ReviewComputational and structural biotechnology journal2023
Accelerating therapeutic protein design with computational approaches toward the clinical stage.
Review in Computational and structural biotechnology journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 40 citations in OpenAlex.
- Integrative Peptide Drug Development: Chemical Engineering, AI-Driven Design, and Cell-Penetrating Peptides.Pharmaceutics · 2026Review
- Developing an artificial intelligence-generated peptide targeting platelet-type von Willebrand disease.Blood advances · 2026Article
- Genetically Engineered Light-Responsive In Situ Hydrogels for Immunomodulation and Multimodal Therapy in Metastatic Triple-Negative Breast Cancer.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Rationally Engineered Small Molecules: Pharmacophore Modeling and Molecular Docking Studies Targeting Toxic Polyglutamine (PolyQ) Repeats in Huntington's Disease.Current drug targets · 2026Article
- Elucidating HER2-directed chimeric antigen receptor (CAR) activation mechanism using homology modeling and all-atom molecular dynamics simulation.Computational and structural biotechnology journal · 2026Article
- Emerging Technologies and Integrated Interdisciplinary Strategies for Mitigating Protein Aggregation in Therapeutic Formulations.Pharmaceutical research · 2026Review
- Artificial intelligence in antibody design and development: harnessing the power of computational approaches.Medical & biological engineering & computing · 2025Review
- Artificial intelligence-driven computational methods for antibody design and optimization.mAbs · 2025Review
- Progress in Molecular Imprinting-From Inhibition of Enzymatic Activity to Regulation of Cellular Pathways.Medicinal research reviews · 2025Review
- Formulation of Recombinant Therapeutic Proteins: Technological Innovation, Regulations, and Evolution Towards Buffer-Free Formulations.Pharmaceutics · 2025Review
- Advancing Alzheimer's Therapy: Computational strategies and treatment innovations.IBRO neuroscience reports · 2025Review
- Engineering Affibody Binders to Death Receptor 5 and Tumor Necrosis Factor Receptor 1 With Improved Stability.Biotechnology and bioengineering · 2025Article
- Revolutionizing oncology: the role of Artificial Intelligence (AI) as an antibody design, and optimization tools.Biomarker research · 2025Review
- BeyondChemical reviews · 2025Review
- Revolutionizing Synthetic Antibody Design: Harnessing Artificial Intelligence and Deep Sequencing Big Data for Unprecedented Advances.Molecular biotechnology · 2025Review
- Revolutionizing Molecular Design for Innovative Therapeutic Applications through Artificial Intelligence.Molecules (Basel, Switzerland) · 2024Review
- Article
- Integrating Computational Design and Experimental Approaches for Next-Generation Biologics.Biomolecules · 2024Review
- Suborgan Level Quantitation of Proteins in Tissues Delivered by Polymeric Nanocarriers.ACS nano · 2024Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Therapeutic protein, represented by antibodies, is of increasing interest in human medicine. However, clinical translation of therapeutic protein is still largely hindered by different aspects of developability, including affinity and selectivity, stability and aggregation prevention, solubility and viscosity reduction, and deimmunization. Conventional optimization of the developability with widely used methods, like display technologies and library screening approaches, is a time and cost-intensive endeavor, and the efficiency in finding suitable solutions is still not enough to meet clinical needs. In recent years, the accelerated advancement of computational methodologies has ushered in a transformative era in the field of therapeutic protein design. Owing to their remarkable capabilities in feature extraction and modeling, the integration of cutting-edge computational strategies with conventional techniques presents a promising avenue to accelerate the progression of therapeutic protein design and optimization toward clinical implementation. Here, we compared the differences between therapeutic protein and small molecules in developability and provided an overview of the computational approaches applicable to the design or optimization of therapeutic protein in several developability issues.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.