J Chem Inf Model - Building a three-dimensional model of CYP2C9 inhibition using the Autocorrelator: an autonomous model generator.

Tópicos

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Resumo

In modern day drug discovery campaigns, computational chemists have to be concerned not only about improving the potency of molecules but also reducing any off-target ADMET activity. There are a plethora of antitargets that computational chemists may have to consider. Fortunately many antitargets have crystal structures deposited in the PDB. These structures are immediately useful to our Autocorrelator: an automated model generator that optimizes variables for building computational models. This paper describes the use of the Autocorrelator to construct high quality docking models for cytochrome P450 2C9 (CYP2C9) from two publicly available crystal structures. Both models result in strong correlation coefficients (R? > 0.66) between the predicted and experimental determined log(IC50) values. Results from the two models overlap well with each other, converging on the same scoring function, deprotonated charge state, and predicted the binding orientation for our collection of molecules.

Resumo Limpo

modern day drug discoveri campaign comput chemist concern improv potenc molecul also reduc offtarget admet activ plethora antitarget comput chemist may consid fortun mani antitarget crystal structur deposit pdb structur immedi use autocorrel autom model generat optim variabl build comput model paper describ use autocorrel construct high qualiti dock model cytochrom p c cypc two public avail crystal structur model result strong correl coeffici r predict experiment determin logic valu result two model overlap well converg score function deproton charg state predict bind orient collect molecul

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