A Deep Learning Drug-Target Binding Affinity Prediction Based on Compound Microstructure and Its Application in COVID-19 Drug Screening

Drug target relationship(DTR)prediction is a rapidly evolving area of research in com-putational drug discovery.Despite recent advances in computational solutions that have overcome the challenges of in vitro and in vivo experiments,most computational methods still focus on binary classification.They ignore the importance of binding affinity,which correctly distinguishes between on-targets and off-targets.In this study,we propose a deep learning model based on the microstruc-ture of compounds and proteins to predict drug-target binding affinity(DTA),which utilizes topo-logical structure information of drug molecules and sequence semantic information of proteins.In this model,graph attention network(GAT)is used to capture the deep features of the compound molecular graph,and bidirectional long short-term memory(BiLSTM)network is used to extract the protein sequence features,and the pharmacological context of DTA is obtained by combining the two.The results show that the proposed model has achieved superior performance in both cor-rectly predicting the value of interaction strength and correctly discriminating the ranking of bind-ing strength compared to the state-of-the-art baselines.A case study experiment on COVID-19 con-firms that the proposed DTA model can be used as an effective pre-screening tool in drug discovery.

Stable titanium metal-organic framework with strong binding affinity for ethaneremoval

Direct separation of high purity ethylene(C_(2)H_(4))from an ethane(C_(2)H_(6))/ethylene mixture is a critical and challenging task owing to the very similar molecular size and physical properties of the two components.While some studies have attempted this separation,there is a lack of excellent porous materials with strong binding affinity for C_(2)H_(6)-selective adsorption via an energy-efficient adsorptive separation process.Herein,we report a titanium metal-organic framework with strong binding affinity and excellent stability for the highly efficient removal of C_(2)H_(6) from C_(2)H_(6)/C_(2)H_(4) mixtures.Single component adsorption isotherms demonstrated a larger amount of adsorbed ethane(1.16 mmol·g^(-1) under 1 kPa)and high C_(2)H_(6)/C_(2)H_(4) selectivity(2.7)for equimolar C_(2)H_(6)/C_(2)H_(4) mixtures,especially in the low-pressure range,which is further confirmed by the results of grand canonical Monte Carlo simulations for C_(2)H_(6) adsorption in this framework.The experimental breakthrough curves showed that C_(2)H_(4) with a high purity was collected directly from both 1:9 and 1:15 C_(2)H_(6)/C_(2)H_(4)(volume ratio)mixtures at 298 K and 100 kPa.Moreover,the unchanged adsorption and separation performance after cycling experiments confirmed the promising applicability of this material in future.

Identification and characterization of GIP1,an Arabidopsis thaliana protein that enhances the DNA binding affinity and reduces the oligomeric state of G-box binding factors

Environmental control of the alcohol dehydrogenase(Adh)and other stress response genes in plants is in part brought about by transcriptional regulation involving the G-box cis-acting DNA element and bZIP G-box Binding Factors(GBFs).The mechanisms of GBF regulation and requirements for additional factors in this control process are not well understood.In an effort to identify potential GBF binding and control partners,maize GBF1 was used as bait in a yeast two-hybrid screen of an A.thaliana cDNA library.GBF Interacting Protein 1(GIP1)arose from the screen as a 496 amino acid protein with a predicted molecular weight of 53,748 kDa that strongly interacts with GBFs.Northern analysis of A.thaliana tissue suggests a 1.8-1.9 kb GIP1 transcript,predominantly in roots.Immunolocalization studies indicate that GIP1 protein is mainly localized to the nucleus.In vitro electrophoretic mobility shift assays using an Adh G-box DNA probe and recombinant A.thaliana GBF3 or maize GBF1,showed that the presence of GIP1 resulted in a tenfold increase in GBF DNA binding activity without altering the migration,suggesting a transient association between GIP1 and GBF.Addition of GIP1 to intentionally aggregated GBF converted GBF to lower molecular weight macromolecular complexes and GIP1 also refolded denatured rhodanese in the absence of ATP.These data suggest GIP1 functions to enhance GBF DNA binding activity by acting as a potent nuclear chaperone or crowbar,and potentially regulates the multimeric state of GBFs,thereby contributing to bZIP-mediated gene regulation.

