Generation of eight hiPSCs lines from two pathogenic variants in CACNA1A using the CRISPR-Cas9 gene editing technology.

Developmental and epileptic encephalopathies (DEEs) are rare severe neurodevelopmental disorders with a cumulative incidence of 1:6.000 live births. Many epileptic conditions arise from single nucleotide variants in CACNA1A (calcium voltage-gated channel subunit alpha1 A), encoding the CaV2.1 calcium channel subunit. Human induced pluripotent stem cells (hiPSCs) are an optimal choice for modeling DEEs, as they can be differentiated in vitro into diverse neuronal subpopulations. Here, we report the generation of hiPSC lines with two pathogenic CACNA1A variants c.1767C > T, p. (Arg589Cys), referred to as R589C and c. 2139G > A, p.(Ala713Thr), referred to as A713T, previously associated with epilepsy. The variants were introduced into a hiPSC line from a healthy individual via CRISPR-Cas9 gene editing technology.

Top-down design of protein architectures with reinforcement learning.

As a result of evolutionary selection, the subunits of naturally occurring protein assemblies often fit together with substantial shape complementarity to generate architectures optimal for function in a manner not achievable by current design approaches. We describe a "top-down" reinforcement learning-based design approach that solves this problem using Monte Carlo tree search to sample protein conformers in the context of an overall architecture and specified functional constraints. Cryo-electron microscopy structures of the designed disk-shaped nanopores and ultracompact icosahedra are very close to the computational models. The icosohedra enable very-high-density display of immunogens and signaling molecules, which potentiates vaccine response and angiogenesis induction. Our approach enables the top-down design of complex protein nanomaterials with desired system properties and demonstrates the power of reinforcement learning in protein design.