Medicine Discovery Research Articles

Synthesis of P(V)-Stereogenic Phosphorus Compounds via Organocatalytic Asymmetric Condensation.

Enantioenriched phosphorus(V)-stereogenic compounds, featuring a pentavalent phosphorus atom as the stereogenic center, are crucial in various natural products, drugs, bioactive molecules, and catalysts/ligands. While a handful of stereoselective synthetic approaches have been developed, achieving direct stereocontrol at the phosphorus atom through catalytic generation of phosphorus(V)-heteroatom bonds continues to be a formidable challenge. Here, we disclose an organocatalytic asymmetric condensation strategy that employs a novel activation mode of stable feedstock phosphinic acids by the formation of mixed phosphinic anhydride as the reactive species to facilitate further catalyst-controlled asymmetric P-O bond formations, involving a dynamic kinetic asymmetric transformation (DYKAT) process with alcohol nucleophiles via a cinchonidine-derived bifunctional catalyst. The resulting H-phosphinate intermediates allow further stereospecific derivatizations, affording modular access to a diverse library of chiral phosphonates and phosphonamidates with notable antibacterial activity. Furthermore, this synthetic platform facilitates P-O/N coupling with various natural products and drugs, presenting a valuable tool for medicine and agrochemical discovery.

Phaleria macrocarpa (Scheff.) Boerl. in Ethnopharmacology: Pharmacognosy, Safety, and Drug Development Perspectives

Phaleria macrocarpa, a medicinal plant from the Thymelaceae family, is predominantly found in Malaysia and Indonesia. This review aims to comprehensively summarize the phytochemical, pharmacological, and toxicological aspects of P. macrocarpa, along with modern approaches and safety concerns. Data for the review were collected from various scientific databases and relevant literature on P. macrocarpa. The review discusses the plant's phytochemical composition and its diverse medicinal properties, including anti-inflammatory, antihypertensive, antidiabetic, antioxidant, antimicrobial, antipyretic, antiulcer, antiviral and anticancer activities. P. macrocarpa has also been used to treat various female health conditions. Additionally, combination therapies and advanced drug delivery systems such as nanoemulsion have been reviewed. These pharmacological activities are attributed to the plant's phytoconstituents. The review will be valuable for researchers involved in medicinal plant research and drug discovery, offering potential for use alongside modern therapeutic agents. However, clinical studies are essential to validate its therapeutic applications. Further research is required to develop standardized herbal pharmaceuticals from P. macrocarpa that are effective, safe, and meet regulatory standards for quality assurance.

Therapeutic and antioxidant properties of Acridocarpus monodii Arène & Jaeger, an endemic plant of Dogon Country in Mali

Acridocarpus monodii Arène & Jaeger is an endemic plant species to the ‘’Dogon Country’’ in Mali. This species is highly popular in Dogon ethnic groups, but no scientific data on its medicinal and biochemical properties are available in Mali. This work aimed to list its medicinal uses and assess its phytochemical composition and antioxidant power. An ethnobotanical investigation based on semi structured questionnaire was used to identify the traditional uses of A. monodii among the local population in three villages (Ireli, Youdiou and Yon-biré) inside ‘’Dogon country’’ in Mali. The phytochemical composition was determined using qualitative tests, while the antioxidant potency was performed using 2,2-diphenyl-1-picryhydazyl (DPPH) and phosphomolybdate (TAC) tests. A total of 45 people were interviewed, the majority of whom were male (82.20%) and over 52 years of age. A. monodii is used to treat a dozen pathologies or diseases, dominated by malaria (71.10%), yellow fever (24.40%) and dysuria (20%). Although, all parts of this species are used to treat these pathologies, leaves (88.90%) were the most coveted followed by roots (37.80%). The use of these parts was significantly (p = 0.016 < 0.05) associated with the educational levels of the respondents (77.70%), who coveted primarily roots and barks, and thus constituted a threat to the species. These medicinal recipes derived from these organs were mostly prepared as decoctions, before being administered by oral (100%) or bath (82.20%) routes. Extracts of A. monodii were found to contain various biocompounds, especially a high quantity of flavonoids and polyphenols and demonstrated increased in vitro antioxidant inhibitory effects. The decoction extracts showed the highest content of phenolic compounds (109.82 ± 2.36 mg GAE/g). The strongest activity for the DPPH free radical scavenging were recorded by the decoction with IC50 = 107.41 ± 4.25 µg/mL and the hydroethanolic macerate with 107.31 ± 9.28 µg/mL. But, based on the results from of TAC test, the antioxidant capacity was higher for the hydroethanolic macerate 42.85 ± 2.59 mg EQ/g than those of the decoction 19.27 ± 0.93 mg EQ/g. This is the first scientific report on the therapeutic use of A. monodii within ‘’Dogon country’’ in Mali. This work highlights its medicinal, phytochemical and biochemical properties and therefore contributes to its improved valorization. These results demonstrated that A. monodii is a promising species for the discovery of novel medicines.

