http://www.quantumbioinc.com/index.htmlPublications related to QuantumBio software applications.enlance@quantumbioinc.comCopyright 2007 QuantumBio Inc.2007-10-11T09:49:58-04:00 hourly 1 2000-01-01T12:00+00:00 Thu, 11 Oct 2007 09:55:53 -0400lance@quantumbioinc.comHome2007-10-11T09:49:58-04:00http://www.quantumbioinc.com/Support/Publications/index_files/6ab50cd43570b669eafd7b45fd03ed99-23.html#unique-entry-id-23http://www.quantumbioinc.com/Support/Publications/index_files/6ab50cd43570b669eafd7b45fd03ed99-23.html#unique-entry-id-23sales@quantumbioinc.com for inclusion in this area of the website.

To get an understanding of QuantumBio's technology, and to study specific examples of the technology in action, see the publications in the following list.

- Fundamental Theory and Critical Assessment of Performance
- Quantum Mechanics Scoring Function (QMScore)
- Quantum Mechanics in Xray Refinement
- Pairwise Decomposition (PWD) and SE-COMBINE
- Quantum Mechanics in NMR Refinement
- Quantum Mechanics in QM-QSAR Applications

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]]>lance@quantumbioinc.comNMR2007-09-15T09:49:26-04:00http://www.quantumbioinc.com/Support/Publications/index_files/b2e08a32b01a76695efb7c4e853c085d-27.html#unique-entry-id-27http://www.quantumbioinc.com/Support/Publications/index_files/b2e08a32b01a76695efb7c4e853c085d-27.html#unique-entry-id-27Abstract: We have generated docking poses for the FKBP-GPI complex using eight docking programs, and compared their scoring functions with scoring based on NMR chemical shift perturbations (NMRScore). Because the chemical shift perturbation (CSP) is exquisitely sensitive on the orientation of the ligand inside the binding pocket, NMRScore offers an accurate and straightforward approach to score different poses. All scoring functions were inspected by their abilities to highly rank the native-like structures and separate them from decoy poses generated for a protein-ligand complex. The overall performance of NMRScore is much better than that of energy-based scoring functions associated with docking programs in both aspects. In summary, we find that the combination of docking programs with NMRScore results in an approach that can robustly determine the binding site structure for a protein-ligand complex, thereby providing a new tool facilitating the structure-based drug discovery process.

Authors: Bing Wang, Lance M. Westerhoff, and Kenneth M. Merz Jr.

Reference: J. Med. Chem., 50 (21), 5128-5134, 2007. (see link for full paper).
]]>lance@quantumbioinc.comTheory2007-09-01T11:53:23-04:00http://www.quantumbioinc.com/Support/Publications/index_files/a290909fd670accb6aa5f5a6cbe14a9c-26.html#unique-entry-id-26http://www.quantumbioinc.com/Support/Publications/index_files/a290909fd670accb6aa5f5a6cbe14a9c-26.html#unique-entry-id-26Abstract: Herein we will focus on the use of quantum mechanics (QM) in drug design (DD) to solve disparate problems from scoring protein–ligand poses to building QM QSAR models. Through the variational principle of QM we know that we can obtain a more accurate representation of molecular systems than classical models, and while this is not a matter of debate, it still has not been shown that the expense of QM approaches is offset by improved accuracy in DD applications. Objectively validating the improved applicability and performance of QM over classical-based models in DD will be the focus of research in the coming years along with research on the conformational sampling problem as it relates to protein–ligand complexes.

Authors: Kaushik Raha, Martin B. Peters, Bing Wang, Ning Yu, Andrew M. Wollacott, Lance M. Westerhoff, and Kenneth M. Merz Jr.

Reference: Drug Discovery Today. 2007, 12:17-18, 725-731. (see link for full paper).]]>lance@quantumbioinc.comGeometry2007-05-30T15:27:51-04:00http://www.quantumbioinc.com/Support/Publications/index_files/5f10df4467c000619fa7f52b7069cbff-25.html#unique-entry-id-25http://www.quantumbioinc.com/Support/Publications/index_files/5f10df4467c000619fa7f52b7069cbff-25.html#unique-entry-id-25Abstract: The ability to discriminate native structures from computer-generated misfolded ones is key to predicting the three-dimensional structure of a protein from its amino acid sequence. Here we describe an assessment of semiempirical methods for discriminating native protein structures from decoy models. The discrimination of decoys entails an analysis of a large number of protein structures and provides a large-scale validation of quantum mechanical methods and their ability to accurately model proteins. We combine our analysis of semiempirical methods with a comparison of an AMBER force field to discriminate decoys in conjunction with a continuum solvent model. Protein decoys provide a rigorous and reliable benchmark for the evaluation of scoring functions, not only in their ability to accurately identify native structures but also to be computationally tractable to sample a large set of non-native models.

Authors: Andrew M. Wollacott and Kenneth M. Merz, Jr.

