Applications of artificial intelligence in digital pathology for gastric cancer DOI Creative Commons
Sheng Chen, Pingan Ding, Honghai Guo

и другие.

Frontiers in Oncology, Год журнала: 2024, Номер 14

Опубликована: Окт. 28, 2024

Gastric cancer is one of the most common cancers and leading causes cancer-related deaths in worldwide. Early diagnosis treatment are essential for a positive outcome. The integration artificial intelligence pathology field increasingly widespread, including histopathological images analysis. In recent years, application digital technology emerged as potential solution to enhance understanding management gastric cancer. Through sophisticated image analysis algorithms, technologies facilitate accuracy sensitivity personalized therapeutic strategies. This review aims evaluate current landscape future transforming pathology, so provide ideas research.

Язык: Английский

Exploring the role of noncoding RNAs in cancer diagnosis, prognosis, and precision medicine DOI Creative Commons
Basmah Eldakhakhny,

Abdulaziz M. Sutaih,

Moaaz A. Siddiqui

и другие.

Non-coding RNA Research, Год журнала: 2024, Номер 9(4), С. 1315 - 1323

Опубликована: Июль 1, 2024

This review article studies the complex field of noncoding RNAs (ncRNAs) in cancer biology, focusing on their potential use as biomarkers and therapeutic targets. NcRNAs include circular (circRNAs), long (lncRNAs), microRNAs (miRNAs). We discuss how ncRNAs affect gene expression cancerous cells, spread cancer, metastasis. The illustrates pathways through which can oncogenesis, tumor suppression, resistance. It also assesses clinical uses non-coding (ncRNAs), including utility diagnosis, prognosis. Besides, for personalized therapy is documented. Finally, it concluded that understanding role ncRNA importance regarding carcinogenesis, therapy.

Язык: Английский

Процитировано

5

Advances and Mechanisms of RNA–Ligand Interaction Predictions DOI Creative Commons
Zhuo Chen, Chengwei Zeng,

Haoquan Liu

и другие.

Life, Год журнала: 2025, Номер 15(1), С. 104 - 104

Опубликована: Янв. 15, 2025

The diversity and complexity of RNA include sequence, secondary structure, tertiary structure characteristics. These elements are crucial for RNA's specific recognition other molecules. With advancements in biotechnology, RNA-ligand structures allow researchers to utilize experimental data uncover the mechanisms complex interactions. However, determining these complexes experimentally can be technically challenging often results low-resolution data. Many machine learning computational approaches have recently emerged learn multiscale-level features predict Predicting interactions remains an unexplored area. Therefore, studying is essential understanding biological processes. In this review, we analyze interaction characteristics by examining structure. Our goal clarify how specifically recognizes ligands. Additionally, systematically discuss methods predicting guide future research directions. We aim inspire creation more reliable prediction tools.

Язык: Английский

Процитировано

0

Designing small molecules that target a cryptic RNA binding site via base displacement DOI Creative Commons
Robert Batey, Lukasz T. Olenginski, Aleksandra J. Wierzba

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Янв. 29, 2025

Abstract Most RNA-binding small molecules have limited solubility, weak affinity, and/or lack of specificity, restricting the medicinal chemistry often required for lead compound discovery. We reasoned that conjugation these unfavorable ligands to a suitable “host” molecule can solubilize “guest” and deliver it site-specifically an RNA interest resolve issues. Using this framework, we designed library was hosted by cobalamin (Cbl) interact with Cbl riboswitch through common base displacement mechanism. Combining in vitro binding, cell-based assays, chemoinformatic modeling, structure-based design, unmasked cryptic binding site within exploited discover compounds affinity exceeding native ligand, antagonize function, or bear no resemblance Cbl. These data demonstrate how privileged biphenyl-like scaffold effectively targets optimizing π-stacking interactions pocket.

Язык: Английский

Процитировано

0

RNA research for drug discovery: Recent advances and critical insight DOI
Patrick Maduabuchi Aja, Peter Chinedu Agu, Celestine O. Ogbu

и другие.