DeepDR: a deep learning library for drug response prediction.

Accurate drug response prediction is critical to advancing precision medicine and drug discovery. Recent advances in deep learning (DL) have shown promise in predicting drug response; however, the lack of convenient tools to support such modeling limits their widespread application. To address this, we introduce DeepDR, the first DL library specifically developed for drug response prediction. DeepDR simplifies the process by automating drug and cell featurization, model construction, training, and inference, all achievable with brief programming. The library incorporates three types of drug features along with nine drug encoders, four types of cell features along with nine cell encoders, and two fusion modules, enabling the implementation of up to 135 DL models for drug response prediction. We also explored benchmarking performance with DeepDR, and the optimal models are available on a user-friendly visual interface. DeepDR can be installed from PyPI (https://pypi.org/project/deepdr). The source code and experimental data are available on GitHub (https://github.com/user15632/DeepDR). Supplementary data are available at Bioinformatics online.

Critical Data for Critical Care: A Primer on Leveraging Electronic Health Record Data for Research From Society of Critical Care Medicine's Panel on Data Sharing and Harmonization.

A growing body of critical care research draws on real-world data from electronic health records (EHRs). The bedside clinician has myriad data sources to aid in clinical decision-making, but the lack of data sharing and harmonization standards leaves much of this data out of reach for multi-institution critical care research. The Society of Critical Care Medicine (SCCM) Discovery Data Science Campaign convened a panel of critical care and data science experts to explore and document unique advantages and opportunities for leveraging EHR data in critical care research. This article reviews and illustrates six organizing topics (data domains and common data elements; data harmonization; data quality; data interoperability and digital infrastructure; data access, sharing, and governance; and ethics and equity) as a data science primer for critical care researchers, laying a foundation for future publications from the SCCM Discovery Data Harmonization and Sharing Guiding Principles Panel.

Supporting diversity in clinical trials: the equitable breakthroughs in medicine site maturity model

BackgroundAmong the most powerful barriers to broader inclusion of diverse participants in clinical trials are social determinants of health, trustworthiness of health care providers and research institutions, and competing pressures on potential participants. Nevertheless, current tools to assess organizational capabilities for clinical trial diversity focus primarily on trial infrastructure, rely solely on quantitative self-reported data, and lack meaningful assessment of capabilities related to community engagement.MethodsThe Equitable Breakthroughs in Medicine (EQBMED) initiative developed a holistic, collaborative, site-driven formative model and accompanying assessment to catalog sites’ current capabilities and identify opportunities for growth in both conducting industry-sponsored clinical trials and enriching diversity of those trials. The model builds upon prior work and reflects unification of two historically distinct components—research operations and community engagement—since sustainable clinical trial diversity efforts must overcome these silos. Here we present the methodology we used to develop the model and accompanying assessment, describe how findings can support clinical trial diversity efforts, and report findings from early field testing at three U.S. sites.ResultsThe first three sites were diverse in size (e.g., < 250–1 K beds), with varying levels of clinical trial capabilities and community engagement. The maturity assessment laid the foundation for sites to identify and prioritize key areas to advance clinical trial diversity capabilities, and each has made tangible progress. In parallel to completing the assessment with these early sites to understand their maturity and set actionable goals, we also collected their feedback on content validity (e.g., clarity, comprehensiveness, terminology) and feasibility (e.g., ability to collect needed information and data, time required). We describe refinements made to improve the assessment and streamline the process. The EQBMED program will deploy the assessment across various site types (e.g., FQHCs, safety net hospitals) and make further refinements as warranted.ConclusionsStrategic investment in clinical trial diversity requires structured assessment of site maturity as a starting point for collaborative action. We propose the EQBMED maturity model as a first step toward informing efforts to increase representation of diverse populations in clinical research.