Reference: Journal of Chemical Theory and Computation. 2007, ASAP Article. (see link for full paper).
]]>lance@quantumbioinc.comXray2007-01-18T12:53:52-05:00http://www.quantumbioinc.com/Support/Publications/index_files/bc689d2fb13458c6fe560cacb2281fe8-21.html#unique-entry-id-21http://www.quantumbioinc.com/Support/Publications/index_files/bc689d2fb13458c6fe560cacb2281fe8-21.html#unique-entry-id-21Abstract: Orf2, a recently identified prenyltransferase of aromatic natural products, displays relaxed substrate selectivity and interesting product regioselectivity. This gives rise to the opportunity to engineer the active site to tune the functionality of terpenoids for therapeutic applications. The structural basis of substrate binding has been determined, but the source of the observed substrate selectivity and product regioselectivity cannot be completely understood on the basis of the static picture that the crystal structures of Orf2 and its complexes afford. The electron density and B-factors of the substrates, particularly those of 1,6-dihydroxynaphthalene, suggest significant conformational fluctuation in the Orf2 binding site. We thoroughly explored the binding of 1,6-dihydroxynaphthalene and quantitatively evaluated the relative free energies of three binding states that we identified in terms of a two-dimensional potential of mean force. The available experimental orientation, which gives the major prenylated product of 1,6-dihydroxynaphthalene, corresponds to the global free energy minimum. Two alternative binding states were identified on the calculated free energy surface, and both are readily accessible at 300 K. The alternative binding conformations were extracted from the potential of mean force calculation and were subjected to further validation against the experimental X-ray diffraction data using a refinement protocol supplemented with a hybrid quantum mechanical and molecular mechanical energy function. The agreement was excellent as indicated by the R and Rfree factors that were comparable to that obtained for the published orientation using a similar protocol. These binding states are the origin of the selectivity and regioselectivity in Orf2-catalyzed aromatic prenylations. Our analyses also suggest that Ser214 and Tyr288, forming hydrogen bonds with the alternative binding states of 1,6-dihydroxynaphthalene and flaviolin, are good candidates for site-directed mutagenesis, and changing them to, for example, their hydrophobic counterparts would affect the substrate selectivity and product regioselectivity.

Authors: Guanglei Cui, Xue Li, and Kenneth M. Merz, Jr.

Reference: Biochemistry. 2007, 46(5), 1303-1311. (see link for full paper).
]]>lance@quantumbioinc.comTheory2006-09-10T11:20:52-04:00http://www.quantumbioinc.com/Support/Publications/index_files/dd8b3e6dda6c666d521e236d6b82e625-14.html#unique-entry-id-14http://www.quantumbioinc.com/Support/Publications/index_files/dd8b3e6dda6c666d521e236d6b82e625-14.html#unique-entry-id-14Abstract: A critical evaluation of the performance of X-ray refinement protocols using various energy functions is presented using the bovine pancreatic trypsin inhibitor (BPTI) protein. The four potential energy functions we explored include: (1) fully quantum mechanical calculations; (2) one based on an incomplete molecular mechanics (MM) energy function employed in the Crystallography and NMR System (CNS) with empirical parameters developed by Engh and Huber (EH), which lacks electrostatic and attractive van der Waals terms; (3) one based on a complete MM energy function (AMBER ff99 parameter set); and (4) the same as 3, with the addition of a Generalized Born (GB) implicit solvation term. The R, R free, real space R values of the refined structures and deviations from the original experimental structure were used to assess the relative performance. It was found that at 1 Å resolution the physically based energy functions 1, 3, and 4 performed better than energy function 2, which we attribute to the better representation of key interactions, particularly electrostatics. The observed departures from the experimental structure were similar for the refinements with physically based energy functions and were smaller than the structure refined with EH. A test refinement was also performed with the reflections truncated at a high-resolution cutoff of 2.5 Å and with random perturbations introduced into the initial coordinates, which showed that low-resolution refinements with physically based energy functions held the structure closer to the experimental structure solved at 1 Å resolution than the EH-based refinements.

Authors: Ning Yu, Xue Li, Guanglei Cui, Seth A. Hayik, and Kenneth M. Merz, Jr.

Reference: Prot. Sci. 2006, 15, 2773-2784. (see link for full paper).
]]>lance@quantumbioinc.comGeometry2006-06-16T11:09:39-04:00http://www.quantumbioinc.com/Support/Publications/index_files/08258f2db9c3b3b55dfc1a1c20a81ca9-12.html#unique-entry-id-12http://www.quantumbioinc.com/Support/Publications/index_files/08258f2db9c3b3b55dfc1a1c20a81ca9-12.html#unique-entry-id-12Abstract: Here we describe the development of a classical force field parameter set to reproduce the geometry of proteins minimized at the semiempirical quantum mechanical level. The overall goal of the development of this new force field is to provide an inexpensive, yet reliable, method to arrive at geometries that are more consistent with a semiempirical treatment of protein structures. Since the minimization of a large number of protein structures at the semiempirical level can become cost-prohibitive, a "preminimization" with an appropriately parametrized classical treatment could potentially lead to more computationally efficient methods for studying protein structures through semiempirical means. Here we demonstrate that this force field allows for more rapid and stable geometry optimizations at the semiempirical level and can aid in the adoption of quantum mechanical calculations for large biological systems.

