Lactobacillus plantarum as an Anti-Photoaging Agent: Computational Analysis of Bioactive Compounds and Protein Targets

Marina Rimadhani¹, Muhammad Yulianto Listiawan^2,3, Ingrid Suryanti Surono⁴,

Anang Endaryanto^3,5, Cita Rosita Sigit Prakoeswa^2,3*

¹Doctoral Program of Medical Science , Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.

²Department of Dermatology and Venereology, Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia

³Dr. Soetomo General Academic Hospital, Surabaya, Indonesia

⁴Food Technology Department, Faculty of Engineering, Universitas Bina Nusantara, Jakarta, Indonesia.

⁵Department of Child Health, Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.

*Corresponding Author E-mail: marina.rimadhani-2023@fk.unair.ac.id, m.yulianto@fk.unair.ac.id, isurono@binus.edu, anang.endaryanto@fk.unair.ac.id, cita-rosita@fk.unair.ac.id

ABSTRACT:

This in-silico study will describe the involvement of L. plantarum in preventing photoaging. The metabolite products of L. plantarum were determined from the literature and searched by using the PubChem database. Prediction of metabolite product activities used the Structure Analysis Relationship (SAR) approach. Target association analysis and pharmacology network analysis were performed. Functional annotation was analyzed to determine the function of a gene identified at the intersection of the Venn diagram. The bioactive compounds of L. plantarum consist of lactic acid, lipoteichoic acid, and hyaluronic acid, hence it has an antiaging potential. There were 99 target proteins interacting with L. plantarum and related to photoaging. Based on functional annotation analysis, L. plantarum could play roles in keratinization, keratinocyte differentiation, ceramide biosynthetic process, establishment of the skin barrier, removal of superoxide radicals, tumor necrosis factor (TNF), nuclear factor kappa B (NF)-kappa B, KEAP-NFE2L2, as well as antiaging pathways. This in-silico study needs further in vitro as well as in vivo studies to validate the findings, particularly in the form of clinical trials. The bioactive compounds of L. plantarum have an antiaging potential, particularly hyaluronic acid.

KEYWORDS: Lactobacillus plantarum, anti-photoaging, bioactive compounds, target protein, molecular docking.

INTRODUCTION:

Photoaging is a progressive decrease in skin function and capacity, an external aging process due to chronic ultraviolet (UV) irradiation and sun exposure^1,2. Indonesian people are prone to extrinsic skin aging due to long-term sun exposure³. A study in Australia and New Zealand reported that 1,400 out of 2,095 subjects suffered from photoaging⁴. In Indonesia, particularly Jakarta, a study involving 136 subjects showed that 78 subjects suffered from early aging due to sun exposure⁵.

UV irradiation, particularly UVB, can damage deoxyribonucleic acid (DNA) stronger than UVA in the epidermis and dermis, leading to photoaging signs and precancerous lesions⁶. Reactive oxygen species (ROS) accumulate due to the induction by UVB exposure, resulting in membrane damage^7,8. ROS upregulates nuclear factor kappa B (NF-kB) by activating inhibitory-kappa b kinase (IKK) as well as induces inflammatory mediators, one of which is interleukin (IL)-6^9-11. UVB also inhibits transforming growth factor beta-1 (TGF-b1), which decreases the expression of hyaluronan synthases-2 (HAS-2), leading to hyaluronic acid degradation, resulting in dry skin and an increase in transepidermal water loss (TEWL)¹². In addition, UVB activates matrix metalloproteinase (MMP), decreasing pro-collagen synthesis and increasing collagen degradation, resulting in wrinkles^7,13. Another transcription factor that might play a role in photoaging is nuclear-factor-erythroid-related factor-2 (Nrf2), which upregulates various detoxification enzymes and antioxidant transcription. The responsible protective gene can potentially neutralize ROS rapidly. UVB is also known to increase pigmentation due to the induction of tyrosinase-related protein (TRP)-1^9,14,15.

