David Hartsough - Academia.edu (original) (raw)
Papers by David Hartsough
The Journal of Physical Chemistry
J Am Chem Soc, 1992
... David S. Hartsough and Kenneth M. Merz, Jr.* Contribution from the Department of Chemistry, 1... more ... David S. Hartsough and Kenneth M. Merz, Jr.* Contribution from the Department of Chemistry, 152 Davey Laboratory, Pennsylvania State University, University Park, Pennsylvania 16802. Received May 26, 1992 ... (b) Mierke, DF; Kessler, H. J. Am. Chem. SOC. 1991, 113, 9466. ...
Flexibility of Serine Protease in Nonaqueous Solvent Samuel Toba David S. Hartsough Kenneth M. Me... more Flexibility of Serine Protease in Nonaqueous Solvent Samuel Toba David S. Hartsough Kenneth M. Merz Jr. Department of Chemistry 152 Davey Laboratory The Pennsylvania State University University Park, Pennsylvania 16802 I. Introduction Recent studies of ...
The Journal of Physical Chemistry, 1994
The Journal of Physical Chemistry, 1995
ABSTRACT
Techniques in Protein Chemistry, 1997
Flexibility of Serine Protease in Nonaqueous Solvent Samuel Toba David S. Hartsough Kenneth M. Me... more Flexibility of Serine Protease in Nonaqueous Solvent Samuel Toba David S. Hartsough Kenneth M. Merz Jr. Department of Chemistry 152 Davey Laboratory The Pennsylvania State University University Park, Pennsylvania 16802 I. Introduction Recent studies of ...
Proteins: Structure, Function, and Bioinformatics, 2005
At the stage of optimization of a chemical series the compounds are normally assayed for binding ... more At the stage of optimization of a chemical series the compounds are normally assayed for binding or inhibition on the target protein as well as on several proteins from a selectivity panel. These proteins are normally identified on the basis of sequence homology to the target protein. Experimental selectivity data are also taken into account if available. Cases when a nonhomologous protein has a significant affinity to the compound series are going to be missed if the selectivity panel is identified by homology. Experimental data is usually either unavailable or limited to a small fraction of proteins that should be considered. We have developed a computational method of identification of selectivity panel proteins. It is based on the evaluation of binding site similarity to the target protein using docking scores of target-selected molecular probes. These probes are obtained by docking a large library of drug-like compounds to the target protein followed by selecting a diverse subset from the best virtual binders. Docking scores of these probes to other proteins measure binding site similarity to the target. Because the method does not require prior knowledge of either affinities or structures of inhibitors for the target, it can be applied to any protein with known 3D structure. Validation of the method includes rediscovery of nonhomologous proteins that bind common ligands: estradiol, tamoxifen, and riboflavin. Given 3D structures, the method can effectively discriminate proteins with similar binding sites from random proteins independent of sequence homology.
Combinatorial Library Methods and Protocols, 2002
Tetrahedron Letters, 1995
Structure and energy calculations at the MP2/6-31G*//UHF/6-31G* level of four transition states f... more Structure and energy calculations at the MP2/6-31G*//UHF/6-31G* level of four transition states for the cyclization of the 3-methyl-, and independently, the 3-fluoro-5-hexenylperoxy radical have been recorded. These calculations indicate that while the methyl substituent prefers to adopt an equatorial disposition on a chair-like transition state construct, the fluorine atom exhibits a strong preference for an axial alignment on the chair-like
Journal of the American Chemical Society, 1993
ABSTRACT
Journal of the American Chemical Society, 1992
... David S. Hartsough and Kenneth M. Merz, Jr.* Contribution from the Department of Chemistry, 1... more ... David S. Hartsough and Kenneth M. Merz, Jr.* Contribution from the Department of Chemistry, 152 Davey Laboratory, Pennsylvania State University, University Park, Pennsylvania 16802. Received May 26, 1992 ... (b) Mierke, DF; Kessler, H. J. Am. Chem. SOC. 1991, 113, 9466. ...
