Target highlights in CASP14 : Analysis of models by structure providers

Abstract The biological and functional significance of selected CASP14 targets are described by the authors of the structures. The authors highlight the most relevant features of the target proteins and discuss how well these features were reproduced in the respective submitted predictions. The overall ability to predict three-dimensional structures of proteins has improved remarkably in CASP14, and many difficult targets were modelled with impressive accuracy. For the first time in the history of CASP, the experimentalists not only highlighted that computational models can accurately reproduce the most critical structural features observed in their targets, but also envisaged that models could serve as a guidance for further studies of biologically-relevant properties of proteins. This article is protected by copyright. All rights reserved.Peer reviewe

Inhibition of \u3cem\u3eEscherichia coli\u3c/em\u3e ATP Synthase Using Bioflavonoids.

ATP synthase is the fundamental means of the cellular energy production in all organisms. Malfunction of ATP synthase is associated with multiple disease conditions. This enzyme is not only implicated in disease conditions but also likely to contribute in new therapies for multiple diseases by being a molecular target for several inhibitors. Bioflavonoids are a class of plant secondary metabolites known to exhibit antioxidants, chemopreventive, and chemotherapeutic properties. Their actual mode of action is not clear; however, some bioflavonoid are known to block the action of enzymes and other substances that promote the growth of cancer cells by binding to the multiple molecular targets in the body including ATP synthase. The most common dietary polyphenol resveratrol was shown to induce apoptosis via mitochondrial pathways and has chemopreventive properties against prostate cancer. Here we report the general inhibitory effects of dietary bioflavonoids on ATP synthase enzyme and intact E. coli cells

Structures of regulatory machinery reveal novel molecular mechanisms controlling B. subtilis nitrogen homeostasis

In Bacillus subtilis, nitrogen homeostasis is controlled by a unique circuitry composed of the regulator TnrA and the repressor GlnR. Here, Schumacher et al. describe a comprehensive molecular dissection of this network that reveals novel mechanisms, including oligomeric transformations, by which their inducible signal transduction domains are employed to provide a readout of nitrogen levels.All cells must sense and adapt to changing nutrient availability. However, detailed molecular mechanisms coordinating such regulatory pathways remain poorly understood. In Bacillus subtilis, nitrogen homeostasis is controlled by a unique circuitry composed of the regulator TnrA, which is deactivated by feedback-inhibited glutamine synthetase (GS) during nitrogen excess and stabilized by GlnK upon nitrogen depletion, and the repressor GlnR. Here we describe a complete molecular dissection of this network. TnrA and GlnR, the global nitrogen homeostatic transcription regulators, are revealed as founders of a new structural family of dimeric DNA-binding proteins with C-terminal, flexible, effector-binding sensors that modulate their dimerization. Remarkably, the TnrA sensor domains insert into GS intersubunit catalytic pores, destabilizing the TnrA dimer and causing an unprecedented GS dodecamer-to-tetradecamer conversion, which concomitantly deactivates GS. In contrast, each subunit of the GlnK trimer “templates” active TnrA dimers. Unlike TnrA, GlnR sensors mediate an autoinhibitory dimer-destabilizing interaction alleviated by GS, which acts as a GlnR chaperone. Thus, these studies unveil heretofore unseen mechanisms by which inducible sensor domains drive metabolic reprograming in the model Gram-positive bacterium B. subtilis

Structures of regulatory machinery reveal novel molecular mechanisms controllingB. subtilisnitrogen homeostasis

All cells must sense and adapt to changing nutrient availability. However, detailed molecular mechanisms coordinating such regulatory pathways remain poorly understood. In Bacillus subtilis, nitrogen homeostasis is controlled by a unique circuitry composed of the regulator TnrA, which is deactivated by feedback-inhibited glutamine synthetase (GS) during nitrogen excess and stabilized by GlnK upon nitrogen depletion, and the repressor GlnR. Here we describe a complete molecular dissection of this network. TnrA and GlnR, the global nitrogen homeostatic transcription regulators, are revealed as founders of a new structural family of dimeric DNA-binding proteins with C-terminal, flexible, effector-binding sensors that modulate their dimerization. Remarkably, the TnrA sensor domains insert into GS intersubunit catalytic pores, destabilizing the TnrA dimer and causing an unprecedented GS dodecamer-to-tetradecamer conversion, which concomitantly deactivates GS. In contrast, each subunit of the GlnK trimer “templates” active TnrA dimers. Unlike TnrA, GlnR sensors mediate an autoinhibitory dimer-destabilizing interaction alleviated by GS, which acts as a GlnR chaperone. Thus, these studies unveil heretofore unseen mechanisms by which inducible sensor domains drive metabolic reprograming in the model Gram-positive bacterium B. subtilis

Combining small angle X-ray scattering (SAXS) with protein structure predictions to characterize conformations in solution

Accurate protein structure predictions, enabled by recent advances in machine learning algorithms, provide an entry point to probing structural mechanisms and to integrating and querying many types of biochemical and biophysical results. Limitations in such protein structure predictions can be reduced and addressed through comparison to experimental Small Angle X-ray Scattering (SAXS) data that provides protein structural information in solution. SAXS data can not only validate computational predictions, but can improve conformational and assembly prediction to produce atomic models that are consistent with solution data and biologically relevant states. Here, we describe how to obtain protein structure predictions, compare them to experimental SAXS data and improve models to reflect experimental information from SAXS data. Furthermore, we consider the potential for such experimentally-validated protein structure predictions to broadly improve functional annotation in proteins identified in metagenomics and to identify functional clustering on conserved sites despite low sequence homology

Universally Accessible Structural Data on Macromolecular Conformation, Assembly, and Dynamics by Small Angle X-Ray Scattering for DNA Repair Insights.

Structures provide a critical breakthrough step for biological analyses, and small angle X-ray scattering (SAXS) is a powerful structural technique to study dynamic DNA repair proteins. As toxic and mutagenic repair intermediates need to be prevented from inadvertently harming the cell, DNA repair proteins often chaperone these intermediates through dynamic conformations, coordinated assemblies, and allosteric regulation. By measuring structural conformations in solution for both proteins, DNA, RNA, and their complexes, SAXS provides insight into initial DNA damage recognition, mechanisms for validation of their substrate, and pathway regulation. Here, we describe exemplary SAXS analyses of a DNA damage response protein spanning from what can be derived directly from the data to obtaining super resolution through the use of SAXS selection of atomic models. We outline strategies and tactics for practical SAXS data collection and analysis. Making these structural experiments in reach of any basic and clinical researchers who have protein, SAXS data can readily be collected at government-funded synchrotrons, typically at no cost for academic researchers. In addition to discussing how SAXS complements and enhances cryo-electron microscopy, X-ray crystallography, NMR, and computational modeling, we furthermore discuss taking advantage of recent advances in protein structure prediction in combination with SAXS analysis

Target highlights in CASP14: Analysis of models by structure providers.

The biological and functional significance of selected Critical Assessment of Techniques for Protein Structure Prediction 14 (CASP14) targets are described by the authors of the structures. The authors highlight the most relevant features of the target proteins and discuss how well these features were reproduced in the respective submitted predictions. The overall ability to predict three-dimensional structures of proteins has improved remarkably in CASP14, and many difficult targets were modeled with impressive accuracy. For the first time in the history of CASP, the experimentalists not only highlighted that computational models can accurately reproduce the most critical structural features observed in their targets, but also envisaged that models could serve as a guidance for further studies of biologically-relevant properties of proteins