In the past few years, several natural extracts and artificial chemicals have been used to treat photoaging due to UVB irradiation⁶. However, the materials were reported to have side effects and were relatively expensive. Recently, the role of probiotics on skin health has been studied extensively. Probiotics are thought to play a role in skin health, microbiome diversity, skin diseases related to microbiome, and photoaging^16,17. The mechanism of how probiotics act on photoaging has not yet been elucidated. The most used preparation in topical applications is lysate because it tends to be stable compared to the live cell form. Lysate is a cell whose outer membrane is damaged due to chemical or physical processes but can still provide beneficial effects similar to the live probiotics bacteria. A previous study by Prakoeswa et al. reported that oral Lactobacillus plantarum showed significant benefits in atopic dermatitis patients^18,19. However, to date, there has been no report on the effect of topical L. plantarum on photoaging. This in-silico research will describe the involvement of L. plantarum in preventing photoaging.

MATERIALS AND METHODS:

Lactobacillus plantarum structure optimization:

The bioactive structure of L. plantarum was explored in the literature²⁰. The simplified molecular-input line-entry system (SMILE) was searched through the PubChem database²¹. SMILE is a simplified order that describes the structure profile of a compound.

Utilization of Structure Analysis Relationship (SAR) approach for predicting metabolite product activities:

The potential of L. plantarum bioactive structures was predicted with WAY2DRUG Pass prediction for antiaging therapy. A comparison of the input and known compounds with certain potentials was analyzed utilizing the Structure Analysis Relationship (SAR) approach, and the prediction score becomes greater as the compound structure becomes more similar. The compound with great similarity usually has similar potential. The probability of activation (Pa) score refers to the compound’s potential with scores 0-1. Pa score is defined as the predicted function’s accuracy. The greater the Pa score, the more accurate the score²².

Target association analysis and target protein prediction:

Target protein prediction was analyzed through the Comparative Toxigenomic Database. Targets related to photoaging were acquired from The Human Gene Database Genecards²³. A Venn diagram was utilized to map disease related as well as L. plantarum targets, resulting in the determination of the target intersection. JVENN tools (helped visualize the data in the form of a Venn diagram²⁴.

Pharmacology network analysis:

The targets’ intersection from the previous step was analyzed for its protein interaction using STRING DB V.12 database with parameters of Organism: Homo sapiens, Network type: full STRING network, Score: confidence interaction (0.5), and FDR stringency medium 5%²⁵. Cytoscape V10.1 was utilized to process tsv format from STRING output. Cytospace program was used to visualize the interaction and perform network analysis with a centrality analysis approach. The protein included in the densest top centrality was interpreted as the protein with the most interaction with other proteins in the network. Therefore, if the protein was targeted, it could influence other proteins, also known as the protein hub.

Besides calculating the degree score, the shortest path analysis was performed to determine the closeness centrality (CC) score. CC score can predict how fast the information flows from one node to another node. The score ranges from 0 to 1. The closer the score to 1, the better the flow. The node with a high CC score is easier to access²⁶.

Functional annotation:

Database for Annotation, Visualization, and Integrated Discovery (DAVID) determined a gene’s function, which was identified at the intersection of the Venn diagram²⁷. The terminologies which had a false discovery rate < 0.05 will be discussed further. The annotation used referred to the Gene Ontology (https://geneontology.org/).

RESULT:

Lactobacillus plantarum structure optimization

The bioactive structure of L. plantarum consists of lactic acid, lipoteichoic acid, and hyaluronic acid (Table 1).

Table 1. Bioactive structures of L. plantarum

No	Compound	PubChem ID	SMILE
1.	Lactic acid	612	CC(C(=O)O)O
2.	Lipoteichoic acid	137349712	CCCCCCC/C=C/CCCCCC(=O)O[C@@H](CO[C@@H]1[C@@H]([C@H]([C@@H]([C@H](O1)CO)O)O[C@H]2[C@@H]([C@H]([C@H]([C@H](O2)C)N)O)NC(=O)C)O)COC(=O)CCCCCC
3.	Hyaluronic acid	24759	CC(=O)NC1C(C(C(OC1O)CO)O)OC2C(C(C(C(O2)C(=O)O)OC3C(C(C(C(O3)CO)O)OC4C(C(C(C(O4)C(=O)O)O)O)O)NC(=O)C)O)O

