Protein-protein interactions: Methods, databases, and applications in virus-host study

Almost all the cellular processes in a living system are controlled by proteins:They regulate gene expression,catalyze chemical reactions,transport small molecules across membranes,and transmit signal across membranes.Even,a viral infection is often initiated through virus-host protein interactions.Protein-protein interactions(PPIs)are the physical contacts between two or more proteins and they represent complex biological functions.Nowadays,PPIs have been used to construct PPI networks to study complex pathways for revealing the functions of unknown proteins.Scientists have used PPIs to find the molecular basis of certain diseases and also some potential drug targets.In this review,we will discuss how PPI networks are essential to understand the molecular basis of virus-host relationships and several databases which are dedicated to virus-host interaction studies.Here,we present a short but comprehensive review on PPIs,including the experimental and computational methods of finding PPIs,the databases dedicated to virus-host PPIs,and the associated various applications in protein interaction networks of some lethal viruses with their hosts.

nNOS-mediated protein-protein interactions:promising targets for treating neurological and neuropsychiatric disorders

Neurological and neuropsychiatric disorders are one of the leading causes of disability worldwide and affect the health of billions of people.Nitric oxide(NO),a free gas with multitudinous bioactivities,is mainly produced from the oxidation of L-arginine by neuronal nitric oxide synthase(nNOS)in the brain.Inhibiting nNOS benefits a variety of neurological and neuropsychiatric disorders,including stroke,depression and anxiety disorders,posttraumatic stress disorder,Parkinson’s disease,Alzheimer’s disease,chronic pain,and drug addiction.Due to critical roles of nNOS in learning and memory and synaptic plasticity,direct inhibition of nNOS may cause severe side effects.Importantly,interactions of several proteins,including post-synaptic density 95(PSD-95),carboxyterminal PDZ ligand of nNOS(CAPON)and serotonin transporter(SERT),with the PSD/Disc-large/ZO-1 homologous(PDZ)domain of nNOS have been demonstrated to influence the subcellular distribution and activity of the enzyme in the brain.Therefore,it will be a preferable means to interfere with nNOS-mediated proteinprotein interactions(PPIs),which do not lead to undesirable effects.Herein,we summarize the current literatures on nNOS-mediated PPIs involved in neurological and neuropsychiatric disorders,and the discovery of drugs targeting the PPIs,which is expected to provide potential targets for developing novel drugs and new strategy for the treatment of neurological and neuropsychiatric disorders.

Prediction of Protein-Protein Interactions by a Novel Model Based on Domain Information

Domain-based protein-protein interactions( PPIs) is a problem that has drawn the attentions of many researchers in recent years and it has been studied using lots of computational approaches from many different perspectives. Existing domain-based methods to predict PPIs typically infer domain interactions from known interacting sets of proteins. However,these methods are costly and complex to implement. In this paper, a simple and effective prediction model is proposed. In this model,an improved multiinstance learning( MIL) algorithm( MilCaA) is designed that doesn't need to take the domain interactions into consideration to construct MIL bags. Then, the pseudo-amino acid composition( PseAAC) transformation method is used to encode the instances in a multi-instance bag and the principal components analysis( PCA) is also used to reduce the feature dimension. Finally, several traditional machine learning and MIL methods are used to verify the proposed model. Experimental results demonstrate that MilCaA performs better than state-of-the-art techniques including the traditional machine learning methods which are widely used in PPIs prediction.

Predicting residue contacts for protein-protein interactions by integration of multiple information

Detailed knowledge of interfacial region between interacting proteins is not only helpful in annotating function for proteins, but also very important for structure-based drug design and disease treatment. However, this is one of the most difficult tasks and current methods are constrained by some factors. In this study, we developed a new method to predict residue-residue contacts of two interacting protein domains by integrating information about evolutionary couplings andamino acid pairwise contact potentials, as well as domain-domain interaction interfaces. The experimental results showed that our proposed method outperformed the previous method with the same datasets. Moreover, the method promises an improvement in the source of template-based protein docking.

