COMPARISON OF MOLECULAR DYNAMICS SIMULATIONS OF DIHYDROFOLATE REDUCTASE BOUND T
COMPARISON OF MOLECULAR DYNAMICS SIMULATIONS OF DIHYDROFOLATE REDUCTASE BOUND T
批准号:
8364374
负责人:
AMY ANDERSON
金额:
$0.2万
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-09-15 至 2013-07-31
关键词:
Active SitesAntifungal TherapyBindingBinding SitesBiomedical ResearchCandida albicansCandida glabrataDNA biosynthesisDihydrofolate ReductaseDockingDrug Delivery SystemsDrug DesignFolateFolic Acid AntagonistsFundingGrantGraphHigh Performance ComputingHousingHumanHydrogen BondingLibrariesLigandsLinkModelingMonitorMycosesNational Center for Research ResourcesNatureOrganismPlayPrincipal InvestigatorProtein BiosynthesisRadialResearchResearch InfrastructureResourcesRoleSolventsSourceStructureSystemTimeUnited States National Institutes of Healthcostdesignflexibilityinhibitor/antagonistmeetingsmolecular dynamicsprogramsscaffoldsimulationsuccess
中文摘要
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英文摘要
This subproject is one of many research subprojects utilizing the resources
provided by a Center grant funded by NIH/NCRR. Primary support for the subproject
and the subproject's principal investigator may have been provided by other sources,
including other NIH sources. The Total Cost listed for the subproject likely
represents the estimated amount of Center infrastructure utilized by the subproject,
not direct funding provided by the NCRR grant to the subproject or subproject staff.
Opportunistic fungal infections have increased significantly over the last few decades creating a need for new antifungal therapies (1-3). Presently, we have a drug design program underway aimed at targeting Dihydrofolate reductase (DHFR) with propargyl-linked inhibitors. DHFR is a well established drug target that is essential for DNA and protein synthesis in all organisms (4-7). Models of Candida albicans dihydrofolate reductase (CaDHFR) (8), Candida glabrata dihydrofolate reductase (CgDHFR) and human DHFR (9) have been created to dock an in-house library of synthetically generated propargyl-linked antifolates. In order for docking models to correlate with empirically determined inhibition results it was necessary to treat key active site residues as flexible. Limited molecular dynamics (MD) simulations were used to allow residues within 3.5 radius of the ligand to move. Most importantly, the flexibility of loop residues (CaDHFR and CgDHFR: Thr 58-Phe 66, HuDHFR: Thr 56-Asn 64) flanking the active site was found to be critical to docking accuracy. Snapshots were taken along the MD trajectory to create an ensemble of structures for docking. Flexibility increased the accuracy of docking results (10) and correlates well with newly determined crystallographic structures of CaDHFR and CgDHFR bound to propargyl-linked antifolates. The interactions between these loop residues and the propargyl-linked ligands play a key role in both fungal potency and human selectivity. When a structural alignment of fungal DHFR is compared with huDHFR the loop residues are displaced at different distances from the folate binding site and therefore, occupy different volumes in the active site with human having the smallest volume. It was thought that increasing the size of the ligand, thus creating unfavorable steric interference in the huDHFR binding site would increase selectivity for fungal DHFR. However, this design strategy has met with limited success. The flexible nature of the loop flanking the binding site allows the huDHFR binding site to accommodate ligands that were designed to be selective for fungal DHFR. In order to understand the role these loop residues play in potency and selectivity we will perform more comprehensive MD simulations at longer time scales that will encompass the entire system including solvent. The resultant simulations will be analyzed by monitoring transient and permanent hydrogen bonds, comparing loop displacement in different species and using different ligand scaffolds. Desmond (D.E. Shaw) which is a highly parallelizable program specifically designed for molecular dynamics simulations will be used to perform all simulations. Therefore, allocations on four resources that have Desmond installed are requested. 1. M. B. Edmond, S. E. Wallace, D. K. McClish, M. A. Pfaller, R. N. Jones and R. P. Wenzel, Clin. Infect. Dis., 1999, 29, 239-244. 2. M. A. Pfaller and D. J. Diekema, J. Clin. Microbiol., 2004, 42, 4419-4431. 3. R. A. Hajjeh, A. N. Sofair, L. H. Harrison, G. M. Lyon, B. A. Arthington-Skaggs, S. A. Mirza, M. Phelan, J. Morgan, W. Lee-Yang, M. A. Ciblak, L. E. Benjamin, L. T. Sanza, S. Huie, S. F. Yeo, M. E. Brandt and D. W. Warnock, J. Clin. Microbiol., 2004, 42, 1519-1527. 4. G. F. Fleming and R. L. Schilsky, Semin. Oncol., 1992, 19, 707-719. 5. B. Roth, B. S. Rauckman, R. Ferone, D. P. Baccanari, J. N. Champness and R. M. Hyde, J. Med. Chem., 1987, 30, 348-356. 6. A. J. Salter, Rev. Infect. Dis., 1982, 4, 196-236. 7. C. Plowe, J. Kublin, D. Kamwendo, R. Mukadam, C. P, M. Molyneux, T. Taylor and E. Terrie, Brit. Med. J., 2004, 545-548. 8. J. L. Paulsen, J. Liu, D. B. Bolstad, A. E. Smith, N. D. Priestley, D. L. Wright and A. C. Anderson, Bioorg. Med. Chem., 2009, 17, 4866-4872. 9. O. Algul, J. L. Paulsen and A. C. Anderson, J. Mol. Graph. Model., 2011, 29, 608-613. 10. J. L. Paulsen and A. C. Anderson, J. Chem. Inf. Model., 2009, 49, 2813-2819.
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