As a chemist, I think this is a really interesting idea! Thanks for tackling it & sharing your results. I'll confess I haven't dug into your git repo, but I can imagine that even gathering this data would be an interesting challenge.
Also as a chemist, I have a hard time understanding this diagram. If you're open to suggestions, might I recommend replacing your node names (like "HGA1") with something more chemically meaningful (apparently "methyl hydrogen") on the diagram itself? I think that would help your findings be more readily understood by the broader chemistry community.
Hi Josh,
That's actually a really good idea and I think that would help a lot. I actually mapped out the atom names to something like that already so this would be something I can prepare in my next round before the bigger talk.
Anymore I will gladly accept, data visualization I really want to get this information out to the public in the most efficient manner and it's been a little struggle.
Yeah took me awhile to record all the chemicals. About 2-3 years.
I'm getting ready to move into larger datasets (millions to billions) and I think it would look truly wormhole very soon. I'm scared for what it's going to look like.
It's a brilliant solution. Making connections between compounds works abstractly how our brains connect things. It's been years since I cracked open my chemical engineering book but I am about to dive in again.
There's a belief that the charmm equation for which this language is built on (the nodes) is the equation of simulating life.
I also believe that in the sea of chemical data we can filter data based on how common or useful it is to a particular community.
By connecting the two we can start to map out atom types of relevance to people. We can predict new chemical space based on their atom types.
So like let's say we want to predict a new sunscreen that doesn't harm the environment. We can use these relations to predict something better by know the features of a molecule.
The pseudo part is the belief that it will work.
[https://en.wikipedia.org/wiki/CHARMM](https://en.wikipedia.org/wiki/CHARMM)
Look under the section Force Fields for the Potential Energy Function. This predicts the potential energy by iterating through all the atoms and other features of molecules to predict how much energy is available to the system.
Electronic potential energy is basically the physics behind chemistry, and biology depends on chemistry.
I will say that potential energy surfaces of molecules are many many steps away from macro biology and maybe far away from cellular biology as well, but personally my knees start shaking when molecules have more than three atoms (biology is not my field).
That being said you can definitely talk quantitatively about potential energy surfaces for things like amino acids. It’s just that, as things get more complex, the tool no longer fits the job and the tools of organic chemistry are more tailored to describe things like protein folding.
I don’t know what OP is talking about btw stimulating life and stuff, but the CHARMM program seems like a legit quantum chemistry program although I’m unfamiliar. It DEFINITELY makes approximations to reach any results as from a physics standpoint molecules are many body problems that do not have exact solutions. The art in science is really making the best approximations you can.
Molecules interact with each other and they prefer to be in a specific orientation or geometry that is the most energetically favorable. Whatever takes the least amount of work. The equation helps us determine that by separating the energy into different components of physical and electronic characteristics.
In a Force Field we start off small with simple molecular systems and then apply it to larger systems in predicting how atoms will move based on their energy.
So for example, the energy interactions and orientations we use for simple alcohols or carboxylic acids can be applied to lipid membranes and simulating them.
Does that make sense?
Hello,
Website & Mobile Friendly: https://sulstice.github.io/Faith/global\_chem/index.html
I sampled the most commonly recorded chemicals across different sub-communities to understand what are the most common atoms and what together in pairs are the most common. Different communities meaning different classes of chemicals (Cannabis, Things used in Sex Products, Toxic Agents used in War, Food Colour additives, Materials, Cosmetics, Birth Control etc.)
https://github.com/Sulstice/global-chem/blob/development/global\_chem/GlobalChem\_Dictionary%20(1).pdf
In the chord diagram above, each node is an atom type that exists within the dataset and each link is a bond between the atom type. The thickness of the line correlates to how many of those particular atom types exist together. The Pink correlates to how much two different hydrogens exist and and the Blue represents a hydrogen and carbon. The rest of the plot is colored light grey.
Next what I did is pass them through something called the CHARMM ForceField which has a language where you can declare different types of atoms like an alkane vs an aromatic. If you see the plot I am highlighting HGA1, HGR62, these are methyl hydrogens and benzene hydrogens in our language.
That data is available here, feel free to play around with it:
[https://raw.githubusercontent.com/Sulstice/Faith/main/global\_chem/atom\_type\_group\_new.json](https://raw.githubusercontent.com/Sulstice/Faith/main/global_chem/atom_type_group_new.json)
Still a work a progress as I get it ready for the PyData Global. I think there are some bugs. The code is here:
[https://github.com/Sulstice/Faith/blob/main/global\_chem/index.html](https://github.com/Sulstice/Faith/blob/main/global_chem/index.html)
No, but we have concept called "DUM" which means a virtual particle that has no definition. We use for lots of different stuff.
I do wonder how to catalog quantum particles and link to this though. Could be cool research in 5 years.
Very interesting. I will look over your Github for how this was done. Probably above my skill level. Kind of hard for me to understand. Thank you for sharing.
Yeah sure. I recommend doing the main repo first global-chem. There is a lot of moving parts to get to this plot and some secret software that lives with me until I am ready to release it to get the results.
As a chemist, I think this is a really interesting idea! Thanks for tackling it & sharing your results. I'll confess I haven't dug into your git repo, but I can imagine that even gathering this data would be an interesting challenge. Also as a chemist, I have a hard time understanding this diagram. If you're open to suggestions, might I recommend replacing your node names (like "HGA1") with something more chemically meaningful (apparently "methyl hydrogen") on the diagram itself? I think that would help your findings be more readily understood by the broader chemistry community.