Using the theory of coevolution to predict protein-protein interactions in non-small cell lung cancer

Systems biology has become an effective approach for understanding the molecular mechanisms underlying the development of lung cancer.In this study,sequences of 100 non-small cell lung cancer (NSCLC)-related proteins were downloaded from the National Center for Biotechnology Information (NCBI) databases.The Theory of Coevolution was then used to build a protein-protein interaction (PPI) network of NSCLC.Adopting the reverse thinking approach,we analyzed the NSCLC proteins one at a time.Fifteen key proteins were identified and categorized into a special protein family F(K),which included Cyclin D1 (CCND1),E-cadherin (CDH1),Cyclin-dependent kinase inhibitor 2A (CDKN2A),chemokine (C-X-C motif) ligand 12 (CXCL12),epidermal growth factor (EGF),epidermal growth factor receptor (EGFR),TNF receptor superfamily,member 6(FAS),FK506 binding protein 12-rapamycin associated protein 1 (FRAP1),O-6-methylguanine-DNA methyltransferase (MGMT),parkinson protein 2,E3 ubiquitin protein ligase (PARK2),phosphatase and tensin homolog (PTEN),calcium channel voltage-dependent alpha 2/delta subunit 2 (CACNA2D2),tubulin beta class I (TUBB),SWI/SNF-related,matrix-associated,actin-dependent regulator of chromatin,subfamily a,member 2 (SMARCA2),and wingless-type MMTV integration site family,member 7A (WNT7A).Seven key nodes of the sub-network were identified,which included PARK2,WNT7A,SMARCA2,FRAP1,CDKN2A,CCND1,and EGFR.The PPI predictions of EGFR-EGF,PARK2-FAS,PTEN-FAS,and CACNA2D2-CDH1 were confirmed experimentally by retrieving the Biological General Repository for Interaction Datasets (BioGRID) and PubMed databases.We proposed that the 7 proteins could serve as potential diagnostic molecular markers for NSCLC.In accordance with the developmental mode of lung cancer established by Sekine et al.,we assumed that the occurrence and development of lung cancer were linked not only to gene loss in the 3p region (WNT7A,3p25) and genetic mutations in the 9p region but also to similar events in the regions of 1p36.2 (FRAP1),6q25.2-q27 (PARK2),and 11q13 (CCND1).Lastly,the invasion or metastasis of lung cancer happened.

A DNA Force Circuit for Exploring Protein-Protein Interactions at the Single-Molecule Level

Protein-protein interactions(PPls)play a crucial role in drug discovery and disease treatment.However,the development of effective drugs targeting PPls remains challenging due to limited methodologies for probing their spatiotemporal anisotropy.Here,we propose a single-molecule approach using a unique force circuit to investigate Ppl dynamics and anisotropy under mechanical forces.Unlike conventional techniques,this approach enables the manipulation and real-time monitoring of individual proteins at specific amino acids with defined geometry,offering insights into molecular mechanisms at the single-molecule level.The DNA force circuit was constructed using click chemistry conjugation methods and genetic code expansion techniques,facilitating orthogonal conjugation between proteins and nucleic acids.The SET domain of the MLL1 protein and the tail of histone H3 were used as a model system to demonstrate the application of the DNA force circuit.With the use of atomic force microscopy and magnetic tweezers,optimized assembly procedures were developed.The DNA force circuit provides an exceptional platform for studying the anisotropy of PPis and holds promise for advancing drug discovery research targeted at PPIs.

