Current Computer - Aided Drug Design - Volume 21, Issue 1, 2025

Diagnosis and treatment planning play a very vital role in improving the survival of oncological patients. However, there is high variability in the shape, size, and structure of the tumor, making automatic segmentation difficult. The automatic and accurate detection and segmentation methods for brain tumors are proposed in this paper.

A modified ResNet50 model was used for tumor detection, and a ResUNetmodel-based convolutional neural network for segmentation is proposed in this paper. The detection and segmentation were performed on the same dataset consisting of pre-contrast, FLAIR, and post-contrast MRI images of 110 patients collected from the cancer imaging archive. Due to the use of residual networks, the authors observed improvement in evaluation parameters, such as accuracy for tumor detection and dice similarity coefficient for tumor segmentation.

The accuracy of tumor detection and dice similarity coefficient achieved by the segmentation model were 96.77% and 0.893, respectively, for the TCIA dataset. The results were compared based on manual segmentation and existing segmentation techniques. The tumor mask was also individually compared to the ground truth using the SSIM value. The proposed detection and segmentation models were validated on BraTS2015 and BraTS2017 datasets, and the results were consensus.

The use of residual networks in both the detection and the segmentation model resulted in improved accuracy and DSC score. DSC score was increased by 5.9% compared to the UNet model, and the accuracy of the model was increased from 92% to 96.77% for the test set.

Osteoporosis (OP) is one of the most common diseases in the elderly population. It is mostly treated with medication, but drug research and development have the disadvantage of taking a long time and having a high cost.

Therefore, we developed a graph neural network with the help of artificial intelligence to provide new ideas for drug research and development for OP.

In this study, we built a new osteoporosis graph (called OPGraph) and proposed a deep graph neural network (called DeepTransformer) to predict new drugs for OP. OPGraph is a graph data model established by gathering features and their interrelationships from a vast amount of OP data. DeepTransformer uses GraphTransformer as its foundational network and applies residual connections for deep layering.

The analysis and results showed that DeepTransformer outperformed numerous models on OPGraph, with area under the curve (AUC) and area under the precision-recall curve (AUPR) reaching 0.9916 and 0.9911, respectively. In addition, we conducted an in vitro validation experiment on two of the seven predicted compounds (Puerarin and Aucubin), and the results corroborated the predictions of our model.

The model we developed with the help of artificial intelligence can effectively reduce the time and cost of OP drug development and reduce the heavy economic burden brought to patient's family by complications caused by osteoporosis.

Receptor tyrosine kinases (RTKs) are potent oncoproteins in cancer that, when mutated or overexpressed, can cause uncontrolled growth of cells, angiogenesis, and metastasis, making them significant targets for cancer treatment. Vascular endothelial growth factor receptor 2 (VEGFR2), is a tyrosine kinase receptor that is produced in endothelial cells and is the most crucial regulator of angiogenic factors involved in tumor angiogenesis. So, a series of new substituted N-(4-((2-aminopyrimidin-5-yl)oxy)phenyl)-N-phenyl cyclopropane-1,1-dicarboxamide derivatives as VEGFR-2 inhibitors have been designed and synthesized.

Utilizing H-NMR, C13-NMR, and mass spectroscopy, the proposed derivatives were produced and assessed. HT-29 and COLO-205 cell lines were used for the cytotoxicity tests. The effective compound was investigated further for the Vegfr-2 kinase inhibition assay, cell cycle arrest, and apoptosis. A molecular docking examination was also carried out with the Maestro-12.5v of Schrodinger.

In comparison to the reference drug Cabozantinib (IC50 = 9.10 and 10.66 μM), compound SP2 revealed promising cytotoxic activity (IC50 = 4.07 and 4.98 μM) against HT-29 and COLO-205, respectively. The synthesized compound SP2 showed VEGFR-2 kinase inhibition activity with (IC50 = 6.82 μM) against the reference drug, Cabozantinib (IC50 = 0.045 μM). Moreover, compound SP2 strongly induced apoptosis by arresting the cell cycle in the G1 phase. The new compounds' potent VEGFR-2 inhibitory effect was noted with key amino acids Asp1044, and Glu883, and the hydrophobic interaction was also observed in the pocket of the VEGFR-2 active site by using a docking study.

The results demonstrate that at the cellular and enzyme levels, the synthetic compounds SP2 are similarly effective as cabozantinib. The cell cycle and apoptosis data demonstrate the effectiveness of the suggested compounds. Based on the findings of docking studies, cytotoxic effects, in vitro VEGFR-2 inhibition, apoptosis, and cell cycle arrest, this research has given us identical or more effective VEGFR-2 inhibitors.