Physician-scientists’ perspectives on key factors, emotions and feelings about selecting and attending continuous professional development events: a mixed-method study

BackgroundAlmost 40% of the Nobel-Prize-winning discoveries in medicine are made by physician-scientists, who are a driving force in the evolving medical, academic and research landscape. However, their training has few defined milestones. To be effective clinicians, educators and researchers, they need to maintain and hone skills, often via continuous professional development (CPD) activities covering different domains. They have recurrently been described as an endangered species. Yet, warnings and recommendations across several decades did not stop the declining number of physician-scientists, which is now a chronic issue. This is further exacerbated by a lack of resources and support, especially after the COVID-19 pandemic.MethodsWe administered a questionnaire called Positive and Negative Affect Schedule (PANAS-GEN) to get an initial emotional snapshot before performing individual semi-structured interviews with five physician-scientists in neurology working in the United Kingdom. We explored the key factors they balance before selecting CPD activities, along with their views on compulsory CPD events and assessments. We investigated their general feelings towards compulsory and non-compulsory CPD, how they felt the night before and the morning of the events, and the perceived consequences attending these have on their learning.ResultsIn our study, physician-scientists tend to choose training in their area of expertise but would enjoy exploring more if they had more time. The CPD choice was chiefly driven by speakers and topics, followed by learning needs. They disputed the utility of the current assessments, which are often seen as box-ticking exercises. While frustration, hostility and negative feelings were voiced for the compulsory ones, other CPD activities were welcomed with excitement, curiosity and a sense of adventure. Enthusiasm and excitement were felt the night before and the morning of the non-compulsory ones. CPD events were perceived to positively affect further learning, with the most immediate consequences being reading an article, networking or interacting with the speakers.DiscussionThis is the first study exploring the key factors driving a group of physician-scientists while selecting CPD activities and investigating their feelings and emotions related to CPD attendance. More engaging and less box-ticking CPD should be on the cards, along with an adequate evaluation of these activities. It is essential to increase enthusiasm, which can facilitate engagement, and decrease frustration surrounding compulsory CPD activities. We still know too little about the role of emotions in learning, especially about CPD. Future studies should investigate the emotional side of learning across different career stages to restore the leaky pipeline and create a tailored environment with benefits for each of the three sides of the physician-scientist’s identity: the clinical, the research, and the academic.

Drug-induced cholestasis (DIC) predictions based on in vitro inhibition of major bile acid clearance mechanisms.

Drug-induced cholestasis (DIC) is recognized as a major safety concern in drug development, as it represents one of the three types of drug-induced liver injury (DILI). Cholestasis is characterized by the disruption of bile flow, leading to intrahepatic accumulation of toxic bile acids. Bile acid regulation is a multifarious process, orchestrated by several hepatic mechanisms, namely sinusoidal uptake and efflux, canalicular secretion and intracellular metabolism. In the present study, we developed a prediction model of DIC using in vitro inhibition data for 47 marketed drugs on nine transporters and five enzymes known to regulate bile acid homeostasis. The resulting model was able to distinguish between drugs with or without DILI concern (p-value = 0.039) and demonstrated a satisfactory predictive performance, with the area under the precision-recall curve (PR AUC) measured at 0.91. Furthermore, we simplified the model considering only two processes, namely reversible inhibition of OATP1B1 and time-dependent inhibition of CYP3A4, which provided an enhanced performance (PR AUC = 0.95). Our study supports literature findings suggesting a contribution not only from a single process inhibition, but a rather synergistic effect of the key bile acid clearance processes in the development of cholestasis. The use of a quantitative model in the preclinical investigations of DIC is expected to reduce attrition rate in advanced development programs and guide the discovery and development of safe medicines.