RF-PSSM:A Combination of Rotation Forest Algorithm and Position-Specific Scoring Matrix for Improved Prediction of Protein-Protein Interactions Between Hepatitis C Virus and Human

The identification of hepatitis C virus(HCV)virus-human protein interactions will not only help us understand the molecular mechanisms of related diseases but also be conductive to discovering new drug targets.An increasing number of clinically and experimentally validated interactions between HCV and human proteins have been documented in public databases,facilitating studies based on computational methods.In this study,we proposed a new computational approach,rotation forest position-specific scoring matrix(RF-PSSM),to predict the interactions among HCV and human proteins.In particular,PSSM was used to characterize each protein,two-dimensional principal component analysis(2DPCA)was then adopted for feature extraction of PSSM.Finally,rotation forest(RF)was used to implement classification.The results of various ablation experiments show that on independent datasets,the accuracy and area under curve(AUC)value of RF-PSSM can reach 93.74% and 94.29%,respectively,outperforming almost all cutting-edge research.In addition,we used RF-PSSM to predict 9 human proteins that may interact with HCV protein E1,which can provide theoretical guidance for future experimental studies.

Ecological network analysis reveals complex responses of tree species life stage interactions to stand variables

Tree interactions are essential for the structure,dynamics,and function of forest ecosystems,but variations in the architecture of life-stage interaction networks(LSINs)across forests is unclear.Here,we constructed 16 LSINs in the mountainous forests of northwest Hebei,China based on crown overlap from four mixed forests with two dominant tree species.Our results show that LSINs decrease the complexity of stand densities and basal areas due to the interaction cluster differentiation.In addition,we found that mature trees and saplings play different roles,the first acting as“hub”life stages with high connectivity and the second,as“bridges”controlling information flow with high centrality.Across the forests,life stages with higher importance showed better parameter stability within LSINs.These results reveal that the structure of tree interactions among life stages is highly related to stand variables.Our efforts contribute to the understanding of LSIN complexity and provide a basis for further research on tree interactions in complex forest communities.

Small molecules targeting protein-protein interactions for cancer therapy

Protein-protein interactions(PPIs)are fundamental to many biological processes that play an important role in the occurrence and development of a variety of diseases.Targeting the interaction between tumour-related proteins with emerging small molecule drugs has become an attractive approach for treatment of human diseases,especially tumours.Encouragingly,selective PPI-based therapeutic agents have been rapidly advancing over the past decade,providing promising perspectives for novel therapies for patients with cancer.In this review we comprehensively clarify the discovery and development of small molecule modulators of PPIs from multiple aspects,focusing on PPIs in disease,drug design and discovery strategies,structure-activity relationships,inherent dilemmas,and future directions.

Molecular dynamics simulations on the interactions between nucleic acids and a phospholipid bilayer

Recently,lipid nanoparticles(LNPs)have been extensively investigated as non-viral carriers of nucleic acid vaccines due to their high transport efficiency,safety,and straightforward production and scalability.However,the molecular mechanism underlying the interactions between nucleic acids and phospholipid bilayers within LNPs remains elusive.In this study,we employed the all-atom molecular dynamics simulation to investigate the interactions between single-stranded nucleic acids and a phospholipid bilayer.Our findings revealed that hydrophilic bases,specifically G in single-stranded RNA(ssRNA)and single-stranded DNA(ssDNA),displayed a higher propensity to form hydrogen bonds with phospholipid head groups.Notably,ssRNA exhibited stronger binding energy than ssDNA.Furthermore,divalent ions,particularly Ca2+,facilitated the binding of ssRNA to phospholipids due to their higher binding energy and lower dissociation rate from phospholipids.Overall,our study provides valuable insights into the molecular mechanisms underlying nucleic acidphospholipid interactions,with potential implications for the nucleic acids in biotherapies,particularly in the context of lipid carriers.

Light-Material Interactions Using Laser and Flash Sources for Energy Conversion and Storage Applications

This review provides a comprehensive overview of the progress in light-material interactions(LMIs),focusing on lasers and flash lights for energy conversion and storage applications.We discuss intricate LMI parameters such as light sources,interaction time,and fluence to elucidate their importance in material processing.In addition,this study covers various light-induced photothermal and photochemical processes ranging from melting,crystallization,and ablation to doping and synthesis,which are essential for developing energy materials and devices.Finally,we present extensive energy conversion and storage applications demonstrated by LMI technologies,including energy harvesters,sensors,capacitors,and batteries.Despite the several challenges associated with LMIs,such as complex mechanisms,and high-degrees of freedom,we believe that substantial contributions and potential for the commercialization of future energy systems can be achieved by advancing optical technologies through comprehensive academic research and multidisciplinary collaborations.