Authors: Andrew M. Wollacott and Kenneth M. Merz, Jr.

Reference: J. Chem. Theory Comput. 2006, 2(4), 1070-1077. (see link for full paper).
]]>lance@quantumbioinc.comXray2006-06-07T11:24:50-04:00http://www.quantumbioinc.com/Support/Publications/index_files/cef00268560fdfecc75499362fd37988-15.html#unique-entry-id-15http://www.quantumbioinc.com/Support/Publications/index_files/cef00268560fdfecc75499362fd37988-15.html#unique-entry-id-15Abstract: β-Secretase, aka β-APP cleaving enzyme (BACE), is an aspartyl protease that has been implicated as a key target in the pathogenesis of Alzheimer's disease (AD). The identification of the protonation states of the key aspartates in -secretase is of great interest both in understanding the reaction mechanism and in guiding the design of drugs against AD. However, the resolutions of currently available crystal structures for BACE are not sufficient to determine the hydrogen atom locations. We have assigned the protonation states of the key aspartates using a novel method, QM/MM X-ray refinement. In our approach, an energy function is introduced to the refinement where the atoms in the active site are modeled by quantum mechanics (QM) and the other atoms are represented by molecular mechanics (MM). The gradients derived from the QM/MM energy function are combined with those from the X-ray target to refine the crystal structure of a complex containing BACE and an inhibitor. A total number of 8 protonation configurations of the aspartyl dyad were considered, and QM/MM X-ray refinements were performed for all of them. The relative stability of the refined structures was scored by constructing the thermodynamic cycle using the energetics calculated by fully quantum mechanical self-consistent reaction field (QM/SCRF) calculations. While all 8 refined structures fit the observed electron density about equally well, we find the monoprotonated configurations to be strongly favored energetically, especially the configuration with the inner oxygen of Asp32 protonated and the hydroxyl of the inhibitor pointing toward Asp228. It was also found that these results depend on the constraints imposed by the X-ray data. We suggest that one of the strengths of this approach is that the resulting structures are a consensus of theoretical and experimental data and remark on the significance of our results in structure based drug design and mechanistic studies.

Authors: Ning Yu, Seth A. Hayik, Bing Wang, Ning Liao, Charles H. Reynolds, and Kenneth M. Merz, Jr.

Reference: J. Chem. Theory Comput. 2006, 2(4), 1057-1069. (see link for full paper).
]]>lance@quantumbioinc.comTheory2006-05-01T12:19:58-04:00http://www.quantumbioinc.com/Support/Publications/index_files/7c10f966aa4cb43c9b03684c5b559904-19.html#unique-entry-id-19http://www.quantumbioinc.com/Support/Publications/index_files/7c10f966aa4cb43c9b03684c5b559904-19.html#unique-entry-id-19Abstract: In recent years, a lot of attention has been focused on the electronic properties of DNA. With recent advances in linear scaling quantum mechanics there are now new tools available to enhance our understanding of the electronic properties of DNA among other biomolecules. Using both explicit solvent models and implicit (continuum) solvent models, the electronic characteristics of a dodecamer duplex DNA have been fully studied using both divide and conquer (D&C), semi-empirical quantum mechanics and non-D&C semi-empirical quantum mechanics. According to the AM1 Hamiltonian, 3.5 electrons (0.3 electron/base pair) are transferred from the duplex to the solvent. According to the density of state (DOS) analysis, in vacuo DNA has a band gap of 1 eV showing that in the absence of solvent, the DNA may exhibit similar properties to those of a semiconductor. Upon increasing solvation (2.5–5.5 Å), the band gap ranges from 3 eV to 6 eV. For the implicit solvent model, the band gap continues this widening trend to 7 eV. Therefore, upon solvation and in the absence of dopants, the DNA should begin to loose its conductive properties. Finally, when one considers the energy and localization of the frontier orbitals (HOMO and LUMO), solvent has a stabilizing effect on the DNA system. The energy of the HOMO drops from 15 eV in vacuo to 2 eV for 5.5 Å of water to −8 eV for the implicit solvent model. Similarly, the LUMO drops from 16 eV for in vacuo to 9 eV for 5.5 Å of water to −1 eV for the implicit model. Beyond the importance of the computed results on the materials properties of DNA, the present work also shows that the behavior of intercalators will be affected by the electronic properties of DNA. This could have an impact on our understanding of how DNA based drugs interact with DNA and on the design of new DNA based small molecule drugs.

Authors: Lance M. Westerhoff and Kenneth M. Merz, Jr.

