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• W4386846484 abstract "Abstract Various approaches have used neural networks as probabilistic models for the design of protein sequences. These inverse folding models employ different objective functions, which come with trade-offs that have not been assessed in detail before. This study introduces probabilistic definitions of protein stability and conformational specificity and demonstrates the relationship between these chemical properties and the $$p(text {structure}|text {seq})$$ <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML> <mml:mrow> <mml:mi>p</mml:mi> <mml:mo>(</mml:mo> <mml:mtext>structure</mml:mtext> <mml:mo>|</mml:mo> <mml:mtext>seq</mml:mtext> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> Boltzmann probability objective. This links the Boltzmann probability objective function to experimentally verifiable outcomes. We propose a novel sequence decoding algorithm, referred to as “BayesDesign”, that leverages Bayes’ Rule to maximize the $$p(text {structure}|text {seq})$$ <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML> <mml:mrow> <mml:mi>p</mml:mi> <mml:mo>(</mml:mo> <mml:mtext>structure</mml:mtext> <mml:mo>|</mml:mo> <mml:mtext>seq</mml:mtext> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> objective instead of the $$p(text {seq}|text {structure})$$ <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML> <mml:mrow> <mml:mi>p</mml:mi> <mml:mo>(</mml:mo> <mml:mtext>seq</mml:mtext> <mml:mo>|</mml:mo> <mml:mtext>structure</mml:mtext> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> objective common in inverse folding models. The efficacy of BayesDesign is evaluated in the context of two protein model systems, the NanoLuc enzyme and the WW structural motif. Both BayesDesign and the baseline ProteinMPNN algorithm increase the thermostability of NanoLuc and increase the conformational specificity of WW. The possible sources of error in the model are analyzed." @default.
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• W4386846484 date "2023-09-19" @default.
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• W4386846484 title "A probabilistic view of protein stability, conformational specificity, and design" @default.
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• W4386846484 doi "https://doi.org/10.1038/s41598-023-42032-1" @default.
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