Strong metal-support interactions between highly dispersed Cu^(+) species and ceria via mix-MOF pyrolysis toward promoted water-gas shift reaction

The modulation of metal-support interfacial interaction is significant but challenging in the design of high-efficiency and high-stability supported catalysts.Here,we report a synthetic strategy to upgrade Cu-CeO_(2)interfacial interaction by the pyrolysis of mixed metal-organic framework(MOF)structure.The obtained highly dispersed Cu/CeO_(2)-MOF catalyst via this strategy was used to catalyze water-gas shift reaction(WGSR),which exhibited high activity of 40.5μmolCOgcat^(-1).s^(-1)at 300℃and high stability of about 120 h.Based on comprehensive studies of electronic structure,pyrolysis strategy has significant effect on enhancing metal-support interaction and then stabilizing interfacial Cu^(+)species under reaction conditions.Abundant Cu^(+)species and generated oxygen vacancies over Cu/CeO_(2)-MOF catalyst played a key role in CO molecule activation and H2O molecule dissociation,respectively.Both collaborated closely and then promoted WGSR catalytic performance in comparison with traditio nal supported catalysts.This study shall offer a robust approach to harvest highly dispersed catalysts with finely-tuned metal-support interactions for stabilizing the most interfacial active metal species in diverse heterogeneous catalytic reactions.

Effects of layer interactions on instantaneous stability of finite Stokes flows

The stability analysis of a finite Stokes layer is of practical importance in flow control. In the present work, the instantaneous stability of a finite Stokes layer with layer interactions is studied via a linear stability analysis of the frozen phases of the base flow. The oscillations of two plates can have different velocity amplitudes, initial phases, and frequencies. The effects of the Stokes-layer interactions on the stability when two plates oscillate synchronously are analyzed. The growth rates of two most unstable modes when δ < 0.12 are almost equal, and δ = δ*/h*, where δ*and h*are the Stokes-layer thickness and the half height of the channel, respectively. However, their vorticities are different. The vorticity of the most unstable mode is symmetric, while the other is asymmetric. The Stokes-layer interactions have a destabilizing effect on the most unstable mode when δ < 0.68, and have a stabilizing effect when δ > 0.68. However, the interactions always have a stabilizing effect on the other unstable mode. It is explained that one of the two unstable modes has much higher dissipation than the other one when the Stokes-layer interactions are strong. We also find that the stability of the Stokes layer is closely related to the inflectional points of the base-flow velocity profile. The effects of inconsistent velocity-amplitude, initial phase, and frequency of the oscillations on the stability are analyzed. The energy of the most unstable eigenvector is mainly distributed near the plate of higher velocity amplitude or higher oscillation frequency. The effects of the initial phase difference are complicated because the base-flow velocity is extremely sensitive to the initial phase.

FLOCKING OF A THERMODYNAMIC CUCKER-SMALE MODEL WITH LOCAL VELOCITY INTERACTIONS

In this paper, we study the flocking behavior of a thermodynamic Cucker–Smale model with local velocity interactions. Using the spectral gap of a connected stochastic matrix, together with an elaborate estimate on perturbations of a linearized system, we provide a sufficient framework in terms of initial data and model parameters to guarantee flocking. Moreover, it is shown that the system achieves a consensus at an exponential rate.