Design and Evaluation of Azaspirocycles as RNA binders.

This study presents efficient synthetic pathways for preparing novel azaspirocycles. These methodologies involve functionalizing key bicyclic hydrazines with a substituent on one of their bridgehead carbon atoms. The desired spirocyclic cores were successfully obtained through double reductive amination reactions, intramolecular cyclizations, and cleavages of the N-N bond. The isolated molecules possess unique three-dimensional structures, suggesting potential applications in medicinal chemistry and drug discovery. With the growing interest in targeting nucleic acids as a complementary approach to protein-targeting strategies for developing novel active compounds, we investigated the potential of the synthesized azaspirocycles as RNA binders. As a proof of concept, we highlight the promising activity of some compounds as strong binders of HIV-1 TAR RNA and inhibitors of Tat/TAR interactions.

The evolution of dbSNP: 25 years of impact in genomic research.

The Single Nucleotide Polymorphism Database (dbSNP), established in 1998 by the National Center for Biotechnology Information (NCBI), has been a critical resource in genomics for cataloging small genetic variations. Originally focused on single nucleotide polymorphisms (SNPs), dbSNP has since expanded to include a variety of genetic variants, playing a key role in genome-wide association studies (GWAS), population genetics, pharmacogenomics, and cancer research. Over 25 years, dbSNP has grown to include more than 4.4 billion submitted SNPs and 1.1 billion unique reference SNPs, providing essential data for identifying disease-related genetic variants and studying human diversity. Integrating large-scale projects like 1000 Genomes, gnomAD, TOPMed, and ALFA has expanded dbSNP's catalog of human genetic variation, increasing its usefulness for research and clinical applications. Keeping up with advancements such as next-generation sequencing and cloud-based infrastructure, dbSNP remains a cornerstone of genetic research supporting continued discoveries in precision medicine and population genomics. DATABASE URL: https://www.ncbi.nlm.nih.gov/snp.

Precision Cut Lung Slices: Emerging Tools for Preclinical and Translational Lung Research. An Official American Thoracic Society Workshop Report.

The urgent need for effective treatments for acute and chronic lung diseases underscores the significance of developing innovative preclinical human research tools. The 2023 ATS Workshop on Precision Cut Lung Slices (PCLS) brought together 35 experts to discuss and address the role of human tissue-derived PCLS as a unique tool for target and drug discovery and validation in pulmonary medicine. With increasing interest and usage, along with advancements in methods and technology, there is a growing need for consensus on PCLS methodology and readouts. The current document recommends standard reporting criteria and emphasizes the requirement for careful collection and integration of clinical metadata. We further discuss current clinically relevant readouts that can be applied to PCLS and highlight recent developments and future steps for implementing novel technologies for PCLS modeling and analysis. The collection and correlation of clinical metadata and multiomic analysis will further advent the integration of this preclinical platform into patient endotyping and the development of tailored therapies for lung disease patients.

Construction of Aryl Azide‐ and Triazole‐Based Unnatural Amino Acid Motifs via the Pd(II)‐Catalyzed C(sp3)−H Arylation

AbstractThis paper reports a method for the synthesis of examples of aryl azide‐ and triazole moiety‐based unnatural amino acid motifs using the Pd(II)‐catalyzed arylation of the prochiral C(sp3)−H bonds of carboxamides of amino acids as one of the key transformations. Synthesis of racemic and enantioenriched aryl azide‐based unnatural amino acid motifs including, norvaline, leucine, norleucine, phenylalanine, 2‐aminobutyric acid, 2‐aminooctanoic acid, and non‐α‐amino acid derivatives were shown. Additionally, we attempted the synthesis of triazole moiety‐installed norvaline, leucine, norleucine, phenylalanine, 2‐aminobutyric acid, 2‐aminooctanoic acid, and non‐α‐amino acid derivatives via the Cu‐catalyzed Click reaction. We also demonstrated the removal of the protecting groups and the synthesis of free amino group‐containing aryl azide‐ or triazole‐based unnatural amino acid motifs and peptides. Generally, azide moiety‐containing unnatural amino acid motifs are important molecular tools in chemical biology. Furthermore, aryl azide‐ and triazole moiety‐containing unnatural amino acid scaffolds are notable substrates in medicinal chemistry and drug discovery research. Accordingly, this work contributes to enriching the library of aryl azide‐ and triazole‐based unnatural amino acid derivatives.

