Methods : a Companion to Methods in Enzymology

DNA-binding proteins are a class of proteins that can interact with DNA molecules through physical and chemical interactions. Their main functions include regulating gene expression, maintaining chromosome structure and stability, and more. DNA-binding proteins play a crucial role in cellular and molecular biology, as they are essential for maintaining normal cellular physiological functions and adapting to environmental changes. The prediction of DNA-binding proteins has been a hot topic in the field of bioinformatics...

BACKGROUND: Breast cancer (BC), the most common form of malignant cancer affecting women worldwide, was characterized by heterogeneous metabolic disorder and lack of effective biomarkers for diagnosis. The purpose of this study is to search for reliable metabolite biomarkers of BC as well as triple-negative breast cancer (TNBC) using serum metabolomics approach. METHODS: In this study, an untargeted metabolomics technique based on ultra-high performance liquid chromatography combined with mass spectrometry (UHPLC-MS) was utilized to investigate the differences in serum metabolic profile between the BC group (n = 53) and non-BC group (n = 57), as well as between TNBC patients (n = 23) and non-TNBC subjects (n = 30)...

A highly efficient sensor has been successfully developed using quinoline-based BODIPY compounds (8-quinoline-4,4-difluoro-4-boro-3a, 4a-diazaindacene (C1) and 7-hydroxy-8-quinoline-4,4-difluoro-4-boro-3a, 4a-diazindacene (C2) to detect Hg2+ ions. The sensor C1 exhibits remarkable selectivity in detecting Hg2+ with a limit of detection 3.06 × 10-8 mol/L. The developed chemical sensors have shown stability, cost-effectiveness, ease of preparation, and remarkable selectivity towards Hg2+ ions compared to other commonly occurring metal ions...

Design of molecules for candidate compound selection is one of the central challenges in drug discovery due to the complexity of chemical space and requirement of multi-parameter optimization. Here we present an application scenario-oriented platform (ID4Idea) for molecular generation in different scenarios of drug discovery. This platform utilizes both library or rule based and generative based algorithms (VAE, RNN, GAN etc.), in combination with various AI learning types (pre-training, transfer learning, reinforcement learning, and active learning etc...

Hazardous cyanide anions (CN- ) are increasingly threatening the environment and human health due to their widespread use in industry and many other fields. Over the past three decades, a large number of probes have been reported to sensitively and selectively detect this toxic anion, while a rather limited number of ratiometric fluorescent probes have been developed. The ratiometric probes have significant potential in bio-imaging and biomedical applications because of the ability to detect CN- in a quick, convenient and affordable way...

Predicting the functionality of missense mutations is extremely difficult. Large-scale genomic screens are commonly performed to identify mutational correlates or drivers of disease and treatment resistance, but interpretation of how these mutations impact protein function is limited. One such consequence of mutations to a protein is to impact its ability to bind and interact with partners or small molecules such as ATP, thereby modulating its function. Multiple methods exist for predicting the impact of a single mutation on protein-protein binding energy, but it is difficult in the context of a genomic screen to understand if these mutations with large impacts on binding are more common than statistically expected...

Many of the health-associated impacts of the microbiome are mediated by its chemical activity, producing and modifying small molecules (metabolites). Thus, microbiome metabolite quantification has a central role in efforts to elucidate and measure microbiome function. In this review, we cover general considerations when designing experiments to quantify microbiome metabolites, including sample preparation, data acquisition and data processing, since these are critical to downstream data quality. We then discuss data analysis and experimental steps to demonstrate that a given metabolite feature is of microbial origin...

The interaction between human microbes and drugs can significantly impact human physiological functions. It is crucial to identify potential microbe-drug associations (MDAs) before drug administration. However, conventional biological experiments to predict MDAs are plagued by drawbacks such as time-consuming, high costs, and potential risks. On the contrary, computational approaches can speed up the screening of MDAs at a low cost. Most computational models usually use a drug similarity matrix as the initial feature representation of drugs and stack the graph neural network layers to extract the features of network nodes...

Due to the abnormal secretion of adreno-cortico-tropic-hormone (ACTH) by tumors, Cushing's disease leads to hypercortisonemia, a precursor to a series of metabolic disorders and serious complications. Cushing's disease has high recurrence rate, short recurrence time and undiscovered recurrence reason after surgical resection. Qualitative or quantitative automatic image analysis of histology images can potentially in providing insights into Cushing's disease, but still no software has been available to the best of our knowledge...

Predicting the therapeutic effect of anti-cancer drugs on tumors based on the characteristics of tumors and patients is one of the important contents of precision oncology. Existing computational methods regard the drug response prediction problem as a classification or regression task. However, few of them consider leveraging the relationship between the two tasks. In this work, we propose a Multi-task Interaction Graph Convolutional Network (MTIGCN) for anti-cancer drug response prediction. MTIGCN first utilizes an graph convolutional network-based model to produce embeddings for both cell lines and drugs...

