4 ms·

> but when the equations of physics are so weak that they can't even fold a protein, how are we going to use them to model the interaction of a potential drug w

> but when the equations of physics are so weak that they can't even fold a protein, how are we going to use them to model the interaction of a potential drug with a protein Minor nit: the equations aren't weak at all — they predict the gyromagnetic moment of an isolated electron to ten decimal digits of agreement with experiment. The weakness is in the computational implementation of those equations, i.e., solving the equations in a reasonable time. You can perform a relativistic quantum monte carlo simulation of protein folding, and I guarantee the results will match those obtained in the lab to whatever level of accuracy you desire, but you'll have to wait longer than the age of the universe for the computation to finish running. Also, for work on small proteins, the calculated chemical properties match the experimentally tested ones very closely nowadays. The problem is all of the unknown interactions that a new drug has with the rest of the human body outside of one protein. And without a large atomistic model of a human body, it's going to be a long time before simulation can solve that problem.

epistasis 10y ago
> The weakness is in the computational implementation of those equations, i.e., solving the equations in a reasonable time. You can perform a relativistic quantum monte carlo simulation of protein folding, and I guarantee the results will match those obtained in the lab to whatever level of accuracy you desire, but you'll have to wait longer than the age of the universe for the computation to finish running. This is precisely what I mean by "weak." The equation looks great on paper, but isn't so useful in practice. And the problem isn't predicting just one protein-drug binding, it's predicting the interaction with all known proteins, all molecular complexes, and the biofilms, etc. I would go so far to say that Physics with a capital P is not so useful for many physical problems at all. Where Physics is useful, it's unbelievably useful, but its domain in the physical world is vanishingly tiny. Physics kind of has the reverse problem of AI. With AI, when you finally solve a problem, it's no longer considered AI, and AI is continued to be considered a failure. With Physics, a problem isn't part of the body of Physics until it's been solved, at which Physics is now considered a great success.

epistasis 10y ago

> The weakness is in the computational implementation of those equations, i.e., solving the equations in a reasonable time. You can perform a relativistic quantum monte carlo simulation of protein folding, and I guarantee the results will match those obtained in the lab to whatever level of accuracy you desire, but you'll have to wait longer than the age of the universe for the computation to finish running. This is precisely what I mean by "weak." The equation looks great on paper, but isn't so useful in practice. And the problem isn't predicting just one protein-drug binding, it's predicting the interaction with all known proteins, all molecular complexes, and the biofilms, etc. I would go so far to say that Physics with a capital P is not so useful for many physical problems at all. Where Physics is useful, it's unbelievably useful, but its domain in the physical world is vanishingly tiny. Physics kind of has the reverse problem of AI. With AI, when you finally solve a problem, it's no longer considered AI, and AI is continued to be considered a failure. With Physics, a problem isn't part of the body of Physics until it's been solved, at which Physics is now considered a great success.