Network pharmacology-based virtual screening of active alkaloid ingredients from Piper nigrum L.and the potential targets against Parkinson’s disease

Ye Chang,Yuxi Wang,Xiaoxiao Huang＊,Shaojiang Song＊

Key Laboratory of Computational Chemistry-Based Natural Antitumor Drug Research &Development,Liaoning Province,School of Traditional Chinese Materia Medica,Shenyang Pharmaceutical University,Shenyang 110016,China

Abstract Parkinson’s disease (PD) is a common neurodegenerative disease.Despite a great deal of research on this disease,there is still no definitive treatment plan.Literature investigations have shown that Piper nigrum L.has a protective effect on the nerve center.Therefore,network pharmacology was used in this study to investigate the therapeutic potential of P.nigrum for PD.As a result,six active alkaloid ingredients and four potential targets were obtained.This study laid the foundation for finding the lead compounds from P.nigrum to treat PD.

Key words: Piper nigrum L.; network pharmacology;Parkinson’s disease

1 Introduction

Parkinson’s disease (PD) is a common neurodegenerative disorder that seriously affects the health of the elderly people [1].The symptoms of PD include motor symptoms and non-motor symptoms.Parkinson’s disease psychosis (PDP) is a common feature of non-motor symptoms,and patients develop illusions,passage hallucinations and presence hallucinations [2].Motor symptoms of PD are bradykinesia,rigidity,resting tremor and a variety of interrelated motor phenomena [3].Pathogenic factors of PD may include age,gender,family inheritance,genetic mutation and environment.The pathogenesis of PD involves many aspects,including mitochondrial dysfunction,neuroinflammation,oxidative stress and accumulation of

α

-synuclein [4].So far,no diseasemodifying therapy has been developed to stop or delay the disease process or mortality.Patients can only relieve their pain with palliative care [5].Besides,the clinical diagnosis of PD is complicated,and relies mostly on the clinical experience of doctors.Although magnetic resonance imaging (MRI) can help diagnose PD [6] and improves the diagnosis efficiency,more therapeutic methods must be developed.

Piper nigrum

L.is a woody vine of Piperaceae,which is widely distributed in tropical and subtropical regions.Previous studies on the chemical components in

P.nigrum

have identified a large number of alkaloid compounds with anticancer,antioxidant,anti-inflammatory and neuroprotective activities [7,8].In this study,we used the method of network pharmacology to screen out the active alkaloid compounds from

P.nigrum

against PD,which laid a foundation for finding the lead compounds against PD.

2 Materials and methods

2.1 Collecting and processing of compounds

A series of 150 reported alkaloid compounds in

P.nigrum

were screened through literature survey.Three-dimensional structures of the compounds were made with ChemBioDraw 3D and optimized with MM2 molecular mechanics.

2.2 Screening and processing of target proteins

We locked in multiple keywords to ensure the accuracy of disease targets collection.Thirtyfive human targets were searched from Therapeutic Target database (TTD;http://bidd.nus.edu.sg/group/cjttd/) and the UnProt database (http://www.UnProt.org) and the three-dimensional structures of the target proteins were downloaded from the RCSB Protein Data Bank database (PDB;http://www.rscb.org/pdb/home/home.do).Finally,we used Sybyl-X(version 2.0,TRIPOS,Inc.) software to optimize the target proteins by removing the original ligands and hydrone,adding hydrogen atom,repairing and optimizing amino acid residues.

2.3 Molecular docking

The 35 target proteins and 150 compounds were used for simulation docking in Sybyl-X(version 2.0,TRIPOS,Inc.) and molecules with scores higher than eight were screened.Molecular docking is a method for designing drugs according to the characteristics of receptors and the interaction between receptors and drug molecules.It mainly studies interactions between molecules and predicts their binding modes and affinity.In this experiment,we first prepared high-resolution target protein crystals,original ligands and structurally optimized compounds.Then we established a receptor model to obtain the macromolecular structure and binding site,and a small molecule database was established as well.Finally,we did docking and scoring.