β-Galactosidase serves as a pivotal biomarker for both cancer and cellular aging. The advancement of fluorescent sensors for tracking β-galactosidase activity is imperative in the realm of cancer diagnosis. We have designed a near-infrared fluorescent probe (PTA-gal) for the detection of β-galactosidase in living systems with large Stokes shifts. PTA-gal exhibits remarkable sensitivity and selectivity in detecting β-galactosidase, producing near-infrared fluorescent signals with a remarkably low detection limit (2...

The International Classification of Diseases (ICD) serves as a global healthcare administration standard, with one of its editions being ICD-10-CM, an enhanced diagnostic classification system featuring numerous new codes for specific anatomic sites, co-morbidities, and causes. These additions facilitate conveying the complexities of various diseases. Currently, ICD-10 coding is widely adopted worldwide. However, public hospitals in Pakistan have yet to implement it and automate the coding process. In this research, we implemented ICD-10-CM coding for a private database and named it Clinical Pool of Liver Transplant (CPLT)...

The development of single cell RNA sequencing (scRNA-seq) has provided new perspectives to study biological problems at the single cell level. One of the key issues in scRNA-seq data analysis is to divide cells into several clusters for discovering the heterogeneity and diversity of cells. However, the existing scRNA-seq data are high-dimensional, sparse, and noisy, which challenges the existing single-cell clustering methods. In this study, we propose a joint learning framework (JLONMFSC) for clustering scRNA-seq data...

Research indicates that miRNAs present in herbal medicines are crucial for identifying disease markers, advancing gene therapy, facilitating drug delivery, and so on. These miRNAs maintain stability in the extracellular environment, making them viable tools for disease diagnosis. They can withstand the digestive processes in the gastrointestinal tract, positioning them as potential carriers for specific oral drug delivery. By engineering plants to generate effective, non-toxic miRNA interference sequences, it's possible to broaden their applicability, including the treatment of diseases such as hepatitis C...

MOTIVATION: The COVID-19 pandemic has been spreading globally for four years, yet specific drugs that effectively suppress the virus remain elusive. Furthermore, the emergence of complications associated with COVID-19 presents significant challenges, making the development of therapeutics for COVID-19 and its complications an urgent task. However, traditional drug development processes are time-consuming. Drug repurposing, which involves identifying new therapeutic applications for existing drugs, presents a viable alternative...

The detection of complex interactions between single nucleotide polymorphisms (SNPs) plays a vital role in genome-wide association analysis (GWAS). The multi-objective evolutionary algorithm is a promising technique for SNP-SNP interaction detection. However, as the scale of SNP data further increases, the exponentially growing search space gradually becomes the dominant factor, causing evolutionary algorithm (EA)-based approaches to fall into local optima. In addition, multi-objective genetic operations consume significant amounts of time and computational resources...

Autoimmune diseases (AD) consist of a spectrum of disease entities whose etiologies are very complex and still not well understood. Every individual has the potential for developing AD under appropriate conditions because the body contains lymphocytes that are potentially reactive with self-antigens. The aims of this study are to (1) explore the flow cytometry method to identify the frequency of various circulating CD4+ T helper (Th) cell-subsets, including Th1, Th2, Th9, Th17, Th17.1, and Th22; (2) In parallel, to examine multiplex ELISA method for pathogenic inflammatory cytokines/chemokines, and (3) To assess the correlation of expression of T cell-subsets with serum cytokines/chemokines and understand its clinical importance with available AD treatments...

In this paper, we discuss how tetrahydrodibenzo[a,j]acridine (4-HA) loses its hydrogen, which makes dibenzo[a,j]acridine (ARM) and also how 4-HA can be synthesized effectively using 2-tetralone in high yield. Dehydrogenative condensation and dehydrogenation are the two processes that make up the overall reaction of this synthetic approach. In addition, the presence of BF3 caused a remarkable fluorescence shift in ARM. Test paper analysis was used for examining the practical usefulness of ARM, which can be seen under UV light, resulting in this unique phenomenon...

Drug-induced liver injury (DILI) is a significant issue in drug development and clinical treatment due to its potential to cause liver dysfunction or damage, which, in severe cases, can lead to liver failure or even fatality. DILI has numerous pathogenic factors, many of which remain incompletely understood. Consequently, it is imperative to devise methodologies and tools for anticipatory assessment of DILI risk in the initial phases of drug development. In this study, we present DMFPGA, a novel deep learning predictive model designed to predict DILI...

All cellular functions and identity of every cell are directly or indirectly depend on its gene expression. Therefore, cells control their gene expression very finely at multiple layers. Cells always fine tune its gene expression profile depending on the internal and external cues to maintain best possible cellular growth condition. Regulation of mRNA production is a major step in the control of gene expression. mRNA production primarily depends on two factors. One is the level of RNA polymerase II (Pol II hereafter) recruitment at the promoter region and another is the amount of Pol II successfully elongating through the whole gene body also known as coding region...