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I don't think quantum computing will have any sort of impact on drug discovery. Chad mentioned quantum computing's impact on drugs. Anybody know what he's refer

I don't think quantum computing will have any sort of impact on drug discovery. Chad mentioned quantum computing's impact on drugs. Anybody know what he's referring to? I haven't seen anything to suggest that there's big problems out there waiting to be solved by powerful computing capabilities. Has anyone else found something that suggests there's active problems waiting for quantum computers? I've always found the missing thing in life saving pharmaceuticals is sick people to test compounds on. Nonetheless, good to see YC pushing the envelope on impactful stuff. I hope they desperately bring some inorganic and organic chemists with 10+ years of experience. It would open a new can of ventures that are meaningful. The good problems, the great ones, are in chemistry.

6nf 10y ago
He means using computational chemistry to predict what different drugs might do without actually having to produce them one by one first. We are terrible at predicting how large molecules will act because they are complex quantum systems. So using a quantum computer to model them will hopefully be very successful.
- kumarski 10y ago
  Math doesn't magically understand chemistry and context. Biology simply isn't that discrete. It's like 4000 years of spaghetti code.
  - 6nf 10y ago
    Have you studied computational chemistry?
hannob 10y ago
> I don't think quantum computing will have any sort of impact on drug discovery. I also was very surprised by that. I think it's probably 98% hype and 2% truth. There might be cases where the better understanding of physics brought by QC will impact a better understanding of biology. But I'd be very surprised if that made a big impact. > I've always found the missing thing in life saving pharmaceuticals is sick people to test compounds on. I don't think that's the case either. I think people who have a life-threatening illness are pretty willing to take part in trials. What I'd rather think is that likely the most important thing is to apply stricter scientific standards. Pharma companies have been complaining that they can't replicate the vast majority of pre-clinical cancer studies. The pharma companies themselves are also guilty of skewing research by hiding results and not sharing data. That's the thing that's holding up research. There's too much crappy science that wastes resources.
- kumarski 10y ago
  This is the case. Finding someone with the perfect storm of conditions is really really tough. The problem is that all the studies really have to be n=1 and the hunt for drug targets is now the hunt for the black swan.
adamgravitis 10y ago
The main computationally intractable problems around drug discovery surround protein folding and identifying macromolecule shapes. This is necessary to infer receptor sites for potential drug targets. The problem is massively intractable. QC could revolutionize the space.
- Hydraulix989 10y ago
  Remember though, NP complete problems still are intractable (exponential complexity) even for quantum computers, to say nothing of NP hard. Unger and Moult (1993) have shown a three-dimensional protein folding model to be NP-complete, and a two- and three-dimensional mathematical model describing the folding process as a free energy minimization problem is NP-hard: https://www.gwern.net/docs/1993-fraenkel.pdf https://www.gwern.net/docs/1993-fraenkel.pdf

6nf 10y ago

He means using computational chemistry to predict what different drugs might do without actually having to produce them one by one first. We are terrible at predicting how large molecules will act because they are complex quantum systems. So using a quantum computer to model them will hopefully be very successful.

kumarski 10y ago
Math doesn't magically understand chemistry and context. Biology simply isn't that discrete. It's like 4000 years of spaghetti code.
- 6nf 10y ago
  Have you studied computational chemistry?

hannob 10y ago

> I don't think quantum computing will have any sort of impact on drug discovery. I also was very surprised by that. I think it's probably 98% hype and 2% truth. There might be cases where the better understanding of physics brought by QC will impact a better understanding of biology. But I'd be very surprised if that made a big impact. > I've always found the missing thing in life saving pharmaceuticals is sick people to test compounds on. I don't think that's the case either. I think people who have a life-threatening illness are pretty willing to take part in trials. What I'd rather think is that likely the most important thing is to apply stricter scientific standards. Pharma companies have been complaining that they can't replicate the vast majority of pre-clinical cancer studies. The pharma companies themselves are also guilty of skewing research by hiding results and not sharing data. That's the thing that's holding up research. There's too much crappy science that wastes resources.

kumarski 10y ago
This is the case. Finding someone with the perfect storm of conditions is really really tough. The problem is that all the studies really have to be n=1 and the hunt for drug targets is now the hunt for the black swan.

adamgravitis 10y ago

The main computationally intractable problems around drug discovery surround protein folding and identifying macromolecule shapes. This is necessary to infer receptor sites for potential drug targets. The problem is massively intractable. QC could revolutionize the space.

Hydraulix989 10y ago
Remember though, NP complete problems still are intractable (exponential complexity) even for quantum computers, to say nothing of NP hard. Unger and Moult (1993) have shown a three-dimensional protein folding model to be NP-complete, and a two- and three-dimensional mathematical model describing the folding process as a free energy minimization problem is NP-hard: https://www.gwern.net/docs/1993-fraenkel.pdf https://www.gwern.net/docs/1993-fraenkel.pdf