International Journal of Molecular Sciences

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4 pages, 201 KiB

Open AccessEditorial

Natural Anticancer Molecules and Their Therapeutic Potential

by Junmin Zhang and Elaine Lai-Han Leung

Int. J. Mol. Sci. 2023, 24(22), 16066; https://doi.org/10.3390/ijms242216066 - 8 Nov 2023

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Abstract

Cancer poses a significant global public health challenge [...] Full article

(This article belongs to the Special Issue Natural Anticancer Molecules and Their Therapeutic Potential)

Research

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12 pages, 7142 KiB

Open AccessArticle

Tubeimoside-1 Enhances TRAIL-Induced Apoptotic Cell Death through STAMBPL1-Mediated c-FLIP Downregulation

by So Rae Song, Seung Un Seo, Seon Min Woo, Ji Yun Yoon, Simmyung Yook and Taeg Kyu Kwon

Int. J. Mol. Sci. 2023, 24(14), 11840; https://doi.org/10.3390/ijms241411840 - 24 Jul 2023

Cited by 1 | Viewed by 1471

Abstract

Tubeimoside-1 (TBMS-1), a traditional Chinese medicinal herb, is commonly used as an anti-cancer agent. In this study, we aimed to investigate its effect on the sensitization of cancer cells to tumor necrosis factor-related apoptosis-inducing ligand (TRAIL). Our results revealed that even though monotherapy [...] Read more.

Tubeimoside-1 (TBMS-1), a traditional Chinese medicinal herb, is commonly used as an anti-cancer agent. In this study, we aimed to investigate its effect on the sensitization of cancer cells to tumor necrosis factor-related apoptosis-inducing ligand (TRAIL). Our results revealed that even though monotherapy using TBMS-1 or TRAIL at sublethal concentrations did not affect cancer cell death, combination therapy using TBMS-1 and TRAIL increased apoptotic cell death. Mechanistically, TBMS-1 destabilized c-FLIP expression by downregulating STAMBPL1, a deubiquitinase (DUB). Specifically, when STAMBPL1 and c-FLIP bound together, STAMBPL1 deubiquitylated c-FLIP. Moreover, STAMBPL1 knockdown markedly increased sensitivity to TRAIL by destabilizing c-FLIP. These findings were further confirmed in vivo using a xenograft model based on the observation that combined treatment with TBMS-1 and TRAIL decreased tumor volume and downregulated STAMBPL1 and c-FLIP expression levels. Overall, our study revealed that STAMBPL1 is essential for c-FLIP stabilization, and that STAMBPL1 depletion enhances TRAIL-mediated apoptosis via c-FLIP downregulation. Full article

(This article belongs to the Special Issue Natural Anticancer Molecules and Their Therapeutic Potential)

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17 pages, 2940 KiB

Open AccessArticle

StackTHPred: Identifying Tumor-Homing Peptides through GBDT-Based Feature Selection with Stacking Ensemble Architecture

by Jiahui Guan, Lantian Yao, Chia-Ru Chung, Ying-Chih Chiang and Tzong-Yi Lee

Int. J. Mol. Sci. 2023, 24(12), 10348; https://doi.org/10.3390/ijms241210348 - 19 Jun 2023

Cited by 6 | Viewed by 2156

Abstract

One of the major challenges in cancer therapy lies in the limited targeting specificity exhibited by existing anti-cancer drugs. Tumor-homing peptides (THPs) have emerged as a promising solution to this issue, due to their capability to specifically bind to and accumulate in tumor [...] Read more.