Residues important to the allosteric regulation on ligand binding affinity in β3 integrins

Integrins are heterodimers that mediate cell adhesion and transduce signals bidirectionally across the cell membrane.Integrins often exist in low affinity(or inactive) states for

Altered hACE2 binding affinity and S1/S2 cleavage efficiency of SARS-CoV-2 spike protein mutants affect viral cell entry

SARS-CoV-2 variants are constantly emerging,hampering public health measures in controlling the number of infections.While it is well established that mutations in spike proteins observed for the different variants directly affect virus entry into host cells,there remains a need for further expansion of systematic and multifaceted comparisons.Here,we comprehensively studied the effect of spike protein mutations on spike expression and proteolytic activation,binding affinity,viral entry efficiency and host cell tropism of eight variants of concern(VOC)and variants of interest(VOI).We found that both the full-length spike and its receptor-binding domain(RBD)of Omicron bind to hACE2 with an affinity similar to that of the wild-type.In addition,Alpha,Beta,Delta and Lambda pseudoviruses gained significantly enhanced cell entry ability compared to the wild-type,while the Omicron pseudoviruses showed a slightly increased cell entry,suggesting the vastly increased rate of transmission observed for Omicron variant is not associated with its affinity to hACE2.We also found that the spikes of Omicron and Mu showed lower S1/S2 cleavage efficiency and inefficiently utilized TMPRSS2 to enter host cells than others,suggesting that they prefer the endocytosis pathway to enter host cells.Furthermore,all variants'pseudoviruses we tested gained the ability to enter the animal ACE2-expressing cells.Especially the infection potential of rats and mice showed significantly increased,strongly suggesting that rodents possibly become a reservoir for viral evolution.The insights gained from this study provide valuable guidance for a targeted approach to epidemic control,and contribute to a better understanding of SARS-CoV-2 evolution.

FingerDTA:A Fingerprint-Embedding Framework for Drug-Target Binding Affinity Prediction

Many efforts have been exerted toward screening potential drugs for targets,and conducting wet experiments remains a laborious and time-consuming approach.Artificial intelligence methods,such as Convolutional Neural Network(CNN),are widely used to facilitate new drug discovery.Owing to the structural limitations of CNN,features extracted from this method are local patterns that lack global information.However,global information extracted from the whole sequence and local patterns extracted from the special domain can influence the drugtarget affinity.A fusion of global information and local patterns can construct neural network calculations closer to actual biological processes.This paper proposes a Fingerprint-embedding framework for Drug-Target binding Affinity prediction(FingerDTA),which uses CNN to extract local patterns and utilize fingerprints to characterize global information.These fingerprints are generated on the basis of the whole sequence of drugs or targets.Furthermore,FingerDTA achieves comparable performance on Davis and KIBA data sets.In the case study of screening potential drugs for the spike protein of the coronavirus disease 2019(COVID-19),7 of the top 10 drugs have been confirmed potential by literature.Ultimately,the docking experiment demonstrates that FingerDTA can find novel drug candidates for targets.All codes are available at http://lanproxy.biodwhu.cn:9099/mszjaas/FingerDTA.git.

Computational Assessment of Protein–protein Binding Affinity by Reversely Engineering the Energetics in Protein Complexes

The cellular functions of proteins are maintained by forming diverse complexes.The stability of these com-plexes is quantified by the measurement of binding affinity,and mutations that alter the binding affinity can cause various diseases such as cancer and diabetes.As a result,accurate estimation of the binding stability and the effects of mutations on changes of binding affinity is a crucial step to understanding the biological functions of proteins and their dysfunctional consequences.It has been hypothesized that the stability of a protein complex is dependent not only on the residues at its binding interface by pairwise interactions but also on all other remaining residues that do not appear at the binding interface.Here,we computationally reconstruct the binding affinity by decomposing it into the contributions of interfacial residues and other non-interfacial residues in a protein complex.We further assume that the contributions of both interfacial and non-interfacial residues to the binding affinity depend on their local structural environments such as solvent-accessible surfaces and secondary structural types.The weights of all corresponding parameters are optimized by Monte-Carlo simulations.After cross-validation against a large-scale dataset,we show that the model not only shows a strong correlation between the absolute values of the experimental and calculated binding affinities,but can also be an effective approach to predict the relative changes of binding affinity from mutations.Moreover,we have found that the optimized weights of many parameters can capture the first-principle chemical and physical features of molecular recognition,therefore re-versely engineering the energetics of protein complexes.These results suggest that our method can serve as a useful addition to current computational approaches for predicting binding affinity and understanding the molecular mechanism of protein–protein interactions.