Breast cancer (BC) is by far seen as the most common malignancy globally, with 2.261 million patients newly diagnosed, accounting for 11.7% of all cancer patients, according to the Global Cancer Statistics Report (2020). The luminal A subtype accounts for at least half of all BC diagnoses. According to TCM theory, Bushen Huoxue Decoction (BSHXD) is a prescription used for cancer treatment that may influence luminal A subtype breast cancer (LASBC).

To analyze the clinical efficacy and underlying mechanisms of BSHXD in LASBC.

Network pharmacology and in vitro experiments were utilized to foresee the underlying mechanism of BSHXD for LASBC.

According to the bioinformatics analysis, BSHXD induced several proliferation and apoptosis processes against LASBC, and the presumed targets of active components in BSHXD were mainly enriched in the HIF-1 and PI3K/AKT pathways. Flow cytometry assay and western blotting results revealed that the rate of apoptosis enhanced in a dose-dependent manner with BSHXD concentration increasing, respectively. BSHXD notably downregulated the expressions of HIF-1α, P-PI3K, PI3K, P-AKT and AKT proteins. However, adding an HIF-1α agonist restored those protein levels.

The study proved that the mechanism of BSHXD in LASBC may be connected to suppressing proliferation by inhibiting the activity of the HIF-1α/PI3K/AKT signaling pathway and promoting apoptosis via the Caspase cascade in LASBC cells.

Neglected tropical diseases (NTDs) are parasitic and bacterial diseases that affect approximately 149 countries, mainly the poor population without basic sanitation. Among these, Human African Trypanosomiasis (HAT), known as sleeping sickness, shows alarming data, with treatment based on suramin and pentamidine in the initial phase and melarsoprol and eflornithine in the chronic phase. Thus, to discover new drugs, several studies point to rhodesain as a promising drug target due to the function of protein degradation and intracellular transport of proteins between the insect and host cells and is present in all cycle phases of the parasite.

Here, based on the previous studies by Nascimento et al. (2021) [5], that show the main rhodesain inhibitors development in the last decade, molecular docking and dynamics were applied in these inhibitors datasets to reveal crucial information that can be into drug design.

Also, our findings using MD simulations and MM-PBSA calculations confirmed Gly¹⁹, Gly²³, Gly⁶⁵, Asp¹⁶¹, and Trp¹⁸⁴, showing high binding energy (ΔGbind between -72.782 to -124.477 kJ.mol^-1). In addition, Van der Waals interactions have a better contribution (-140,930 to -96,988 kJ.mol^-1) than electrostatic forces (-43,270 to -6,854 kJ.mol^-1), indicating Van der Waals interactions are the leading forces in forming and maintaining ligand-rhodesain complexes. Thus, conventional and covalent docking was employed and highlighted the presence of Michael acceptors in the ligands in a peptidomimetics scaffold, and interaction with Gly¹⁹, Gly²³, Gly⁶⁵, Asp¹⁶¹, and Trp¹⁸⁴ is essential to the inhibiting activity. Furthermore, the Dynamic Cross-Correlation Maps (DCCM) show more correlated movements for all complexes than the free rhodesain and strong interactions in the regions of the aforementioned residues. Principal Component Analysis (PCA) demonstrates complex stability corroborating with RMSF and RMSD.

This study can provide valuable insights that can guide researchers worldwide to discover a new promising drug against HAT.

Sanguinarine (SAN) has been reported to have antioxidant, anti-inflammatory, and antimicrobial activities with potential for the treatment of osteoporosis (OP).

This work purposed to unravel the molecular mechanisms of SAN in the treatment of OP.

OP-related genes and SAN-related targets were predicted from public databases. Differential expression analysis and VennDiagram were adopted to detect SAN-related targets against OP. Protein-protein interaction (PPI) network was served for core target identification. Molecular docking and DeepPurpose algorithm were further adopted to investigate the binding ability between core targets and SAN. Gene pathway scoring of these targets was calculated utilizing gene set variation analysis (GSVA). Finally, we explored the effect of SAN on the expressions of core targets in preosteoblastic MC3T3-E1 cells.

A total of 21 candidate targets of SAN against OP were acquired. Furthermore, six core targets were identified, among which CASP3, CTNNB1, and ERBB2 were remarkably differentially expressed in OP and healthy individuals. The binding energies of SAN with CASP3, CTNNB1, and ERBB2 were -6, -6.731, and -7.162 kcal/mol, respectively. Moreover, the GSVA scores of the Wnt/calcium signaling pathway were significantly lower in OP cases than in healthy individuals. In addition, the expression of CASP3 was positively associated with Wnt/calcium signaling pathway. CASP3 and ERBB2 were significantly lower expressed in SAN group than in DMSO group, whereas the expression of CTNNB1 was in contrast.

