In silico antiplasmodial effects of phytocompounds derived from Andrographis paniculata on validated drug targets of different stages of Plasmodium falciparum

Background:Andrographis paniculata has been widely reported as an herbal plant for malaria treatment.The increasing rate of resistance to recommended antimalarial drugs has justified the need for a continuous search for new and more potent drugs that target all stages of the Plasmodium falciparum life cycle from natural plant sources.This study aimed to determine the antiplasmodial effect of phytocompounds derived from A.paniculata on the stages of plasmodium falciparum.Methods:Phytocompounds from A.paniculata were identified by Gas Chromatography-Mass Spectrophotometry(GCMS)analysis.The phytocompounds were screened for their druggability using Lipinski’s rule of five and subjected to Absorption,Distribution,Metabolism,Excretion,Toxicity(ADMET)and druglikeness analysis.The phytocompounds were docked against some validated drug targets at different stages of Plasmodium falciparum(hepatic,asexual,sexual,and vector targets)using PyRx software to analyze the inhibitory potential and protein-ligand interaction.Thereafter,the stability and flexibility of the best complexes were assessed through molecular dynamics simulations at 50ns using WebGRO.Result:The 7a-Isopropenyl-4,5-dimethyloctahydroinden-4-yl exhibited a higher binding affinity and better stability throughout the simulation period with P.falciparum dihydrofolate reductase-thymidylate synthase and Plasmodium falciparum M1 alanyl aminopeptidase for asexual blood stage and gametocyte stage of Plasmodium falciparum,respectively than the existing drugs.Meanwhile,N-Ethyl-3-methoxy-4-methylphenethylamine was also found to have a higher binding affinity and more stability throughout the simulation period with P.falciparum purine nucleoside phosphorylase and Plasmodium falciparum gametocyte surface protein for Hepatic schizonts stage of Plasmodium falciparum and gametocyte transmission blocking stage,respectively,than the existing drugs.Conclusion:The 7a-Isopropenyl-4,5-dimethyloctahydroinden-4-yl and N-Ethyl-3-methoxy-4 methylphenethylamine from A.paniculata are predicted as an antimalarial drug candidate.Thus,it is recommended that in vitro and in vivo bioassays be conducted on these hit compounds to validate these predictions.

Network biology:A promising approach for drug target identification against neurodevelopmental disorders

Biological entities are involved in complicated and complex connections;hence,discovering biological information using network biology ideas is critical.In the past few years,network biology has emerged as an integrative and systems-level approach for understanding and interpreting these complex interactions.Biological network analysis is one method for reducing enormous data sets to clinically useful knowledge for disease diagnosis,prognosis,and treatment.The network of biological entities can help us predict drug targets for several diseases.The drug targets identified through the systems biology approach help in targeting the essential biological pathways that contribute to the progression and development of the disease.The novel strategical approach of system biologyassisted pharmacology coupled with computer-aided drug discovery(CADD)can help drugs fight multifactorial diseases efficiently.In the present review,we have summarized the role and application of network biology for not only unfolding the mechanism of complex neurodevelopmental disorders but also identifying important drug targets for diseases like ADHD,Autism,Epilepsy,and Intellectual Disability.Systems biology has emerged as a promising approach to identifying drug targets and aiming for targeted drug discovery for the precise treatment of neurodevelopmental disorders.

Fluorescence imaging of drug target proteins using chemical probes

Fluorescence imaging can provide valuable information on the expression,distribution,and activity of drug target proteins.Chemical probes are useful small-molecule tools for fluorescence imaging with high structural flexibility and biocompatibility.In this review,we briefly introduce two classes of fluorescent probes for the visualization of drug target proteins.Enzymatically activatable probes make use of the specific enzymatic transformations that generally produce a fluorogenic response upon reacting with target enzymes.Alternatively,specific imaging can be conferred with a ligand that drives the probes to target proteins,where the labeling relies on noncovalent binding,covalent inhibition,or traceless labeling by ligand-directed chemistry.

