hybrid molecular mechanicscoarse-grained simulations for structural prediction of g-protein coupled receptorligand complexes混合分子mechanicscoarse-grained模拟结构预测g蛋白耦合receptorligand复合物.pdfVIP

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hybrid molecular mechanicscoarse-grained simulations for structural prediction of g-protein coupled receptorligand complexes混合分子mechanicscoarse-grained模拟结构预测g蛋白耦合receptorligand复合物.pdf

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hybrid molecular mechanicscoarse-grained simulations for structural prediction of g-protein coupled receptorligand complexes混合分子mechanicscoarse-grained模拟结构预测g蛋白耦合receptorligand复合物

Hybrid Molecular Mechanics/Coarse-Grained Simulations for Structural Prediction of G-Protein Coupled Receptor/ Ligand Complexes ` 1,2. 2,3. 2,3,4. 5 2,3,6 Michael Leguebe , Chuong Nguyen , Luciana Capece , Zung Hoang , Alejandro Giorgetti *, Paolo Carloni2,3,7 ´ 1 INRIA Bordeaux Sud-Ouest, Institut de Mathematiques de Bordeaux, Talence, France, 2 Computational Biophysics, German Research School for Simulation Sciences, ¨ ¨ Julich, Germany, 3 JARA - High-Performance Computing, Julich, Germany, 4 International Centre for Genetic Engineering and Biotechnology, Trieste, Italy, 5 Vietnam National University Ho Chi Minh City, Ho Chi Minh City, Vietnam, 6 Department of Biotechnology, University of Verona, Verona, Italy, 7 Institute for Advanced Simulation, ¨ ¨ IAS-5 Intitute for Computational Biomedicine, Forschungszentrum Julich, Julich, Germany Abstract Understanding how ligands bind to G-protein coupled receptors (GPCRs) provides insights into a myriad of cell processes and is crucial for drug development. Here we extend a hybrid molecular mechanics/coarse-grained (MM/CG) approach applied previously to enzymes to GPCR/ligand complexes. The accuracy of this method for structural predictions is established by comparison with recent atomistic molecular dynamics simulations on the human b2 adrenergic receptor, a member of the GPCRs superfamily. The results obtained with the MM/CG methodology show a good agreement