Time-efficient flexible superposition of medium-sized molecules
We present an efficient algorithm for the structural alignment of medium-sized organic molecules. The algorithm has been developed for applications in 3D QSAR and in receptor modeling. The method assumes one of the molecules, the reference ligand, to be presented in the conformation that it adopts i...
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Veröffentlicht in: | Journal of computer-aided molecular design 1997-07, Vol.11 (4), p.357-368 |
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description | We present an efficient algorithm for the structural alignment of medium-sized organic molecules. The algorithm has been developed for applications in 3D QSAR and in receptor modeling. The method assumes one of the molecules, the reference ligand, to be presented in the conformation that it adopts inside the receptor pocket. The second molecule, the test ligand, is considered to be flexible, and is assumed to be given in an arbitrary low-energy conformation. Ligand flexibility is modeled by decomposing the test ligand into molecular fragments, such that ring systems are completely contained in a single fragment. Conformations of fragments and torsional angles of single bonds are taken from a small finite set, which depends on the fragment and bond, respectively. The algorithm superimposes a distinguished base fragment of the test ligand onto a suitable region of the reference ligand and then attaches the remaining fragments of the test ligand in a step-by-step fashion. During this process, a scoring function is optimized that encompasses bonding terms and terms accounting for steric overlap as well as for similarity of chemical properties of both ligands. The algorithm has been implemented in the FLEXS system. To validate the quality of the produced results, we have selected a number of examples for which the mutual superposition of two ligands is experimentally given by the comparison of the binding geometries known from the crystal structures of their corresponding protein-ligand complexes. On more than two-thirds of the test examples the algorithm produces rms deviations of the predicted versus the observed conformation of the test ligand below 1.5 A. The run time of the algorithm on a single problem instance is a few minutes on a common-day workstation. The overall goal of this research is to drastically reduce run times, while limiting the inaccuracies of the model and the computation to a tolerable level. |
doi_str_mv | 10.1023/A:1007959729800 |
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The algorithm has been developed for applications in 3D QSAR and in receptor modeling. The method assumes one of the molecules, the reference ligand, to be presented in the conformation that it adopts inside the receptor pocket. The second molecule, the test ligand, is considered to be flexible, and is assumed to be given in an arbitrary low-energy conformation. Ligand flexibility is modeled by decomposing the test ligand into molecular fragments, such that ring systems are completely contained in a single fragment. Conformations of fragments and torsional angles of single bonds are taken from a small finite set, which depends on the fragment and bond, respectively. The algorithm superimposes a distinguished base fragment of the test ligand onto a suitable region of the reference ligand and then attaches the remaining fragments of the test ligand in a step-by-step fashion. During this process, a scoring function is optimized that encompasses bonding terms and terms accounting for steric overlap as well as for similarity of chemical properties of both ligands. The algorithm has been implemented in the FLEXS system. To validate the quality of the produced results, we have selected a number of examples for which the mutual superposition of two ligands is experimentally given by the comparison of the binding geometries known from the crystal structures of their corresponding protein-ligand complexes. On more than two-thirds of the test examples the algorithm produces rms deviations of the predicted versus the observed conformation of the test ligand below 1.5 A. The run time of the algorithm on a single problem instance is a few minutes on a common-day workstation. The overall goal of this research is to drastically reduce run times, while limiting the inaccuracies of the model and the computation to a tolerable level.</description><identifier>ISSN: 0920-654X</identifier><identifier>EISSN: 1573-4951</identifier><identifier>DOI: 10.1023/A:1007959729800</identifier><identifier>PMID: 9334902</identifier><language>eng</language><publisher>Netherlands: Springer Nature B.V</publisher><subject>Algorithms ; Binding Sites ; Chemical properties ; Computer Simulation ; Folic Acid - analogs & derivatives ; Folic Acid - chemistry ; Folic Acid - metabolism ; Fragments ; Humans ; Ligands ; Mathematical analysis ; Mathematical models ; Methotrexate - chemistry ; Methotrexate - metabolism ; Models, Chemical ; Models, Molecular ; Protein Conformation ; Proteins - chemistry ; Receptors ; Run time (computers) ; Studies ; Tetrahydrofolate Dehydrogenase - chemistry ; Tetrahydrofolate Dehydrogenase - metabolism ; Three dimensional</subject><ispartof>Journal of computer-aided molecular design, 1997-07, Vol.11 (4), p.357-368</ispartof><rights>Kluwer Academic Publishers 1997</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c312t-d39b42235c0374b7bec5639e2e62356045a9c35a94bd5d5a5c522fc7f3e910083</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/9334902$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lemmen, C</creatorcontrib><creatorcontrib>Lengauer, T</creatorcontrib><title>Time-efficient flexible superposition of medium-sized molecules</title><title>Journal of computer-aided molecular design</title><addtitle>J Comput Aided Mol Des</addtitle><description>We present an efficient algorithm for the structural alignment of medium-sized organic molecules. The algorithm has been developed for applications in 3D QSAR and in receptor modeling. The method assumes one of the molecules, the reference ligand, to be presented in the conformation that it adopts inside the receptor pocket. The second molecule, the test ligand, is considered to be flexible, and is assumed to be given in an arbitrary low-energy conformation. Ligand flexibility is modeled by decomposing the test ligand into molecular fragments, such that ring systems are completely contained