Accelerating Factor Xa inhibitor discovery with a de novo drug design pipeline

Small-molecule drugs are essential for maintaining human health. The objective of this study is to identify a molecule that can inhibit the Factor Xa protein and be easily procured. An optimization-based de novo drug design framework, Drug CAMD, that integrates a deep learning model with a mixed-integer nonlinear programming model is used for designing drug candidates. Within this framework, a virtual chemical library is specifically tailored to inhibit Factor Xa. To further filter and narrow down the lead compounds from the designed compounds, comprehensive approaches involving molecular docking,binding pose metadynamics(BPMD), binding free energy calculations, and enzyme activity inhibition analysis are utilized. To maximize efficiency in terms of time and resources, molecules for in vitro activity testing are initially selected from commercially available portions of customized virtual chemical libraries. In vitro studies assessing inhibitor activities have confirmed that the compound EN300-331859shows potential Factor Xa inhibition, with an IC_(50)value of 34.57 μmol·L^(-1). Through in silico molecular docking and BPMD, the most plausible binding pose for the EN300-331859-Factor Xa complex are identified. The estimated binding free energy values correlate well with the results obtained from biological assays. Consequently, EN300-331859 is identified as a novel and effective sub-micromolar inhibitor of Factor Xa.

Toxicity and binding analyses of Bacillus thuringiensis toxin Vip3A in Cry1Ac-resistant and-susceptible strains of Helicoverpa armigera(Hübner)

The Bacillus thuringiensis vegetative insecticidal protein, Vip3 A, represents a new family of Bt toxin and is currently applied to commercial transgenic cotton. To determine whether the Cry1Ac-resistant Helicoverpa armigera is cross-resistant to Vip3 Aa protein, insecticidal activities, proteolytic activations and binding properties of Vip3 Aa toxin were investigated using Cry1Ac-susceptible（96S） and Cry1Ac-resistant H. armigera strain（Cry1Ac-R）. The toxicity of Vip3 Aa in Cry1Ac-R slightly reduced compared with 96 S, the resistance ratio was only 1.7-fold. The digestion rate of full-length Vip3 Aa by gut juice extracts from 96 S was little faster than that from Cry1Ac-R. Surface plasmon resonance（SPR） showed there was no significant difference between the binding affinity of Vip3 Aa and BBMVs between 96 S and Cry1Ac-R strains, and there was no significant competitive binding between Vip3 Aa and Cry1 Ac in susceptible or resistant strains. So there had little cross-resistance between Vip3 Aa and Cry1 Ac,Vip3A＋Cry proteins maybe the suitable pyramid strategy to control H. armigera in China in the future.

Effective anti-inflammatory phenolic compounds from dandelion:identification and mechanistic insights using UHPLC-ESI-MS/MS,fluorescence quenching and anisotropy,molecular docking and dynamics simulation

This novel study identifi es the effective anti-inflammatory phenolic compounds in dandelion and provides mechanistic insights into their interactions with receptor proteins(toll-like receptor 4,TLR4;co-receptor myeloid differentiation protein-2,MD-2)using UHPLC-ESI-MS/MS,lipopolysaccharide(LPS)-stimulated THP-1 cell line,fluorescence quenching and anisotropy,molecular docking(single ligand and multi-ligand docking)and molecular dynamics simulation.A 50%aqueous methanol extract had a greater anti-inflammatory effect and higher chicoric acid content,compared with the 100%water and 100%methanol extracts.Chicoric acid,chlorogenic acid,methylophiopogonone A,caffeic acid,gallic acid monohydrate and 4’-O-demethylbroussonin A had relatively high binding energies and contents in all extracts.Chicoric acid competed with chlorogenic acid,4’-O-demethylbroussonin A and quercetin for MD-2.Among dandelion’s phenolics,chicoric acid most effectively hindered TLR4-MD-2 complex formation,with a quenching constant of 0.62×10^(6) L/mol for MD-2 or TLR4 at 320 K,and binding energies of-6.87 and-5.97 kcal/mol,respectively,for MD-2 and TLR4.