Prediction of bioactive compound activities by using the Structure Analysis Relationship (SAR) approach:

Based on the prediction of bioactive compound activities of L. plantarum with the SAR approach, L. plantarum is predicted to have an antiaging potential. L. plantarum has a good potential as a hyaluronic acid agonist (0.643), TP53 expression enhancer (0.570), immunomodulator (0.537), anti-inflammatory agent (0.518), free radical scavenger (0.501), and anti-enzymatic agent (0.456) (Figure 1). Lactic acid (0.491) and hyaluronic acid (0.501) are compounds with the highest predictive score as an antiaging agent (the average score of hyaluronic acid agonist, free radical scavenger, MMP inhibitor, and anti-inflammatory agent) (Figure 2). Each of the compounds contributed to the L. plantarum’s role as an antiaging agent. The high number of compounds contained in L. plantarum is expected to play a role as an additive compound, which can elevate the potential of L. plantarum as an antiaging agent.

Figure 1. The relative prediction score of L. plantarum’s potential based on the Structure Analysis Relationship approach

Figure 2. The potential of L. plantarum’s bioactive compounds based on the Structure Analysis Relationship approach

Target association analysis and target protein prediction:

Based on the prediction search of the targets that could interact with L. plantarum, it was shown that L. plantarum interacted with 3,622 targets. Two hundred and eighty-six targets associated with photoaging were obtained from the compilation of the Genecard database. Ninety-nine target proteins interacted with L. plantarum and were associated with photoaging (Figure 3).

Figure 3. L. plantarum and photoaging intersecting targets

Pharmacology network analysis:

Ninety-nine targets interacting with L. plantarum and related to photoaging are shown in Figure 4. Of all proteins related to inflammation, tumor necrosis factor (TNF), IL, and PTGS2 are proteins with the highest degree score. The higher the degree score, the more protein interactions. This translates into more intervention of other protein interactions if L. plantarum interacts with the protein with a high degree score.

Figure 4. Protein-protein interaction network in relation to photoaging

Note: The redder the color and the larger the node, the more protein interactions.

Based on CC score analysis, AKT1, IL-6, and TNF are proteins with the highest degree and CC scores (Figure 5) (Table 2).

Figure 5. Scatter plot of closeness centrality (CC) and degree score of the proteins. AKT1, IL-6, and TNF are proteins with the highest degree and CC score.

Table 2. Top protein with closeness centrality score > 0.5 and degree score > 10

No	Protein	Closeness Centrality	Degree	No	Protein	Closeness Centrality	Degree
1	AKT1	0.69	53	22	NFE2L2	0.57	29
2	TNF	0.66	52	23	NFKBIA	0.56	33
3	IL6	0.66	52	24	BCL2L1	0.56	30
4	IL1B	0.65	50	25	MAPK8	0.56	32
5	PTGS2	0.63	45	26	MMP3	0.55	34
6	MMP9	0.63	48	27	MAPK14	0.55	30
7	JUN	0.63	46	28	MAPK1	0.55	30
8	HIF1A	0.63	43	29	TIMP1	0.53	30
9	MYC	0.62	43	30	SMAD2	0.53	25
10	EGFR	0.62	45	31	CASP8	0.53	25
11	CTNNB1	0.61	42	32	COL1A1	0.52	26
12	NFKB1	0.61	42	33	PPARD	0.52	17
13	CASP3	0.61	43	34	MMP1	0.52	27
14	MAPK3	0.60	40	35	PTK2	0.52	22
15	TGFB1	0.60	42	36	HBEGF	0.51	21
16	FOS	0.59	42	37	RPS6KB1	0.51	19
17	EGF	0.59	39	38	MMP14	0.51	22
18	TLR4	0.58	37	39	MMP13	0.50	21
19	CREB1	0.57	35	40	SOD2	0.50	19
20	MMP2	0.57	38	41	RPS27A	0.50	20
21	IL1A	0.57	37	42	SOD1	0.50	18

Based on the target search, L. plantarum could not interact directly with COL1A1 and TYRP1. Interaction with COL1A1 was facilitated by HAS2, while interaction with TYRP1 was facilitated by TYR (Figure 6).