Reference: J. Mol. Graph. Mod. 2006, 24(6), 440-455. (see link for full paper).
]]>lance@quantumbioinc.comPWD2006-02-14T10:28:49-05:00http://www.quantumbioinc.com/Support/Publications/index_files/e57157e5227ebbd60c0f154d90b7c965-3.html#unique-entry-id-3http://www.quantumbioinc.com/Support/Publications/index_files/e57157e5227ebbd60c0f154d90b7c965-3.html#unique-entry-id-3Abstract: A scheme to decompose the intermolecular interaction energy of a series of complexes at the semiempirical (SE) level has been developed and validated. The comparative binding energy analysis (COMBINE) (Ortiz, A. R.; Pisabarro, M. T.; Gago, F.; Wade, R. C. J. Med. Chem. 1995, 38, 2681-2691) and the semiempirical quantum mechanical method pairwise energy decomposition (PWD) (Raha, K.; van der Vaart, A. J.; Riley, K. E.; Peters, M. B.; Westerhoff, L. M. Kim, H.; Merz, K. M., Jr. J. Am. Chem. Soc. 2005, 127, 6583-6594) were coupled together to form SE-COMBINE. This approach calculates the residue pairwise electrostatic interaction energies, and QSAR models were built with the energies as descriptors using partial least squares (PLS). The application of SE-COMBINE was used as an investigation of the intermolecular interactions between 88 benzamidine inhibitors and trypsin and to test the ability of this new method to predict binding free energies. The predictive capability of SECOMBINE is shown to be comparable to those of other QSAR methods, and using graphical intermolecular interaction maps (IMMs) enhances the interpretability of receptor-based QSARs.

Authors: Martin B. Peters and Kenneth M. Merz, Jr.

Reference: J. Chem. Theory Comput. 2006, 2, 383-399. (see link for full paper).
]]>lance@quantumbioinc.comNMR2005-12-01T12:56:42-05:00http://www.quantumbioinc.com/Support/Publications/index_files/423eee3d4b3e360dc8a35a87e835b7db-22.html#unique-entry-id-22http://www.quantumbioinc.com/Support/Publications/index_files/423eee3d4b3e360dc8a35a87e835b7db-22.html#unique-entry-id-22Abstract: A fast approach to calculate nuclear magnetic resonance (NMR) chemical shifts within the quantum mechanical/molecular mechanical (QM/MM) framework has been developed. The QM treatment is based on our recently implemented MNDO/NMR method (Wang et al. J. Chem. Phys. 2004, 120, 11392). The effect of the QM/MM partitioning on chemical shifts has been investigated by test calculations on the water dimer and on the protein crambin. It has been shown that the quantum mechanical treatment of the hydrogen bond and nearby groups with significant magnetic susceptibilities is necessary in order to reproduce the full QM results. The method is also applied to a protein-ligand complex FKBP-GPI, and excellent agreement for proton chemical shifts of the ligand is obtained by including the side-chain atoms of the binding site residues into the QM region. The NMR chemical shift calculations using QM/MM-minimized structures still yield satisfactory results. Our results demonstrate that this QM/MM NMR method is able to treat critical regions of very large macromolecules without compromising accuracy if a relatively large QM region is used.

Authors: Bing Wang and Kenneth M. Merz, Jr.

Reference: J. Chem. Theory Comput. 2005, 2(1), 209-215. (see link for full paper).
]]>lance@quantumbioinc.comQMScore2005-06-21T10:17:40-04:00http://www.quantumbioinc.com/Support/Publications/index_files/2807f61390fd124459a6640b9a237f83-1.html#unique-entry-id-1http://www.quantumbioinc.com/Support/Publications/index_files/2807f61390fd124459a6640b9a237f83-1.html#unique-entry-id-1Abstract: Computational methods to calculate binding affinity in protein-ligand interaction are of immense interest because of obvious practical applications in structure-based drug design. Scoring functions attempt to calculate the variation in binding affinity of ligands-inhibitors bound to protein targets at various levels of theory. In this study we use semiempirical quantum mechanics to design a scoring function that can calculate the electrostatic interactions and solvation free energy expected during complexation. This physically based approach has the ability to capture binding affinity trends in a diverse range of protein-ligand complexes. We also show the predictive power of this scoring function within protein targets and its ability to score ligand poses docked to a protein target. We also demonstrate the ability of this scoring function to discriminate between native and decoy poses and highlight the crucial role played by electrostatic interactions in molecular recognition. Finally we compare the performance of our scoring function with other available scoring functions in the literature.

Authors: Kaushik Raha and Kenneth M. Merz, Jr.

Reference: J. Med. Chem. 2005, 48, 4558-4575. (see link for full paper).
]]>lance@quantumbioinc.comPWD2005-04-15T19:46:04-04:00http://www.quantumbioinc.com/Support/Publications/index_files/9e529bd5ea9c434089ed26a7951f1015-0.html#unique-entry-id-0http://www.quantumbioinc.com/Support/Publications/index_files/9e529bd5ea9c434089ed26a7951f1015-0.html#unique-entry-id-0Abstract: Pairwise decomposition of the interaction energy between molecules is shown to be a powerful tool that can increase our understanding of macromolecular recognition processes. Herein we calculate the pairwise decomposition of the interaction energy between the protein human carbonic anhydrase II (HCAII) and the fluorine-substituted ligand N-(4-sulfamylbenzoyl)benzylamine (SBB) using semiempirical quantum mechanics based methods. We dissect the interaction between the ligand and the protein by dividing the ligand and the protein into subsystems to understand the structure-activity relationships as a result of fluorine substitution. In particular, the off-diagonal elements of the Fock matrix that is composed of the interaction between the ionic core and the valence electrons and the exchange energy between the subsystems or atoms of interest is examined in detail. Our analysis reveals that the fluorine-substituted benzylamine group of SBB does not directly affect the binding energy. Rather, we find that the strength of the interaction between Thr199 of HCAII and the sulfamylbenzoyl group of SBB affects the binding affinity between the protein and the ligand. These observations underline the importance of the sulfonamide group in binding affinity as shown by previous experiments (Maren, T. H.; Wiley: C. E. J. Med. Chem. 1968, 11, 228-232). Moreover, our calculations qualitatively agree with the structural aspects of these proteinligand complexes as determined by X-ray crystallography.

