Intrinsically disordered proteins (IDPs) are a newly recognized class of functional proteins that rely on a lack of stable structure for function. They are highly prevalent in biology, play fundamental roles, and are extensively involved in human diseases. For signaling and regulation, IDPs often fold into stable structures upon binding to specific targets. The mechanisms of these coupled binding and folding processes are of significant importance because they underlie the organization of regulatory networks that dictate various aspects of cellular decision-making. This review first discusses the challenge in detailed experimental characterization of these heterogeneous and dynamics proteins and the unique and exciting opportunity for physics-based modeling to make crucial contributions, and then summarizes key lessons from recent de novo simulations of the structure and interactions of several regulatory IDPs.

We have simulated pure liquid butane, methanol and hydrated alanine polypeptide with the Monte Carlo technique using three kinds of random number generators -the standard Linear Congruential Generator (LCG), a modification of the LCG with additional randomization used in the BOSS software, and the "Mersenne Twister" generator by Matsumoto and Nishimura. While using the latter two random number generators leads to reasonably similar physical features, the LCG produces a significant different results. For the pure fluids, a noticeable expansion occurs. Using the original LCG on butane yields a molecular volume of 171.4 Å 3 per molecule compared to ca. 163.6-163.9 Å 3 for the other two generators, a deviation of about 5%. For methanol, the LCG produces an average volume of 86.3 Å 3 per molecule, which is about 24% higher than the 68.8-70.2 Å 3 obtained with the random number generator in BOSS and the generator by Matsumoto and Nishimura. In case of the hydrated tridecaalanine peptide, the volume and energy tend to be noticeably greater with the LCG than with the BOSS (modified LCG) random number generator. For the simulated hydrated extended conformation of tridecaalanine, the difference in volume reached ca. 87%. The uniformity and periodicity of the generators do not seem to play the crucial role in these phenomena. We conclude that it is important to test a random number generator by modeling a system such as the pure liquid methanol with a well-established force field before routinely employing it in Monte Carlo simulations.

We have extended our previous studies of calculating acidity constants for the acidic residues found in the turkey ovomucoid third domain protein (OMTKY3) by determining the relative pKa values for the basic residues (Lys13, Arg21, Lys29, Lys34, His52, and Lys55). A polarizable force field (PFF) was employed. The values of the pKa were found by direct comparison of energies of solvated protonated and deprotonated forms of the protein. Poisson Boltzmann (PBF) and Generalized Born (SGB) continuum solvation models represent the hydration, and a non-polarizable fixed-charges OPLS-AA force field was used for comparison. Our results indicate that (i) the pKa values of the basic residues can be found in close agreement with the experimental values when a PFF is used in conjunction with the PBF solvation model, (ii) it is sufficient to take into the account only the residues which are in close proximity (hydrogen bonded) to the residue in question, and (iii) The PBF solvation model is superior to the SGB solvation model for these pKa calculations. The average error with the PBF/PFF model is only 0.7 pH units, compared with 2.2 and 6.1 units for the PBF/OPLS and SGB/OPLS, respectively. The maximum deviation of the PBF/PFF results from the experimental values is 1.7 pH units compared with 6.0 pH units for the PBF/OPLS. Moreover, the best results were obtained while using an advanced non-polar energy calculation scheme. The overall conclusion is that this methodology and force field are suitable for accurate assessment of pKa shifts for both acidic basic protein residues.

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To better understand the adsorption of long-chain poly(1 → 4)-β-D-glucans on carbon surfaces as well as interactions responsible for this adsorption, we use a comparative study involving mesoporous carbon-silica composite materials that have been etched to varying degrees and all-atom molecular dynamics simulations. The materials synthesized as part of this etching study consist of an as-synthesized composite material (MCN-MSN), MCN-MSN-0.5 (composite materials consisting of 50% carbon by mass), MCN-MSN-0.3 (composite materials consisting of 70% carbon by mass), and MCN, in which silica etching was conducted using an aqueous ethanolic solution of either NaOH or HF. Data for the adsorption of long-chain glucans to these materials from concentrated aqueous HCl (37 wt %) solution demonstrate a direct relationship between the amount of β-glu adsorption and the magnitude of exposed carbon mesopore surface area, which systematically increases and is also accompanied by an increase in the mesopore size during silica etching. This demonstrates β-glu adsorption as occurring on internal carbon mesopores rather than exclusively on the external carbon surface. These experimental data on adsorption were corroborated by molecular dynamics (MD) simulations of β-glu adsorption to a graphene bilayer separated by a distance of 3.2 nm, chosen to correspond to the carbon mesopore diameter of the experimental system. Simulation results using a variety of β-glu solvent systems demonstrate the rapid adsorption of a β-glu strand on the graphitic carbon surface via axial coupling and are consistent with experimentally observed trends in fast adsorption kinetics. Solvent-mediated effects such as small-scale hydrophobicity and preferential interactions with ions are shown to play important roles in modulating glucan adsorption to carbon surfaces, whereas experimental data on hydrophobically modified silica demonstrate that hydrophobicity in and of itself is insufficient to cause β-glu adsorption from concentrated aqueous HCl solution.