One of the major challenges in cancer therapy lies in the limited targeting specificity exhibited by existing anti-cancer drugs. Tumor-homing peptides (THPs) have emerged as a promising solution to this issue, due to their capability to specifically bind to and accumulate in tumor tissues while minimally impacting healthy tissues. THPs are short oligopeptides that offer a superior biological safety profile, with minimal antigenicity, and faster incorporation rates into target cells/tissues. However, identifying THPs experimentally, using methods such as phage display or in vivo screening, is a complex, time-consuming task, hence the need for computational methods. In this study, we proposed StackTHPred, a novel machine learning-based framework that predicts THPs using optimal features and a stacking architecture. With an effective feature selection algorithm and three tree-based machine learning algorithms, StackTHPred has demonstrated advanced performance, surpassing existing THP prediction methods. It achieved an accuracy of 0.915 and a 0.831 Matthews Correlation Coefficient (MCC) score on the main dataset, and an accuracy of 0.883 and a 0.767 MCC score on the small dataset. StackTHPred also offers favorable interpretability, enabling researchers to better understand the intrinsic characteristics of THPs. Overall, StackTHPred is beneficial for both the exploration and identification of THPs and facilitates the development of innovative cancer therapies. Full article

(This article belongs to the Special Issue Natural Anticancer Molecules and Their Therapeutic Potential)

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14 pages, 18986 KiB

Open AccessArticle

Curcumin and Plumbagin Synergistically Target the PI3K/Akt/mTOR Pathway: A Prospective Role in Cancer Treatment

by Iftikhar Ahmad, Mehboob Hoque, Syed Sahajada Mahafujul Alam, Torki A. Zughaibi and Shams Tabrez

Int. J. Mol. Sci. 2023, 24(7), 6651; https://doi.org/10.3390/ijms24076651 - 2 Apr 2023

Cited by 21 | Viewed by 2751

Abstract

Cancer development is associated with the deregulation of various cell signaling pathways brought on by certain genetic and epigenetic alterations. Therefore, novel therapeutic strategies have been developed to target those pathways. The phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) (PI3K/Akt/mTOR) [...] Read more.

Cancer development is associated with the deregulation of various cell signaling pathways brought on by certain genetic and epigenetic alterations. Therefore, novel therapeutic strategies have been developed to target those pathways. The phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) (PI3K/Akt/mTOR) pathway is one major deregulated pathway in various types of cancer. Several anticancer drug candidates are currently being investigated in preclinical and/or clinical studies to target this pathway. Natural bioactive compounds provide an excellent source for anticancer drug development. Curcumin and plumbagin are two potential anticancer compounds that have been shown to target the PI3K/Akt/mTOR pathway individually. However, their combinatorial effect on cancer cells is still unknown. This study aims to investigate the synergistic effect of these two compounds on the PI3K/Akt/mTOR pathway by employing a sequential molecular docking and molecular dynamics (MD) analysis. An increase in binding affinity and a decrease in inhibition constant have been observed when curcumin and plumbagin were subjected to sequential docking against the key proteins PI3K, Akt, and mTOR. The MD simulations and molecular mechanics combined with generalized Born surface area (MM-GBSA) analyses validated the target proteins’ more stable conformation when interacting with the curcumin and plumbagin combination. This indicates the synergistic role of curcumin and plumbagin against cancer cells and the possible dose advantage when used in combination. The findings of this study pave the way for further investigation of their combinatorial effect on cancer cells in vitro and in vivo models. Full article

(This article belongs to the Special Issue Natural Anticancer Molecules and Their Therapeutic Potential)

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17 pages, 3192 KiB

Open AccessArticle

6-Shogaol as a Novel Thioredoxin Reductase Inhibitor Induces Oxidative-Stress-Mediated Apoptosis in HeLa Cells

by Shoujiao Peng, Shaopeng Yu, Junmin Zhang and Jiange Zhang

Int. J. Mol. Sci. 2023, 24(5), 4966; https://doi.org/10.3390/ijms24054966 - 4 Mar 2023

Cited by 10 | Viewed by 2046

Abstract

Inhibition of thioredoxin reductase (TrxR) is a crucial strategy for the discovery of antineoplastic drugs. 6-Shogaol (6-S), a primary bioactive compound in ginger, has high anticancer activity. However, its potential mechanism of action has not been thoroughly investigated. In this study, we demonstrated [...] Read more.