Authors: Kaushik Raha, Arjan J. van der Vaart, Kevin E. Riley, Martin B. Peters, Lance M. Westerhoff, Hwanho Kim, and Kenneth M. Merz, Jr.

Reference: J. Am. Chem. Soc. 2005, 127, 6583-6594. (see link for full paper).
]]>lance@quantumbioinc.comXray2005-03-01T10:42:16-05:00http://www.quantumbioinc.com/Support/Publications/index_files/25eb2e3d192dd24d606d3289ef36e6b8-5.html#unique-entry-id-5http://www.quantumbioinc.com/Support/Publications/index_files/25eb2e3d192dd24d606d3289ef36e6b8-5.html#unique-entry-id-5Abstract: A novel method is proposed in which combined energy restraints derived from linear-scaling semiempirical quantum mechanical (QM) calculations and X-ray diffraction data are combined to refine crystal structures of proteins. Its performance has been tested on a small protein molecule, bovine pancreatic trypsin inhibitor (BPTI). The refinement involves minimization of the sum of a geometric energy function and an X-ray target function based on either the least-square residual or the maximum-likelihood formalism. For comparison, similar refinement runs have also been performed using energy restraints derived from the force field available in the Crystallography & NMR System (CNS) program. The QM refinements were carried out with weights that were varied by several orders of magnitude and the optimal weights were identified by observing the trend in the final free R values, QM heats of formation and coordinate root-mean-square deviations (r.m.s.d.s) from the crystal structure. It is found that the QM weights are typically smaller but generally on the same scale as the molecular-mechanics (MM) weights for the respective X-ray target functions. The crystallographic R, free R, real-space R values and correlation coefficients based on the structures refined with the energy restraints derived from our QM calculations and Engh and Huber parameters are comparable, suggesting that the QM restraints are capable of maintaining reasonable stereochemistry to a similar degree as the force-field parameters. A detailed inspection of the structures refined with the QM and MM energy restraints reveals that one of the common differences between them and the crystal structure is that the strained bond angles in the crystal structure are corrected after energetically restrained refinements. Systematic differences in certain bond lengths between the QM-refined structures and the statistical averages of experimental structures have also been observed and discussed.

Authors: Ning Yu, Hemant P. Yennawar, and Kenneth M. Merz, Jr.

Reference: Acta Cryst. D. 2005, 61(3), 322-332. (see link for full paper).
]]>lance@quantumbioinc.comXray2004-12-10T10:34:39-05:00http://www.quantumbioinc.com/Support/Publications/index_files/1a4f387b5140493d0a0641ae202c96af-4.html#unique-entry-id-4http://www.quantumbioinc.com/Support/Publications/index_files/1a4f387b5140493d0a0641ae202c96af-4.html#unique-entry-id-4Abstract: The electron density distributions of a small dipeptide molecule, glycyl-L-threonine dihydrate whose structure has recently been determined using accurate single-crystal X-ray diffraction to a resolution of 0.43A ˚ , have been studied theoretically at the semiempirical level and Hartree–Fock level employing varying sizes of basis sets up to the valence triple-zeta plus polarization level. Both theoretical structure factors and dynamic deformation maps are computed using the electronic wavefunctions derived in vacuo using MO methods. General agreement between theory and experiment is good and improves when larger basis sets are employed. The dynamic theoretical structure factors calculated at the HF/6-311G** level for all the experimentally observed reflection angles fit the experimental ones better with about a 0.01 decrease in the Rw value compared to the Independent Atom Model (IAM). The semiempirical MNDO density performs consistently better than the minimal basis Hartree–Fock density, but is shown to be slightly inferior to the Hartree–Fock density employing split-valence basis sets. The partial atomic charges are also computed and compared to experimental charges derived from the kappa refinement procedure.

Authors: Ning Yu and Kenneth M. Merz, Jr.

