Alien life on Earth. Credit: popculturegeek.com

Recap: A few years ago Wolfe-Simon and colleagues discovered that arsenic can be used as an electron donor and acceptor in certain bacteria which live in arsenic-rich conditions.  That was really cool and interesting, because arsenic, usually a poison, is used by these bacteria to breathe, one of the most basic functions of life.

About Arsenic

The “poison of the aristocrats” is toxic to most life simply because arsenic resembles very closely one of the most basic atoms of life:  phosphorus. Phosphorus is used in the cell membrane, in proteins, as a signalling molecule, as part of the energy “coinage” (ATP), and in the DNA backbone. Ingesting arsenic fools life’s machinery into thinking that it is actually phosphorus and incorporate it. But that’s when the machinery starts breaking down, because arsenic is not phosphorous, and it gums up the works. It’s like putting cooking oil on your car instead of motor oil. Your car may run for a while, but pretty soon smoking and seizing will start, and your engine will die.

Martha Wise poisoned her mother, Sophia, Hazel, and her uncle and aunt; Fred; Glenke, Sr., and wife. Credit: the PK paper, Flickr

But GFAJ-1 seems to be using arsenic as a replacement for phosphorous. Actually, it manages to grow in media that  only has trace amounts of phosphate, and large concentrations of arsenate. (The “-ate” suffixsimply means the oxygenated form of both elements: PO3 for phosphate and AsO4 for arsenate.) GFAJ-1 goes forth and multiplies in arsenate-only conditions, but not in media that are devoid of  arsenate and phosphate. It actually grows best with phosphate. So the growth rates induced by the nutrients looks like this: phosphate > arsenate > nothing. When growing GFAJ-1on arsenate, the scientists also measured the intracellular concentration of phosphate, and it was well below what was needed to sustain life.  Does that mean GFAJ-1 uses arsenate instead of phosphate? To answer this question, the scientists used radiolabeled arsenate to answer that question. The radioactive arsenate was detected mostly in the DNA, also in proteins, but some was also found in the membrane. Also, the arsenate-growing bacteria had much less phosphate in them than is necessary to sustain life.

So it seems that arsenate is being used by the cells in lieu of phosphate, but is arsenate truly being incorporated into biomolecules in the same manner as phosphate? The researchers checked that with DNA, looking at the structure using synchrotron X-ray studies. This technique let them look at the actual structure of the DNA, although the resolution is not as good as that of X-ray crystallography. They did find that arsenate was incorporated in the DNA backbone in the same manner of phosphate.

And not only does GFAJ-1 survive, it thrives. A  Following such a radical change from known biochemistry. Since the arsenate is in the DNA,  it means that the whole DNA-replication and transcription machinery — hundreds of proteins — are all adapted to replicating and transcribing arsenate DNA (and very likely arsenate RNA too!)

Does all this mean GFAJ-1 is a new form of life?

New Life?

The current thought is that all life on earth is descended from LUCA: the Last Universal Common Ancestor. LUCA had several traits that were incorporated into all life, such as lipid membranes, DNA as the genetic material, proteins as cellular machinery and also using phosphorous in several critical roles in life, including in the DNA backbone. So “new life” would mean that GFA-J1 is derived from a different common ancestor. If this is the case, than GFA-J1 is indeed a new life form, and the implications of this finding are mind-boggling: why stop at two ancestors? Why not three, five, or 1,000 different ancestors to life on earth, each producing its own biochemical progeny, with its own unique traits? After all, the reason we may not recognize biochemically-distinct life as life, is that we are not looking for it. All our tools are geared to detecting and analyzing life with the biochemistry we know. The fact that this team of scientists have managed to use tools to analyze such a deviation from known biochemistry is a huge accomplishment. Just look how long it took us to find this radical, yet oddly familiar, departure from conventional phosphate-based biochemistry.

The question therefore is now: does substituting phosphorous by arsenic in the backbone mean that GFAJ-1 is derived from a different common ancestor than all other life that we know on earth? Unlikely. I would say that using arsenic as a phosphorus substitute is a very radical adaptation to phosphorus poor and arsenic-rich conditions. GFAJ-1 is still using the same biochemistry, with a heavy phosphorus adaptation. Obviously, many enzymes are adjusted to the arsenate lifestyle. Sequencing GFAJ-1′s genome would probably be the next step, as this could provide us with leads as to how enzymes in GFAJ-1  can use arsenate and arsenate containing molecules.