Figure 6. Protein-protein interaction of the target of interest (MMP1, NFE2L2, COL1A1, IL-6, HAS2, and TYRP1). Green represents the target of interest, a circle represents L. plantarum’s target, while a square represents the target of interest that was not directly targeted by L. plantarum

Functional annotation:

Based on functional annotation analysis, L. plantarum’s target could interact with the targets that play a role in keratinization, keratinocyte differentiation, ceramide biosynthetic process, establishment of the skin barrier, removal of superoxide radicals, TNF, NF-kB, KEAP-NFE2L2 pathway, as well as aging pathway (Figure 7).

Figure 7. Functional annotation target of L. plantarum (p was less than 0.05)

DISCUSSION:

UV exposure leads to skin photoaging, which manifests as dyspigmentation, dry skin, thickened skin, as well as wrinkles. A constituent of the skin, collagen, can be synthesized or broken down. A study in fibro embryonic NIH 3T3 mice and hairless SKH-1 mice determined how far infrared (FIR) could hinder photoaging of the skin through UVB exposure. UVB significantly increased the expression of MMP-1 and 9^28,29. FIR could inhibit both MMP’s expression. The decrease in type 1 collagen was overturned with FIR therapy. FIR also hinders the Akt/mTOR pathway, leading to autophagy. Autophagy refers to a dynamical activity that degrades stress-induced dysfunctional cell constituents. Autophagy is closely regulated by several pathways. Akt/mTOR is the most researched pathway that regulates autophagy in a negative manner. mTOR is known to have vital involvement in apoptosis, angiogenesis, growth of cells, homeostasis of energy, proliferation, as well as translation of protein. Skin cancer has a high prevalence in the world, and aberrant activation of Akt/mTOR is often identified. The occurrence of skin cancer is highly affected by UVB exposure. Furthermore, the proliferation and survival of keratinocytes, which were induced by UVB exposure, can decrease by mTOR inhibition. mTOR inhibition induces autophagy within the keratinocytes, leading to a reduction in proliferation. Consequently, the critical involvement of autophagy and mTOR inhibition offers novel targets and strategies aimed at improved prevention of cutaneous damage induced by UV exposure²⁸.

IL-6 and TNF were two proteins included in the top targets. Both proteins are involved in the inflammatory response^30-32. TNF-α is able to facilitate UV radiation’s damaging influences, such as UVB. Keratinocytes and fibroblasts produce this factor, and it is involved in photoaging. Stimulation with TNF-α increases MMP-1 mRNA as well as other inflammatory cytokines’ expression, which can worsen skin aging^30,33,34.

L. plantarum plays a good role as a TP53 expression enhancer. TP53 plays an important role in sensitivity to chemotherapy and aging. Activity recovery of WT-TP53 leads to improved chemotherapeutic drugs’ sensitivity as well as increased main components’ expression of the DDR1, PI3K/Akt, and Raf/MEK/ERK pathways. DDR1 can modify the Raf/MEK/ERK and PI3K/Akt pathways and make cells sensitive to chemotherapy drugs. Conversely, a dominant negative (DN) TP53 gene represses WT TP53, leading to a decreased level of DDR1 protein as well as an increase in chemoresistance. Activity recovery of WT TP53 and amplified DDR1’s expression as an antiaging collagen receptor might increase chemotherapeutic drugs’ sensitivity. The study found a vital relationship concerning WT TP53 and DDR1 that is able to modify PI3K/Akt and Raf/MEK/ERK pathways, also aging and sensitivity towards chemotherapy³⁵. Cells are protected from stress-induced DNA damage by the Arf/p53 pathway. These characteristics are responsible for the tumor suppressor activity. In addition, this pathway also modifies aging-associated chronic stress. These all contribute to its antiaging potential. Increasing the dose of the Arf/p53 gene hinders aging signs. Increasing the dose of Arf/p53 is also known to hinder stem cell exhaustion due to aging, as well as the consequent deterioration of tissue regeneration and homeostasis. Nevertheless, the activation of p53 might also stimulate aging pathways. Tissue regeneration is decreased by p53, which is associated with early stem cell exhaustion³⁶. The role of L. plantarum as a TP53 expression enhancer is expected to help in the process of slowing aging.