Reference: Mol. Phys. 2004, 102, 2545-2557. (see link for full paper).
]]>lance@quantumbioinc.comQSAR2004-11-03T10:46:58-05:00http://www.quantumbioinc.com/Support/Publications/index_files/397678090f68a60f2811438cf9f9fe6b-6.html#unique-entry-id-6http://www.quantumbioinc.com/Support/Publications/index_files/397678090f68a60f2811438cf9f9fe6b-6.html#unique-entry-id-6Abstract: A semiempirical quantum mechanical approach is described for the creation of molecular field-based QSAR models from a set of aligned ligand structures. Each ligand is characterized by a set of probe interaction energy (PIE) values computed at various grid points located near the surface of the ligand. Single-point PM3 calculations afford these PIE values, which represents a pool of independent variables from which multilinear regression models of activity are built. The best n-variable fit is determined by constructing an initial regression using standard forward stepwise selection, followed by refinement using a simulated annealing technique. The resulting fit provides an easily interpreted 3D physical model of ligand binding affinity. Validation against three literature datasets demonstrates the ability of the semiempirical potential to model critical binding interactions in diverse systems.

Authors: Steve Dixon, Kenneth M. Merz, Jr., Giorgio Lauri, and James C. Ianni

Reference: J. Comp. Chem. 2004, 26(1), 23-34. (see link for full paper).
]]>lance@quantumbioinc.comThird Party2004-09-15T12:47:57-04:00http://www.quantumbioinc.com/Support/Publications/index_files/29f1930034c899345767feb11b627eab-20.html#unique-entry-id-20http://www.quantumbioinc.com/Support/Publications/index_files/29f1930034c899345767feb11b627eab-20.html#unique-entry-id-20Abstract: β-Secretase (BACE) is a critical enzyme in the production of β-amyloid, a protein that has been implicated as a potential cause of Alzheimer's disease (AD). There are two aspartic acid residues (Asp 32 and Asp 228) present in the catalytic region of BACE that can adopt multiple protonation states. The protonation state and precise location of the protons for these two residues, particularly in the presence of an inhibitor, are subjects of great interest since they have a direct bearing on the mechanism of aspartyl proteases and efforts to model β-secretase. We have carried out full liner-scaling quantum mechanical (QM) calculations that include Poisson-Boltzmann solvation in order to identify the preferred protonation state and proton location in the presence and absence of an inhibitor. These calculations favor the monoprotonated state in the presence of ligand, and di-deprotonated state in the absence of ligand. Further the proton in the monoprotonated state is located on the inner oxygen of Asp 228. These results have implications for the catalytic mechanism of BACE and related aspartyl proteases. They also provide a reference state for the protein in structure-based modeling studies of this therapeutically important target.

Authors: Ramkumar Rajamani and Charles H. Reynolds

Reference: J. Med. Chem. 2004, 47(21), 5159-5166. (see link for full paper).
]]>lance@quantumbioinc.comNMR2004-08-25T10:50:48-04:00http://www.quantumbioinc.com/Support/Publications/index_files/3c39374d9a00e54d4f8c827f1444fc53-7.html#unique-entry-id-7http://www.quantumbioinc.com/Support/Publications/index_files/3c39374d9a00e54d4f8c827f1444fc53-7.html#unique-entry-id-7Abstract: Recently, we have developed a fast approach to calculate NMR chemical shifts using the divide and conquer method at the semiempirical level. To demonstrate the utility of this approach for characterizing protein-ligand interactions, we used the deviation of calculated chemical shift perturbations from experiment to determine the orientation of a ligand (GPI-1046) in the binding pocket of the FK506 binding protein (FKBP12). Moreover, we were able to select the native state of the ligand from a collection of decoy poses. A key hydrogen bond between O1 and HN in Ile56 was also identified. Our results suggest that ligand-induced chemical shift perturbations can be used to refine protein/ligand structures.

Authors: Bing Wang, Kaushik Raha, and Kenneth M. Merz, Jr.

Reference: J. Am. Chem. Soc. 2004, 126(37), 11430-11431. (see link for full paper).
]]>lance@quantumbioinc.comTheory2004-08-11T11:35:52-04:00http://www.quantumbioinc.com/Support/Publications/index_files/06266c0ea07fae37b2c2911aa609a953-18.html#unique-entry-id-18http://www.quantumbioinc.com/Support/Publications/index_files/06266c0ea07fae37b2c2911aa609a953-18.html#unique-entry-id-18Abstract: Recent studies have shown that semiempirical methods (e.g., PM3 and AM1) for zinc-containing compounds are unreliable for modeling structures containing zinc ions with ligand environments similar to those observed in zinc metalloenzymes. To correct these deficiencies a reparameterization of zinc at the PM3 level was undertaken. In this effort we included frequency corrected B3LYP/6-311G* zinc metalloenzyme ligand environments along with previously utilized experimental data. Average errors for the heats of formation have been reduced from 46.9 kcal/mol (PM3) to 14.2 kcal/mol for this new parameter set, termed ZnB for Zinc, Biological. In addition, the new parameter sets predict geometries for the Bacillus fragilis active site model and other zinc metalloenzyme mimics that are qualitatively in agreement with high-level ab initio results, something existing parameter sets failed to do.

Authors: Edward N. Brothers, Dimas Suarez, David W. Deerfield, and Kenneth M. Merz, Jr.