In brief: bacteria  uses arsenic instead of phsophorus. Cool and exciting? Definitely. Is this huge? Yes. Extends our biochemical horizons? Certainly. New life? Unlikely

Felisa Wolfe-Simon, Jodi Switzer Blum, Thomas R. Kulp, Gwyneth W. Gordon, Shelley E. Hoeft, Jennifer Pett-Ridge, John F. Stolz, Samuel M. Webb, Peter K. Weber, Paul C. W. Davies, Ariel D. Anbar, & Ronald S. Oremland (2010). A Bacterium That Can Grow by Using Arsenic Instead of Phosphorus Science : 10.1126/science.1197258

Yes, it’s that time when we all get together in front of the screen to watch another beautiful game played by that fantastic team contributing to the Carnival of Evolution. This time hosted on the lovely green pitch of Byte Size Biology. So get your popcorn, sunflower-seeds, crisps or any other culturally-appropriate sports-watching food and…… the referee whistles! The game has begun!

Phenotypes! How do they happen?

Kicking off is Grrlsicentist from Punctuated Equilibrium telling us How the Penguin got its Tuxedo. While skillfully dribbling across the field, she tells the story of fossilized feathers from a giant, extinct penguin which contain fossilized melanosomes: intracellular structures whose shape can that tell us of the feather coloration of the bird. No, it was not black and white, but rather brownish and gray. However, melanosomes also strengthen the feathers, and today’s giant melanosomes, giving the familiar black coloration may have evolved as a results of a selection for feather strength, rather than color. Feather-minded (but far from feather brained!) she touches the ball across the defender and reports on how the parrot got its beautiful plumage. (Norwegian Blue?) Would you have thought resistance to bacteria degradation?! A short pass to Jerry A. Coyne who, while on the same topic, explains in Why Evolution is True about the evolution of cat coat-patterns and other issues relating to genetics of the coat in cats.  He makes a quick pass to Bjørn Østman who may have personally discovered the next stage* in feline evolution: the six digit cat! Bjørn toe-punches the ball hard and…

…the ball travels high forward left  to be intercepted by Eric Michael Johnson from The Primate Diaries in Exile. He high-knees the ball twice while asking whether our ancestors were polygamists, monogamists, or happy sluts? All this in his post: “Sex Evolution and the Case of the Missing Polygamists“. Eric launches it off with a strong left kick, the ball arches and jumps once on the ground, only to encounter  Jason Goldman’s knee, bouncing the ball while showing a movie which presents two different hypotheses explaining how wolves were domesticated into dogs. The first: young wolves would be adopted into the camps of early humans. Only those who were most tame would breed with eachother, and over many generations, the domestic dog would emerge. The second: wolves “chose” to be domesticated – they noticed a lot of tasty trash around human encampments, and if they were unafraid enough to hang around, they got to eat lots of leftovers, and those individuals would mate, and over generations, the domestic dog would emerge. His theory-and-ball juggling are interrupted by Kevin Z who takes over smoothly and talks about eyes and sex in lizardfishes posted at Deep Sea News. Kevin now with a square pass to John Wilkins who ponders a rather big question in our understanding of speciation: how many concepts of species are out there? He passes the ball all the way to Hannah Waters in the 16 meter box, who cleanly intercepts the ball while asking a related question: are Eukarya actually part of the Archaea domain, making life a two-domain system, or does the three-domain system still hold? But just as she is about to turn the ball around preparing for a shot at the goal, the referee (whom some say is biased towards the now-defunct 5 domain hypothesis) whistles for an offside violation, prompting loud boos from the crowd! Hannah grudgingly relinquishes the ball, which is given to the other team.

Evolution and Creationism

ProbabilityZero dead-balls a strong and furious kick. Furious over the agenda of the US Tea Party that includes teaching creationism in US public schools. All this in the recurial blog. The ball travels to Jayson D Cooke who is asking in an open letter why the University of Southern Queensland in Australia is hosting a creationist event under a scientific guise, he also defended his opinion on the air. Meanwhile in the stands, Michael D. Barton is selling cartoons of Darwin and evolution (from both sides of the fence, also here) from The Dispersal of Darwin. Some of the football fans accuse Michael of selling products of a man who advocated “Might is Right”. That is patently untrue, for many different reasons, the chief one being a misunderstanding of the word “fittest” in “survival of the fittest”. Fittest does not means “strongest”, but “the best able to reproduce”. However, Michael’s business associate, Eric Johnson decides to talk to the crowd about Darwin as a compassionate person, as manifested in his opposition to vivisection.

