Proteins-Structure Function and Bioinformatics最新文献

The RAF1-RAP1A interaction activates the MAPK/ERK pathway which is very crucial in the carcinogenesis process. This protein complex influences tumor formation, proliferation, and metastasis. Understanding aberrant interactions driven by clinical mutations is vital for targeted therapies. Hence, the current study focuses on the screening of clinically reported substitutions in the RAF1 and RAP1A genes using predictive algorithms integrated with all-atoms simulation, essential dynamics, and binding free energy methods. Survival analysis results revealed a strong association between RAF1 and RAP1A expression levels and diminished survival rates in cancer patients across different cancer types. Integrated machine learning algorithms showed that among the 134 mutations reported for these 2 proteins, only 13 and 35 were classified as deleterious mutations in RAF1 and RAP1P, respectively. Moreover, one mutation in RAF1 reported elevated levels of binding between RAF1 and RAP1P while in RAP1A, 7 mutations were reported to increase the binding affinity. The high-binding mutations, P34Q and V60F, were subjected to protein-protein coupling which confirmed the increase in the binding affinity. Wild-type and mutant RAF1-RAP1P bound complexes were subjected to molecular simulation investigation, revealing enhanced structural stability, increased compactness, and stabilized residue fluctuations of the mutant systems in contrast to the wild-type. In addition, hydrogen bonding analysis revealed a variation in the binding paradigm which further underscores the impact of these substitutions on the coupling of RAF1 and RAP1A. Principal component analysis (PCA) and free energy landscape (FEL) evaluation further determined dynamical variations in the wild-type and mutant complexes. Finally, the Gibbs free energy for each complex was estimated and found to be -71.94 ± 0.38 kcal/mol for the wild-type, -95.57 ± 0.37 kcal/mol for the V60F, and -85.76 ± 0.72 kcal/mol for P34Q complex. These findings confirm the effect of these variants on increasing the binding affinity of RAF1 to RAP1P. These mutations can therefore be targeted for cancer therapy to modulate the activity of the MAPK/ERK signaling pathway.

Acquired resistance to first-line treatments in various cancers both promotes cancer recurrence as well as limits effective treatment. This is true for epidermal growth factor receptor (EGFR) mutations, for which secondary EGFR mutations are one of the principal mechanisms conferring resistance to the covalent inhibitor osimertinib. Thus, it is very important to develop a deeper understanding of the secondary mutational resistance mechanisms associated with EGFR mutations arising in tumors treated with osimertinib to expedite the development of innovative therapeutic drugs to overcome acquired resistance. This work uses all-atom molecular dynamics (MD) simulations to investigate the conformational variation of two reported EGFR mutants (L858R/L718Q and L858R/L792H) that resist osimertinib. The wild-type EGFR kinase domain and the L858R mutant are used as the reference. Our MD simulation results revealed that both the L718Q and L792H secondary mutations induce additional hydrogen bonds between the residues in the active pocket and the residues with the water molecules. These additional hydrogen bonds reduce the exposure area of C797, the covalent binding target of osimertinib. The additional hydrogen bonds also influence the binding affinity of the EGFR kinase domain by altering the secondary structure and flexibility of the amino acid residues in the domain. Our work highlights how the two reported mutations may alter both residue-residue and residue-solvent hydrogen bonds, affecting protein binding properties, which could be helpful for future drug discovery.