2.4 Constructing compound target-protein network

According to the target prediction results of the 150 chemical components of

P.nigrum

,the compound-target correspondence relationship was established in an excel table,and imported into Cytoscape 3.6.1 software to construct the network.The nodes in the network represented compounds and targets and the edges indicated the compoundtarget interactions.After treatment,a prediction map of relevant targets of the components was obtained,which was used to identify the compounds in

P.nigrum

and clarify their binding ability to PDrelated proteins.

3 Results and discussion

3.1 Prediction of potential compounds

We used Sybyl-X (version 2.0,TRIPOS,Inc.)software to dock 150 candidate alkaloid compounds with 35 potential targets of PD.As shown in Fig.1,the molecular network graph contained 127 nodes and 677 edges,where regular octagons and inverted triangles represented the active compounds and target proteins,respectively.Docking score was used as a standard to evaluate the binding abilities of compounds to target proteins.The relationship between the binding ability and the docking score was proportional.Compounds with docking scores greater than 8 were screened,and these compounds had better activities than others.

Fig.1 The compounds-target proteins network.Regular octagons represent the compounds,while inverted triangles stand for target proteins.The degree of relevance is proportional to the color and shape.Compounds in the inner circle show much more interactions with target proteins than those in the outer circles

In molecular networks,degree and betweenness centrality are two important topological parameters reflecting the interaction ability of compounds with target proteins.Degree is the number of neighbors represented by nodes in an undirected graph.The importance of a node in information transmission is reflected by betweenness centrality.These parameters are used to quantify the impact of nodes and interactive communication of information between nodes.The compound-target protein network was shown in Fig.1.We compared the scores of 150 compounds with eight.Results showed that 1-(eicosa-2

E

,4

E

,14

Z

-trienyl)piperidine (27),1-(octadeca-2

E

,4

E

,14

Z

-trienyl)pyrrolidine (67) [9],pipyaqubine(70) [10],(2

E

,4

E

,12

Z

)-

N

-isobutyl-octadeca-2,4,12-trienamide (94),

N

-isobutyl-(2

E

,4

E

,14

Z

)-eicosa-2,4,14-trienamide (95) [11] and (2

Z

,4

Z

)-

N

-isobutyleicosa-2,4-dienamide (100) [12] had more potent activity than other compounds.Potentially active alkaloid compounds were shown in Fig.2.The degree and betweenness of the six potentially active alkaloid compounds were shown in Table 1.

Fig.2 Structures of potentially active alkaloid compounds.

Table 1 The molecules with higher degree and betweenness in molecular-target network map

3.2 Prediction of target proteins

Twenty targets were identified to be closely related to 107 chemical components in the molecular network.These targets indicated that many potentially active proteins could be targeted by more than one compound.Through molecular network analysis,we screened seven target proteins with orders of magnitude greater than 40 and displayed them in Table 2.Among the thirty-five target proteins,amine oxidase (flavin-containing) B(2v5z),amine oxidase [flavin-containing] A (2z5y),amine oxidase [flavin-containing] B (2xfn) and myeloperoxidase (5mfa) were predicted to be the most promising targets.Fig.3 showed the network relationship between the most potentially active target proteins and compounds.

Fig.3 Network relationship between the most potentially active target proteins and compounds

Table 2 Target proteins with higher degree in molecule-target network map

4 Conclusion

Network analysis showed that 107 alkaloid compounds of

P.nigrum

could interact with related proteins,among which 1-(eicosa-2

E

,4

E

,14

Z

-trienyl)piperidine (27),1-(octadeca-2

E

,4

E

,14

Z

-trienyl)pyrrolidine (67),pipyaqubine (70),(2

E

,4

E

,12

Z

)-

N

-isobutyl-octadeca-2,4,12-trienamide (94),

N

-isobutyl-(2

E

,4

E

,14

Z

)-eicosa-2,4,14-trienamide(95) and (2

Z

,4

Z

)-

N

-isobutyl-eicosa-2,4-dienamide(100) had better activities.In addition,four potential targets were predicted,namely amine oxidase(flavin-containing) B (2v5z),amine oxidase [flavincontaining] A (2z5y),amine oxidase [flavincontaining] B (2xfn) and myeloperoxidase (5mfa).This research will help us to find the lead compounds from

P.nigrum

for the treatment of PD,and lay the foundation for further research on its action pathway and mechanism.