Lucas Brouwers from thoughtomics appears from ProbabilityZero’s blind-side, grabs the ball and, considerably faster than plate tectonics, advances up the pitch to the rival penalty box. Although, speaking of plate tectonics, Lucas talks about how freshwater crabs help us map continental drift. He is tackled by a rival player, falls, gets up, picking burrs from his socks, and wondering how they evolved? (The burrs, not the socks.) The answer comes from Melissa who while out walking the dog talks about the burry man, the burry dog and burdock. Why she is walking the dog in the middle of a football game? No idea.

Lucas forward-passes to another player concerned with speciation, Jeremy Yoder at Denim and Tweed talks about the speciation of rockfish: it appears that in many cases depth, not geographic distance, is the allopatric factor in rockfish speciation.  He passes it to DeLene Beeland who takes this question even further: how do we define species in the first place? She turns the ball around, sets for a kick and… goooooaaaaaaal!!!!! Yes! In the stands, Digital Cuttlefish dances with joy.

The referee whistles for halftime, and the players, sweaty and covered with mud and burrs step off the pitch.

Halftime

While we are waiting for the second half to begin, Bjørn Østman tells the viewers at home why intelligent people watch more TV. Or, perhaps not? Read to find out. This public service announcement has been sponsored by Time Tree: just enter the names two species, and find out how long ago they diverged! While the players are resting, they audience watches a beautiful video of the Applied Evolution Summit in Heron Island, courtesy of R. Ford Denison from This Week in Evolution. Also, Bjørn announces the long-awaited results of the Carnival of Evolution Readers Survey. One interesting point that came up is the contentious phrasing of the question: “do you believe in evolution?”

The second half begins. A short pass by Greg Laden explaining what is the most important human adaptation. (Hint: no, not bipedalism.) Zen Faulkes sprints forward – and wonders: did sprinting behavior shape the stings of scorpions, or is this explanation yet another “just so” evolutionary story? Cross-pass to R. Ford Denison who talks about the evolutionary benefits of cooperation and kin selection. Specifically, that Hamilton’s rule still holds, even though it has recently come under fire in a much publicized article in Nature. Competition is also an adaptive force, and Becky Ward tells us about the weird competition between a spider and a plant: both of which are predators! She passes to Lucas Brouwers, who makes small adjustment to the ball’s trajectory before passing it on, noting that evolution also generates novelty through subtle tinkering.

So how does the game end? It doesn’t. Evolution does not end. It just keeps going on and on and on… The next Carnival will be hosted at This Scientific Life. It is never to early to submit.

I recently received an email from a graduate student in Philosophy regarding protein function. Not sure if that person wants his name advertised, so I will keep it to myself.

“I am a fan of your blog, and interested in the philosophy of biology. One particularly interesting question is what makes something have a function; when it comes to artifacts, we just check with whoever designed the thing. It gets more complicated when functions change, and things are used for purposes other than what they were originally designed for, but it’s still pretty straightforward. However, biological functions can’t go that route (unless maybe one is a fan of intelligent design). I’m curious what you think about this, after seeing you mention your interest in predicting the function of genes and proteins. Is the function of something just the causal role that it plays in some larger mechanism? Do you have to include evolutionary considerations? If you ever have the time, I’d love to hear your thoughts about this.”

Thanks very much

My rather rambling answer follows:
“Ouff, you’ve opened a pretty big can of worms, which many of us are having a problem with.

Function in biology is context dependent. An enzyme catalyzes a biochemical reaction, say, removing a phosphate molecule from a protein, However, by removing that phosphate from the protein, the enzyme changes something in the function of the cell, as phosphate molecules are the ‘signaling currency’ of the cell. So the enzyme fulfills a cellular function as well. Finally, suppose this cell is in a developing embryo, and the phosphate removal in this type of protein in many catalyzes the creation of a limb, or a particular organ or tissue: now we have a whole organismal functional context. Which one of those: the biochemical, cellular or organismal is the ‘real’ function of the cell? Well, obviously all three are ‘real’.