Early-life exposure to per-and polyfluoroalkyl substances:Analysis of levels,health risk and binding abilities to transport proteins

Per-and polyfluoroalkyl substances(PFAS)can pass through the placenta and adversely affect fetal development.However,there is a lack of comparison of legacy and emerging PFAS levels among different biosamples in pregnant women and their offspring.This study,based on the Shanghai Maternal–Child Pairs Cohort,analyzed the concentrations of 16 PFAS in the maternal serum,cord serum,and breast milk samples from 1,076 motherchild pairs.The placental and breastfeeding transfer efficiencies of PFAS were determined in maternal-cord and maternal-milk pairs,respectively.The binding affinities of PFAS to five transporters were simulated using molecular docking.The results suggested that PFAS were frequently detected in different biosamples.The median concentration of perfluorooctane sulfonate(PFOS)was the highest at 8.85 ng/mL,followed by perfluorooctanoic acid(PFOA)at 7.13 ng/mL and 6:2 chlorinated polyfluorinated ether sulfonate at 5.59 ng/mL in maternal serum.The median concentrations of PFOA were highest in cord serum(4.23 ng/mL)and breast milk(1.08 ng/mL).PFAS demonstrated higher placental than breastfeeding transfer efficiencies.The transfer efficiencies and the binding affinities of most PFAS to proteins exhibited alkyl chain length-dependent patterns.Furthermore,we comprehensively assessed the estimated daily intakes(EDIs)of PFAS in breastfeeding infants of different age groups and used the hazard quotient(HQ)to characterize the potential health risk.EDIs decreased with infant age,and PFOS had higher HQs than PFOA.These findings highlight the significance of considering PFAS exposure,transfer mechanism,and health risks resulting from breast milk intake in early life.

A larval specific OBP able to bind the major female sex pheromone component in Spodoptera exigua(Hübner)

Odorant binding proteins （OBPs） in insects are postulated to solubilize and transport the hydrophobic odorants across the hydrophilic antennal lymph to the olfactory receptors （ORs） located on the dendrite membrane of the sensory neurons. OBPs in adult insects have been intensively reported, but those in larvae are rarely addressed. In our study, a full-length OBP cDNA, namely SexiOBP13, was cloned by RT-PCR and RACE strategy from the heads of Spodoptera exigua larvae. The quantitative real-time PCR （qPCR） measurement indicated that SexiOBP13 was highly expressed in larval head, but very low in other parts of larva and was not detected in any tissues of adult. The binding affinities of SexiOBP13 to plant volatiles and female sex pheromone components were measured by competitive binding assays. Interestingly, SexiOBP13 displayed a high binding affinity （Ki=3.82 IJmol L-1） to Z9,E12-14：Ac, the major sex pheromone component of S. exigua, while low affinities to the tested host plant volatiles （Ki〉27 μmol L-l）. The behavioral tests further confirmed that Z9,E12-14：Ac was indeed active to elicit the behavioral activity of the third instar larvae of S. exigua. Taken together, our results suggest that SexiOBP13 may play a role in reception of female sex pheromone in S. exigua larvae. The ecological significance of the larvae preference to the adult female sex pheromone was discussed.

CHEMICAL DERIVATION OF HUMAN INSULIN SUPERAGONISM

The role of three highly conserved insulin residues Tyr^B26 was studied to better understand the relationship between insulin and receptor from rat adipose tissue plasma membranes, lnsulin analogues with a single amino acid substitution or single N-methylation of the peptide bond in the position B26 were all shortened in the C-terminus of the B-chain by four amino acids. The effect of modifications was followed by the binding to the insulin receptor. From our results, we can deduce several conclusions： （1） the replacement of tyrosine in the position B26 by histidine, [N-MeHis^B26]-des-tetrapeptide-（B27-B30）-insulin-B26-amide and [N-MeGlu^B26]-des-tetrapeptide- （B2-B30）-insulin-B26-amide, have no significant effect on the binding affinity and they show binding affinity 105%, 190% and 208%, respectively, of that of human insulin; （2） [Aad^B26] -des-tetrapeptide-（B27-B30）-insulin-B26-amide and [Phe（4-carboxy^B26）]-des-tetrapeptide- （B27~B30）-insulin-B26-amide affect the potency highly positively in vitro studies; they show binding affinity 529 and 289 %, respectively, of that of human insulin.