At-Line LC-QTOF-ESI-MS/MS Fractionation of Impatiens balsamina Linn. Coupled With a Simple DPPH for Rapid Identification and Guided Isolation of Antioxidant.

Reactive oxygen species (ROS) and ultraviolet (UV) light are significant factors to impair skin disorders. Impatiens balsamina Linn. (IB), a traditional Chinese and Thai herbal medicine, has long been used to treat skin and nail diseases, potentially due to its radical-scavenging properties. However, specific antioxidant compounds in IB have not been well defined. This work aims to rapidly identify, target, and isolate antioxidant biomarkers in IB using at-line LC-ESI-QTOF-(MS/MS) coupled with a simple DPPH assay and comprehensively investigate the antioxidant activities of IB extract and isolated biomarker. Following liquid chromatography (LC), the eluent of IB extract was split into two streams (9:1 ratio). The majority was fractionated for DPPH assay in 96-well plates, whereas 10% underwent chemical identification using ESI-QTOF-MS. Antioxidants in IB were identified, targeted, and promptly isolated through transfer from analytical LC to preparative HPLC. IB and the isolated biomarkers were evaluated for antioxidant effects using various antiradical assays and in suppressing ROS induced by UV in skin cells, keratinocytes, and fibroblasts. Thirty-one chemical constituents were identified, with four tentatively identified as potent antioxidants. Kaempferol emerged as a potential antioxidant biomarker in IB, exhibiting superior antioxidant activity in various invitro assays compared with positive controls. Both IB extract and kaempferol effectively reduced UVB-induced ROS in skin cells. This study represents the first comprehensive identification of antioxidants and chemical constituents in IB, pinpointing kaempferol as a key antioxidant biomarker. Its rapid identification using at-line techniques holds promise for advancing bioactive compound discovery in herbal medicine.

Endophytic Streptomyces: an underexplored source with potential for novel natural drug discovery and development.

Streptomyces has long been considered as key sources for natural compounds discovery in medicine and agriculture. These compounds have been demonstrated to possess different biological activities, including antibiotic, antifungal, anticancer, and antiviral effects. As a result, new pharmaceuticals and antibiotics have been developed. Nevertheless, there have been only a few novel discoveries of bioactive compounds in the past decades from Streptomyces in natural habitats. There is, therefore, now a renewed search for new Streptomyces species having the potential to produce many compounds from one strain in lesser explored natural habitats that may be helpful in fighting diseases. Consequently, modern genome mining approaches are imperative for discovering structurally novel natural compounds with therapeutic applications from untapped sources. In light of these facts, endophytic Streptomyces from plants may offer new avenues for the discovery of bioactive compounds with distinctive chemical properties and activities. In the present review, we present the progress made in isolating natural compounds from endophytic Streptomyces originating from plants which have remarkable antimicrobial, cytotoxic, and antifungal properties. A different of distinct structural classes of compounds were reported from endophytic Streptomyces, such as indolosequiterpene, macrolides, flavones, peptides, naphthoquinones, and terpenoids. Further, we discussed modern genomics progress in finding biosynthetic gene clusters (BGCs) encoding compounds. Overall, this review might provide valuable insights into the potential for novel drug discovery from untapped endophytic Streptomyces in the future.

Health Care Language Models and Their Fine-Tuning for Information Extraction: Scoping Review.