Local coordination and electronic interactions of Pd/MXene via dual‐atom codoping with superior durability for efficient electrocatalytic ethanol oxidation

Catalyst design relies heavily on electronic metal‐support interactions,but the metal‐support interface with an uncontrollable electronic or coordination environment makes it challenging.Herein,we outline a promising approach for the rational design of catalysts involving heteroatoms as anchors for Pd nanoparticles for ethanol oxidation reaction(EOR)catalysis.The doped B and N atoms from dimethylamine borane(DB)occupy the position of the Ti_(3)C_(2)lattice to anchor the supported Pd nanoparticles.The electrons transfer from the support to B atoms,and then to the metal Pd to form a stable electronic center.A strong electronic interaction can be produced and the d‐band center can be shifted down,driving Pd into the dominant metallic state and making Pd nanoparticles deposit uniformly on the support.As‐obtained Pd/DB–Ti_(3)C_(2)exhibits superior durability to its counterpart(∼14.6%retention)with 91.1%retention after 2000 cycles,placing it among the top single metal anodic catalysts.Further,in situ Raman and density functional theory computations confirm that Pd/DB–Ti_(3)C_(2)is capable of dehydrogenating ethanol at low reaction energies.

Magnetic Interactions with Strain Gradient in Ultrathin Pr_(0.67)Sr_(0.33)MnO_(3) Films

Strain gradient is a normal phenomenon around a heterostructural interface in ultrathin film,and it is important to determine its effect on magnetic interactions to understand interfacial coupling.In this work,ultrathin Pr_(0.67)Sr_(0.33)MnO_(3)(PSMO)films on different substrates are studied.For PSMO film under different in-plane strain conditions,the saturated magnetization and Curie temperature can be qualitatively explained by double-exchange interaction and the Jahn-Teller distortion.However,the difference in the saturated magnetization with zero field cooling and 5 T field cooling is proportional to the strain gradient.Strain-gradient-induced structural disorder is proposed to enhance phonon-electron antiferromagnetic interactions and the corresponding antiferromagnetic-to-ferromagnetic phase transition via a strong magnetic field during the field cooling process.A non-monotonous structural transition of the MnO_(6) octahedral rotation can enlarge the strain gradient in PSMO film on a SrTiO_(3) substrate.This work demonstrates the existence of the flexomagnetic effect in ultrathin manganite film,which should be applicable to other complex oxide systems.

T cell interactions with microglia in immune-inflammatory processes of ischemic stroke

The primary mechanism of secondary injury after cerebral ischemia may be the brain inflammation that emerges after an ischemic stroke,which promotes neuronal death and inhibits nerve tissue regeneration.As the first immune cells to be activated after an ischemic stroke,microglia play an important immunomodulatory role in the progression of the condition.After an ischemic stroke,peripheral blood immune cells(mainly T cells)are recruited to the central nervous system by chemokines secreted by immune cells in the brain,where they interact with central nervous system cells(mainly microglia)to trigger a secondary neuroimmune response.This review summarizes the interactions between T cells and microglia in the immune-inflammatory processes of ischemic stroke.We found that,during ischemic stroke,T cells and microglia demonstrate a more pronounced synergistic effect.Th1,Th17,and M1 microglia can co-secrete proinflammatory factors,such as interferon-γ,tumor necrosis factor-α,and interleukin-1β,to promote neuroinflammation and exacerbate brain injury.Th2,Treg,and M2 microglia jointly secrete anti-inflammatory factors,such as interleukin-4,interleukin-10,and transforming growth factor-β,to inhibit the progression of neuroinflammation,as well as growth factors such as brain-derived neurotrophic factor to promote nerve regeneration and repair brain injury.Immune interactions between microglia and T cells influence the direction of the subsequent neuroinflammation,which in turn determines the prognosis of ischemic stroke patients.Clinical trials have been conducted on the ways to modulate the interactions between T cells and microglia toward anti-inflammatory communication using the immunosuppressant fingolimod or overdosing with Treg cells to promote neural tissue repair and reduce the damage caused by ischemic stroke.However,such studies have been relatively infrequent,and clinical experience is still insufficient.In summary,in ischemic stroke,T cell subsets and activated microglia act synergistically to regulate inflammatory progression,mainly by secreting inflammatory factors.In the future,a key research direction for ischemic stroke treatment could be rooted in the enhancement of anti-inflammatory factor secretion by promoting the generation of Th2 and Treg cells,along with the activation of M2-type microglia.These approaches may alleviate neuroinflammation and facilitate the repair of neural tissues.