Expression and functional characterization of odorant-binding protein 2 in the predatory mite Neoseiulus barkeri

Olfaction plays a crucial role for arthropods in foraging,mating,and oviposition.The odorant-binding protein(OBP)gene is considered one of the most important olfactory genes.However,little is known about its functions in predatory mites.Here,we used Neoseiulus barkeri,an important commercialized natural pest control,to explore the chemosensory characteristics of OBP.In this study,N.barkeri was attracted by methyl salicylate(MeSA)and showed higher crawling speeds under MeSA treatment.Then,we identified and cloned an OBP gene named Nbarobp2 and analyzed its expression profiles in the predatory mite.Nbarobp2 was 663 bp,was highly expressed in larval and nymphal stages,and was significantly upregulated in N.barkeri under MeSA treatment.Nbarobp2 encoded 202 amino acid residues with a molecular weight of 23 kDa(after removing the signal peptide).Sequence comparisons revealed that the OBPs in Arachnida shared 6 conserved cysteine sites,but were distinguishable from the OBPs of Insecta on the phylogenetic tree.RNA interference,Western blotting,and binding affinity assays further proved that Nbarobp2 was involved in volatile perception in predatory mites.This study shed light on the functional characteristics of OBPs in predatory mites,providing a new insight for better biological control.

Molecular Modelling of the Therapeutic agents for COVID-19 Treatment

Objective:We aimed to develop a bioinformatics approach for drug discovery variety of effective drugs for Coronavirus disease treatment(COVID-19).Methods:First,the structure of relevant drugs have been optimized and prepared as input data for docking software.Then,The X-ray structure of SARS CoV-2(PDB ID:6VWW)and 2019-nCoV(PDB ID:6M0J)receptors is prepared by eliminating water molecules and unique ligands.Finally,significant interactions have been reported with Discovery Studio 4.5 Client software.Results:The MolDock Score value indicated the positive effect of drugs on the inactivation of COVID-19.Cobicistat and Ritonavir drugs have the most inhibitory effect(MolDock Scores:-160.49 and-205.91 kj/mol),and a wide spectrum of interactions such as Van der Waals,conventional hydrogen bond,carbon-hydrogen bond,Pi-doner hydrogen bond,Pi-Pi stacked,Pi Pi T-shaped,Alkyl,and Pi Alkyl is contributed in final binding affinity.

Principles of amino-acid–ribonucleotide interaction revealed by binding affinities between homogeneous oligopeptides and singlestranded RNA molecules

We have determined the binding strengths between ribonucleotides of adenine(A),guanine(G),uracil(U),and cytosine(C)in homogeneous single-stranded ribonucleic acids(ssRNAs)and homo-decapeptides consisting of 20 common amino acids.We use a bead-based fluorescence assay for these measurements in which decapeptides are immobilized on the bead surface and ssRNAs are in solutions.The results provide a molecular basis for analyzing selectivity,specificity,and polymorphisms of amino-acid–ribonucleotide interactions.Comparative analyses of the distribution of the binding energies reveal unique binding strength patterns assignable to each pair of amino acid and ribonucleotide originating from the chemical structures.Pronounced favorable(such as Arg–G)and unfavorable(such as Met–U)binding interactions can be identified in selected groups of amino acid and ribonucleotide pairs that could provide basis to elucidate energetics of amino-acid–ribonucleotide interactions.Such interaction selectivity,specificity,and polymorphism manifest the contributions from RNA backbone,RNA bases,as well as main chain and side chain of the amino acids.Such characteristics in peptide–RNA interactions might be helpful for understanding the mechanism of protein–RNA specific recognition and the design of RNA nano-delivery systems based on peptides and their derivatives.

Q-BioLiP:A Comprehensive Resource for Quaternary Structure-based Protein-ligand Interactions

Since its establishment in 2013,BioLiP has become one of the widely used resources for protein-ligand interactions.Nevertheless,several known issues occurred with it over the past decade.For example,the protein-ligand interactions are represented in the form of single chain-based tertiary structures,which may be inappropriate as many interactions involve multiple protein chains(known as quaternary structures).We sought to address these issues,resulting in Q-BioLiP,a comprehensive resource for quaternary structure-based protein-ligand interactions.The major features of Q-BioLiP include:(1)representing protein structures in the form of quaternary structures rather than single chain-based tertiary structures;(2)pairing DNA/RNA chains properly rather than separation;(3)providing both experimental and predicted binding affinities;(4)retaining both biologically relevant and irrelevant interactions to alleviate the wrong justification of ligands’biological relevance;and(5)developing a new quaternary structure-based algorithm for the modelling of protein-ligand complex structure.With these new features,Q-BioLiP is expected to be a valuable resource for studying biomolecule interactions,including protein-small molecule interaction,protein-metal ion interaction,protein-peptide interaction,protein-protein interaction,protein-DNA/RNA interaction,and RNA-small molecule interaction.Q-BioLiP is freely available at https://yanglab.qd.sdu.edu.cn/Q-BioLiP/.

