Proteins-Structure Function and Bioinformatics最新文献

Antibody light chain amyloidosis is a disorder in which protein aggregates, mainly composed of immunoglobulin light chains, deposit in diverse tissues impairing the correct functioning of organs. Interestingly, due to the high susceptibility of antibodies to mutations, AL amyloidosis appears to be strongly patient-specific. Indeed, every patient will display their own mutations that will make the proteins involved prone to aggregation thus hindering the study of this disease on a wide scale. In this framework, determining the molecular mechanisms that drive the aggregation could pave the way to the development of patient-specific therapeutics. Here, we focus on a particular patient-derived light chain, which has been experimentally characterized. We investigated the early phases of the aggregation pathway through extensive full-atom molecular dynamics simulations, highlighting a structural rearrangement and the exposure of two hydrophobic regions in the aggregation-prone species. Next, we moved to consider the pathological dimerization process through docking and molecular dynamics simulations, proposing a dimeric structure as a candidate pathological first assembly. Overall, our results shed light on the first phases of the aggregation pathway for a light chain at an atomic level detail, offering new structural insights into the corresponding aggregation process.

Proteolysis Targeting Chimeras (PROTACs) are an emerging therapeutic modality and chemical biology tools for Targeted Protein Degradation (TPD). PROTACs contain a ligand targeting the protein of interest, a ligand recruiting an E3 ligase and a linker connecting these two ligands. There are over 600 E3 ligases known so far, but only a handful have been exploited for TPD applications. A key reason for this is the scarcity of ligands binding various E3 ligases and the paucity of structural data available, which complicates ligand design across the family. In this study, we aim to progress PROTAC discovery by proposing a shortlist of E3 ligases that can be prioritized for covalent targeting by performing systematic structural ligandability analysis on a chemoproteomic dataset of potentially reactive cysteines across hundreds of E3 ligases. One of the goals of this study is to apply AlphaFold (AF) models for ligandability evaluations, as for a vast majority of these ligases an experimental structure is not available in the protein data bank (PDB). Using a combination of pocket features, AF model quality and additional aspects, we propose a shortlist of E3 ligases and corresponding cysteines that can be prioritized to potentially discover covalent ligands and expand the PROTAC toolbox.

Hydration plays a crucial role in the refolding of intrinsically disordered proteins into amyloid fibrils; however, the specific interactions between water and protein that may contribute to this process are still unknown. In our previous studies of alpha-synuclein (aSyn), we have shown that waters confined in fibril cavities are stabilizing features of this pathological fold; and that amino acids that hydrogen bond with these confined waters modulate primary and seeded aggregation. Here, we extend our aSyn molecular dynamics (MD) simulations with three new polymorphs and correlate MD trajectory information with known post-translational modifications (PTMs) and experimental data. We show that cavity residues are more evolutionarily conserved than non-cavity residues and are enriched with PTM sites. As expected, the confinement within hydrophilic cavities results in more stably hydrated amino acids. Interestingly, cavity PTM sites display the longest protein-water hydrogen bond lifetimes, three-fold greater than non-PTM cavity sites. Utilizing the deep mutational screen dataset by Newberry et al. and the Thioflavin T aggregation review by Pancoe et al. parsed using a fibril cavity/non-cavity definition, we show that hydrophobic changes to amino acids in cavities have a larger effect on fitness and aggregation rate than residues outside cavities, supporting our hypothesis that these sites are involved in the inhibition of aSyn toxic fibrillization. Finally, we expand our study to include analysis of fibril structures of tau, FUS, TDP-43, prion, and hnRNPA1; all of which contained hydrated cavities, with tau, FUS, and TDP-43 recapitulating our PTM results in aSyn fibril cavities.