Regulatory effects of GRK2 on GPCRs and possible use as a drug target

G protein-coupled receptor kinase 2(GRK2),as a key Ser/Thr protein kinase,belong to the member of the G protein-coupled receptor kinase(GRK)family.The C-terminus of GRK2 including a plekstrin homology domain and the N-terminus of GRK2 including the RGS homology domain with binding sites for several proteins and lipids such as G protein-coupled receptors(GPCRs),G protein,phospholipase C,phosphatidylinositol 4,5-bisphosphate,extracellular signal-regulated kinase,protein kinase A and Gβγ,which can regulate the activity of GRK2.GRK2 can regulate GPCR desensitization and internalization by phosphorylating the GPCR,promoting the affinity of binding to arrestins,and uncoupling the receptors from G proteins,which play an important role in maintaining the balance between the receptors and signal transduction.Previous studies have indicated that cardiac GRK2overexpression can promote the phosphorylation ofβ-adrenergic receptor(βAR)leading toβAR desensitization and internalization,which play a pivotal role in inducing heart failure(HF)-related dysfunction and myocyte death.GRK2,as a regulator of cell function,is overexpression in hypertension.Overexpression GRK2 can inhibit Akt/e NOS signaling pathway and decreased the production and activation of e NOS leading to endothelial dysfunction.Collagen-induced arthritis induces the upregulation of GRK2 expression in fibroblast-like synoviocytes.In this review,we mainly discussed the evidence for the association between GRK2 overexpression and various diseases,which suggests that GRK2 may be an effective drug target for preventing and treating heart failure,hypertension and inflammatory disease.

Experimental study on magnetic drug targeting in treating cholangiocarcinoma based on internal magnetic fields

Objective: To evaluate the effect of magnetic nanoparticle containing 5-fluorouracil (5-FU) targeting in treating chol- angiocarcinoma based on internal magnetic fields built inside the tumor. Methods: 32 nude mice of BABL/C bearing ectopic tumor were built by subcutaneouly injecting cholangiocarcinoma cell line QBC 939. Three weeks after tumor inoculation, the animal models were divided equally into four groups at random including: (a) group A, consisting of internal magnetic field built by magnetic biliary stent wires inserted into tumor tissue and receiving magnetic nanoparticles containing 5-FU administered via tail vein injection at 250 mg/kg for consecutive five days; (b) group B, receiving placebo (sodium chloride); (c) group C, receiving pure magnetic biliary stent wires without the applying of magnetic nanoparticles; (d) group D, consisting of external magnetic fields and the same treatment of magnetic nanoparticles containing 5-FU as group A. The tumor volumes were measured every 3 days, totally six times from treatment started. Tumor tissues were observed by transmission electron microscope when the nude mice were killed after the observation period. Results: The experimental group (group A) showed significantly therapeutic efficacy. Moreover, apoptosis of tumor cells could be easily detected in this group. Conclusion: Magnetic particles containing 5-FU combined with internal magnetic field can effectively treat cholangiocarcinoma, and its therapeutic efficacy is better than that of the traditional method based on external magnetic fields.

Leishmaniasis:Current status of available drugs and new potential drug targets

The control of Leishmania infection relies primarily on chemotherapy till date.Resistance to pentavalent antimonials,which have been the recommended drugs to treat cutaneous and visceral leishmaniasis,is now widespread in Indian subcontinents.New drug formulations like amphotericin B,its lipid formulations,and miltefosine have shown great efGcacy to treat leishmaniasis but their high cost and therapeutic complications limit their usefulness.In addition, irregular and inappropriate uses of these second line drugs in endemic regions like state of Bihar, India threaten resistance development in the parasite.In context to the limited drug options and unavailability of either preventive or prophylactic candidates,there is a pressing need to develop true antileishmanial drugs to reduce the disease burden of this debilitating endemic disease.Notwithstanding significant progress of leishmanial research during last few decades, identification and characterization of novel drugs and drug targets are far from satisfactory.This review will initially describe current drug regimens and later will provide an overview on few important biochemical and enzymatic machineries that could be utilized as putative drug targets for generation of true antileishmanial drugs.

Chemical proteomics:terra incognita for novel drug target profiling

The growing demand for new therapeutic strategies in the medical and pharmaceutic fields has resulted in a pressing need for novel druggable targets.Paradoxically,however,the targets of certain drugs that are already widely used in clinical practice have largely not been annotated.Because the pharmacologic effects of a drug can only be appreciated when its interactions with cellular components are clearly delineated,an integrated deconvolution of drug-target interactions for each drug is necessary.The emerging field of chemical proteomics represents a powerful mass spectrometry(MS)-based affinity chromatography approach for identifying proteome-wide small molecule-protein interactions and mapping these interactions to signaling and metabolic pathways.This technique could comprehensively characterize drug targets,profile the toxicity of known drugs,and identify possible off-target activities.With the use of this technique,candidate drug molecules could be optimized,and predictable side effects might consequently be avoided.Herein,we provide a holistic overview of the major chemical proteomic approaches and highlight recent advances in this area as well as its potential applications in drug discovery.