Journal of the American Chemical Society, 1996
We have investigated the serine protease γ-chymotrypsin (γ-CT) in three different solvation envir... more We have investigated the serine protease γ-chymotrypsin (γ-CT) in three different solvation environments using molecular dynamics simulations. These solvation environments include the following:(1) γ-CT taken from the crystal structure of Yennawar et al.(Biochemistry ...
The Journal of Organic Chemistry, 1989
C2-HJ, 2.46 (dd, J = 8,2 Hz, H9), 1.98 (m, C16-HJ, 1.84 (m, Hll), 1.72 (dd, J = 12.8, 2 Hz, H10-e... more C2-HJ, 2.46 (dd, J = 8,2 Hz, H9), 1.98 (m, C16-HJ, 1.84 (m, Hll), 1.72 (dd, J = 12.8, 2 Hz, H10-endo), 1.52 (m, H10-exo), 1.37 (m, CH2's), 1.22 (m, CHis), 1.16 (m, H15), 0.72 (m, H15); I3C NMR ... 39.9 (ClO), 45.5, 46.0 (Cl, C14), 47.7 (Cll), 50.0 (C9), 124.7 (C7), 125.1, ...
The Journal of Organic Chemistry, 1989
Journal of Computer-Aided Molecular Design, 2005
Structure-based screening using fully flexible docking is still too slow for large molecular libr... more Structure-based screening using fully flexible docking is still too slow for large molecular libraries. High quality docking of a million molecule library can take days even on a cluster with hundreds of CPUs. This performance issue prohibits the use of fully flexible docking in the design of large combinatorial libraries. We have developed a fast structure-based screening method, which utilizes docking of a limited number of compounds to build a 2D QSAR model used to rapidly score the rest of the database. We compare here a model based on radial basis functions and a Bayesian categorization model. The number of compounds that need to be actually docked depends on the number of docking hits found. In our case studies reasonable quality models are built after docking of the number of molecules containing 50dockinghits.TherestofthelibraryisscreenedbytheQSARmodel.OptionallyafractionoftheQSAR−prioritizedlibrarycanbedockedinordertofindthetruedockinghits.Thequalityofthemodelonlydependsonthetrainingsetsize−notonthesizeofthelibrarytobescreened.Therefore,forlargerlibrariesthemethodyieldshighergaininspeednochangeinperformance.Prioritizingalargelibrarywiththesemodelsprovidesasignificantenrichmentwithdockinghits:itattainsthevaluesof50 docking hits. The rest of the library is screened by the QSAR model. Optionally a fraction of the QSAR-prioritized library can be docked in order to find the true docking hits. The quality of the model only depends on the training set size-not on the size of the library to be screened. Therefore, for larger libraries the method yields higher gain in speed no change in performance. Prioritizing a large library with these models provides a significant enrichment with docking hits: it attains the values of 50dockinghits.TherestofthelibraryisscreenedbytheQSARmodel.OptionallyafractionoftheQSAR−prioritizedlibrarycanbedockedinordertofindthetruedockinghits.Thequalityofthemodelonlydependsonthetrainingsetsize−notonthesizeofthelibrarytobescreened.Therefore,forlargerlibrariesthemethodyieldshighergaininspeednochangeinperformance.Prioritizingalargelibrarywiththesemodelsprovidesasignificantenrichmentwithdockinghits:itattainsthevaluesof13 and $35 at the beginning of the score-sorted libraries in our two case studies: screening of the NCI collection and a combinatorial libraries on CDK2 kinase structure. With such enrichments, only a fraction of the database must actually be docked to find many of the true hits. The throughput of the method allows its use in screening of large compound collections and in the design of large combinatorial libraries. The strategy proposed has an important effect on efficiency but does not affect retrieval of actives, the latter being determined by the quality of the docking method itself.
