Improving the quality of protein NMR structures by Rosetta refinement and its application in molecular replacement

This dissertation demonstrates restrained Rosetta refinement can improve the quality of protein NMR structures and describes a protocol to improve their phasing power. Recent studies manifest unrestrained Rosetta refinement can improve the stereochemical quality and geometry of protein NMR structures, to move NMR structures closer to their X-ray counterparts and consequently to improve their phasing power in a few cases. In this study, we intend to explore whether those observations stand corrected in general and the impact of incorporating NMR experimental restraints into Rosetta refinement. We developed a newer version of PdbStat software to convert Cyana/Xplor formatted restraints into Rosetta formatted restraints. Based on a dataset of 41 NESG NMR/X-ray structure pairs, we have done unrestrained and restrained Rosetta refinement for all the NMR structures. The knowledge based structural quality Z-scores are significantly improved by Rosetta refinement with or without restraints. Compared with unrestrained Rosetta refined structures, restrained Rosetta refined structures fit the experimental data better, are in better agreement with their X-ray counterparts and are generally of better phasing power, while unrestrained Rosetta refinement often drives the NMR structures further from their X-ray counterparts especially when the structural similarity between NMR structures and X-ray structures is high. To summarize, a majority of the experimental NMR restraints still apply for X-ray crystal structures determined at crystalline environment, and they can be utilized to guide Rosetta refinement to improve the quality of NMR structures. Molecular replacement (MR) is widely used for addressing the phase problem in X-ray crystallography. Historically, crystallographers have had limited success using NMR structures as MR search models. Here, we report a comprehensive investigation of the utility of protein NMR structures as MR search models, using a dataset of 25 NESG NMR/X-ray structure pairs. Starting from NMR ensembles prepared by an improved protocol, FindCore, correct MR solutions were obtained for 22 targets. Rosetta refinement of NMR structures provided MR solutions for another two proteins. We also demonstrate that such properly prepared NMR ensembles and X-ray crystal structures have similar performance when used as MR search models for homologous structures, particularly for targets with sequence identity >40%.Ph. D.Includes bibliographical referencesIncludes vitaby Binchen Ma

FIGURE 1 from Statistical Assessment of Drug Synergy from <i>In Vivo</i> Combination Studies Using Mouse Tumor Models

The quantification of in vivo synergy based on an unbiased metric of drug effect. A, Definition of eGR, an unbiased metric of in vivo drug effect. Upper graphs shows two synthetic curves, for illustrative purposes, depicting tumor growth and shrinkage measured by TV. Bottom graphs show the same tumor growth curves in natural log scale, and illustrate the calculation of eGR, which is defined as , where AUC is the size of the colored area and d is the study duration in days (see Materials and Methods for details). B, The 4-group design is the most common in vivo combination study, which has four treatment groups for the vehicle control, drug A, drug B, and drug A+B, with fixed doses for the two drugs. A group usually has multiple mice that vary in tumor growth curves and number of TV datapoints. C, The average tumor growth curves of the four groups. The relative survival is calculated for drugs A, B, A+B based on TV at a particular day, then the CI and SS are estimated under several models, only Bliss independence model is shown. D, Bootstrap confidence internals and P values are calculated for both CI and SS. The histogram, overlaid by a red fitted density curve, shows the distribution of 1,000 bootstrap values for CI or SS; the red dashed vertical line indicates additive effect (1 for CI and 0 for SS); the black triangle marks the calculated value for CI or SS; the blue horizontal line indicates the 95% confidence interval. invivoSyn is the name of our method as well as the software package implementing it.</p

FIGURE 7 from Statistical Assessment of Drug Synergy from <i>In Vivo</i> Combination Studies Using Mouse Tumor Models