To add a twist, suppose that a this enzyme is also active in removing phosphates from proteins in the adult animal. Now the animal has reached maturity, and because of a mutation in one of the cells that enzyme does not work anymore. The intra-cellular signaling becomes defective and the protein accumulates in its ‘phosphorylated’ form. This signals a division of the cell, and suddenly you have a pre-cancerous situation. So from a health point of view, this mutant plays a role in the survival and proliferation of cancer cells. Interestingly, a protein that causes our spittle to froth (don’t try doing this around other people, gross), was first discovered as a nasopharenygeal cancer associated protein, and it is named as such. Many genes and proteins are named after they are found to do one thing, even though we generally associate them with something else, simply because of the context in which they were discovered.

Also, there are moonlighting proteins, which may simply perform different functions. A protein called APIS is part of the proteasome: a cellular protein shredder which is itself a rather large protein complex. APIS also plays a role in transcribing DNA to RNA: thus, it is part of a protein creation complex, and of a destruction complex. See this short paper on Moonlighting proteins.

Yes, evolutionary considerations always come in to play, it is the lens through which we examine all biological phenomena. Evolution does cause certain proteins to be ‘multi-purposed’, also, some types of protein structures are more amenable to a certain set of functions than others. Furthermore, certain proteins are ‘promiscuous‘: certain enzymes may work on more than a single substrate (“Promiscuous” is different from “moonlighting”, where enzymes do completely different jobs; being “promiscuous” means a single enzyme does the same thing, but with different partners: i.e. catalyze the destruction of a sugar, but with different types of sugar molecules). Promiscuous enzymes can clearly show a ‘trajectory of evolution’ i.e. going from being very specific for one substrate, to non-specific for several substrates (or vice-versa). Promiscuity is a good example of molecular adaptation and tradeoff: a promiscuous enzyme means you have a jack-of-all-trades in your genomic complement, and you have to spend less energy on controlling the production of several different enzymes for several different tasks. However, the flipside of having a jack of all trades is that he is the master of none: the catalysis reactions are generally less efficient, which may cause problems for the cell/organism.

Phew, I hope I managed to convey some of the complexities of this issue, and how we try to deal with them in a systematic fashion.
[... edited out]

Cheers,

me”

The difference between moonlighting...

...and promiscuous

Jeffery, C. (2003). Moonlighting proteins: old proteins learning new tricks Trends in Genetics, 19 (8), 415-417 DOI: 10.1016/S0168-9525(03)00167-7

Some background information: we have sequenced more than 1000 genomes of microbes, and hundreds of plants and animals. Additionally, we have millions of partial DNA sequences, RNA sequences, proteins, genomic fragments and millions of genes sequenced from metagenomic data. Problem: for most of these sequenced genes, we do not know what they are doing. That’s right:  most of the sequence data that we have is just that: data. Not information. We are amassing an ever-growing collection of books that are written in a mostly incomprehensible  language. We know (or “educatedly guess”) where the words in those books (the genes)  are located, because we have sequence signals that indicate where the bits of the DNA that code for genes is. For some of the words, we know the meaning. But in many cases, (and by some estimates in most cases) we fail to understand the meaning of the words (genes) in those books (genomes). Drawing further on the book<–>genome and gene<–>word metaphor, we sometimes know one  meaning of a word, but we all know that words in human languages can hold different meanings, depending on context. “Whatever floats your boat” can be read literally, but more often this particular collection of words in this order is a figure of speech. The same thing goes for genes: a gene may code for a certain enzyme, catalyzing a simple chemical reaction. But in another context, it may perform  developmental function for the whole organism, which has different implications than just the biochemical level.

Where's one of those when we need them?

We can’t just rely on computational means to find out what’s doing what. Bioinformatics can help us annotate genes that are similar to those already discovered, and in some cases give us new insights to the function of unknown genes. But for truly novel functions, and to known whether our boat is real or a metaphor for “what works best” we may need to run experiments. And we need a good collaboration between those who do the computational work, and those who do the experimental work in identifying which are the most important books to look at, and what words in them we need to decipher first.

The COMBREX meeting aims to start this large-scale and long-term decoding, a collaboration between experimentalists and computational biologists.
Note that the COMBREX workshop is part of the larger Microbial Genomics meeting at Lake Arrowhead, California.