Isopentenyl phosphate kinases (IPKs) have recently garnered attention for their central role in biocatalytic "isoprenol pathways," which seek to reduce the synthesis of the isoprenoid precursors to two enzymatic steps. Furthermore, the natural promiscuity of IPKs toward non-natural alkyl-monophosphates (alkyl-Ps) as substrates has hinted at the isoprenol pathways' potential to access novel isoprenoids with potentially useful activities. However, only a handful of IPK crystal structures have been solved to date, and even fewer of these contain non-natural substrates bound in the active site. The current study sought to elucidate additional ternary complexes bound to non-natural substrates using the IPK homolog from Thermococcus paralvinellae (TcpIPK). Four such structures were solved, each bound to a different non-natural alkyl-P and the phosphoryl donor substrate/product adenosine triphosphate (ATP)/adenosine diphosphate (ADP). As expected, the quaternary, tertiary, and secondary structures of TcpIPK closely resembled those of IPKs published previously, and kinetic analysis of a novel alkyl-P substrate highlighted the potentially dramatic effects of altering the core scaffold of the natural substrate. Even more interesting, though, was the discovery of a trend correlating the position of two α helices in the active site with the magnitude of an IPK homolog's reaction rate for the natural reaction. Overall, the current structures of TcpIPK highlight the importance of continued structural analysis of the IPKs to better understand and optimize their activity with both natural and non-natural substrates.

Infected cell protein 0 (ICP0) is an immediate-early regulatory protein of herpes simplex virus 1 (HSV-1) that possesses E3 ubiquitin ligase activity. ICP0 transactivates viral genes, in part, through its C-terminal dimer domain (residues 555-767). Deletion of this dimer domain results in reduced viral gene expression, lytic infection, and reactivation from latency. Since ICP0's dimer domain is associated with its transactivation activity and efficient viral replication, we wanted to determine the structure of this specific domain. The C-terminus of ICP0 was purified from bacteria and analyzed by X-ray crystallography to solve its structure. Each subunit or monomer in the ICP0 dimer is composed of nine β-strands and two α-helices. Interestingly, two adjacent β-strands from one monomer "reach" into the adjacent subunit during dimer formation, generating two β-barrel-like structures. Additionally, crystallographic analyses indicate a tetramer structure is formed from two β-strands of each dimer, creating a "stacking" of the β-barrels. The structural protein database searches indicate the fold or structure adopted by the ICP0 dimer is novel. The dimer is held together by an extensive network of hydrogen bonds. Computational analyses reveal that ICP0 can either form a dimer or bind to SUMO1 via its C-terminal SUMO-interacting motifs but not both. Understanding the structure of the dimer domain will provide insights into the activities of ICP0 and, ultimately, the HSV-1 life cycle.

The receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein must undergo a crucial conformational transition to invade human cells. It is intriguing that this transition is accompanied by a synchronized movement of the entire spike protein. Therefore, it is possible to design allosteric regulators targeting non-RBD but hindering the conformational transition of RBD. To understand the allosteric mechanism in detail, we establish a computational framework by integrating coarse-grained molecular dynamic simulations and a state-of-the-art neural network model called neural relational inference. Leveraging this framework, we have elucidated the allosteric pathway of the SARS-CoV-2 spike protein at the residue level and identified the molecular mechanisms involved in the transmission of allosteric signals. The movement of D614 is coupled with that of Q321. This interaction subsequently influences the movement of K528/K529, ultimately coupling with the movement of RBD during conformational changes. Mutations that weaken the interactions within this pathway naturally block the allosteric signal transmission, thereby modulating the conformational transitions. This observation also offers a rationale for the distinct allosteric patterns observed in the SARS-CoV spike protein. Our result provides a useful method for analyzing the dynamics of potential viral variants in the future.

