Computational Analysis for the Rational Design of Anti-Amyloid Beta (ABeta) Antibodies
| Autor: | Ray Luo, Theodora Po, D’Artagnan Greene, Jennifer Pan, Tanya Tabibian |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Aging Amyloid beta Drug design Computational biology Molecular Dynamics Simulation Neurodegenerative Alzheimer's Disease Article Epitope Antibodies 03 medical and health sciences 0302 clinical medicine Engineering Alzheimer Disease Materials Chemistry Acquired Cognitive Impairment Effective treatment Computational analysis Physical and Theoretical Chemistry Amyloid beta-Peptides biology Chemistry Rational design Neurosciences Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) Biomolecules (q-bio.BM) Surfaces Coatings and Films Brain Disorders 030104 developmental biology Quantitative Biology - Biomolecules Docking (molecular) 5.1 Pharmaceuticals FOS: Biological sciences Drug Design Neurological Physical Sciences Chemical Sciences biology.protein Dementia Antibody Development of treatments and therapeutic interventions 030217 neurology & neurosurgery |
| Zdroj: | The journal of physical chemistry. B, vol 122, iss 16 |
| Popis: | Alzheimer’s disease (AD) is a neurodegenerative disorder that lacks effective treatment options. Anti-amyloid beta (Aβ) antibodies are the leading drug candidates to treat AD, but the results of clinical trials have been disappointing. Introducing rational mutations into anti-Aβ antibodies to increase their effectiveness is a way forward, but the path to take is unclear. In this study, we demonstrate the use of computational fragment-based docking and MMPBSA binding free energy calculations in the analysis of anti-Aβ antibodies for rational drug design efforts. Our fragment-based docking method successfully predicts the emergence of the common EFRH epitope. MD simulations coupled with MMPBSA binding free energy calculations are used to analyze scenarios described in prior studies, and we computationally introduce rational mutations into PFA1 to predict mutations that can improve its binding affinity toward the pE3-Aβ(3–8) form of Aβ. Two out of our four proposed mutations are predicted to stabilize binding. Our study demonstrates that a computational approach may lead to an improved drug candidate for AD in the future. |
| Databáze: | OpenAIRE |
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