The ATP-dependent phosphorylation activity of cyclin-dependent kinase 1 (CDK1), an essential enzyme for cell cycle progression, is regulated by interactions with Cyclin-B, substrate, and Cks proteins. We have recently shown that active site acetylation in CDK1 abrogated binding to Cyclin-B which posits an intriguing long-range communication between the catalytic site and the protein-protein interaction (PPI) interface. Now, we demonstrate a general allosteric link between the CDK1 active site and all three of its PPI interfaces through atomistic molecular dynamics (MD) simulations. Specifically, we examined ATP binding free energies to CDK1 in native nonacetylated (K33wt) and acetylated (K33Ac) forms as well as the acetyl-mimic K33Q and the acetyl-null K33R mutant forms, which are accessible in vitro. In agreement with experiments, ATP binding is stronger in K33wt relative to the other three perturbed states. Free energy decomposition reveals, in addition to expected local changes, significant and selective nonlocal entropic responses to ATP binding/perturbation of K33 from the $\mathrm{\alpha C}$ -helix, activation loop (A-loop), and $\mathrm{\alpha G}$ - $\alpha$ H segments in CDK1 which interface with Cyclin-B, substrate, and Cks proteins, respectively. Statistical analysis reveals that while entropic responses of protein segments to active site perturbations are on average correlated with their dynamical changes, such correlations are lost in about 9%-48% of the dataset depending on the segment. Besides proving the bi-directional communication between the active site and the CDK1:Cyclin-B interface, our study uncovers a hitherto unknown mode of ATP binding regulation by multiple PPI interfaces in CDK1.

Protein-protein interactions (PPIs) play an essential role in life activities. Many artificial intelligence algorithms based on protein sequence information have been developed to predict PPIs. However, these models have difficulty dealing with various sequence lengths and suffer from low generalization and prediction accuracy. In this study, we proposed a novel end-to-end deep learning framework, RSPPI, combining residual neural network (ResNet) and spatial pyramid pooling (SPP), to predict PPIs based on the protein sequence physicochemistry properties and spatial structural information. In the RSPPI model, ResNet was employed to extract the structural and physicochemical information from the protein three-dimensional structure and primary sequence; the SPP layer was used to transform feature maps to a single vector and avoid the fixed-length requirement. The RSPPI model possessed excellent cross-species performance and outperformed several state-of-the-art methods based either on protein sequence or gene ontology in most evaluation metrics. The RSPPI model provides a novel strategy to develop an AI PPI prediction algorithm.

The MC1R protein is a receptor found in melanocytes that plays a role in melanin synthesis. Mutations in this protein can impact hair color, skin tone, tanning ability, and increase the risk of skin cancer. The MC1R protein is activated by the alpha-melanocyte-stimulating hormone (α-MSH). Previous studies have shown that mutations affect the interaction between MC1R and α-MSH; however, the mechanism behind this process is poorly understood. Our study aims to shed light on this mechanism using molecular dynamics (MD) simulations to analyze the Asp84Glu and Asp294His variants. We simulated both the wild-type (WT) protein and the mutants with and without ligand. Our results reveal that mutations induce unique conformations during state transitions, hindering the switch between active and inactive states and decreasing cellular levels of cAMP. Interestingly, Asp294His showed increased ligand affinity but decreased protein activity, highlighting that tighter binding does not always lead to increased activation. Our study provides insights into the molecular mechanisms underlying the impact of MC1R mutations on protein activity.

Despite the ubiquity of membrane occupation recognition nexus (MORN) motifs across diverse species in both eukaryotic and prokaryotic organisms, these protein domains remain poorly characterized. Their significance is underscored in the context of the Alsin protein, implicated in the debilitating condition known as infantile-onset ascending hereditary spastic paralysis (IAHSP). Recent investigations have proposed that mutations within the Alsin MORN domain disrupt proper protein assembly, precluding the formation of the requisite tetrameric configuration essential for the protein's inherent biological activity. However, a comprehensive understanding of the relationship between the biological functions of Alsin and its three-dimensional molecular structure is hindered by the lack of available experimental structures. In this study, we employed and compared several protein structure prediction algorithms to identify a three-dimensional structure for the putative MORN of Alsin. Furthermore, inspired by experimental pieces of evidence from previous studies, we employed the developed models to predict and investigate two homo-dimeric assemblies, characterizing their stability. This study's insights into the three-dimensional structure of the Alsin MORN domain and the stability dynamics of its homo-dimeric assemblies suggest an antiparallel linear configuration stabilized by a noncovalent interaction network.