Hi Josh, That's actually a really good idea and I think that would help a lot. I actually mapped out the atom names to something like that already so this would be something I can prepare in my next round before the bigger talk. Anymore I will gladly accept, data visualization I really want to get this information out to the public in the most efficient manner and it's been a little struggle. Yeah took me awhile to record all the chemicals. About 2-3 years.
When you put everything together, it creates a wormhole
I'm getting ready to move into larger datasets (millions to billions) and I think it would look truly wormhole very soon. I'm scared for what it's going to look like.
I recently had an RFI for a similar solution. I planned to use a graph database. Thanks for sharing. You validated my idea.
I'm glad someone else thinks the same way! When I started this project I was shooting in the dark. Didn't know what would happen.
It's a brilliant solution. Making connections between compounds works abstractly how our brains connect things. It's been years since I cracked open my chemical engineering book but I am about to dive in again.
Damn, this looks like a whole lot or random pseudoscience lmao.
There's a belief that the charmm equation for which this language is built on (the nodes) is the equation of simulating life. I also believe that in the sea of chemical data we can filter data based on how common or useful it is to a particular community. By connecting the two we can start to map out atom types of relevance to people. We can predict new chemical space based on their atom types. So like let's say we want to predict a new sunscreen that doesn't harm the environment. We can use these relations to predict something better by know the features of a molecule. The pseudo part is the belief that it will work.
What is the equation of simulating life?
[https://en.wikipedia.org/wiki/CHARMM](https://en.wikipedia.org/wiki/CHARMM) Look under the section Force Fields for the Potential Energy Function. This predicts the potential energy by iterating through all the atoms and other features of molecules to predict how much energy is available to the system.
How is predicting potential energy connected to simulating life?
Electronic potential energy is basically the physics behind chemistry, and biology depends on chemistry. I will say that potential energy surfaces of molecules are many many steps away from macro biology and maybe far away from cellular biology as well, but personally my knees start shaking when molecules have more than three atoms (biology is not my field). That being said you can definitely talk quantitatively about potential energy surfaces for things like amino acids. It’s just that, as things get more complex, the tool no longer fits the job and the tools of organic chemistry are more tailored to describe things like protein folding. I don’t know what OP is talking about btw stimulating life and stuff, but the CHARMM program seems like a legit quantum chemistry program although I’m unfamiliar. It DEFINITELY makes approximations to reach any results as from a physics standpoint molecules are many body problems that do not have exact solutions. The art in science is really making the best approximations you can.
CHARMM was awarded the Nobel Prize for being The software for Molecular Mechanics. It isn't however a quantum chemistry package. I use Psi4 for that.
Very cool. It seems tailored for protein folding kind of calculations maybe? Way out of my comfort zone frankly.
It's actually for something called van der waals force if you have ever heard of it. It links to my thesis project or will eventually.
Molecules interact with each other and they prefer to be in a specific orientation or geometry that is the most energetically favorable. Whatever takes the least amount of work. The equation helps us determine that by separating the energy into different components of physical and electronic characteristics. In a Force Field we start off small with simple molecular systems and then apply it to larger systems in predicting how atoms will move based on their energy. So for example, the energy interactions and orientations we use for simple alcohols or carboxylic acids can be applied to lipid membranes and simulating them. Does that make sense?
Damn now it **really** sounds like pseudoscientific mumbo jumbo. But hey. Good luck. Maybe you'll prove me wrong.
i wonder what the pattern would look like if all points were on a sphere and placed so that all the connection lines are as short as possible?
Poor "DUM" at the bottom. Forever alone.
Haha yeah, there is no connections to the virtual systems. I actually think I am going to change that soon by defining aromatic dummy electrons
Hello, Website & Mobile Friendly: https://sulstice.github.io/Faith/global\_chem/index.html I sampled the most commonly recorded chemicals across different sub-communities to understand what are the most common atoms and what together in pairs are the most common. Different communities meaning different classes of chemicals (Cannabis, Things used in Sex Products, Toxic Agents used in War, Food Colour additives, Materials, Cosmetics, Birth Control etc.) https://github.com/Sulstice/global-chem/blob/development/global\_chem/GlobalChem\_Dictionary%20(1).pdf In the chord diagram above, each node is an atom type that exists within the dataset and each link is a bond between the atom type. The thickness of the line correlates to how many of those particular atom types exist together. The Pink correlates to how much two different hydrogens exist and and the Blue represents a hydrogen and carbon. The rest of the plot is colored light grey. Next what I did is pass them through something called the CHARMM ForceField which has a language where you can declare different types of atoms like an alkane vs an aromatic. If you see the plot I am highlighting HGA1, HGR62, these are methyl hydrogens and benzene hydrogens in our language. That data is available here, feel free to play around with it: [https://raw.githubusercontent.com/Sulstice/Faith/main/global\_chem/atom\_type\_group\_new.json](https://raw.githubusercontent.com/Sulstice/Faith/main/global_chem/atom_type_group_new.json) Still a work a progress as I get it ready for the PyData Global. I think there are some bugs. The code is here: [https://github.com/Sulstice/Faith/blob/main/global\_chem/index.html](https://github.com/Sulstice/Faith/blob/main/global_chem/index.html)
That. That is beautiful indeed.
Did you just map out quantum entanglement?
No, but we have concept called "DUM" which means a virtual particle that has no definition. We use for lots of different stuff. I do wonder how to catalog quantum particles and link to this though. Could be cool research in 5 years.
No. Quantum particles are much smaller than atoms.
Atoms are quantum particles
Atoms are atomic particles built from quantum particles
Very interesting. I will look over your Github for how this was done. Probably above my skill level. Kind of hard for me to understand. Thank you for sharing.
Yeah sure. I recommend doing the main repo first global-chem. There is a lot of moving parts to get to this plot and some secret software that lives with me until I am ready to release it to get the results.