Here is the announcement. Feel free to cut & paste and forward:

Announcing the first COMBREX Workshop for Computational and Experimental Determination of Protein Function. September 15, 2010 Lake Arrowhead, California USA

COMBREX (Computational Bridge to Experiments) is a new NIH funded effort that aims to increase the pace of experimental determination of the function of large and high priority gene families in bacterial genomes. The Principal investigators are  Richard Roberts (New England Biolabs) Simon Kasif (Boston University) and Martin Steffen (Boston University), this effort will form a consortium of experimental and computational biologists that would collaborate directly to test the predicted functions or specificity of high-priority genes.

Central to this effort would be the creation of a community web-based database that will  allow computational and experimental scientists to communicate easily and assist experimentalists in identifying high-priority genes with high-quality computational predictions. Experimentalists will be able to submit bids (proposals) to validate individual predictions, and if successful, will receive modest funding from COMBREX to perform the validation.

The website can be found at http://combrex.bu.edu/ .

A workshop to discuss issues related to the formation and operation of COMBREX will take place on Wednesday, September 15, 2010, as part of the 18th Annual International Meeting on Microbial Genomics at Lake Arrowhead, CA, outside of Los Angeles. A preliminary program can be found at http://www.mimg.ucla.edu/arrowhead2010/program.html (COMBREX is formerly SciBay). Confirmed speakers include Richard Roberts, Simon
Kasif, Manuel Ferrer (CSIC, Madrid), Patricia Babbit (UCSF), John Gerlt (Illinois), Peter Karp (SRI), Alexander Yakunin (Toronto), Steven Brenner (UC Berkeley) and Bruno Sobral (Virginia Tech).

The morning session will provide an overview of COMBREX, including both the experimental and computational challenges, related talks, and a
description of topics to be discussed by breakout groups. These groups will convene in the afternoon to discuss the topics and prepare a short summary, for presentation to the entire workshop after dinner.

Topics to be discussed by the breakout groups will roughly divide into the following areas: (1) whole genome annotation, (2) assessment of computational predictions, (3) use of structure to predict function, and (4) infrastructure for function annotation. General topics to be discussed include:

1. How to prioritize predictions?

2. How to evaluate experimental bids?

3. How to handle non-enzymatic proteins?

4. How best to handle predictions/phenotypes from high-throughput experimentation?

A key desired outcome of the workshop is the identification of opportunities and catalysis collaborations between computational and experimental biologists.

We hope you will be able to join us for this event. You can register at: http://www.mimg.ucla.edu/arrowhead2010/registration.html

For further information please contact the organizers:

Co-chairs: Martin Steffen, Boston University, steffen ‘at’ bu ‘dot’ edu
Iddo Friedberg, Miami University, i.friedberg ‘at’ muohio ‘dot’ edu

Steering Committee: Simon Kasif and Richard J. Roberts

As part of the process of manufacturing  a new car,  the designers will take the blueprints to the factory floor. There they will set up an experimental assembly line, tinkering with the manufacturing process of the prototype until it is ready for mass-production. Can we do the same with the machinery of life – the assembly of proteins? Can we set up an alternative assembly line for a new protein prototype — and then actually set up a working assembly line for the whole new protein?  A proof-of-concept has been published this week in Nature by Jason Chin’s group at the Medical Research Council Laboratory of Molecular Biology, Cambridge UK.

If there is a single common denominator to all life, it is the genetic code. All life is built around DNA encoding information for proteins  nucleotide triplets or codons. Since there are four types of nucleotides (A,T,G,C)  that are read in words of thee, there are 4³ = 64 possible codons: more than enough to encode for the 22 amino acids that make up proteins. There is nothing more basic and fundamental to life on Earth than the three-letter based genetic code.

Until now.

Chin’s group has created a four-nucleotide codon system.  It is not that the DNA is different: it is the way the cellular machinery decoding  RNA transcripts interprets the nucleotide sequence. Ribosomes –large RNA and protein complexes  which are the platform upon which messenger RNA is read and decoded — are set to serve up messenger RNA three nucleotides at a time. (Messenger RNA or mRNA is a transcript of the DNA which is carried to the ribosome.)  Transfer RNA or tRNA is a short RNA molecule that shuttles the proper amino acid to the ribosome, but will only attach if the proper codon is served up by the ribosome. The whole protein synthesis “assembly line” looks something like this:

Protein synthesis. Credit: Wikimedia Commons.