Reference: J. Comp. Chem. 2004, 25(14), 1677-1692. (see link for full paper).
]]>lance@quantumbioinc.comNMR2004-06-22T10:25:11-04:00http://www.quantumbioinc.com/Support/Publications/index_files/34256680a06f7694d9977ecc5885617c-2.html#unique-entry-id-2http://www.quantumbioinc.com/Support/Publications/index_files/34256680a06f7694d9977ecc5885617c-2.html#unique-entry-id-2Abstract: A new approach to calculate nuclear magnetic resonance chemical shifts has been implemented at the semiempirical modified neglect of diatomic overlap level using gauge-including atomic orbitals. The perturbed density matrix with respect to the magnetic field is obtained by the diagonalization of the complex Fock matrix using the divide and conquer (DC) method, instead of by solving the computationally expensive coupled perturbed Hartree–Fock equations. Adopting the Patchkovskii and Thiel parameters [S. Patchkovskii and W. Thiel J. Comput. Chem. 20, 1220 (1999)], we were able to reproduce their results for small organic molecules. The errors introduced by DC method are negligible, as shown by the calculations on a series of polyalaine structures. Test calculations on proteins have demonstrated that our approach makes it possible to calculate chemical shifts routinely on systems with hundreds of atoms with good accuracy.

Authors: Bing Wang, Edward N. Brothers, Arjan van der Vaart, and Kenneth M. Merz, Jr.

Reference: J. Chem. Phys. 2004, 120(24), 11329-11400. (see link for full paper).
]]>lance@quantumbioinc.comQMScore2004-01-09T11:28:59-05:00http://www.quantumbioinc.com/Support/Publications/index_files/74898bad6df39312635de42e57aa03b3-16.html#unique-entry-id-16http://www.quantumbioinc.com/Support/Publications/index_files/74898bad6df39312635de42e57aa03b3-16.html#unique-entry-id-16Abstract: In this communication, we report the development of a novel quantum mechanics-based scoring function to predict free energy of ligand binding in the zinc metalloenzymes carbonic anhydrase (CA) and carboxypeptidase A (CPA). In particular, the AM1 method is used in conjunction with solvation modeling to predict the relative binding affinities of 18 CA and 5 CPA inhibitors. The effect of metal-ligand charge transfer is also discussed and shown to be different in CPA and CA, providing a further challenge to computing metalloenzyme binding affinities.

Authors: Kaushik Raha and Kenneth M. Merz, Jr.

Reference: J. Am. Chem. Soc. 2004, 126(4), 1020-1021. (see link for full paper).
]]>lance@quantumbioinc.comTheory2002-02-13T11:31:56-05:00http://www.quantumbioinc.com/Support/Publications/index_files/1b1f66c152e586c2144bf35621462d75-17.html#unique-entry-id-17http://www.quantumbioinc.com/Support/Publications/index_files/1b1f66c152e586c2144bf35621462d75-17.html#unique-entry-id-17Abstract: Sodium is very important as a counterion in biology. However, when used with the most common semiempirical Hamiltonians, such as AM1 or PM3, sodium is modeled as a point charge that can accept no electron density, called a "sparkle". To better model sodium, we derived two sets of sodium parameters, which treat sodium on the same footing as other atoms parametrized in semiempirical methods. One set is compatible with the AM1 parameter set, while the second is compatible with PM3. These parameters were derived using a modified genetic algorithm with a diverse set of 71 compounds. The average unsigned error for the heats of formation was 10.3 kcal/mol for AM1 and 10.5 kcal/mol for PM3.

Authors: Edward N. Brothers and Kenneth M. Merz, Jr.

Reference: J. Phys. Chem. B. 2002, 106(10), 2779-2785. (see link for full paper).
]]>lance@quantumbioinc.comTheory2000-12-15T11:13:50-05:00http://www.quantumbioinc.com/Support/Publications/index_files/150bcbc9898850474541a6488f53912d-13.html#unique-entry-id-13http://www.quantumbioinc.com/Support/Publications/index_files/150bcbc9898850474541a6488f53912d-13.html#unique-entry-id-13Abstract: We present a detailed analysis of the performance of the semiempirical divide and conquer method as compared with standard semiempirical MO calculations. The influence of different subsetting schemes involving dual buffer regions on the magnitude of the errors in energies and computational cost of the calculations are discussed. In addition, the results of geometry optimizations on several protein systems (453 to 4088 atoms) driven by a quasi-Newton algorithm are also presented. These results indicate that the divide and conquer approach gives reliable energies and gradients and suggest that protein geometry optimization using semiempirical methods can be routinely feasible using current computational resources.

Authors: Arjan van der Vaart, Dimas Suárez, and Kenneth M. Merz, Jr.

