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I'm asking this as a layperson without much knowledge in biology, so please correct me if my understanding is wrong.

Recently DeepMind's AlphaFold managed to predict protein structure from acid amino sequence with stunning accuracy. We are being told that this could "pave ways toward advances in drug discovery."

But I fail to see how it can happen. From my understanding the combination of protein structure is infinite, and if we tweak a protein structure that works good to fight against a virus, it will either work better or worse, but the key point is we don't know until we try. So essentially this is still a hit-and-miss thing, depending purely on dumb luck.

So how can the fast, accurate prediction of protein folding help in drug discovery?

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  • $\begingroup$ Why is this question downvoted? $\endgroup$
    – Graviton
    Jul 30 at 0:55
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Firstly protein structures are not infinite. Most proteins adopt specific structure.
Drugs carry out their function by binding to its target protein. Structure prediction helps drug discovery process in two ways -

  1. it allows identification of pockets in target proteins (where drugs can bind) whose structures are not yet solved using experimental methods
  2. it allows in silico experimentation i.e. you can take a large number of molecules and simulate whether they will bind to a specific location in your target

I would suggest going through these reviews to get a better overview of the importance of fast and accurate structure determination in drug discovery :

  1. Verinde and Hol, 1994, Structure
  2. Montfort and Workman, 2017, Essays in Biochemistry
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Simulation of Ligand-Receptor binding usually involves the retrieval of X-ray crystallography of the desired protein (Receptor) from bioinformatic databases. The X-ray data of the protein contains important features of the protein, one of which is Protein conformation (Folding status). Gathering X-ray crystallography data of a specific new polypeptide is an extremely hard, time consuming process which requires advanced techniques and accurate purification of the protein from biological systems. Therefore if an algorithm can predict the folding of a protein correctly (at least to some extents) , other algorithms can benefit from this independence from experimental results. Fast, simultaneous docking surveys (Virtual Screening) would be available with a lot more ease eventually leading to designing new medications only by computer simulations (Which requires extremely less financial budget compared to testing each candidate molecule one by one on animals)

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