Inhibition of thioredoxin reductase (TrxR) is a crucial strategy for the discovery of antineoplastic drugs. 6-Shogaol (6-S), a primary bioactive compound in ginger, has high anticancer activity. However, its potential mechanism of action has not been thoroughly investigated. In this study, we demonstrated for the first time that 6-S, a novel TrxR inhibitor, promoted oxidative-stress-mediated apoptosis in HeLa cells. The other two constituents of ginger, 6-gingerol (6-G) and 6-dehydrogingerduone (6-DG), have a similar structure to 6-S but fail to kill HeLa cells at low concentrations. 6-Shogaol specifically inhibits purified TrxR1 activity by targeting selenocysteine residues. It also induced apoptosis and was more cytotoxic to HeLa cells than normal cells. The molecular mechanism of 6-S-mediated apoptosis involves TrxR inhibition, followed by an outburst of reactive oxygen species (ROS) production. Furthermore, TrxR knockdown enhanced the cytotoxic sensitivity of 6-S cells, highlighting the physiological significance of targeting TrxR by 6-S. Our findings show that targeting TrxR by 6-S reveals a new mechanism underlying the biological activity of 6-S and provides meaningful insights into its action in cancer therapeutics. Full article

(This article belongs to the Special Issue Natural Anticancer Molecules and Their Therapeutic Potential)

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25 pages, 4957 KiB

Open AccessArticle

Investigating a Library of Flavonoids as Potential Inhibitors of a Cancer Therapeutic Target MEK2 Using in Silico Methods

by Wejdan M. AlZahrani, Shareefa A. AlGhamdi, Sayed S. Sohrab and Mohd Rehan

Int. J. Mol. Sci. 2023, 24(5), 4446; https://doi.org/10.3390/ijms24054446 - 23 Feb 2023

Cited by 6 | Viewed by 1967

Abstract

The second leading cause of death in the world is cancer. Mitogen-activated protein kinase (MAPK) and extracellular signal-regulated protein kinase (ERK) 1 and 2 (MEK1/2) stand out among the different anticancer therapeutic targets. Many MEK1/2 inhibitors are approved and widely used as anticancer [...] Read more.

The second leading cause of death in the world is cancer. Mitogen-activated protein kinase (MAPK) and extracellular signal-regulated protein kinase (ERK) 1 and 2 (MEK1/2) stand out among the different anticancer therapeutic targets. Many MEK1/2 inhibitors are approved and widely used as anticancer drugs. The class of natural compounds known as flavonoids is well-known for their therapeutic potential. In this study, we focus on discovering novel inhibitors of MEK2 from flavonoids using virtual screening, molecular docking analyses, pharmacokinetic prediction, and molecular dynamics (MD) simulations. A library of drug-like flavonoids containing 1289 chemical compounds prepared in-house was screened against the MEK2 allosteric site using molecular docking. The ten highest-scoring compounds based on docking binding affinity (highest score: −11.3 kcal/mol) were selected for further analysis. Lipinski’s rule of five was used to test their drug-likeness, followed by ADMET predictions to study their pharmacokinetic properties. The stability of the best-docked flavonoid complex with MEK2 was examined for a 150 ns MD simulation. The proposed flavonoids are suggested as potential inhibitors of MEK2 and drug candidates for cancer therapy. Full article

(This article belongs to the Special Issue Natural Anticancer Molecules and Their Therapeutic Potential)

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16 pages, 2168 KiB

Open AccessArticle

Accelerating the Discovery of Anticancer Peptides through Deep Forest Architecture with Deep Graphical Representation

by Lantian Yao, Wenshuo Li, Yuntian Zhang, Junyang Deng, Yuxuan Pang, Yixian Huang, Chia-Ru Chung, Jinhan Yu, Ying-Chih Chiang and Tzong-Yi Lee

Int. J. Mol. Sci. 2023, 24(5), 4328; https://doi.org/10.3390/ijms24054328 - 21 Feb 2023

Cited by 14 | Viewed by 2989

Abstract

Cancer is one of the leading diseases threatening human life and health worldwide. Peptide-based therapies have attracted much attention in recent years. Therefore, the precise prediction of anticancer peptides (ACPs) is crucial for discovering and designing novel cancer treatments. In this study, we [...] Read more.

