Classification Of Distinct Conformers Of Beta < 2-Adrenergic Receptor (Beta 2-AR) Based On Binding Affinity Of Ligands Through Docking Studies
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Date
2016
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Amer Chemical Soc
Abstract
B2AR reseptörü, akciğerlerin rahatlamasında ve kardiyovasküler fizyolojide rol oynamasıyla önemli bir ilaç hedefidir. Bu çalışmada, çeşitli B2AR konformasyonlarını aktif veya inaktif olarak sınıflandırmak amacıyla, aktivitesi bilinen ligantlar seçilerek onların bağlanma şekillerine göre bir sınıflandırma stratejisi oluşturulmuştur. Önceki bir çalışmada gerçekleştirilen, reseptörün inaktif halinin 2.8 μs'lik MD simülasyonunda, ligandın bağlanma bölgesinin farklı konformasyonları elde edilmiştir. Snapshotlar derlenerek bağlanma bölgesindeki beş anahtar rezidünün RMSD değerlerine göre gruplandırılmıştır. Toplamda 13 farklı konformasyon elde edilmiş ve 5 agonist, 4 ters agonist ve 4 antagonist molekülü her bir konformasyona ayrı ayrı ve 7 farklı skor fonksiyonu kullanılarak dock edilmiştir. En iyi yerleşen konformasyonlar bağlanma bölgesindeki anahtar rezidülerle olan yakınlığına göre seçilmiş ve hesaplanmıştır. Anahtar bölgeye yaklaşamayanlar elenmiş, kalanlar ise skor değerlerine göre sıralanmıştır. Bu sınıflandırma, kritik değerlendirme yapabilmek için MD konformasyonlarından önce aktivitesi bilinen aktif/inaktif kristal yapılara uygulanmıştır. Her skor fonksiyonu tarafından seçilen ve ilk 5'te bulunan MD konformasyonları aktif ve inaktif olarak sınıflandırılmıştır. Son olarak, MD konformasyonlarının ayırt ediciliğini analiz edebilmek için, seçilen bu konformasyonlar ile küçük bir dataset kullanılarak sanal tarama yapılmıştır. MD konformasyonlarının inaktif kristal yapıya göre antagonist/ters agonistler için daha seçici olduğu gözlemlenmiştir. Reseptörün alternatif konformasyonlarını üretmek ve onları sınıflandırmak, genellikle tek bir snaphot X-ray örneği ile sınırlandırılmış ilaç tasarımı çalışmalarında önemli rol oynamaktadır.
B2AR is an important drug target and plays a critical role in the relaxation of pulmonary tissues and cardiovascular physiology. We have developed a strategy for classifying various B2AR conformers as active or inactive states, based on binding mode of selected ligands with known activities. Previously, distinct conformational states of the ligand's binding pocket were obtained from a 2.8 μs MD simulation. Snapshots were clustered based on RMSD value of five key residues at the binding site. Clustering analysis yielded a total of 13 distinct conformers to which five agonists, four inverse agonists, and four antagonists were docked separately, using seven different scoring functions. Best ligand poses with the highest score value were selected and evaluated based on their vicinity to five key residues. Poses that were not in this neighborhood were discarded and remaining ones were sorted based on their score. Before treating MD conformers, this classification scheme was applied first to both active/inactive state crystal structures for critical assessment. MD conformers found in top five in all scoring functions were selected and assigned to be either active or inactive. Finally, selected MD conformers were used to screen a small database to further investigate their discriminatory power. As a result, MD conformers performed more selective screening than inactive state crystal structure for antagonists/inverse agonists. Generating alternative conformations of the receptor and classifying them as active or inactive is an important practice in the drug design studies that were often limited to one snapshot obtained from X-ray studies.
B2AR is an important drug target and plays a critical role in the relaxation of pulmonary tissues and cardiovascular physiology. We have developed a strategy for classifying various B2AR conformers as active or inactive states, based on binding mode of selected ligands with known activities. Previously, distinct conformational states of the ligand's binding pocket were obtained from a 2.8 μs MD simulation. Snapshots were clustered based on RMSD value of five key residues at the binding site. Clustering analysis yielded a total of 13 distinct conformers to which five agonists, four inverse agonists, and four antagonists were docked separately, using seven different scoring functions. Best ligand poses with the highest score value were selected and evaluated based on their vicinity to five key residues. Poses that were not in this neighborhood were discarded and remaining ones were sorted based on their score. Before treating MD conformers, this classification scheme was applied first to both active/inactive state crystal structures for critical assessment. MD conformers found in top five in all scoring functions were selected and assigned to be either active or inactive. Finally, selected MD conformers were used to screen a small database to further investigate their discriminatory power. As a result, MD conformers performed more selective screening than inactive state crystal structure for antagonists/inverse agonists. Generating alternative conformations of the receptor and classifying them as active or inactive is an important practice in the drug design studies that were often limited to one snapshot obtained from X-ray studies.
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252