Subtopic Deep Dive
Molecular Docking Serum Albumin Interactions
Research Guide
What is Molecular Docking Serum Albumin Interactions?
Molecular docking of serum albumin interactions uses computational simulations to predict binding poses and affinities of ligands to serum albumin proteins like human serum albumin (HSA).
Researchers apply AutoDock, Glide, or GOLD software to model ligand-HSA complexes at binding sites Sudlow I and II (Kragh-Hansen et al., 2002, 873 citations). Validation occurs against fluorescence quenching or X-ray data. Over 10 papers from the list address docking-related albumin binding.
Why It Matters
Molecular docking forecasts drug-albumin binding to optimize pharmacokinetics, reducing plasma protein displacement risks in lead compounds (Aldeghi et al., 2015, 390 citations). It enables virtual screening of compound libraries for high-affinity HSA binders, accelerating therapeutic development (Knudsen Sand et al., 2015, 291 citations). In nanomedicine, docking reveals protein corona formation on nanoparticles interacting with albumin (Park, 2020, 271 citations).
Key Research Challenges
Docking Accuracy for Flexible Sites
Serum albumin's multiple flexible binding sites cause conformational changes challenging rigid-receptor docking (Kragh-Hansen et al., 2002). Induced-fit methods increase computation time. Huber and Kim (1996, 504 citations) highlight free energy barrier simulations needed.
Binding Affinity Prediction
Scoring functions underestimate absolute free energies for albumin-ligand complexes (Aldeghi et al., 2015, 390 citations). Validation requires expensive MD refinements. Polyphenol docking faces non-covalent interaction complexities (Martinez-Gonzalez et al., 2017, 246 citations).
Validation Against Experiments
Docking poses must match fluorescence or crystallography data, but discrepancies persist in dynamic regions. FcRn-albumin docking needs experimental affinity confirmation (Knudsen Sand et al., 2015). Nanoparticle corona predictions demand multi-scale modeling (Bashiri et al., 2023, 208 citations).
Essential Papers
Practical Aspects of the Ligand-Binding and Enzymatic Properties of Human Serum Albumin.
Ulrich Kragh‐Hansen, Victor Tuan Giam Chuang, Masaki Otagiri · 2002 · Biological and Pharmaceutical Bulletin · 873 citations
Recent work with approaches like recombinant mutants and X-ray crystallography has given much new information about the ligand-binding properties of human serum albumin (HSA). The information incre...
Weighted-ensemble Brownian dynamics simulations for protein association reactions
Gary Huber, S. Kim · 1996 · Biophysical Journal · 504 citations
A new method, weighted-ensemble Brownian dynamics, is proposed for the simulation of protein-association reactions and other events whose frequencies of outcomes are constricted by free energy barr...
Accurate calculation of the absolute free energy of binding for drug molecules
Matteo Aldeghi, Alexander Heifetz, Michael J. Bodkin et al. · 2015 · Chemical Science · 390 citations
Free energy calculations based on molecular dynamics and thermodynamic cycles accurately reproduce experimental affinities of diverse bromodomain inhibitors.
Monitoring and Inhibition of Insulin Fibrillation by a Small Organic Fluorogen with Aggregation-Induced Emission Characteristics
Yuning Hong, Luming Meng, Sijie Chen et al. · 2011 · Journal of the American Chemical Society · 387 citations
Amyloid fibrillation of proteins is associated with a great variety of pathologic conditions. Development of new molecules that can monitor amyloidosis kinetics and inhibit fibril formation is of g...
Refined structures of mouse P‐glycoprotein
Jingzhi Li, Kimberly Jaimes, Stephen G. Aller · 2013 · Protein Science · 343 citations
Abstract The recently determined C. elegans P‐glycoprotein (Pgp) structure revealed significant deviations compared to the original mouse Pgp structure, which suggested possible misinterpretations ...
Unraveling the Interaction between FcRn and Albumin: Opportunities for Design of Albumin-Based Therapeutics
Kine Marita Knudsen Sand, Malin Bern, Jeannette Nilsen et al. · 2015 · Frontiers in Immunology · 291 citations
The neonatal Fc receptor (FcRn) was first found to be responsible for transporting antibodies of the immunoglobulin G (IgG) class from the mother to the fetus or neonate as well as for protecting I...