Cancer is one of the leading diseases threatening human life and health worldwide. Peptide-based therapies have attracted much attention in recent years. Therefore, the precise prediction of anticancer peptides (ACPs) is crucial for discovering and designing novel cancer treatments. In this study, we proposed a novel machine learning framework (GRDF) that incorporates deep graphical representation and deep forest architecture for identifying ACPs. Specifically, GRDF extracts graphical features based on the physicochemical properties of peptides and integrates their evolutionary information along with binary profiles for constructing models. Moreover, we employ the deep forest algorithm, which adopts a layer-by-layer cascade architecture similar to deep neural networks, enabling excellent performance on small datasets but without complicated tuning of hyperparameters. The experiment shows GRDF exhibits state-of-the-art performance on two elaborate datasets (Set 1 and Set 2), achieving 77.12% accuracy and 77.54% F1-score on Set 1, as well as 94.10% accuracy and 94.15% F1-score on Set 2, exceeding existing ACP prediction methods. Our models exhibit greater robustness than the baseline algorithms commonly used for other sequence analysis tasks. In addition, GRDF is well-interpretable, enabling researchers to better understand the features of peptide sequences. The promising results demonstrate that GRDF is remarkably effective in identifying ACPs. Therefore, the framework presented in this study could assist researchers in facilitating the discovery of anticancer peptides and contribute to developing novel cancer treatments. Full article

(This article belongs to the Special Issue Natural Anticancer Molecules and Their Therapeutic Potential)

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Review

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23 pages, 6247 KiB

Open AccessReview

Analogues of Anticancer Natural Products: Chiral Aspects

by Jindra Valentová, Lucia Lintnerová, Natalia Miklášová, Bianka Oboňová and Ladislav Habala

Int. J. Mol. Sci. 2023, 24(6), 5679; https://doi.org/10.3390/ijms24065679 - 16 Mar 2023

Cited by 9 | Viewed by 3119

Abstract

Life is chiral, as its constituents consist, to a large degree, of optically active molecules, be they macromolecules (proteins, nucleic acids) or small biomolecules. Hence, these molecules interact disparately with different enantiomers of chiral compounds, creating a preference for a particular enantiomer. This [...] Read more.

Life is chiral, as its constituents consist, to a large degree, of optically active molecules, be they macromolecules (proteins, nucleic acids) or small biomolecules. Hence, these molecules interact disparately with different enantiomers of chiral compounds, creating a preference for a particular enantiomer. This chiral discrimination is of special importance in medicinal chemistry, since many pharmacologically active compounds are used as racemates—equimolar mixtures of two enantiomers. Each of these enantiomers may express different behaviour in terms of pharmacodynamics, pharmacokinetics, and toxicity. The application of only one enantiomer may improve the bioactivity of a drug, as well as reduce the incidence and intensity of adverse effects. This is of special significance regarding the structure of natural products since the great majority of these compounds contain one or several chiral centres. In the present survey, we discuss the impact of chirality on anticancer chemotherapy and highlight the recent developments in this area. Particular attention has been given to synthetic derivatives of drugs of natural origin, as naturally occurring compounds constitute a major pool of new pharmacological leads. Studies have been selected which report the differential activity of the enantiomers or the activities of a single enantiomer and the racemate. Full article

(This article belongs to the Special Issue Natural Anticancer Molecules and Their Therapeutic Potential)

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