In response to the intricate language, specialized terminology outside everyday life, and the frequent presence of abbreviations and acronyms inherent in health care text data, domain adaptation techniques have emerged as crucial to transformer-based models. This refinement in the knowledge of the language models (LMs) allows for a better understanding of the medical textual data, which results in an improvement in medical downstream tasks, such as information extraction (IE). We have identified a gap in the literature regarding health care LMs. Therefore, this study presents a scoping literature review investigating domain adaptation methods for transformers in health care, differentiating between English and non-English languages, focusing on Portuguese. Most specifically, we investigated the development of health care LMs, with the aim of comparing Portuguese with other more developed languages to guide the path of a non-English-language with fewer resources. This study aimed to research health care IE models, regardless of language, to understand the efficacy of transformers and what are the medical entities most commonly extracted. This scoping review was conducted using the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) methodology on Scopus and Web of Science Core Collection databases. Only studies that mentioned the creation of health care LMs or health care IE models were included, while large language models (LLMs) were excluded. The latest were not included since we wanted to research LMs and not LLMs, which are architecturally different and have distinct purposes. Our search query retrieved 137 studies, 60 of which met the inclusion criteria, and none of them were systematic literature reviews. English and Chinese are the languages with the most health care LMs developed. These languages already have disease-specific LMs, while others only have general-health care LMs. European Portuguese does not have any public health care LM and should take examples from other languages to develop, first, general-health care LMs and then, in an advanced phase, disease-specific LMs. Regarding IE models, transformers were the most commonly used method, and named entity recognition was the most popular topic, with only a few studies mentioning Assertion Status or addressing medical lexical problems. The most extracted entities were diagnosis, posology, and symptoms. The findings indicate that domain adaptation is beneficial, achieving better results in downstream tasks. Our analysis allowed us to understand that the use of transformers is more developed for the English and Chinese languages. European Portuguese lacks relevant studies and should draw examples from other non-English languages to develop these models and drive progress in AI. Health care professionals could benefit from highlighting medically relevant information and optimizing the reading of the textual data, or this information could be used to create patient medical timelines, allowing for profiling.

Advances in the Synthesis of 3‐Acyl‐2‐Pyridones: Strategies and Methods for Accessing the Versatile Scaffold

ABSTRACTThe syntheses and bioevaluation of 3‐acyl‐2‐pyridones have garnered significant interest in recent years as a novel class of compounds with diverse biological activities. The bioactivities cover a wide range of therapeutic areas including antimicrobial, antitumor, anti‐inflammatory, antifungal, antibiotic, neuritogenic, cytotoxic, and antiviral activities. Therefore, 3‐acyl‐2‐pyridone scaffold offers a versatile platform for the development of new molecules with potential applications in medicinal chemistry. The recent exploration on synthesis and bioevaluation of 3‐acyl‐2‐pyridones has yielded promising results, making them attractive targets for further optimization and development of new therapeutic agents. This review summarizes the available information on total synthesis of 3‐acyl‐2‐pyridone containing natural products, and the other synthetic strategies developed for accessing the 3‐acyl pyridones such as multicomponent synthesis, condensation reaction, microwave‐assisted synthesis, catalytic hydrogenation reactions, metalation reaction, Michael addition, and formylation reactions. The presented information may serve as a valuable resource for researchers working in the field of medicinal chemistry and drug discovery, stimulating further exploration and development of this intriguing scaffold.

Advancements and Applications of Artificial Intelligence in Pharmaceutical Sciences: A Comprehensive Review

