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MYC, fusion oncoproteins and transcription factors have shapeless, flexible regions that drugs cannot grip. Deep-learning protein design tools such as RFdiffusion may be able to invent binders that clamp them, for use as degradation handles, intrabodies or targeting domains for CAR and bispecific therapies rather than as drugs themselves.
Deep-learning protein design (RFdiffusion, AlphaFold-based hallucination) has produced high-affinity binders to structured targets and, increasingly, to peptides and disordered segments. Intrinsically disordered regions of MYC, fusion oncoproteins and transcription factors are the classic undruggable surfaces. Designed binders could serve as degradation handles, intrabodies, or CAR and bispecific targeting domains rather than as drugs themselves.
Shares Generate:Biomedicines, Drugging the 'undruggable' cancer targets, The undruggable drivers.
Shares Drugging the 'undruggable' cancer targets, AI-driven drug & target discovery, The undruggable drivers.
Shares Drugging the 'undruggable' cancer targets, AI-driven drug & target discovery, The undruggable drivers.
Shares Drugging the 'undruggable' cancer targets, The undruggable drivers.
Shares Drugging the 'undruggable' cancer targets, AI-driven drug & target discovery, The undruggable drivers.
Shares Drugging the 'undruggable' cancer targets, The undruggable drivers.
Shares Drugging the 'undruggable' cancer targets, The undruggable drivers.
Shares Generate:Biomedicines, AI-driven drug & target discovery.
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