they can design the peptides that are able to interfere with protein disease-associated conformations, i.e. trap proteins in their inactive state (see: http://jgcaesarea.blogspot.com/2009/08/compugen-evolution-of-new-platform-for.html), and block protein-protein interactions which give rise to disease (see: http://jgcaesarea.blogspot.com/2010/04/compugen-molecular-locksmith.html).

The ability to:

(1) locate the "door" to a specific disease along the length of a given protein (proteins are generally between 50 and 2,000 amino acids in length and consist of 20 types of amino acids), which can assume multiple conformations, and

(2) block the "keyhole" with a custom designed peptide,

provides further evidence of the power of Compugen's cutting-edge science.

[As noted in prior blog entries, I am a Compugen shareholder, this blog entry is not a recommendation to buy or sell Compugen shares, and in mid-September 2009 I began work as a part-time external consultant to Compugen. The opinions expressed herein are mine and are based on publicly available information. This blog entry has not been authorized or approved by Compugen.]

2 comments:

  1. The problem with this is that this only deals with the very preliminary search for a drug that will work. It does nothing to speed up the drug approval process which is the real problem.

    And do you think most drug companies are honestly looking for the best drug? No, of course not.

    However, there are very many similar compounds that would work.

    The first question asked after finding something would be:

    A) Is this patentable? If not, ignore it.

    The next is:

    B) Does this exist in nature? If yes, ignore it, unless you can modify it in such a way so that you have something to patent.

    The next question is:

    C) Does someone else own the rights to this?

    If yes, ignore it. Unless you think it is really good in which case try to make a me-too different molecule that works, even if it would have more side effects or work less well.

    D) Is it likely someone else owns this: If yes, be very careful.

    Finally:

    E) Is this a molecule we own? If yes, try to find a justification for it.

    Better let's just go through all the molecules we own and see if one of them would be the job. Best, look at the all the molecules that have been through preliminary drug testing for safety, even for some other purpose, and see if one of them can be used for something or other.

    The drug research and approval process is already very, very broken.

    ReplyDelete
  2. Jeffery,

    Thanks for the ongoing synthesis of CGEN's developments that you provide. Question for you: do you see CGEN's real value in the drug candidates it has in its pipeline or in the computational platform it has developed for predicting novel compounds? My thinking is that while Pharma certainly have an interest in the drug candidates in the pipeline the bigger interest will be in how CGEN discovers these candidates which should make CGEN an acquisition target at some point.

    ReplyDelete