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all right hello everyone how's it going

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my name's Sean I'm from the University

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of Maryland Baltimore County and today

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we're going to be looking at xenoamino

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acids a look into biochemistry as we

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don't know it so I'm going to fly

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through a lot of this because it's only

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a six minute talk but please come for

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feel free to come find me at my poster

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outside afterwards so my project

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attempts to merge Theory with experiment

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in order to test if a alternative amino

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acid set is capable of building protein

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structure now to do this we need to

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select a candidate alphabet from

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plausible Alternatives and from there

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use our collaborators over at the

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Charles University in Prague to build

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oligopeptides now I'm going to take a

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step back here and go over some very

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quick background

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um so all life on Earth since Luca has

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used the same set of 20 Alpha amino

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acids to construct metabolism now

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multiple disciplines agree that there

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were far more than 20 available for

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early evolution in the origins of life

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and over the last decade or so there's

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been

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um theoretical work that identifies a

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simple but statistical profile that

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distinguishes life's amino acids from

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Alternatives and that is that the 20

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amino acids used by life exhibit a

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non-random coverage of size and

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hydrophobicity when we Define coverage

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as the range of values in a set and with

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how and how they how evenly they

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distribute across that range

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so what do I mean by that exactly I want

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you to consider a set of five amino

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acids and pick any physical chemical

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descriptor this could be size this could

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be volume I'm sorry uh log P this could

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be charge and you're going to measure

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them rank order them and plot them on

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that axis from here what we can do is we

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can get the intervals between each amino

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acid and this ties into our our idea of

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coverage which breaks down into two

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components which is range and evenness

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so range is simply just the sum of these

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intervals between each amino acid and

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evenness is the sample variance of these

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intervals now this ties back into what I

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said the coded 20 amino acids are

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statistically non-random in one in about

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two and a half million alternative

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alphabets would have the same or better

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coverage in size and hydrophobicity

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now why exactly are we looking at range

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and evenness well range allows for a

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broader diversity of structures and

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functions and evenness allows for the

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best approximation of any desired

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physical chemistry so I like to think of

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it as trying to recreate a black and

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white painting using a defined set of

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tiles and you need to pick which colors

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you want to use to try and get that

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painting as close as possible now range

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is effectively the difference between

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having black and white tiles versus just

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different Shades of Gray and evenness is

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among the black and white tiles having

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an even distribution going from black to

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white

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now why exactly are we looking at log p

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and volume log p is just a measure of

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hydrophobicity and hydrophobic collapse

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is crucial for protein folding and for

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volume volume determines the physical

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space that allows for protein folding

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so now that we have this idea of

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coverage in our mind I would like to

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very quickly go over our workflow I'm

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going to skip essentially everything

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except that top right corner where all

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we're doing is we have a heuristic

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search protocol that searches a library

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of purchasable amino acids

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and from there we are in a constant

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feedback loop with our empiricist

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collaborators in attempting to

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eventually get a candidate alphabet

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now I'm sure you are all dying to see

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what one of these alphabets look like

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right

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so here we go uh this is our current

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alphabet now big emphasis on current

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um because of that iterative feedback

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loop this is definitely subject to

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change and probably will change before

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we start constructing oligopeptides from

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a set but here is our first set um this

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is simply just one example of around 10

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to the 14 possible High coverage sets

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that we could pick from so there are a

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lot of variation that we can change and

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play with with the empiricists now again

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the goal here is to synthesize these

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like a peptides from a completely

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non-canonical set

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and that's hopefully what we'll be doing

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in a few weeks

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now I would like to very quickly end on

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a deeper note of who cares

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why would an advanced science to design

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an alternative amino acid set and I

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would like to kind of bring that

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question to this idea of is there such a

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thing as a good or bad amino acid

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alphabet now before the empiricists and

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the crowd jump out of their chairs and

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strangle me

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um yes the empiricists are saying of

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course there are bad amino acid sets the

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20 are very good at what they do but

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theorists are pushing back a little bit

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and saying well you know Evolution can

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find any needle in any Haystack so I

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would like to believe that the the truth

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lies somewhere in between but what we're

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really trying to do here is begin to

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characterize good versus bad using an

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adaptation of 1980s behavioral thinking

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so optimality theory for life's amino

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acids now I'd like to conclude just by

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thanking our sponsors or I'm sorry our

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sponsors are funders

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and our collaborators over at the

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Charles University in Prague and if you

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would like to talk to me about this in

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much much greater depth please find me

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at poster 24 which is outside thank you

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all so much I really appreciate it

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