Inflammation and dysregulation of immune response in Alzheimer disease, the drug target for the future

It has been demonstrated that inflammation and dysregulation of immune response are involved in the pathogenesis of Alzheimer disease (AD). Inflammation is an early event in AD development, especially inflammasome and pro-inflammatory molecules are pathogenic factor in AD. Our data showed that activated immune cells may contribute to the pathogenesis of AD, since the mice with immune cells knock out demonstrated differentsings in the neurodegenerative process and T cells aid clearance of plaques in mice and infiltrating parenchymal T-cell in AD brain mainly in the light of amyloid pathology, and immune treatment is effective, etc. However, the direct evidence on T and B cells infiltrating into the brain of APP transgenic mice have not yet found. Whether aged T cells are pathogenic in AD?How is role of aged B cells? These questions are still unclear. In conclusion, activated immune cells,and inflammatory molecules may play important roles in neurodegenerative disorders, such as AD. The mechanisms of behind this are needed to further study. Inhibiting inflammation in the early phase of AD and restore normal immune regulation are new drug target for the future.

Predicted essential proteins of Plasmodium falciparum for potential drug targets

Objective:To identify novel drug targets for treatment of Plasmodium falciparum.Methods: Local BT.ASTP were used to find the proteins non-homologous to human essential proteins as novel drug targets.Functional domains of novel drug targets were identified by InterPro and Pfam.3D structures of potential drug targets were predicated by the SWISS-MODEL workspace. Ligands and ligand-binding sites of the proteins were searched by Ef-seek.Results:Three essential proteins were identified that might be considered as potential drug targets.AAN37254.1 belonged to 1-deoxy-D-xylulose 5-phosphate reductoisomerase,CAD50499.1 belonged to chorismale synthase,CAD51220.1 belonged to FAD binging 3 family,but the function of CAD51220.1 was unknown.The 3D structures,ligands and ligand-binding sites of AAM37254.1 and CAD50499.1 were successfully predicated.Conclusions:Two of these potential drug targets are key enzymes in 2-C-methyl-d-erythritol 4-phosphate pathway and shikimate pathway, which are absent in humans,so these two essential proteins are good potential drug targets.The function and 3D structures of CAD50499.1 is still unknown,it still need further study.

Discovery and validation of potential drug targets based on the phylogenetic evolution of GPCRs

Target identification is a critical step following the discovery of small molecules that elicit a biological phenotype. G-protein coupled recaptors (GPCRs) are among the most important drug targets for the pharmaceutical industry. The present work seeks to provide an in silico model of known GPCR protein fishing technologies in order to rapidly fish out potential drug targets on the basis of amino acid sequences and seven transmembrane regions (TMs) of GPCRs. Some scoring matrices were trained on 22 groups of GPCRs in the GPCRDB database. These models were employed to predict the GPCR proteins in two groups of test sets. On average, the mean correct rate of each TM of 38 GPCRs from two test sets (ST23 and ST24) was found 62% and 57.5%, respectively, using training set 18 (SLD18);the mean hit rate of each TM of 38 GPCRs from ST23 and ST24 was found 68.1% and 64.7%, respectively. Based on the scoring matrices of PreMod, the mean correct rate of each TM of GPCRs from ST23 and ST24 was found 62% and 62.04%, respectively;the mean hit rate of each TM of GPCRs from ST23 and ST24 was found 67.7% and 68.0%, respecttively. The means of GPCRs in ST23 based on SLD18 is close to those based on PreMod;whereas the means of GPCRs in ST24 based on?SLD18 is less than those based on PreMod. Moreover, the accuracy (“2”) and validity (“2 + 1”) rates of prediction all seven TMs of 38 GPCRs by the scoring matrices of PreMod are more than those by SLD18, SLA14 and SLA3;whereas the hit rates (94.74% and 97.37%) by PreMod are less than those of?SLA3 but bigger than those of?SLD18 and SLA14, respectively. This is the reason that we choose PreMod to predict some potential drug targets. 22 GPCR proteins in the sense chain of chromosome 19 constructing validation set were predicted and validated by PreMod whose hit rate is up to 90.91%. Further evaluation is under investigation.

