4 ms·

There are a great many biologists and bioinformaticians who don't "get" phylogenetics. Please, please don't be one of them. I worked with some world class evolu

by JunkDNA 13y ago

There are a great many biologists and bioinformaticians who don't "get" phylogenetics. Please, please don't be one of them. I worked with some world class evolutionary biologists in the drug industry early in my career and I was blown away by how useful this often ignored corner of biology has become when married with modern bioinformatics techniques. Here's an example: let's say you're trying to develop a new drug against a virus. You can isolate huge numbers of the virus from infected individuals and sequence the DNA very cheaply. Using selective pressure analysis you can look for regions of DNA that are being selected for over multiple generations of the virus. Why? Because these might be important for survival. If your drug can target those regions of the protein, the virus will have an uphill battle mutating and creating resistance to your drug. Here's one more: You can use phylogenetic techniques on individual proteins to see how closely related they are. Why do this? Because if you're developing an antibiotic, you want to know that the bacterial version has a sufficiently large evolutionary distance from the human version. Now you can do this at scale for huge numbers of bacterial proteins and identify the ones with the biggest distance from their human orthologs. This allows you to identify bad antibiotic targets upfront before pouring all sorts of money into experiments (or at the very least, going into said experiments with your eyes wide open).

teej 13y ago
This is frightening and fascinating at the same time. Thanks for sharing.
pvnick 13y ago
I actually agree with you regarding bioinformatics, and the subject you describe is one which I'm exploring as a career path. I was describing an indictment of classification schemes, not bioinformatics, and it seems there are plenty of respondents here that have misunderstood me. Which I suppose is either an indictment of the care with which I constructed my original comment or a lack of attention to the other comments I've made in this thread. Edit: Also, hi Mike!
ronaldx 13y ago
> if you're developing an antibiotic... Beautiful examples in theory, but blown out of the water in practice. In the current age of bioinformatics, practical modern antivirals and antibacterials are not being identified, not at all[0]. As such, I find it awkward and outdated to claim that novel drug discovery is a great testament to phylogenetics and bioinformatics. Can anyone offer a practical example of how bioinformatics has genuinely been (pref. statistically) useful in successful drug discovery? I would also be interested in evidence that existing antibioitics could have been discovered more effectively, using new methods ab initio. [0] e.g. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2095086/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2095086/ "the success rate of discovery has gone down"
- mynewwork 13y ago
  Can anyone explain why ronaldx is being downmodded for this comment? As someone who knows nothing of bioinformatics or their relation to drug discovery, I see nothing wrong with his post. Perhaps what he is saying is incorrect, but can someone explain why?
- JunkDNA 13y ago
  >Beautiful examples in theory, but blown out of the water in practice I will admit that this work was largely done 10 years ago, so it's certainly a bit outdated. I will also concede that the current state of affairs in antimicrobials research is dreadful. >Can anyone offer a practical example of how bioinformatics has genuinely been (pref. statistically) useful in successful drug discovery? I can offer no data that stands up to a rigorous statistical analysis that you seek as far as bioinformatics impact on drug discovery is concerned. This is the primary reason most of us with bioinformatics experience who used to work in the pharma industry don't work there anymore (and for a great many of us this was not by choice). >As such, I find it awkward and outdated to claim that novel drug discovery is a great testament to phylogenetics and bioinformatics. Where did I make this claim? I chose the examples I did (which are real and actual examples by the way) of the way one can use phylogenetics to point out to the parent poster that it's not all crusty old geezers arguing about whether two almost indistinguishable variants of mice are part of the same taxon (which is the view a great many people who have never worked in the field often have). I chose these examples because they are practical examples of phylogenetic techniques that are easy to explain in a forum such as this in a few paragraphs. I can't speak to the viral one, as I was only peripherally involved in that work, but my very first job was taking bacterial sequences, making alignments, and looking at the phylogenetic trees to see whether or not they were too close to eukaryotes for comfort. This was the policy of the company where I worked: the antimicrobials team wanted to ensure both spectrum (that targets they were going after were actually present in medically important bugs) and specificity (that they weren't sloppy targets that you might accidentally hit a human enzyme with). There were a great many targets that I personally de-prioritized because they were no good purely from an informatics perspective.

by JunkDNA 13y ago

teej 13y ago

This is frightening and fascinating at the same time. Thanks for sharing.

pvnick 13y ago

I actually agree with you regarding bioinformatics, and the subject you describe is one which I'm exploring as a career path. I was describing an indictment of classification schemes, not bioinformatics, and it seems there are plenty of respondents here that have misunderstood me. Which I suppose is either an indictment of the care with which I constructed my original comment or a lack of attention to the other comments I've made in this thread. Edit: Also, hi Mike!

ronaldx 13y ago

> if you're developing an antibiotic... Beautiful examples in theory, but blown out of the water in practice. In the current age of bioinformatics, practical modern antivirals and antibacterials are not being identified, not at all[0]. As such, I find it awkward and outdated to claim that novel drug discovery is a great testament to phylogenetics and bioinformatics. Can anyone offer a practical example of how bioinformatics has genuinely been (pref. statistically) useful in successful drug discovery? I would also be interested in evidence that existing antibioitics could have been discovered more effectively, using new methods ab initio. [0] e.g. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2095086/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2095086/ "the success rate of discovery has gone down"

mynewwork 13y ago
Can anyone explain why ronaldx is being downmodded for this comment? As someone who knows nothing of bioinformatics or their relation to drug discovery, I see nothing wrong with his post. Perhaps what he is saying is incorrect, but can someone explain why?
JunkDNA 13y ago
>Beautiful examples in theory, but blown out of the water in practice I will admit that this work was largely done 10 years ago, so it's certainly a bit outdated. I will also concede that the current state of affairs in antimicrobials research is dreadful. >Can anyone offer a practical example of how bioinformatics has genuinely been (pref. statistically) useful in successful drug discovery? I can offer no data that stands up to a rigorous statistical analysis that you seek as far as bioinformatics impact on drug discovery is concerned. This is the primary reason most of us with bioinformatics experience who used to work in the pharma industry don't work there anymore (and for a great many of us this was not by choice). >As such, I find it awkward and outdated to claim that novel drug discovery is a great testament to phylogenetics and bioinformatics. Where did I make this claim? I chose the examples I did (which are real and actual examples by the way) of the way one can use phylogenetics to point out to the parent poster that it's not all crusty old geezers arguing about whether two almost indistinguishable variants of mice are part of the same taxon (which is the view a great many people who have never worked in the field often have). I chose these examples because they are practical examples of phylogenetic techniques that are easy to explain in a forum such as this in a few paragraphs. I can't speak to the viral one, as I was only peripherally involved in that work, but my very first job was taking bacterial sequences, making alignments, and looking at the phylogenetic trees to see whether or not they were too close to eukaryotes for comfort. This was the policy of the company where I worked: the antimicrobials team wanted to ensure both spectrum (that targets they were going after were actually present in medically important bugs) and specificity (that they weren't sloppy targets that you might accidentally hit a human enzyme with). There were a great many targets that I personally de-prioritized because they were no good purely from an informatics perspective.