Technical Documents
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.
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