CASP3, CTNNB1, and ERBB2 emerge as potential targets of SAN in OP prevention and treatment.

Uncaria tomentosa is a traditional medicinal herb renowned for its anti-inflammatory, antioxidant, and immune-enhancing properties. In the realm of neurodegenerative diseases (NDDS), CLASP proteins, responsible for regulating microtubule dynamics in neurons, have emerged as critical players. Dysregulation of CLASP proteins is associated with NDDS, such as Alzheimer's, Parkinson's, and Huntington's diseases. Consequently, comprehending the role of CLASP proteins in NDDS holds promise for the development of innovative therapeutic interventions.

The objectives of the research were to identify phytoconstituents in the hydroalcoholic extract of Uncaria tomentosa (HEUT), to evaluate its antioxidant potential through in vitro free radical scavenging assays and to explore its potential interaction with CLASP using in silico molecular docking studies.

HPLC and LC-MS techniques were used to identify and quantify phytochemicals in HEUT. The antioxidant potential was assessed through DPPH, ferric reducing antioxidant power (FRAP), nitric oxide (NO) and superoxide (SO) free radical scavenging methods. Interactions between conventional quinovic acid, chlorogenic acid, epicatechin, corynoxeine, rhynchophylline and syringic acid and CLASP were studied through in silico molecular docking using Auto Dock 4.2.

The HEUT extract demonstrated the highest concentration of quinovic acid derivatives. HEUT exhibited strong free radical-scavenging activity with IC50 values of 0.113 µg/ml (DPPH) and 9.51 µM (FRAP). It also suppressed NO production by 47.1 ± 0.37% at 40 µg/ml and inhibited 77.3 ± 0.69% of SO generation. Additionally, molecular docking revealed the potential interaction of quinovic acid with CLASP for NDDS.

The strong antioxidant potential of HEUT and the interaction of quinovic acid with CLASP protein suggest a promising role in treating NDDS linked to CLASP protein dysregulation.

In recent years, the incidence of rectal prolapse has increased significantly due to the sedentary lifestyle and irregular eating habits of modern life. However, there is a lack of clinical studies on the treatment of rectal prolapse with traditional Chinese medicine (TCM) with a large sample size. Therefore, this study investigated the characteristics of rectal prolapse treatment formulas and then studied the network pharmacology of their core therapeutic drugs, which can help to provide a reference for the treatment and postoperative care of rectal prolapse patients.

This study aimed to explore the prescription characteristics and the mechanism of action of core drugs in the treatment of rectal prolapse in Chinese medicine through data mining and bioinformatics techniques.

We collected the diagnosis and treatment information of patients with rectal prolapse from January 2014 to September 2021 in the electronic case database of Nanjing Hospital of TCM, mined the patient information and prescription features using R, screened the active ingredients of the core pairs of drugs and disease drug intersection targets using TCMSP and GnenCard databases, and constructed a Protein-protein interaction (PPI) network using STRING and Cytoscape, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the intersecting targets were performed using Metascape and R.

We found that prolapse is easy to occur in people over 50 years old, preferably in autumn and winter. Commonly used therapeutic Chinese medicines include Glycyrrhiza glabra, Radix angelicae sinensis, Radix astragali, Atractylodes macrocephala, and Pericarpium citri reticulatae, which are mostly deficiency tonic medicines, warm in nature, and belong to spleen meridian. The core therapeutic medicinal pair was “Bupleuri radix-Cimicifugae rhizoma”. There were 190 common targets of Bupleuri radix and Cimicifugae rhizoma, and 71 intersection targets of the drug pair and prolapse. The main components of the core drugs for the treatment of prolapse may be quercetin, kaempferol, Stigmasterol, etc, and the core targets may be CASP3, AKT1, HIF1A, etc. The total number of GO entries for the intersection targets of “Bupleuri radix-Cimicifugae rhizoma” and diseases was 3495, among which the molecular functions accounted for the largest proportion, mainly Pathways in cancer, IL-18 signaling pathway, etc. KEGG enriched pathway analysis yielded 168 results, and the major pathways were pathways in cancer, lipid and atherosclerosis, IL-17 signaling pathway, etc.

This study adopted real-world research methodology and used data mining and bioinformatics technology to mine the medication law of rectal prolapse and its core drug action mechanism from the clinical information of Chinese medicine.