The Journal of Physical Chemistry
J Am Chem Soc, 1992
... David S. Hartsough and Kenneth M. Merz, Jr.* Contribution from the Department of Chemistry, 1... more ... David S. Hartsough and Kenneth M. Merz, Jr.* Contribution from the Department of Chemistry, 152 Davey Laboratory, Pennsylvania State University, University Park, Pennsylvania 16802. Received May 26, 1992 ... (b) Mierke, DF; Kessler, H. J. Am. Chem. SOC. 1991, 113, 9466. ...
Flexibility of Serine Protease in Nonaqueous Solvent Samuel Toba David S. Hartsough Kenneth M. Me... more Flexibility of Serine Protease in Nonaqueous Solvent Samuel Toba David S. Hartsough Kenneth M. Merz Jr. Department of Chemistry 152 Davey Laboratory The Pennsylvania State University University Park, Pennsylvania 16802 I. Introduction Recent studies of ...
The Journal of Physical Chemistry, 1994
The Journal of Physical Chemistry, 1995
ABSTRACT
Techniques in Protein Chemistry, 1997
Flexibility of Serine Protease in Nonaqueous Solvent Samuel Toba David S. Hartsough Kenneth M. Me... more Flexibility of Serine Protease in Nonaqueous Solvent Samuel Toba David S. Hartsough Kenneth M. Merz Jr. Department of Chemistry 152 Davey Laboratory The Pennsylvania State University University Park, Pennsylvania 16802 I. Introduction Recent studies of ...
Proteins: Structure, Function, and Bioinformatics, 2005
At the stage of optimization of a chemical series the compounds are normally assayed for binding ... more At the stage of optimization of a chemical series the compounds are normally assayed for binding or inhibition on the target protein as well as on several proteins from a selectivity panel. These proteins are normally identified on the basis of sequence homology to the target protein. Experimental selectivity data are also taken into account if available. Cases when a nonhomologous protein has a significant affinity to the compound series are going to be missed if the selectivity panel is identified by homology. Experimental data is usually either unavailable or limited to a small fraction of proteins that should be considered. We have developed a computational method of identification of selectivity panel proteins. It is based on the evaluation of binding site similarity to the target protein using docking scores of target-selected molecular probes. These probes are obtained by docking a large library of drug-like compounds to the target protein followed by selecting a diverse subset from the best virtual binders. Docking scores of these probes to other proteins measure binding site similarity to the target. Because the method does not require prior knowledge of either affinities or structures of inhibitors for the target, it can be applied to any protein with known 3D structure. Validation of the method includes rediscovery of nonhomologous proteins that bind common ligands: estradiol, tamoxifen, and riboflavin. Given 3D structures, the method can effectively discriminate proteins with similar binding sites from random proteins independent of sequence homology.
Combinatorial Library Methods and Protocols, 2002
Tetrahedron Letters, 1995
Structure and energy calculations at the MP2/6-31G*//UHF/6-31G* level of four transition states f... more Structure and energy calculations at the MP2/6-31G*//UHF/6-31G* level of four transition states for the cyclization of the 3-methyl-, and independently, the 3-fluoro-5-hexenylperoxy radical have been recorded. These calculations indicate that while the methyl substituent prefers to adopt an equatorial disposition on a chair-like transition state construct, the fluorine atom exhibits a strong preference for an axial alignment on the chair-like
Journal of the American Chemical Society, 1993
ABSTRACT
Journal of the American Chemical Society, 1992
... David S. Hartsough and Kenneth M. Merz, Jr.* Contribution from the Department of Chemistry, 1... more ... David S. Hartsough and Kenneth M. Merz, Jr.* Contribution from the Department of Chemistry, 152 Davey Laboratory, Pennsylvania State University, University Park, Pennsylvania 16802. Received May 26, 1992 ... (b) Mierke, DF; Kessler, H. J. Am. Chem. SOC. 1991, 113, 9466. ...
