HIV maturation requires multiple cleavage of long polyprotein chains into functional proteins that include the viral protease itself. Initial cleavage by the protease dimer occurs from within these precursors, and yet only a single protease monomer is embedded in each polyprotein chain. Self-activation has been proposed to start from a partially dimerized protease formed from monomers of different chains binding its own N termini by self-association to the active site, but a complete structural understanding of this critical step in HIV maturation is missing. Here, we captured the critical self-association of immature HIV-1 protease to its extended amino-terminal recognition motif using large-scale molecular dynamics simulations, thus confirming the postulated intramolecular mechanism in atomic detail. We show that self-association to a catalytically viable state requires structural cooperativity of the flexible β-hairpin “flap” regions of the enzyme and that the major transition pathway is first via self-association in the semiopen/open enzyme states, followed by enzyme conformational transition into a catalytically viable closed state. Furthermore, partial N-terminal threading can play a role in self-association, whereas wide opening of the flaps in concert with self-association is not observed. We estimate the association rate constant ( k _on ) to be on the order of ∼1 × 10 ⁴ s ⁻¹ , suggesting that N-terminal self-association is not the rate-limiting step in the process. The shown mechanism also provides an interesting example of molecular conformational transitions along the association pathway.

De novo protein design is of fundamental interest to synthetic biology, with a plethora of computational methods of various degrees of generality developed in recent years. Here, we introduce AlphaDesign, a hallucination-based computational framework for de novo protein design developed with maximum generality and usability in mind, which combines AlphaFold with autoregressive diffusion models to enable rapid generation and computational validation of proteins with controllable interactions, conformations and oligomeric state without the requirement for class-dependent model re-training or fine-tuning. We apply our framework to design and systematically validate in vivo active inhibitors of a family of bacterial phage defense systems with toxic effectors called retrons, paving the way towards efficient, rational design of novel proteins as biologics.