Stimuli-responsive, self-assembling nanomaterials hold a great promise to revolutionize medicine and technology. However, current discovery is slow and often serendipitous. Here we report a multiscale modeling study to elucidate the pH-controlled self-assembly of nanofibers from the peptide amphiphiles, palmitoyl-I-A₃E₄-NH₂. The coarse-grained simulations revealed the formation of random-coil based spherical micelles at strong electrostatic repulsion. However, at weak or no electrostatic repulsion, the micelles merge into a nanofiber driven by the β-sheet formation between the peptide segments. The all-atom constant pH molecular dynamics revealed a cooperative transition between random coil and β-sheet in the pH range 6-7, matching the CD data. Interestingly, although the bulk pK_a is more than one unit below the transition pH, consistent with the titration data, the highest pK_a's coincide with the transition pH, suggesting that the latter may be tuned by modulating the pK_a's of a few solvent-buried Glu side chains. Together, these data offer, to our best knowledge, the first multiresolution and quantitative view of the pH-dependent self-assembly of nanofibers. The novel protocols and insights gained are expected to advance the computer-aided design and discovery of pH-responsive nanomaterials.

Since its inception nearly a half century ago, CHARMM has been playing a central role in computational biochemistry and biophysics. Commensurate with the developments in experimental research and advances in computer hardware, the range of methods and applicability of CHARMM have also grown. This review summarizes major developments that occurred after 2009 when the last review of CHARMM was published. They include the following: new faster simulation engines, accessible user interfaces for convenient workflows, and a vast array of simulation and analysis methods that encompass quantum mechanical, atomistic, and coarse-grained levels, as well as extensive coverage of force fields. In addition to providing the current snapshot of the CHARMM development, this review may serve as a starting point for exploring relevant theories and computational methods for tackling contemporary and emerging problems in biomolecular systems. CHARMM is freely available for academic and nonprofit research at https://academiccharmm.org/program.