To change the interpretation of the genetic code from three lettered words  to four, Chin and his colleagues had to make new ribosomes, and new tRNAs.  To create these new ribosomes, they designed orthogonal ribosomes, or o-ribosomes. O-ribosomes are genes inserted to produce extra ribosomes that operate in the cell alongside the regular ribosomes. The cell functions because it has the regular ribosomes to maintain its viability. The ribosomal RNA in the o-ribosomes is free to be mutated to create new unnatural traits: in this case, the ability to serve as a platform read four-letter codons. They selected for Escherichia coli bacterial cells that expressed a o-ribosomes which translated a four-letter codon in a gene, which would otherwise go untranslated by the regular ribosome. The gene gives the bacterial cells resistance to the antibiotic chloramphenicol. So cells that survive a dosage of chloramphenicol are those which have functioning o-ribosomes, as they have the chloramphenicol resistance gene that is being translated by the o-ribosomes.

They also needed to create new tRNAs that have an four-nucleotide anticodon (the part that complementarily binds to the messenger RNA –  see figure above.)  So the surviving E. coli cells have a population of working o-ribosomes, regular ribosomes, modified tRNA (with a  four-letter anticodon) and regular tRNA.

Then they took their work a step further. Each three-letter tRNA carries a specific amino-acid, depending on its anticodon. Thus tRNA_AAG will always have a phenylalanine attached, because CTT (the complement of AAG on the messenger RNA) codes for phenylalanine. If you start messing with that, the translation machinery will produce non-functional proteins, which will probably kill the cells pretty quick. But with the orthogonal 4-letter code machinery, that is not really a problem: the orthogonal machinery operates alongside the normal one. Also, there are no amino acids naturally assigned to any four letter code, because this code does not appear in nature in the first place! So Chin’s lab assigned an unnatural amino acids to a four-letter code. The non-naturally occurring p-azido-l-phenylalanine amino acid was assigned to tRNA_UCCU. They then showed that the whole alternative translational machinery worked by synthesizing a mutant of the protein calmodulin which used this amino-acid in its structure.

Why do it? Well, personally I don’t see the need for justification: just being able to do it is so cool!  But seriously: think of the ability to design proteins from up to 4⁴=256 different amino acids other than the 22 we have now.  The possibilities of tinkering with existing proteins using this orthogonal, four-letter based machinery are huge. The other benefit of this orthogonal synthesis setup is the ability to control this orthogonal translational machinery: because it does not use the three-letter vocabulary, this orthogonal machinery would be much easier to manipulate, tinker with and switch on and off without getting in the way of regular cellular translational machinery. The analogy to a car assembly line breaks here. It is as if two different models are being assembled on the same line just by using different robots. The better analogy is for a program source code to be read by two different compilers, each producing a different program. Awesome.

Another example of polypharmacology is a drug that binds to multiple targets in the human body. This could be used for overcoming drug resistance, a known problem with cancer. Cancer tumors often develop a resistance to anti-cancer drugs by simple natural selection: the protein that the drug binds to mutates, and no longer binds the drug. However, if the drug acts by binding redundantly to several proteins, it would be more effective, since several mutations would be required to effect drug resistance.

Another important polypharmacological consideration  is toxicity. If a drug binds to one protein, its drug target, it may also bind to another one which it should not bind to as it disrupts the normal functions and the health of the patient. If the side effects outweigh the cure, the drug is no good.

How one drug (cyan) can bind to two different proteins with different overall shapes (pink and green), but with similar binding sites

Because it can either increase  profits, or conversely derail a whole process of drug development, predicting polypharmacophoric effects is very much something drug developers want. A study published yesterday in PLoS Computational Biology by Jacob Durrant and his colleagues suggest a way  bioinformatics and theoretical biophysics can help in identifying multiple drug targets. Durrant’s goal was simple: given the molecular structure of a candidate drug, which proteins are expected to bind it? The strategy this group took is a combination of bioinformatic and experimental screening.

Finding additional drug targets in four  steps

Reproduced under CC license from doi:10.1371/journal.pcbi.1000648.g001. Click for original image.

Step 1 (A-C in the figure above): identify the known target protein. Now pick all the protein structures that are not similar to it. Why those that are not similar? Similar proteins could be potential drug targets, since they have a similar shape to the known target protein. But here they are interested in finding targets from proteins that are of a different shape, and have no homology to the known target protein: secondary targets.

