Let's take a look at our Proximity-based Labeling (PL for short) technology!

For scientific researchers studying molecular biology, when they obtain an interesting gene/protein and want to conduct in - depth functional verification, the study of protein - protein interactions is an essential part. Protein - protein and protein - nucleic acid interactions are widespread in various life processes and play important regulatory roles. Developing methods for large - scale analysis of interactions between biomolecules is of great significance for exploring biological functions and disease intervention. Although traditional biochemical research methods such as pulldown, Co - IP, and yeast two - hybrid are widely used to uncover potential protein - protein interactions, they all have their own drawbacks and limitations.

Xianlian Jiedu Decoction alleviates colorectal cancer by regulating metabolic profiles, intestinal microbiota and metabolites

"With government support, publishing is not a problem." Traditional Chinese medicine (TCM) research has always been a hot topic. The typical research pattern is component identification → network pharmacology analysis → molecular docking analysis → experimental validation. These routines may have become tiresome. Today, I would like to share a different research strategy in TCM: a combination of non-targeted TCM analysis + gut microbiota + metabolomics. This approach is novel, highly reproducible, and you too can publish such a paper using this strategy.

Integrative single-cell and bulk transcriptomes analyses reveals heterogeneity of serine-glycine-one-carbon metabolism with distinct prognoses and therapeutic vulnerabilities in HNSCC

At the forefront of modern medical research, scientists are using techniques like single-cell RNA sequencing and bulk transcriptome analysis to probe the mysteries of cancer. It’s akin to holding a high-powered microscope to listen to cancer’s “inner monologue,” one cell at a time. Today, let’s explore a new study that unveils the hidden role of a crucial metabolic pathway in head and neck squamous cell carcinoma (HNSCC)—the serine-glycine-one-carbon (SGOC) metabolism. What’s more, the study introduces a magical 4-SGOC gene prognostic signature, like a “map of the future” for clinicians. Let’s dive into this scientific adventure!

Fully assembled spliceosome pre activation structure of brewing yeast

RNA splicing is one of the important processes in regulating gene expression in eukaryotes. In the 1970s, scientists first discovered the discontinuity of eukaryotic genes, indicating that after genetic information is transferred from DNA to RNA, it needs to undergo "cutting" and "splicing" of effective genetic information. This splicing of effective genetic information and the removal of "invalid" genetic information is called RNA splicing. RNA splicing is widely present in eukaryotes. With the evolution of species, the number of genes containing introns increases, and the frequency of RNA splicing also increases accordingly, making it possible for one gene to encode multiple proteins.

Sequencing reveals gene switch controlling wing pattern of armyworm

An important goal of studying evolution is to identify the genetic changes behind the emergence of a new morphological structure in organisms. According to the official website of the University of Cambridge in the UK, scientists have found through genetic sequencing analysis of various Amazon armyworms that the gene switches that control different stripes and spots on their wings are independent, and different armyworms have these gene switches, like a gene "paintbrush box" that can produce new patterns through cross species mating.

New study reveals 241 genes associated with brain dysfunction

Researchers from the Geisinger Health System in Pennsylvania, USA, compiled 241 genes related to brain dysfunction and discovered 17 new gene mutations associated with brain developmental disorders, including autism, epilepsy, schizophrenia, and bipolar disorder. The related research results were published on January 28, 2016 in the journal JAMA Psychiatry.

Chemical proteomics — Target engagement & MoA elucidation

Chemical proteomics enables proteome-wide interrogation of small-molecule engagement in biologically relevant systems. By combining probe-based enrichment and mass spectrometry with orthogonal validation, it supports robust target identification, mechanism-of-action elucidation, and off-target risk assessment to strengthen translational confidence. The white paper focuses on concepts and applications, while the implementation guide details workflows, controls, and QC.

Bioinformatics — Multi-omics integration & biomarker discovery

Bioinformatics provides a rigorous framework for extracting actionable biology from public and in-house datasets. Key applications include: 1、Integrative analysis across cohorts and multi-omics layers to prioritize biomarkers and therapeutic targets 2、Molecular subtyping, pathway inference, and immune microenvironment profiling for mechanistic interpretation 3、Reproducible workflows with publication-ready visualization and reportable outputs for decision support The white paper summarizes core methodologies, while the implementation guide specifies pipelines, QC checkpoints, and deliverables.

PROTAC — Targeted protein degradation strategy

PROTAC technology advances targeted protein degradation by enabling catalytic removal of disease-relevant proteins through E3 ligase recruitment. The documents emphasize rational degrader design and optimization, along with quantitative strategies to assess degradation potency, selectivity, and downstream functional consequences across in vitro and in vivo settings. The white paper covers principles and evaluation logic, while the technical guide provides assay workflows and interpretation.

Self-assembly — Nanostructure engineering for delivery

Self-assembly offers a modular route to engineer nanostructured systems for delivery and functional biomaterials. Key applications include: 1、Formulation design and controllable assembly for diverse payloads and therapeutic contexts 2、Comprehensive physicochemical characterization, including size distribution, morphology, and stability metrics 3、Encapsulation, release behavior, and efficacy-oriented evaluation to support iterative optimization and scale-up readiness The white paper explains design rationale, while the implementation guide details preparation, characterization, and decision criteria.

Spatial proteomics — In situ neighborhood mapping

Spatial proteomics quantifies where proteins reside and how local networks are organized within cells and tissues, enabling context-aware biology in complex microenvironments. Key applications include: 1、Proximity labeling to capture compartment-resolved protein neighborhoods in situ 2、Time-restricted labeling to record transient or weak interactions with reduced perturbation 3、Control strategies and orthogonal validation to improve specificity and interpretability of LC–MS readouts The white paper outlines positioning and paradigms, while the implementation guide provides stepwise workflows, controls, and validation.

AI-driven drug discovery — Computational acceleration from target to lead

AI-driven drug discovery accelerates hypothesis generation and compound prioritization by coupling data curation with computational learning and physics-informed evaluation. Key applications include: 1、Structure- and ligand-based virtual screening to rank candidates and propose binding hypotheses 2、Molecular design and optimization guided by predictive models for potency and developability 3、ADMET risk forecasting integrated with docking and molecular dynamics to enable iterative, evidence-based refinement The white paper introduces the end-to-end framework, while the implementation guide clarifies workflows, outputs, and iteration loops.