Proteins are used in various biotechnological applications, often requiring the optimization of protein properties by introducing specific amino-acid exchanges. Deep mutational scanning (DMS) is an effective high-throughput method for evaluating the effects of these exchanges on protein function. DMS data can then inform the training of a neural network to predict the impact of mutations. Most approaches use some representation of the protein sequence for training and prediction. As proteins are characterized by complex structures and intricate residue interaction networks, directly providing structural information as input reduces the need to learn these features from the data. We introduce a method for encoding protein structures as stacked 2D contact maps, which capture residue interactions, their evolutionary conservation, and mutation-induced interaction changes. Furthermore, we explored techniques to augment neural network training performance on smaller DMS datasets. To validate our approach, we trained three neural network architectures originally used for image analysis on three DMS datasets, and we compared their performances with networks trained solely on protein sequences. The results confirm the effectiveness of the protein structure encoding in machine learning efforts on DMS data. Using structural representations as direct input to the networks, along with data augmentation and pretraining, significantly reduced demands on training data size and improved prediction performance, especially on smaller datasets, while performance on large datasets was on par with state-of-the-art sequence convolutional neural networks. The methods presented here have the potential to provide the same workflow as DMS without the experimental and financial burden of testing thousands of mutants. Additionally, we present an open-source, user-friendly software tool to make these data analysis techniques accessible, particularly to biotechnology and protein engineering researchers who wish to apply them to their mutagenesis data.

This is a short appreciation of the contributions made by E. James Milner-White to the field of protein structure, in particular his description of small hydrogen-bonded motifs.

The new viral strains of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are continuously rising, becoming more virulent, and transmissible. Therefore, the development of new antiviral drugs is essential. Due to its significant role in the viral life cycle of SARS-CoV-2, the main protease (Mpro) enzyme is a leading target for antiviral drug design. The Mpro monomer consists of domain DI, DII, and DI-DII interface. Twenty-one conserved water molecules (W4-W24) are occupied at these domains according to multiple crystal structure analyses. The crystal and MD structures reveal the presence of eight conserved water sites in domain DI, DII and remaining in the DI-DII interface. Grid-based inhomogeneous fluid solvation theory (GIST) was employed on MD structures of Mpro native to predict structural and thermodynamic properties of each conserved water site for focusing to identify the specific conserved water molecules that can easily be displaced by proposed ligands. Finally, MD water W13 is emerged as a promising candidate for water mimic drug design due to its low mean interaction energy, loose binding character with the protein, and its involvement in a water-mediated H-bond with catalytic His41 via the interaction Thr25(OG)---W13---W---His41(NE2). In this context, water occupancy, relative interaction energy, entropy, and topologies of W13 are thermodynamically acceptable for the water displacement method. Therefore, the strategic use of W13's geometrical position in the DI domain may be implemented for drug discovery against COVID disease by designing new ligands with appropriately oriented chemical groups to mimic its structural, electronic, and thermodynamic properties.

Our globin census update allows us to refine our vision of globin origin, evolution, and structure to function relationship in the context of the currently accepted tree of life. The modern globin domain originates as a single domain, three-over-three α-helical folded structure before the diversification of the kingdoms of life (Bacteria, Archaea, Eukarya). Together with the diversification of prokaryotes, three monophyletic globin families (M, S, and T) emerged, most likely in Proteobacteria and Actinobacteria, displaying specific sequence and structural features, and spread by vertical and horizontal gene transfer, most probably already present in the last universal common ancestor (LUCA). Non-globin domains were added, and eventually lost again, creating multi-domain structures in key branches of M- (FHb and Adgb) and the vast majority of S globins, which with their coevolved multi-domain architectures, have predominantly "sensor" functions. Single domain T-family globins diverged into four major groups and most likely display functions related to reactive nitrogen and oxygen species (RNOS) chemistry, as well as oxygen storage/transport which drives the evolution of its major branches with their characteristic key distal residues (B10, E11, E7, and G8). M-family evolution also lead to distinctive major types (FHb and Fgb, Ngb, Adgb, GbX vertebrate Gbs), and shows the shift from high oxygen affinity controlled by TyrB10-Gln/AsnE11 likely related to RNOS chemistry in microorganisms, to a moderate oxygen affinity storage/transport function controlled by hydrophobic B10/E11-HisE7 in multicellular animals.