Research Progress on the Bone Metastasis Mechanism of Prostate Cancer and Bone-Targeted Drugs

Prostate cancer is a common male malignant tumor,and bone metastasis is one of the common complications in the late stage of prostate cancer.The mechanism of prostate cancer bone metastasis is a complex process involving multiple factors and steps.In recent years,with in-depth research on the mechanism of prostate cancer bone metastasis and the development of new drugs,important progress has been made in the treatment of prostate cancer bone metastasis.Based on this,this article introduces the mechanism of prostate cancer bone metastasis and the research progress of several bone-targeted drugs to provide reference and inspiration for future research.

Spatiotemporally resolved metabolomics and isotope tracing reveal CNS drug targets

Deconvolution of potential drug targets of the central nervous system(CNS)is particularly challenging because of the complicated structure and function of the brain.Here,a spatiotemporally resolved metabolomics and isotope tracing strategy was proposed and demonstrated to be powerful for deconvoluting and localizing potential targets of CNS drugs by using ambient mass spectrometry imaging.This strategy can map various substances including exogenous drugs,isotopically labeled metabolites,and various types of endogenous metabolites in the brain tissue sections to illustrate their microregional distribution pattern in the brain and locate drug action-related metabolic nodes and pathways.The strategy revealed that the sedative-hypnotic drug candidate YZG-331 was prominently distributed in the pineal gland and entered the thalamus and hypothalamus in relatively small amounts,and can increase glutamate decarboxylase activity to elevateγ-aminobutyric acid(GABA)levels in the hypothalamus,agonize organic cation transporter 3 to release extracellular histamine into peripheral circulation.These findings emphasize the promising capability of spatiotemporally resolved metabolomics and isotope tracing to help elucidate the multiple targets and the mechanisms of action of CNS drugs.

Iron oxide nanoparticles in magnetic drug targeting and ferroptosis-based cancer therapy

Iron oxide(IO)nanoparticles(NPs)have gained significant attention in the field of biomedicine,particularly in drug targeting and cancer therapy.Their potential in magnetic drug targeting(MDT)and ferroptosis-based cancer therapy is highly promising.IO NPs serve as an effective drug delivery system(DDS),utilizing external magnetic fields(EMFs)to target cancer cells while minimizing damage to healthy organs.Additionally,IO NPs can generate reactive oxygen species(ROS)and induce ferroptosis,resulting in cytotoxic effects on cancer cells.This article explores how IO NPs can potentially revolutionize cancer research,focusing on their applications in MDT and ferroptosis-based therapy.

Drug–Target Interaction Prediction Model Using Optimal Recurrent Neural Network

Drug-target interactions prediction(DTIP)remains an important requirement in thefield of drug discovery and human medicine.The identification of interaction among the drug compound and target protein plays an essential pro-cess in the drug discovery process.It is a lengthier and complex process for pre-dicting the drug target interaction(DTI)utilizing experimental approaches.To resolve these issues,computational intelligence based DTIP techniques were developed to offer an efficient predictive model with low cost.The recently devel-oped deep learning(DL)models can be employed for the design of effective pre-dictive approaches for DTIP.With this motivation,this paper presents a new drug target interaction prediction using optimal recurrent neural network(DTIP-ORNN)technique.The goal of the DTIP-ORNN technique is to predict the DTIs in a semi-supervised way,i.e.,inclusion of both labelled and unlabelled instances.Initially,the DTIP-ORNN technique performs data preparation process and also includes class labelling process,where the target interactions from the database are used to determine thefinal label of the unlabelled instances.Besides,drug-to-drug(D-D)and target-to-target(T-T)interactions are used for the weight initia-tion of the RNN based bidirectional long short term memory(BiLSTM)model which is then utilized to the prediction of DTIs.Since hyperparameters signifi-cantly affect the prediction performance of the BiLSTM technique,the Adam optimizer is used which mainly helps to improve the DTI prediction outcomes.In order to ensure the enhanced predictive outcomes of the DTIP-ORNN techni-que,a series of simulations are implemented on four benchmark datasets.The comparative result analysis shows the promising performance of the DTIP-ORNN method on the recent approaches.