Gene, Год журнала: 2025, Номер 947, С. 149342 - 149342

Опубликована: Фев. 19, 2025

Язык: Английский

Процитировано

0

Specific Interaction between a Fluoroquinolone Derivative, KG022, and RNAs with a Single Bulge DOI

Rika Ichijo,

Gota Kawai

Biochemistry, Год журнала: 2025, Номер unknown

Опубликована: Март 11, 2025

Small compounds targeting RNAs are recognized as a promising modality in drug discovery. We have found that fluoroquinolone derivative, KG022, binds to with single-bulged residues. It has been demonstrated by 1H NMR KG022 bulged G or C and GC AU base pair at the 3′ adjacent In present study, effects of pairs 5′ residues on interaction were analyzed mainly NMR. was prefers UA CG residues, indicating stable complex is formed stacking among ring purine bases sides. addition, this confirmed analysis 19F-NMR spectra. Analysis temperature dependences spectra revealed forms more having position than those pairs. This work presented useful information for development small molecules higher affinity target RNAs.

Язык: Английский

Процитировано

0

Structure‐Binding Relationship of 2‐Amino‐1,8‐Naphthyridine Dimers: Role of Linkage Positions on DNA and RNA Recognition DOI Creative Commons
Bimolendu Das,

Satoki Kuwahara,

Ryosuke Ishimaru

и другие.

Chemistry - A European Journal, Год журнала: 2025, Номер unknown

Опубликована: Апрель 10, 2025

Abstract The study explores the synthesis, structural analysis, and binding properties of eight analogs 2‐amino‐1,8‐naphthyridine dimers (ANPxys) targeting DNA RNA. These dimers, derived from ANP77, are connected at varying positions to investigate how positional alterations influence molecular conformations their interactions with nucleic acids. primary focus lies on evaluating effects these variations RNA through fluorescence quenching thermal denaturation assays. Absorption measurements revealed distinct electronic states for ANPxys, emission maxima between 389.5 398.5 nm. Conformational analysis indicated that most ANPxys adopt unstacked in aqueous solutions, though some, like ANP47 ANP67, showed higher probabilities stacked conformations. Thermal studies demonstrated bind stabilize cytosine‐rich motifs affinities, ANP77 showing strongest effects. U/CC across 256 sequences unique patterns each ANPxy, reflecting sequence specificity. Hierarchical clustering grouped into parallel‐stacked twisted‐stacked clusters, correlating preferences. This work highlights critical role connection determining ANPxy specificity conformational behavior. findings provide a basis designing small molecules tunable structures enhanced RNA‐binding capabilities, paving way development RNA‐targeted therapeutics.

Язык: Английский

Процитировано

0

Advances in artificial intelligence-envisioned technologies for protein and nucleic acid research DOI Creative Commons
Amol D. Gholap, Abdelwahab Omri

Drug Discovery Today, Год журнала: 2025, Номер unknown, С. 104362 - 104362

Опубликована: Апрель 1, 2025

Artificial intelligence (AI) and machine learning (ML) have revolutionized pharmaceutical research, particularly in protein nucleic acid studies. This review summarizes the current status of AI ML applications sector, focusing on innovative tools, web servers, databases. paper highlights how these technologies address key challenges drug development including high costs, lengthy timelines, complexity biological systems. Furthermore, potential personalized medicine, cancer response prediction, biomarker identification is discussed. The integration research promises to accelerate discovery, reduce ultimately lead more effective therapeutic strategies.

Язык: Английский

Процитировано

0

The prediction of RNA-small molecule binding sites in RNA structures based on geometric deep learning DOI

Chunjiang Sang,

Jiasai Shu,

Kang Wang

и другие.

International Journal of Biological Macromolecules, Год журнала: 2025, Номер 310, С. 143308 - 143308

Опубликована: Апрель 21, 2025

Язык: Английский

Процитировано

0

19F-NMR in RNA structural biology: exploring structures, dynamics, and small molecule interactions DOI
CongBao Kang

European Journal of Medicinal Chemistry, Год журнала: 2025, Номер unknown, С. 117682 - 117682

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Applications of artificial intelligence in digital pathology for gastric cancer DOI Creative Commons
Sheng Chen, Pingan Ding, Honghai Guo

и другие.

Frontiers in Oncology, Год журнала: 2024, Номер 14

Опубликована: Окт. 28, 2024

Gastric cancer is one of the most common cancers and leading causes cancer-related deaths in worldwide. Early diagnosis treatment are essential for a positive outcome. The integration artificial intelligence pathology field increasingly widespread, including histopathological images analysis. In recent years, application digital technology emerged as potential solution to enhance understanding management gastric cancer. Through sophisticated image analysis algorithms, technologies facilitate accuracy sensitivity personalized therapeutic strategies. This review aims evaluate current landscape future transforming pathology, so provide ideas research.

Язык: Английский

Процитировано

0