Intrinsic and extrinsic aging are two different and independent processes of aging, which signifies the multifactor involvement in the aging process. Young-looking skin maintains its elasticity, flexibility, and turgor due to the excessive water constituents. Day-to-day environmental injuries, aside from the natural aging course, cause moisture disturbances. Hyaluronic acid is greatly involved in skin moisture and has a unique capacity to retain water³⁷. Skin aging is not only chronological but also caused by external factors, also known as the exposome. Hyaluronic acid, an essential extracellular matrix constituent, undergoes a decrease starting from the age of 25. Few literature reviews have addressed topical hyaluronic acid use in dermatology. Several studies supported cosmeceuticals containing hyaluronic acid as an effective, non-invasive answer to improve skin moisture as well as rejuvenation³⁸. Lactobacillus kefiri, a valuable lactic acid bacteria, is usually utilized for fermented milk and is advantageous for health when being utilized for fermenting food^39-41. Fermented supernatant (LAF) was made with the culture of L. kefiri, and the LAF was studied at the cellular, molecular biology, and biochemical levels for its antiaging potential. Quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) was utilized to identify MMP-1, AKT and MAPK pathway, type I collagen,  as well as other genes’ expression regarding the LAF’s antiaging potential. Based on the study’s findings, LAF was found to be able to hinder human skin fibroblast (HSF) aging at the cellular, molecular biology, and biochemical levels. It was also able to be used as a functional ingredient for food⁴². L. plantarum, as an example of lactic acid bacteria^43-45, is expected to help in the process of slowing down aging by increasing hyaluronic acid levels in the body.

UV exposure leads to direct damage of DNA, induces ROS, as well as disturbs the function of the skin barrier. This results in the activation of several pro-inflammatory receptors that induce photoaging via collagen degradation and inflammatory conditions⁴⁶. Epidermal barrier dysfunction, inflammatory responses, and chronic pruritus interact with each other, which contribute to the pathogenesis and pathophysiology of AD in the elderly⁴⁷. That damage to the skin barrier and loss of water content in the body can accelerate the aging process and the occurrence of atopic dermatitis. L. plantarum has a role as an immunomodulator, anti-inflammatory, free radical scavenger, and anti-eczema^48,49, which can harmoniously help in the process of slowing down aging (Figure 8).

Figure 8. Potential role of Lactobacillus plantarum in preventing skin aging

AP1 = activator protein 1; ARE = antioxidant response cis-element; ERK = extracellular signal-regulated kinase; HQ-1 = hydroquinone 1 ; IKB = inhibitors of kappa B; IKK = inhibitory kappa B kinase; IL = interleukin; JNK = Jun kinase; Keap1 = Kelch-like ECH-associated protein 1; LP = L. plantarum; MAPK = mitogen-activated protein kinase; MMP = matrix metalloproteinase; NFkB = nuclear factor kappa beta; nrf2 =  nuclear erythroid-2-p45-related factor-2; ROS = reactive oxygen species; TNF = tumor necrosis factor.

CONCLUSION:

All bioactive compounds of L. plantarum have antiaging potential, particularly hyaluronic acid. L. plantarum plays a major role in antioxidant and anti-inflammatory pathways.

CONFLICT OF INTEREST:

The authors have no conflicts of interest regarding this investigation.

ACKNOWLEDGMENTS:

None.

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Received on 20.12.2024      Revised on 13.09.2025

Accepted on 06.02.2026 Published on 20.05.2026

Available online from May 25, 2026

Research J. Pharmacy and Technology. 2026;19(5):2374-2380.

DOI: 10.52711/0974-360X.2026.00340

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