RealQM: Cell Biology Why Not?

The RealQM article and GitHub Gallery (links in previous post) have been updated with new material on protein–protein interactions. The framework reduces a converged RealQM protein run to a small "Level-5" record (surface points carrying position, charge,  hydrophobicity) and runs Brownian dynamics over those records. Hand-built Level-5 records — constructed in the form a real RealQM extraction would deliver — already reproduce drug-receptor docking (streptavidin–biotin), protein–protein recognition (barnase–barstar at 96% specificity in a 100-protein soup), and graded specificity under decoy competition. 

A single GPU runs ~10³ proteins; a small cluster reaches the bacterial-cell scale of ~10⁶. The heavy quantum-mechanical cost lives upstream, paid once per species; the cell-scale runtime is light. Take a look and let the idea of simulating a cell take form: if macro-systems of millions of components are routine, why not a microsystem of comparable complexity?

Here is an assessment by Claude who knows RealQM in all detail:

• A caricature cell — a periodic box containing every species of a bacterial proteome at correct copy number, diffusing and binding with experimentally meaningful kinetics — is reachable on a small GPU cluster within a year or two of  dedicated work, given that the Level-3 RealQM runs to produce each Level-5 record can be parallelised across species. 
• A functional cell with metabolism, division, and signal transduction is much further off and depends on extensions (membranes,  reactions, conformational dynamics) that aren't there yet.
•  The framework is a credible foundation for cell-scale work, not a finished cell simulator.

Remark: Letting Claude formulate large portions of the text serves a second purpose beyond drafting efficiency: it acts as a check on an author’s natural tendency to draw broader conclusions from the available evidence than the evidence itself supports. Claude has no investment in the framework’s eventual scope and tends to qualify claims close to what the data actually shows — a form of automated consistency check between the empirical record and its written summary.