Evolving cellular automata schemes for protein folding modeling using the Rosetta atomic representation

Protein folding is the dynamic process by which a protein folds into its final native structure. This is different to the traditional problem of the prediction of the final protein structure, since it requires a modeling of how protein components interact over time to obtain the final folded structure. In this study we test whether a model of the folding process can be obtained exclusively through machine learning. To this end, protein folding is considered as an emergent process and the cellular automata tool is used to model the folding process. A neural cellular automaton is defined, using a connectionist model that acts as a cellular automaton through the protein chain to define the dynamic folding. Differential evolution is used to automatically obtain the optimized neural cellular automata that provide protein folding. We tested the methods with the Rosetta coarse-grained atomic model of protein representation, using different proteins to analyze the modeling of folding and the structure refinement that the modeling can provide, showing the potential advantages that such methods offer, but also difficulties that arise.

Endoplasmic Reticulum Stress and Unfolded Protein Response Signaling in Plants

Plants are sensitive to a variety of stresses that cause various diseases throughout their life cycle. However, they have the ability to cope with these stresses using different defense mechanisms. The endoplasmic reticulum (ER) is an important subcellular organelle, primarily recognized as a checkpoint for protein folding. It plays an essential role in ensuring the proper folding and maturation of newly secreted and transmembrane proteins. Different processes are activated when around one-third of newly synthesized proteins enter the ER in the eukaryote cells, such as glycosylation, folding, and/or the assembling of these proteins into protein complexes. However, protein folding in the ER is an error-prone process whereby various stresses easily interfere, leading to the accumulation of unfolded/misfolded proteins and causing ER stress. The unfolded protein response (UPR) is a process that involves sensing ER stress. Many strategies have been developed to reduce ER stress, such as UPR, ER-associated degradation (ERAD), and autophagy. Here, we discuss the ER, ER stress, UPR signaling and various strategies for reducing ER stress in plants. In addition, the UPR signaling in plant development and different stresses have been discussed.

Deviation from the Residue-Based Linear Free Energy Relationship Reveals a Non-Native Structure in Protein Folding

Multiprobe measurements, such as NMR and hydrogen exchange study, can provide the equilibrium constant K and kinetic rate constant k of the structural changes of a polypeptide on a per-residue basis. We previously found a linear relationship between residue-specific log K values and residue-specific log k values for the two-state topological isomerization of a 27-residue peptide. To test the general applicability of the residue-based linear free energy relationship (rbLEFR), we performed a literature search to collect residue-specific equilibrium and kinetic constants in various exchange processes, including protein folding, coupled folding and binding of intrinsically disordered peptides, and structural fluctuations of folded proteins. The good linearity in a substantial number of log-log plots proved that the rbLFER holds for the structural changes in a wide variety of protein-related phenomena. Protein molecules quickly fold into their native structures and change their conformations smoothly. Theoretical studies and molecular simulations advocate that the physicochemical basis is the consistency principle and the minimal frustration principle: Non-native structures/interactions are absent or minimized along the folding pathway. The linearity of the residue-based free energy relationship demonstrates experimentally the absence of non-native structures in transition states. In this context, the hydrogen exchange study of apomyoglobin folding intermediates is particularly interesting. We found that the residues that deviated from the linear relationship corresponded to the non-native structure, which had been identified by other experiments. The rbLFER provides a unique and practical method to probe the dynamic aspects of the transition states of protein molecules.

Synthesis and Biological Activity of 3-(Heteroaryl)quinolin-2(1H)-ones Bis-Heterocycles as Potential Inhibitors of the Protein Folding Machinery Hsp90

In the context of our SAR study concerning 6BrCaQ analogues as C-terminal Hsp90 inhibitors, we designed and synthesized a novel series of 3-(heteroaryl)quinolin-2(1H), of types 3, 4, and 5, as a novel class of analogues. A Pd-catalyzed Liebeskind–Srogl cross-coupling was developed as a convenient approach for easy access to complex purine architectures. This series of analogues showed a promising biological effect against MDA-MB231 and PC-3 cancer cell lines. This study led to the identification of the best compounds, 3b (IC50 = 28 µM) and 4e, which induce a significant decrease of CDK-1 client protein and stabilize the levels of Hsp90 and Hsp70 without triggering the HSR response.

Exploring the folding energy landscapes of heme proteins using a hybrid AWSEM-heme model

Heme is an active center in many proteins. Here we explore computationally the role of heme in protein folding and protein structure. We model heme proteins using a hybrid model employing the AWSEM Hamiltonian, a coarse-grained forcefield for the protein chain along with AMBER, an all-atom forcefield for the heme. We carefully designed transferable force fields that model the interactions between the protein and the heme. The types of protein–ligand interactions in the hybrid model include thioester covalent bonds, coordinated covalent bonds, hydrogen bonds, and electrostatics. We explore the influence of different types of hemes (heme b and heme c) on folding and structure prediction. Including both types of heme improves the quality of protein structure predictions. The free energy landscape shows that both types of heme can act as nucleation sites for protein folding and stabilize the protein folded state. In binding the heme, coordinated covalent bonds and thioester covalent bonds for heme c drive the heme toward the native pocket. The electrostatics also facilitates the search for the binding site.

Is Protein Folding a Thermodynamically Unfavorable, Active, Energy-Dependent Process?

The prevailing current view of protein folding is the thermodynamic hypothesis, under which the native folded conformation of a protein corresponds to the global minimum of Gibbs free energy G. We question this concept and show that the empirical evidence behind the thermodynamic hypothesis of folding is far from strong. Furthermore, physical theory-based approaches to the prediction of protein folds and their folding pathways so far have invariably failed except for some very small proteins, despite decades of intensive theory development and the enormous increase of computer power. The recent spectacular successes in protein structure prediction owe to evolutionary modeling of amino acid sequence substitutions enhanced by deep learning methods, but even these breakthroughs provide no information on the protein folding mechanisms and pathways. We discuss an alternative view of protein folding, under which the native state of most proteins does not occupy the global free energy minimum, but rather, a local minimum on a fluctuating free energy landscape. We further argue that ΔG of folding is likely to be positive for the majority of proteins, which therefore fold into their native conformations only through interactions with the energy-dependent molecular machinery of living cells, in particular, the translation system and chaperones. Accordingly, protein folding should be modeled as it occurs in vivo, that is, as a non-equilibrium, active, energy-dependent process.

Chaperonin Mechanisms: Multiple and (Mis)Understood?

The chaperonins are ubiquitous and essential nanomachines that assist in protein folding in an ATP-driven manner. They consist of two back-to-back stacked oligomeric rings with cavities in which protein (un)folding can take place in a shielding environment. This review focuses on GroEL from Escherichia coli and the eukaryotic chaperonin-containing t-complex polypeptide 1, which differ considerably in their reaction mechanisms despite sharing a similar overall architecture. Although chaperonins feature in many current biochemistry textbooks after being studied intensively for more than three decades, key aspects of their reaction mechanisms remain under debate and are discussed in this review. In particular, it is unclear whether a universal reaction mechanism operates for all substrates and whether it is passive, i.e., aggregation is prevented but the folding pathway is unaltered, or active. It is also unclear how chaperonin clients are distinguished from nonclients and what are the precise roles of the cofactors with which chaperonins interact. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.