Integrated causal inference modeling uncovers novel causal factors and potential therapeutic targets of Qingjin Yiqi granules for chronic fatigue syndrome

Objective:Chronic fatigue syndrome(CFS)is a prevalent symptom of post-coronavirus disease 2019(COVID-19)and is associated with unclear disease mechanisms.The herbal medicine Qingjin Yiqi granules(QJYQ)constitute a clinically approved formula for treating post-COVID-19;however,its potential as a drug target for treating CFS remains largely unknown.This study aimed to identify novel causal factors for CFS and elucidate the potential targets and pharmacological mechanisms of action of QJYQ in treating CFS.Methods:This prospective cohort analysis included 4,212 adults aged≥65 years who were followed up for 7 years with 435 incident CFS cases.Causal modeling and multivariate logistic regression analysis were performed to identify the potential causal determinants of CFS.A proteome-wide,two-sample Mendelian randomization(MR)analysis was employed to explore the proteins associated with the identified causal factors of CFS,which may serve as potential drug targets.Furthermore,we performed a virtual screening analysis to assess the binding affinity between the bioactive compounds in QJYQ and CFS-associated proteins.Results:Among 4,212 participants(47.5%men)with a median age of 69 years(interquartile range:69–70 years)enrolled in 2004,435 developed CFS by 2011.Causal graph analysis with multivariate logistic regression identified frequent cough(odds ratio:1.74,95%confidence interval[CI]:1.15–2.63)and insomnia(odds ratio:2.59,95%CI:1.77–3.79)as novel causal factors of CFS.Proteome-wide MR analysis revealed that the upregulation of endothelial cell-selective adhesion molecule(ESAM)was causally linked to both chronic cough(odds ratio:1.019,95%CI:1.012–1.026,P=2.75 e^(−05))and insomnia(odds ratio:1.015,95%CI:1.008–1.022,P=4.40 e^(−08))in CFS.The major bioactive compounds of QJYQ,ginsenoside Rb2(docking score:−6.03)and RG4(docking score:−6.15),bound to ESAM with high affinity based on virtual screening.Conclusions:Our integrated analytical framework combining epidemiological,genetic,and in silico data provides a novel strategy for elucidating complex disease mechanisms,such as CFS,and informing models of action of traditional Chinese medicines,such as QJYQ.Further validation in animal models is warranted to confirm the potential pharmacological effects of QJYQ on ESAM and as a treatment for CFS.

Recent advances in promising drugs for primary prevention of gastroesophageal variceal bleeding with cirrhotic portal hypertension

Background:Gastroesophageal variceal bleeding is one of the most severe complications of patients with cirrhosis.Although primary prevention drugs,including non-selectiveβ-blockers,have effectively reduced the incidence of bleeding,their efficacy is limited due to side effects and related contraindications.With recent advances in precision medicine,precise drug treatment provides better treatment efficacy.Data sources:Literature search was conducted in PubMed,MEDLINE and Web of Science for relevant articles published up to May 2022.Information on clinical trials was obtained from https://clinicaltrials.gov/and http://www.chictr.org.cn/.Results:The in-depth understanding of the pathogenesis and advances of portal hypertension has enabled the discovery of multiple molecular targets for promising drugs.According to the site of action,these drugs could be classified into four classes:intrahepatic,extrahepatic,both intrahepatic and extrahepatic targets and others.All these classes of drugs offer advantages over traditional treatments in prevention of gastroesophageal variceal bleeding in patients with cirrhotic portal hypertension.Conclusions:This review classified and summarized the promising drugs,which prevent gastroesophageal variceal bleeding by targeting specific markers of pathogenesis of portal hypertension,demonstrating the significance of using the precision medicine strategy to discover and develop promising drugs for the primary prevention of gastroesophageal variceal bleeding in patients with cirrhotic portal hypertension.