in a single fragment. Conformations of fragments and torsional angles of single bonds are taken from a small finite set, which depends on the fragment and bond, respectively. The algorithm superimposes a distinguished base fragment of the test ligand onto a suitable region of the reference ligand and then attaches the remaining fragments of the test ligand in a step-by-step fashion. During this process, a scoring function is optimized that encompasses bonding terms and terms accounting for steric overlap as well as for similarity of chemical properties of both ligands. The algorithm has been implemented in the FLEXS system. To validate the quality of the produced results, we have selected a number of examples for which the mutual superposition of two ligands is experimentally given by the comparison of the binding geometries known from the crystal structures of their corresponding protein-ligand complexes. On more than two-thirds of the test examples the algorithm produces rms deviations of the predicted versus the observed conformation of the test ligand below 1.5 A. The run time of the algorithm on a single problem instance is a few minutes on a common-day workstation. The overall goal of this research is to drastically reduce run times, while limiting the inaccuracies of the model and the computation to a tolerable level.</description><subject>Algorithms</subject><subject>Binding Sites</subject><subject>Chemical properties</subject><subject>Computer Simulation</subject><subject>Folic Acid - analogs & derivatives</subject><subject>Folic Acid - chemistry</subject><subject>Folic Acid - metabolism</subject><subject>Fragments</subject><subject>Humans</subject><subject>Ligands</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Methotrexate - chemistry</subject><subject>Methotrexate - metabolism</subject><subject>Models, Chemical</subject><subject>Models, Molecular</subject><subject>Protein Conformation</subject><subject>Proteins - chemistry</subject><subject>Receptors</subject><subject>Run time (computers)</subject><subject>Studies</subject><subject>Tetrahydrofolate Dehydrogenase - chemistry</subject><subject>Tetrahydrofolate Dehydrogenase - 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analogs & derivatives</topic><topic>Folic Acid - chemistry</topic><topic>Folic Acid - metabolism</topic><topic>Fragments</topic><topic>Humans</topic><topic>Ligands</topic><topic>Mathematical analysis</topic><topic>Mathematical models</topic><topic>Methotrexate - chemistry</topic><topic>Methotrexate - metabolism</topic><topic>Models, Chemical</topic><topic>Models, Molecular</topic><topic>Protein Conformation</topic><topic>Proteins - chemistry</topic><topic>Receptors</topic><topic>Run time (computers)</topic><topic>Studies</topic><topic>Tetrahydrofolate Dehydrogenase - chemistry</topic><topic>Tetrahydrofolate Dehydrogenase - metabolism</topic><topic>Three dimensional</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lemmen, C</creatorcontrib><creatorcontrib>Lengauer, T</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Computing Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>Materials Science Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of computer-aided molecular design</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lemmen, C</au><au>Lengauer, T</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Time-efficient flexible superposition of medium-sized molecules</atitle><jtitle>Journal of computer-aided molecular design</jtitle><addtitle>J Comput Aided Mol Des</addtitle><date>1997-07-01</date><risdate>1997</risdate><volume>11</volume><issue>4</issue><spage>357</spage><epage>368</epage><pages>357-368</pages><issn>0920-654X</issn><eissn>1573-4951</eissn><abstract>We present an efficient algorithm for the structural alignment of medium-sized organic molecules. The algorithm has been developed for applications in 3D QSAR and in receptor modeling. The method assumes one of the molecules, the reference ligand, to be presented in the conformation that it adopts inside the receptor pocket. The second molecule, the test ligand, is considered to be flexible, and is assumed to be given in an arbitrary low-energy conformation. Ligand flexibility is modeled by decomposing the test ligand into molecular fragments, such that ring systems are completely contained in a single fragment. Conformations of fragments and torsional angles of single bonds are taken from a small finite set, which depends on the fragment and bond, respectively. The algorithm superimposes a distinguished base fragment of the test ligand onto a suitable region of the reference ligand and then attaches the remaining fragments of the test ligand in a step-by-step fashion. During this process, a scoring function is optimized that encompasses bonding terms and terms accounting for steric overlap as well as for similarity of chemical properties of both ligands. The algorithm has been implemented in the FLEXS system. To validate the quality of the produced results, we have selected a number of examples for which the mutual superposition of two ligands is experimentally given by the comparison of the binding geometries known from the crystal structures of their corresponding protein-ligand complexes. On more than two-thirds of the test examples the algorithm produces rms deviations of the predicted versus the observed conformation of the test ligand below 1.5 A. The run time of the algorithm on a single problem instance is a few minutes on a common-day workstation. The overall goal of this research is to drastically reduce run times, while limiting the inaccuracies of the model and the computation to a tolerable level.</abstract><cop>Netherlands</cop><pub>Springer Nature B.V</pub><pmid>9334902</pmid><doi>10.1023/A:1007959729800</doi><tpages>12</tpages></addata></record> |
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subjects | Algorithms Binding Sites Chemical properties Computer Simulation Folic Acid - analogs & derivatives Folic Acid - chemistry Folic Acid - metabolism Fragments Humans Ligands Mathematical analysis Mathematical models Methotrexate - chemistry Methotrexate - metabolism Models, Chemical Models, Molecular Protein Conformation Proteins - chemistry Receptors Run time (computers) Studies Tetrahydrofolate Dehydrogenase - chemistry Tetrahydrofolate Dehydrogenase - metabolism Three dimensional |
title | Time-efficient flexible superposition of medium-sized molecules |
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