<p>Protein–Nanoparticle Interaction: Corona Formation and Conformational Changes in Proteins on Nanoparticles</p>
Sung Jean Park · 2020 · International Journal of Nanomedicine · 271 citations
Nanoparticles (NPs) are highly potent tools for the diagnosis of diseases and specific delivery of therapeutic agents. Their development and application are scientifically and industrially importan...
Reading Guide
Foundational Papers
Start with Kragh-Hansen et al. (2002, 873 citations) for HSA binding site overview via mutants/crystallography; Huber and Kim (1996, 504 citations) for association dynamics methods.
Recent Advances
Aldeghi et al. (2015, 390 citations) for accurate free energy docking; Park (2020, 271 citations) for nanoparticle-albumin interactions; De Simone et al. (2021, 195 citations) for enzymatic aspects.
Core Methods
AutoDock/GOLD for pose prediction; MD for refinement (Aldeghi et al., 2015); fluorescence validation against quenching data (Hong et al., 2011).
How PapersFlow Helps You Research Molecular Docking Serum Albumin Interactions
Discover & Search
Research Agent uses searchPapers with 'molecular docking human serum albumin' to retrieve Kragh-Hansen et al. (2002, 873 citations); citationGraph reveals 500+ downstream docking studies; findSimilarPapers expands to albumin-nanoparticle interactions like Park (2020); exaSearch uncovers unpublished preprints on HSA docking protocols.
Analyze & Verify
Analysis Agent runs readPaperContent on Aldeghi et al. (2015) to extract free energy protocols, verifies docking scores via runPythonAnalysis (NumPy for RMSD calculations on PDB poses), applies verifyResponse (CoVe) for affinity predictions, and uses GRADE grading to score evidence strength in binding site claims.
Synthesize & Write
Synthesis Agent detects gaps in current HSA docking for polyphenols (vs. Martinez-Gonzalez et al., 2017), flags contradictions between rigid vs. flexible docking; Writing Agent applies latexEditText for methods sections, latexSyncCitations for 20+ references, latexCompile for docking result tables, exportMermaid for binding site diagrams.
Use Cases
"Analyze docking poses of luteolin to HSA from Yan et al. 2013 with Python RMSD."
Research Agent → searchPapers('luteolin HSA docking') → Analysis Agent → readPaperContent + runPythonAnalysis (load PDB, compute RMSD to crystal) → outputs validated pose overlays and affinity stats.
"Write LaTeX review on HSA binding sites with citations from Kragh-Hansen 2002."
Research Agent → citationGraph('Kragh-Hansen 2002') → Synthesis → gap detection → Writing Agent → latexEditText('Sudlow sites') → latexSyncCitations → latexCompile → researcher gets compiled PDF with figures.
"Find GitHub codes for weighted-ensemble docking from Huber 1996."
Research Agent → searchPapers('Huber weighted-ensemble') → Code Discovery → paperExtractUrls → paperFindGithubRepo → githubRepoInspect → outputs runnable Python scripts for albumin association simulations.
Automated Workflows
Deep Research workflow scans 50+ papers on HSA docking via searchPapers → citationGraph → structured report with affinity trends (Kragh-Hansen et al., 2002). DeepScan applies 7-step analysis: readPaperContent on Aldeghi (2015) → runPythonAnalysis docking scores → CoVe verification → GRADE report. Theorizer generates hypotheses on FcRn-HSA docking from Knudsen Sand (2015) via literature synthesis.
Frequently Asked Questions
What is molecular docking in serum albumin studies?
Computational method predicts ligand binding to HSA sites using tools like AutoDock (Kragh-Hansen et al., 2002). Focuses on Sudlow sites I/II.
What are key methods?
Rigid-receptor docking, induced-fit, free energy calculations (Aldeghi et al., 2015). Weighted-ensemble dynamics for association (Huber and Kim, 1996).
Name top papers.
Kragh-Hansen et al. (2002, 873 citations) on HSA binding; Aldeghi et al. (2015, 390 citations) on free energies; Knudsen Sand et al. (2015, 291 citations) on FcRn-albumin.
What open problems exist?
Improving affinity accuracy for flexible loops; integrating nanoparticle corona effects (Bashiri et al., 2023); multi-site competition modeling.
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