Alternative title: Small changes in protein structure improves quantum mechanics-based chemical shift prediction Can QM-based chemical shift prediction be made as accurate as empirical methods by making small changes to the protein structure? If these changes are small enough, it may not make sense to talk if an improvement Real question (not addressed here) if protein structure determination is more accurate with ProCS15. E.g. does one get better structures starting from 4-6 Å structures? Comparison to CHARMM only refinement?
ABSTRACT We present ProCS15: A program that computes the isotropic chemical shielding values of backbone and Cβ atoms given a protein structure in less than a second. ProCS15 is based on around 2.35 million OPBE/6-31G(d,p)//PM6 calculations on tripeptides and small structural models of hydrogen-bonding. The ProCS15-predicted chemical shielding values are compared to experimentally measured chemical shifts for Ubiquitin and the third IgG-binding domain of Protein G through linear regression and yield RMSD values below 2.2, 0.7, and 4.8 ppm for carbon, hydrogen, and nitrogen atoms respectively. These RMSD values are very similar to corresponding RMSD values computed using OPBE/6-31G(d,p) for the entire structure for each protein. The maximum RMSD values can be reduced by using NMR-derived structural ensembles of Ubiquitin. For example, for the largest ensemble the largest RMSD values are 1.7, 0.5, and 3.5 ppm for carbon, hydrogen, and nitrogen. The corresponding RMSD values predicted by several empirical chemical shift predictors range between 0.7 - 1.1, 0.2 - 0.4, and 1.8 - 2.8 ppm for carbon, hydrogen, and nitrogen atoms, respectively.
INTRODUCTION For centuries, humans have wondered if there is intelligent life elsewhere in the universe. With the advent of telescopes capable of detecting planets around other stars, exoplanets, we would like to determine if these planets are capable of harboring life. In our solar system, spacecrafts and landers have been sent to our terrestrial neighbors to look for life. Sample return missions, though costly in both time and money, are one sure fire way to discover if a material ever has, ever could, or contains any familiar life. Barring that, in situ measurement from landers are next best. For exoplanets, these methods are impossible. Therefore, we use remote sensing techniques. What light should we look for to detect life? Life, as we know it, requires certain surface and atmospheric conditions. We require oxygen to breathe, ozone to protect us from harmful rays, and liquid water on the surface to serve as a catalyst for biochemical reactions. These signatures of life can be detected in the spectrum of a planetary atmosphere. To understand how biology can affect the atmosphere it is critical to understand atmospheres in habitable and non-habitable situations. Ideally a spectrum would reveal features related to water and ozone. Direct imaging of a planet would be ideal. Both of these techniques rely on the planet being bright enough and distant enough from its star to resolve them separately. The systems for which these techniques have been applied are few in number. Conversely, there are a number of photometric surveys searching for and characterizing exoplanets. Kepler’s high-precision light curves have provided a cornucopia of information buried within the noise of other surveys. Not only are they able to provide a measure of stellar limb darkening, the period of the planet, the size of the planet, and the orbital semi-major axis, but these light curves may also provide information about the temperature, albedo, and even mass of the planet. In our project, we will demonstrate what can be learned from the albedo and temperature for several well-known exoplanets. We will introduce the components of light curves and their relationship to the geometry of the system. We later discuss the atmospheric implications for these planets, and finally what a potentially habitable terrestrial planet would look like.