Achieving asymmetric redox chemistry for oxygen evolution reaction through strong metal-support interactions

Water electrolysis poses a significant challenge for balancing catalytic activity and stability of oxygen evolution reaction(OER)electrocatalysts.In this study,we address this challenge by constructing asymmetric redox chemistry through elaborate surface OO–Ru–OH and bulk Ru–O–Ni/Fe coordination moieties within single-atom Ru-decorated defective NiFe LDH nanosheets(Ru@d-NiFe LDH)in conjunction with strong metal-support interactions(SMSI).Rigorous spectroscopic characterization and theoretical calculations indicate that single-atom Ru can delocalize the O 2p electrons on the surface and optimize d-electron configurations of metal atoms in bulk through SMSI.The^(18)O isotope labeling experiment based on operando differential electrochemical mass spectrometry(DEMS),chemical probe experiments,and theoretical calculations confirm the encouraged surface lattice oxygen,stabilized bulk lattice oxygen,and enhanced adsorption of oxygen-containing intermediates for bulk metals in Ru@d-NiFe LDH,leading to asymmetric redox chemistry for OER.The Ru@d-NiFe LDH electrocatalyst exhibits exceptional performance with an overpotential of 230 mV to achieve 10 mA cm^(−2)and maintains high robustness under industrial current density.This approach for achieving asymmetric redox chemistry through SMSI presents a new avenue for developing high-performance electrocatalysts and instills confidence in its industrial applicability.

Dietary polyphenols reduced the allergenicity ofβ-lactoglobulin via non-covalent interactions:a study on the structure-allergenicity relationship

Studies showed that complexation of polyphenols with milk allergens reduced their immunogenic potential.However,the relationship between structures of polyphenols and their hypoallergenic effects on milk allergens in association with physiological and conformational changes of the complexes remain unclear.In this study,polyphenols from eight botanical sources were extracted to prepare non-covalent complexes withβ-lactoglobulin(β-LG),a major allergen in milk.The dominant phenolic compounds bound toβ-LG with a diminished allergenicity were identified to investigate their respective role on the structural and allergenic properties ofβ-LG.Extracts from Vaccinium fruits and black soybeans were found to have great inhibitory effects on the IgE-and IgG-binding abilities ofβ-LG.Among the fourteen structure-related phenolic compounds,flavonoids and tannins with larger MWs and multi-hydroxyl substituents,notably rutin,EGCG,and ellagitannins were more potent to elicit changes on the conformational structures ofβ-LG to decrease the allergenicity of complexedβ-LG.Correlation analysis further demonstrated that a destabilized secondary structure and protein depolymerization caused by polyphenol-binding were closely related to the allergenicity property of formed complexes.This study provides insights into the understanding of structure-allergenicity relationship ofβ-LG-polyphenol interactions and would benefit the development of polyphenol-fortified matrices with hypoallergenic potential.

Drug-Drug Interactions in Patients with Breast Cancer

The research paper investigates the intricate landscape of drug-drug interactions (DDIs) within the context of breast cancer treatment, with a particular focus on the elderly population and the use of complementary and alternative medicine (CAM). The study underscores the heightened susceptibility of elderly patients to DDIs due to the prevalence of polypharmacy and the widespread utilization of CAM among breast cancer patients. The potential ramifications of DDIs, encompassing adverse drug events and diminished treatment efficacy, are elucidated. The paper accentuates the imperative for healthcare providers to comprehensively understand both conventional and CAM therapies, enabling them to provide patients with informed guidance regarding safe and efficacious treatment options, culminating in enhanced patient outcomes.