A unified view of in vitro and in vivo synergy. Drug efficacy measurement, study design, and CI calculation are illustrated for the typical fixed-ratio in vitro combination study (A–C) and 4-group in vivo combination study (D–F). A, In in vitro cell assays, drug efficacy is measured at a single timepoint (e.g., 72 hours, the red dashed line) for a series of drug concentrations, where higher concentrations exert stronger antiproliferative effect as quantified by confluence percentage. B, In an in vitro combination study with the fixed-ratio design, dose–response curves are inferred for drugs A, B, A+B, using efficacy measured at 72 hours. C, The CI is estimated for a range of drug concentrations where high concentration causes higher fraction of affected (FA) cells. Therefore, the CI is dose dependent. D, In in vivo studies, drug efficacy is measured at a fixed dose (growth curve pointed by the red arrow) for the study duration. E, In an in vivo combination study with the 4-group design, tumor growth curves were obtained for vehicle control, drugs A, B, and A+B, each with a fixed dose. CI can be calculated at a particular day (cf. Eq. 4). F, The CI is calculated for a range of days in the study duration. Therefore, the CI is time dependent. We note that exponential growth kinetics is assumed for both cell proliferation (A) and tumor growth (D) under drug treatment, and well before reaching maximal values constrained by nutrient and space. Previous studies have provided theoretical (equation 5 in ref. 33) and empirical justifications (31).</p

FIGURE 6 from Statistical Assessment of Drug Synergy from <i>In Vivo</i> Combination Studies Using Mouse Tumor Models

Assessing synergy with tumor regrowth. Simulations were conducted to obtain empirical statistical power to detect Bliss synergy with respect to the number of mice n in a group, assuming equal number of mice in all four groups but with tumor regrowth. TV is measured twice a week for 3 weeks (on days 0, 4, 7, 10, 14, 18, 21) assuming that tumor DT is 7 days, and the TV cutoff is set to 3,000 mm3. No synergy is imposed. A and B, Tumors regrow under combo treatment due to intrinsic resistance where 10% of tumor cells are intrinsically resistant to treatments A and A+B. C and D, Tumors regrow under combo treatment due to induced resistance where 10% of tumor cells resume growth with initial GR at day 10 under treatments A and A+B. In both scenarios, empirical power exhibits dependence on both mouse number n and observation time Tobs. When Tobs is sufficiently long (40–60 days), invivoSyn shows low empirical power, therefore low FDR, for synergy detection.</p

Protein NMR Structures Refined with Rosetta Have Higher Accuracy Relative to Corresponding X‑ray Crystal Structures

We have found that refinement of protein NMR structures using Rosetta with experimental NMR restraints yields more accurate protein NMR structures than those that have been deposited in the PDB using standard refinement protocols. Using 40 pairs of NMR and X-ray crystal structures determined by the Northeast Structural Genomics Consortium, for proteins ranging in size from 5–22 kDa, restrained Rosetta refined structures fit better to the raw experimental data, are in better agreement with their X-ray counterparts, and have better phasing power compared to conventionally determined NMR structures. For 37 proteins for which NMR ensembles were available and which had similar structures in solution and in the crystal, all of the restrained Rosetta refined NMR structures were sufficiently accurate to be used for solving the corresponding X-ray crystal structures by molecular replacement. The protocol for restrained refinement of protein NMR structures was also compared with restrained CS-Rosetta calculations. For proteins smaller than 10 kDa, restrained CS-Rosetta, starting from extended conformations, provides slightly more accurate structures, while for proteins in the size range of 10–25 kDa the less CPU intensive restrained Rosetta refinement protocols provided equally or more accurate structures. The restrained Rosetta protocols described here can improve the accuracy of protein NMR structures and should find broad and general for studies of protein structure and function

De novo design of a fluorescence-activating β-barrel.

The regular arrangements of β-strands around a central axis in β-barrels and of α-helices in coiled coils contrast with the irregular tertiary structures of most globular proteins, and have fascinated structural biologists since they were first discovered. Simple parametric models have been used to design a wide range of α-helical coiled-coil structures, but to date there has been no success with β-barrels. Here we show that accurate de novo design of β-barrels requires considerable symmetry-breaking to achieve continuous hydrogen-bond connectivity and eliminate backbone strain. We then build ensembles of β-barrel backbone models with cavity shapes that match the fluorogenic compound DFHBI,&nbsp;and use a hierarchical grid-based search method to simultaneously optimize the rigid-body placement of DFHBI in these cavities and the identities of the surrounding amino acids to achieve high shape and chemical complementarity. The designs have high structural accuracy and bind and fluorescently activate DFHBI in vitro and in Escherichia coli, yeast and mammalian cells. This de novo design of small-molecule binding activity, using backbones custom-built to bind the ligand, should enable the design of increasingly sophisticated ligand-binding proteins, sensors and catalysts that are not limited by the backbone geometries available in known protein structures