Glucocorticoids-based prodrug design:Current strategies and research progress

Attributing to their broad pharmacological effects encompassing anti-inflammation,antitoxin,and immunosuppression,glucocorticoids(GCs)are extensively utilized in the clinic for the treatment of diverse diseases such as lupus erythematosus,nephritis,arthritis,ulcerative colitis,asthma,keratitis,macular edema,and leukemia.However,longterm use often causes undesirable side effects,including metabolic disorders-induced Cushing's syndrome(buffalo back,full moon face,hyperglycemia,etc.),osteoporosis,aggravated infection,psychosis,glaucoma,and cataract.These notorious side effects seriously compromise patients'quality of life,especially in patients with chronic diseases.Therefore,glucocorticoid-based advanced drug delivery systems for reducing adverse effects have received extensive attention.Among them,prodrugs have the advantages of low investment,low risk,and high success rate,making them a promising strategy.In this review,we propose the strategies for the design and summarize current research progress of glucocorticoid-based prodrugs in recent decades,including polymer-based prodrugs,dendrimer-based prodrugs,antibody-drug conjugates,peptide-drug conjugates,carbohydrate-based prodrugs,aliphatic acid-based prodrugs and so on.Besides,we also raise issues that need to be focused on during the development of glucocorticoid-based prodrugs.This review is expected to be helpful for the research and development of novel GCs and prodrugs.

Drug resistance mechanisms and novel drug targets for tuberculosis therapy

Drug-resistant tuberculosis （TB） poses a significant challenge to the successful treatment and control of TB worldwide. Resistance to anti-TB drugs has existed since the beginning of the chemotherapy era. New insights into the resistant mechanisms of anti-TB drugs have been provided. Better understanding of drug resistance mechanisms helps in the development of new tools for the rapid diagnosis of drug- resistant TB. There is also a pressing need in the development of new drugs with novel targets to improve the current treatment of TB and to prevent the emergence of drug resistance in Mycobacterium tuber- culosis. This review summarizes the anti-TB drug resistance mechanisms, furnishes some possible novel drug targets in the development of new agents for TB therapy and discusses the usefulness using known targets to develop new anti-TB drugs. Whole genome sequencing is currently an advanced technology to uncover drug resistance mechanisms in M. tuberculosis. However, further research is required to unravel the significance of some newly discovered gene mutations in their contribution to drug resistance.

Structures of EV71 RNA-dependent RNA polymerase in complex with substrate and analogue provide a drug target against the hand-foot-and-mouth disease pandemic in China

Enterovirus 71(EV71),one of the major causative agents for hand-foot-and-mouth disease(HFMD),has caused more than 100 deaths among Chinese children since March 2008.The EV71 genome encodes an RNAdependent RNA polymerase(RdRp),denoted 3D^(pol),which is central for viral genome replication and is a key target for the discovery of specific antiviral therapeutics.Here we report the crystal structures of EV71 RdRp(3D^(pol))and in complex with substrate guanosine-5'-triphosphate and analog 5-bromouridine-5'-triphosphate best to 2.4Åresolution.The structure of EV71 RdRp(3D^(pol))has a wider open thumb domain compared with the most closely related crystal structure of poliovirus RdRp.And the EV71 RdRp(3D^(pol))complex with GTP or Br-UTP bounded shows two distinct movements of the polymerase by substrate or analogue binding.The model of the complex with the template:primer derived by superimposition with foot-and-mouth disease virus(FMDV)3D/RNA complex reveals the likely recognition and binding of template:primer RNA by the polymerase.These results together provide a molecular basis for EV71 RNA replication and reveal a potential target for anti-EV71 drug discovery.

Drug target inference by mining transcriptional data using a novel graph convolutional network framework

A fundamental challenge that arises in biomedicine is the need to characterize compounds in a relevant cellular context in order to reveal potential on-target or offtarget effects.Recently,the fast accumulation of gene transcriptional profiling data provides us an unprecedented opportunity to explore the protein targets of chemical compounds from the perspective of cell transcriptomics and RNA biology.Here,we propose a novel Siamese spectral-based graph convolutional network(SSGCN)model for inferring the protein targets of chemical compounds from gene transcriptional profiles.Although the gene signature of a compound perturbation only provides indirect clues of the interacting targets,and the biological networks under different experiment conditions further complicate the situation,the SSGCN model was successfully trained to learn from known compound-target pairs by uncovering the hidden correlations between compound perturbation profiles and gene knockdown profiles.On a benchmark set and a large time-split validation dataset,the model achieved higher target inference accuracy as compared to previous methods such as Connectivity Map.Further experimental validations of prediction results highlight the practical usefulness of SSGCN in either inferring the interacting targets of compound,or reversely,in finding novel inhibitors of a given target of interest.