Step 2 (D): take this set of dissimilar proteins, and look for binding site similarities. Binding sites are clefts in the protein that may bind drugs. If those clefts are similar in shape to the cleft in the known target proteins, they may bind the drug. Leave only those non-homologous proteins that have similar binding sites (D in the figure)

Step 3 (E): Now add all the proteins that are homologous to the set generated in step 2. This increases the number of possible targets to homologs of the proteins that were initially selected only for binding site similarity.

Step 4 (F): take the drug molecule, and try to dock it to the various protein structures. Rank the druggability of each protein according to the score provided by the drug docking software (Autodock).

Experimental verification

Now for the cool part. Durrant and colleagues tested  the computational prediction in the lab, using the compound NSC-45208. NSC-45208 inhibits a protein responsible for RNA processing in Trypanosoma brucei. So we know it is a potential drug against African sleeping sickness. What else is it good for?

(NSC-45208), 4,5-dihydroxy-3-(1-naphthyldiazenyl)-2,7 -naphthalenedisulfonic acid, a recently discovered inhibitor of T. brucei RNA editing ligase 1 (TbREL1)

“The predicted secondary targets that gave the best docking scores, H. sapiens mitochondrial 2-enoyl thioester reductase (HsETR1), T. brucei UDP-galactose 4′ epimerase (TbGalE), H. sapiens phosphodiesterase 9A (HsPDE9A2), and Streptococcus pneumoniae teichoic acid phosphorylcholine esterase (SpPce), were subsequently tested experimentally.”

Durrant and his colleagues tested their predictions that NSC-45208 also binds to two human proteins (HsETR1 and HsPDE9A2), one additional Trypansome protein (TbGalE), and a bacterial (Streptococcus pneumoniae) protein (SpPce). Not only binds, but also inhibits their enzymatic activity. Their predictions worked well on the top two predicted targets: NSC-45308 inhibited the enzymatic activity of HsETR1and TbGalE, but HsPDE9A2 and SpPce were not affected by the drug.

At first blush, this does not seem to be much of a batting average: two positives and two false positives. But we have to remember that the experimental verification of these predictions — even if you have a good enzymatic assay to check predictions– can be very time- and resource consuming. An exhaustive test of the predictions for several compounds and many target enzymes is still not possible. As initial proof-of-principle, this work goes much farther than most other joint experimental / computational works I have read. The authors also go into lengthy and detailed discussions on limitations and improvements, as well as on another form of non-specific inhibition of the secondary targets, makes for a really interesting read on polypharmacological considerations in drug screening.

The structures’ PDB codes are:

1CMW, 1DF9/2QID, 1G40, 1G44, 1L6L, 2OU1, 1RID, 1Y8E, 2A01, and 2HR0 Some of them are still in the databank.

The University of Alabama at Birmingham has requested that the Research Collaboratory for Structural Bioinformatics Protein Data Bank remove certain protein structure files deposited by a former UAB employee. UAB also has identified nine publications related to the same protein structures that should be retracted from various scientific journals, and is making those journals aware of this matter.

Allegations of data fabrication and/or falsification were made concerning certain protein structures published by the former UAB employee. In accordance with UAB’s scientific integrity policy, and that of the Office of Research Integrity of the U.S. Department of Health & Human Services, UAB empanelled a committee of experts with no conflicting interests to investigate these allegations. After a thorough examination of the available data, which included a re-analysis of each structure alleged to have been fabricated, the committee found a preponderance of evidence that structures 1BEF, 1CMW, 1DF9/2QID, 1G40, 1G44, 1L6L, 2OU1, 1RID, 1Y8E, 2A01, and 2HR0 were more likely than not falsified and/or fabricated and recommended that they be removed from the public record.

“Scientific misconduct is absolutely unacceptable,” said UAB Scientific Integrity Officer Richard B. Marchase, Ph.D., vice president for Research and Economic Development. “It was important that the files be removed from the database and the articles be retracted to ensure that future research in the areas of macromolecular structure analysis and the function of proteins could continue uncompromised by faulty data.”

Some of these structures date back to 2002; this has been going on for quite a while then.  Apparently the investigation ended May 2009, but UAB only  issued a statrement today. The associated papers are also being retracted.  If anyone has more information on this strange affair, please share here.