: Artificial intelligence (AI) has revolutionized the pharmaceutical industry, improving drug discovery, development, and personalized patient care. Through machine learning (ML), deep learning, natural language processing (NLP), and robotic automation, AI has enhanced efficiency, accuracy, and innovation in the field. The purpose of this review is to shed light on the practical applications and potential of AI in various pharmaceutical fields. These fields include medicinal chemistry, pharmaceutics, pharmacology and toxicology, clinical pharmacy, pharmaceutical biotechnology, pharmaceutical nanotechnology, pharmacognosy, and pharmaceutical management and economics. By leveraging AI technologies such as ML, deep learning, NLP, and robotic automation, this review delves into the role of AI in enhancing drug discovery, development processes, and personalized patient care. It analyzes AI's impact in specific areas such as drug synthesis planning, formulation development, toxicology predictions, pharmacy automation, and market analysis. Artificial intelligence integration into pharmaceutical sciences has significantly improved medicinal chemistry, drug discovery, and synthesis planning. In pharmaceutics, AI has advanced personalized medicine and formulation development. In pharmacology and toxicology, AI offers predictive capabilities for drug mechanisms and toxic effects. In clinical pharmacy, AI has facilitated automation and enhanced patient care. Additionally, AI has contributed to protein engineering, gene therapy, nanocarrier design, discovery of natural product therapeutics, and pharmaceutical management and economics, including marketing research and clinical trials management. Artificial intelligence has transformed pharmaceuticals, improving efficiency, accuracy, and innovation. This review highlights AI's role in drug development and personalized care, serving as a reference for professionals. The future promises a revolutionized field with AI-driven methodologies.

Anion-driven C[sbnd]F bond cleavage of trifluoromethyl N-aryl hydrazones toward the assembly of N-heterocycles

Herein we report an efficient and convenient method for synthesizing 1H-benzo[d]imidazoles via a base-promoted reaction of readily available α-CF3 ketone-derived hydrazones with o-phenylenediamines. The key innovation is the anion-driven triple-cleavage of the CF bond in the CF3 group, which acts as a C1 synthon at the 2-position of the 1H-benzo[d]imidazole. This novel approach simplifies the synthesis and can be extended to the preparation of benzo[d]oxazoles and benzo[d]thiazoles. Our method offers a versatile and robust platform for the synthesis of important heterocyclic compounds, with potential applications in medicinal chemistry and drug discovery.

One-step nanoscale expansion microscopy reveals individual protein shapes.

The attainable resolution of fluorescence microscopy has reached the subnanometer range, but this technique still fails to image the morphology of single proteins or small molecular complexes. Here, we expand the specimens at least tenfold, label them with conventional fluorophores and image them with conventional light microscopes, acquiring videos in which we analyze fluorescence fluctuations. One-step nanoscale expansion (ONE) microscopy enables the visualization of the shapes of individual membrane and soluble proteins, achieving around 1-nm resolution. We show that conformational changes are readily observable, such as those undergone by the ~17-kDa protein calmodulin upon Ca2+ binding. ONE is also applied to clinical samples, analyzing the morphology of protein aggregates in cerebrospinal fluid from persons with Parkinson disease, potentially aiding disease diagnosis. This technology bridges the gap between high-resolution structural biology techniques and light microscopy, providing new avenues for discoveries in biology and medicine.

Innovative Synthesis of 3,5-Disubstituted Pyrazoline with Heterocyclic System for Hybrid Development

The synthesis of 3,5-disubstituted pyrazolines, integrated with heterocyclic systems, represents a crucial area of chemical research due to their pharmacological and biological significance. This article reviews various synthetic methods used to prepare 3,5-disubstituted pyrazolines with different heterocyclic groups. The methodology employed in this study entails a multi-step synthesis, where readily available starting materials are transformed into complex pyrazoline derivatives through strategic reaction sequences. Incorporating heterocyclic systems not only enhances the structural diversity but also imparts unique chemical and biological properties to these compounds. Various heterocyclic groups, such as furans, thiophenes, and pyridines, are introduced at the 3,5-positions of the pyrazoline ring, yielding a versatile library of compounds. This study highlights the potential applications of these novel compounds in medicinal chemistry and drug discovery, emphasizing their bioactivity against specific targets. Preliminary data suggests that certain derivatives possess promising pharmacological activities, making them potential candidates for further development as therapeutic agents. In summary, this review provides a valuable contribution to the field of organic synthesis, offering a novel and efficient route to synthesize 3,5-disubstituted pyrazolines with heterocyclic systems. Furthermore, the structural activity relationship of the compounds is also discussed. The structural diversity and potential pharmacological properties of these compounds make them valuable candidates for further exploration and development in drug discovery and related areas.