Reference: J. Chem. Phys. 2000, 113(23), 10512-10523. (see link for full paper).
]]>lance@quantumbioinc.comTheory2000-11-14T11:02:36-05:00http://www.quantumbioinc.com/Support/Publications/index_files/a8f50a729c6120a04192cefc5f28a30e-10.html#unique-entry-id-10http://www.quantumbioinc.com/Support/Publications/index_files/a8f50a729c6120a04192cefc5f28a30e-10.html#unique-entry-id-10Abstract: A linear-scaling revolution is occurring in quantum chemistry. This development is allowing for the first time the routine examination of large molecular assembles (e.g., proteins and DNA in water) using electronic structure methods. One of these approaches is the divide and conquer method and, in this article, we review the implementation of this approach for semiempirical Hamiltonians. This is then followed by brief reviews of three application areas. First, we will discuss the charge distribution of biological molecules in solution as described by quantum mechanics. In particular, the role polarization and charge transfer plays in affecting the charge distribution of proteins will be discussed. Next, we will examine the energetic consequences of charge transfer and polarization on biomolecular solvation. The final section will describe the computation of solvation free energies using a combined divide and conquer/Poisson-Boltzmann approach. The application of linear scaling quantum mechanical methods to biology is only just beginning, but the future is very bright, and it is our opinion that quantum mechanics will have a profound influence on our understanding of biological systems in the coming years.

Authors: Arjan van der Vaart, Valentin Gogonea, Steven L. Dixon, and Kenneth M. Merz, Jr.

Reference: J. Comp. Chem. 2000, 21(16), 1494-1504. (see link for full paper).
]]>lance@quantumbioinc.comTheory1999-06-15T11:05:59-04:00http://www.quantumbioinc.com/Support/Publications/index_files/4cd7dba3e98b125b0e2d21b521fe1475-11.html#unique-entry-id-11http://www.quantumbioinc.com/Support/Publications/index_files/4cd7dba3e98b125b0e2d21b521fe1475-11.html#unique-entry-id-11Abstract: In this paper we report a method for solving the Schrödinger equation for large molecules in solution which involved merging a linear scaling divide and conquer (D&C) semiempirical algorithm with the Poisson-Boltzmann (PB) equation. We then assess the performance of our self-consistent reaction field (SCRF) approach by comparing our D&C-PB calculations for a set of 29 neutral and 36 charged molecules with those obtained by ab initio GVB and DFT (B3LYP) methods, Cramer and Truhlar's semiempirical generalized-Born SM5 model, and with the experimental solvation free energies. Furthermore, we show that our SCRF method can be used to perform fully quantum mechanical calculations of proteins in solution in a reasonable amount of time on a modern workstation. We believe that all electrostatic interactions in biological systems require a quantum mechanical description in order to obtain an accurate representation. Thus, our new SCRF method should have an impact on the computational study of physical and chemical phenomena occurring in proteins and nucleic acids, which are, in general, strongly influenced by electrostatic interactions. Moreover, this may lead to novel insights into classic problems like protein folding or drug design.

Authors: Valentin Gogonea and Kenneth M. Merz, Jr.

Reference: J. Phys. Chem. A. 1999, 103(26), 5171-5188. (see link for full paper).
]]>lance@quantumbioinc.comTheory1997-07-15T10:55:02-04:00http://www.quantumbioinc.com/Support/Publications/index_files/3e342f5da691d397257bbfbdf45de8c5-8.html#unique-entry-id-8http://www.quantumbioinc.com/Support/Publications/index_files/3e342f5da691d397257bbfbdf45de8c5-8.html#unique-entry-id-8Abstract: A detailed review of the semiempirical divide-and-conquer (D&C) method is given, including a new approach to subsetting, which involves dual buffer regions. Comparisons are drawn between this method and other semiempirical macromolecular schemes. D&C calculations are carried out using a basic 32 Mbyte memory workstation on a variety of peptide systems, including proteins containing up to 1960 atoms. Aspects of storage and SCF convergence are addressed, and parallelization of the D&C algorithm is discussed.

Authors: Steven L. Dixon and Kenneth M. Merz, Jr.

Reference: J. Chem. Phys. 1997, 107(3), 879-893. (see link for full paper).
]]>lance@quantumbioinc.comTheory1996-05-01T10:57:22-04:00http://www.quantumbioinc.com/Support/Publications/index_files/e3d50e807ec5bfb4d5e10ff3ced3b89f-9.html#unique-entry-id-9http://www.quantumbioinc.com/Support/Publications/index_files/e3d50e807ec5bfb4d5e10ff3ced3b89f-9.html#unique-entry-id-9Abstract: Details are provided for the implementation of a density matrix divide-and-conquer approximation into the framework of molecular orbital theory on nonperiodic systems. Originally developed for density functional theory, the divide-and-conquer procedure is one of the most promising in a growing list of techniques that exhibit linear scaling with respect to the number of basis functions in the system. The key to linear scaling is the division of the electronic structure calculation into a series of calculations over a set of small, overlapping subsystems. A semiempirical molecular orbital program designed around the divide-and-conquer approach has been written and a number of tests are carried out on polyglycine structures in order to evaluate its performance. For the systems examined, linear scaling is indeed observed, and the accuracy of the calculations can be controlled quite readily by the manner in which the system is divided into its component subsystems. For very large structures, the expense associated with the computation of two-center interactions will ultimately dominate the calculation, and quadratic scaling will become apparent. Techniques to linearize this aspect of the calculation are investigated and discussed.

Authors: Steven L. Dixon and Kenneth M. Merz, Jr.

Reference: J. Chem. Phys. 1996, 104(17), 6643-6649. (see link for full paper).
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