Covalent Organic Framework with Predesigned Single-Ion Traps for Highly Efficient Palladium Recovery from Wastes

The recovery of palladium from waste streams is of importance for metal recycling and environmental remediation.Herein,we present a“single-ion trap”strategy for efficiently recovering Pd(II)from superacidic solutions and laboratory wastes.This was realized by rational design and synthesis of an antiparallel stacked covalent organic framework(ACOF)with hydrazine-carbonyl sites and pyridine sites for cooperative Pd(II)capture.The single-ion traps provided Lewis base sites with a high Pd(II)binding affinity,enabling the trapping of Pd(II)ions under a wide range of conditions.The developed ACOF-1 adsorbent demonstrated fast kinetics,excellent selectivity,and a high adsorption capacity of 412.9±14.2 mg/g for Pd(II)in a 3M HNO_(3) solution.When applied in a packed column,ACOF-1 dynamically captured Pd(II)from3M HNO_(3) solutions or laboratorywastes containing trace amounts of palladium and many other metals,realizing extraction efficiencies of 232.9 and 320.9 mg/g,respectively.Detailed experimental and theoretical studies revealed that the single-ion traps offered exceptionally strong binding of Pd(II)under both acidic and high ionic strength conditions,enabling selective adsorptive behavior not accessible using traditional adsorbents.Importantly,the general design strategy reported here could be used to create porous adsorbents for the capture of other precious metals.

Target binding and residence:a new determinant of DNA double-strand break repair pathway choice in CRISPR/Cas9 genome editing

The clustered regularly interspaced short palindromic repeats(CRISPR)/CRISPR-associated protein 9(Cas9)is widely used for targeted genomic and epigenomic modifications and imaging in cells and organisms,and holds tremendous promise in clinical applications.The efficiency and accuracy of the technology are partly determined by the target binding affinity and residence time of Cas9-single-guide RNA(sgRNA)at a given site.However,little attention has been paid to the effect of target binding affinity and residence duration on the repair of Cas9-induced DNA double-strand breaks(DSBs).We propose that the choice of DSB repair pathway may be altered by variation in the binding affinity and residence duration of Cas9-sgRNA at the cleaved target,contributing to significantly heterogeneous mutations in CRISPR/Cas9 genome editing.Here,we discuss the effect of Cas9-sgRNA target binding and residence on the choice of DSB repair pathway in CRISPR/Cas9 genome editing,and the opportunity this presents to optimize Cas9-based technology.

High affinity soluble ILT2 receptor:a potent inhibitor of CD8^(+)T cell activation

Using directed mutagenesis and phage display on a soluble fragment of the human immunoglobulin superfamily receptor ILT2(synonyms:LIR1,MIR7,CD85j),we have selected a range of mutants with binding affinities enhanced by up to 168,000-fold towards the conserved region of major histocompatibility complex(MHC)class I molecules.Produced in a dimeric form,either by chemical cross-linking with bivalent polyethylene glycol(PEG)derivatives or as a genetic fusion with human IgG Fc-fragment,the mutants exhibited a further increase in ligand-binding strength due to the avidity effect,with resident half-times(t1/2)on the surface of MHC I-positive cells of many hours.The novel compounds antagonized the interaction of CD8 co-receptor with MHC I in vitro without affecting the peptide-specific binding of T-cell receptors(TCRs).In both cytokine-release assays and cell-killing experiments the engineered receptors inhibited the activation of CD8^(+)cytotoxic T lymphocytes(CTLs)in the presence of their target cells,with subnanomolar potency and in a dose-dependent manner.As a selective inhibitor of CD8^(+)CTL responses,the engineered high affinity ILT2 receptor presents a new tool for studying the activation mechanism of different subsets of CTLs and could have potential for the development of novel autoimmunity therapies.