Journal of the American Chemical Society, 1996
We have investigated the serine protease γ-chymotrypsin (γ-CT) in three different solvation envir... more We have investigated the serine protease γ-chymotrypsin (γ-CT) in three different solvation environments using molecular dynamics simulations. These solvation environments include the following:(1) γ-CT taken from the crystal structure of Yennawar et al.(Biochemistry ...
The Journal of Organic Chemistry, 1989
C2-HJ, 2.46 (dd, J = 8,2 Hz, H9), 1.98 (m, C16-HJ, 1.84 (m, Hll), 1.72 (dd, J = 12.8, 2 Hz, H10-e... more C2-HJ, 2.46 (dd, J = 8,2 Hz, H9), 1.98 (m, C16-HJ, 1.84 (m, Hll), 1.72 (dd, J = 12.8, 2 Hz, H10-endo), 1.52 (m, H10-exo), 1.37 (m, CH2's), 1.22 (m, CHis), 1.16 (m, H15), 0.72 (m, H15); I3C NMR ... 39.9 (ClO), 45.5, 46.0 (Cl, C14), 47.7 (Cll), 50.0 (C9), 124.7 (C7), 125.1, ...
The Journal of Organic Chemistry, 1989
Journal of Computer-Aided Molecular Design, 2005
Structure-based screening using fully flexible docking is still too slow for large molecular libr... more Structure-based screening using fully flexible docking is still too slow for large molecular libraries. High quality docking of a million molecule library can take days even on a cluster with hundreds of CPUs. This performance issue prohibits the use of fully flexible docking in the design of large combinatorial libraries. We have developed a fast structure-based screening method, which utilizes docking of a limited number of compounds to build a 2D QSAR model used to rapidly score the rest of the database. We compare here a model based on radial basis functions and a Bayesian categorization model. The number of compounds that need to be actually docked depends on the number of docking hits found. In our case studies reasonable quality models are built after docking of the number of molecules containing 50dockinghits.TherestofthelibraryisscreenedbytheQSARmodel.OptionallyafractionoftheQSAR−prioritizedlibrarycanbedockedinordertofindthetruedockinghits.Thequalityofthemodelonlydependsonthetrainingsetsize−notonthesizeofthelibrarytobescreened.Therefore,forlargerlibrariesthemethodyieldshighergaininspeednochangeinperformance.Prioritizingalargelibrarywiththesemodelsprovidesasignificantenrichmentwithdockinghits:itattainsthevaluesof50 docking hits. The rest of the library is screened by the QSAR model. Optionally a fraction of the QSAR-prioritized library can be docked in order to find the true docking hits. The quality of the model only depends on the training set size-not on the size of the library to be screened. Therefore, for larger libraries the method yields higher gain in speed no change in performance. Prioritizing a large library with these models provides a significant enrichment with docking hits: it attains the values of 50dockinghits.TherestofthelibraryisscreenedbytheQSARmodel.OptionallyafractionoftheQSAR−prioritizedlibrarycanbedockedinordertofindthetruedockinghits.Thequalityofthemodelonlydependsonthetrainingsetsize−notonthesizeofthelibrarytobescreened.Therefore,forlargerlibrariesthemethodyieldshighergaininspeednochangeinperformance.Prioritizingalargelibrarywiththesemodelsprovidesasignificantenrichmentwithdockinghits:itattainsthevaluesof13 and $35 at the beginning of the score-sorted libraries in our two case studies: screening of the NCI collection and a combinatorial libraries on CDK2 kinase structure. With such enrichments, only a fraction of the database must actually be docked to find many of the true hits. The throughput of the method allows its use in screening of large compound collections and in the design of large combinatorial libraries. The strategy proposed has an important effect on efficiency but does not affect retrieval of actives, the latter being determined by the quality of the docking method itself.