The blood protein von Willebrand factor (VWF) is a large multimeric protein that, when activated, binds to blood platelets, tethering them to the site of vascular injury and initiating blood coagulation. This process is critical for the normal hemostatic response, but especially under inflammatory conditions, it is thought to be a major player in pathological thrombus formation. For this reason, VWF has been the target for the development of anti-thrombotic therapeutics. However, it is challenging to prevent pathological thrombus formation while still allowing normal physiological blood coagulation, as currently available anti-thrombotic therapeutics are known to cause unwanted bleeding, in particular intracranial hemorrhage. This work explores the possibility of inhibiting VWF selectively under the inflammatory conditions present during pathological thrombus formation. In particular, the A2 domain of VWF is known to inhibit the neighboring A1 domain from binding to the platelet surface receptor GpIbα, and this auto-inhibitory mechanism has been shown to be removed by oxidizing agents released during inflammation. Hence, finding drug molecules that bind at the interface between A1 and A2 only under oxidizing conditions could restore such an auto-inhibitory mechanism. Here, by using a combination of computational docking, molecular dynamics simulations, and free energy perturbation calculations, a ligand from the ZINC15 database was identified that binds at the A1A2 interface, with the interaction being stronger under oxidizing conditions. The results provide a framework for the discovery of drug molecules that bind to a protein selectively in the presence of inflammatory conditions.

Understanding the sequence-structure relationship in protein is of fundamental interest, but has practical applications such as the rational design of peptides and proteins. This relationship in the Type I left-handed β-helix containing proteins is updated and revisited in this study. Analyzing the available experimental structures in the Protein Data Bank, we could describe, further in detail, the structural features that are important for the stability of this fold, as well as its nucleation and termination. This study is meant to complete previous work, as it provides a separate analysis of the N-terminal and C-terminal rungs of the helix. Particular sequence motifs of these rungs are described along with the structural element they form.

Histidine kinases (HKs) are a central part of bacterial environmental-sensing two-component systems. They provide their hosts with the ability to respond to a wide range of physical and chemical signals. HKs are multidomain proteins consisting of at least a sensor domain, dimerization and phosphorylation domain (DHp), and a catalytic domain. They work as homodimers and the existence of two different autophosphorylation mechanisms (cis and trans) has been proposed as relevant for pathway specificity. Although several HKs have been intensively studied, a precise sequence-to-structure explanation of why and how either cis or trans phosphorylation occurs is still unavailable nor is there any evolutionary analysis on the subject. In this work, we show that AlphaFold can accurately determine whether an HK dimerizes in a cis or trans structure. By modeling multiple HKs we show that both cis- and trans-acting HKs are common in nature and the switch between mechanisms has happened multiple times in the evolutionary history of the family. We then use AlphaFold modeling to explore the molecular determinants of the phosphorylation mechanism. We conclude that it is the difference in lengths of the helices surrounding the DHp loop that determines the mechanism. We also show that very small changes in these helices can cause a mechanism switch. Despite this, previous evidence shows that for a particular HK the phosphorylation mechanism is conserved. This suggests that the phosphorylation mechanism participates in system specificity and mechanism switching provides these systems with a way to diverge.

The ongoing global pandemic of the coronavirus 2019 (COVID-19) disease is caused by the virus SARS-CoV-2, with very few highly effective antiviral treatments currently available. The machinery responsible for the replication and transcription of viral RNA during infection is made up of several important proteins. Two of these are nsp12, the catalytic subunit of the viral polymerase, and nsp9, a cofactor of nsp12 involved in the capping and priming of viral RNA. While several recent studies have determined the structural details of the interaction of nsp9 with nsp12 in the context of RNA capping, very few biochemical or biophysical details are currently available. In this study, we have used a combination of surface plasmon resonance (SPR) experiments, size exclusion chromatography (SEC) experiments, and biochemical assays to identify specific nsp9 residues that are critical for nsp12 binding as well as RNAylation, both of which are essential for the RNA capping process. Our data indicate that nsp9 dimerization is unlikely to play a significant functional role in the virus. We confirm that a set of recently discovered antiviral peptides inhibit nsp9-nsp12 interaction by specifically binding to nsp9; however, we find that these peptides do not impact RNAylation. In summary, our results have important implications for future drug discovery efforts to combat SARS-CoV-2 and any newly emerging coronaviruses.