Correlation Analyses on Binding Affinity of Sialic Acid Analogues with Influenza Virus Neuraminidase-1 Using ab Initio MO Calculations on Their Complex Structures

Hitaoka, Seiji; Harada, Masataka; Yoshida, Tatsusada; Chuman, Hiroshi

doi:10.1021/ci100225b

Cited by 45 publications

(47 citation statements)

References 90 publications

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“…Also, a good single point calculation is more likely to be a good representation of the system than one from which the phase space is poorly sampled. Other studies have used MM/MD simulations ascertain an optimal system conformation before further analysis using FMO [79]. For the 14 X-ray structures examined the average local strain energy (the potential energy of the X-ray structure minus the value of the energy at a near local minimum) was 6 kcal/mol, which is an acceptably reasonable energy [80].…”

Section: Resultsmentioning

confidence: 99%

Prediction of cyclin-dependent kinase 2 inhibitor potency using the fragment molecular orbital method

et al. 2011

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BackgroundThe reliable and robust estimation of ligand binding affinity continues to be a challenge in drug design. Many current methods rely on molecular mechanics (MM) calculations which do not fully explain complex molecular interactions. Full quantum mechanical (QM) computation of the electronic state of protein-ligand complexes has recently become possible by the latest advances in the development of linear-scaling QM methods such as the ab initio fragment molecular orbital (FMO) method. This approximate molecular orbital method is sufficiently fast that it can be incorporated into the development cycle during structure-based drug design for the reliable estimation of ligand binding affinity. Additionally, the FMO method can be combined with approximations for entropy and solvation to make it applicable for binding affinity prediction for a broad range of target and chemotypes.ResultsWe applied this method to examine the binding affinity for a series of published cyclin-dependent kinase 2 (CDK2) inhibitors. We calculated the binding affinity for 28 CDK2 inhibitors using the ab initio FMO method based on a number of X-ray crystal structures. The sum of the pair interaction energies (PIE) was calculated and used to explain the gas-phase enthalpic contribution to binding. The correlation of the ligand potencies to the protein-ligand interaction energies gained from FMO was examined and was seen to give a good correlation which outperformed three MM force field based scoring functions used to appoximate the free energy of binding. Although the FMO calculation allows for the enthalpic component of binding interactions to be understood at the quantum level, as it is an in vacuo single point calculation, the entropic component and solvation terms are neglected. For this reason a more accurate and predictive estimate for binding free energy was desired. Therefore, additional terms used to describe the protein-ligand interactions were then calculated to improve the correlation of the FMO derived values to experimental free energies of binding. These terms were used to account for the polar and non-polar solvation of the molecule estimated by the Poisson-Boltzmann equation and the solvent accessible surface area (SASA), respectively, as well as a correction term for ligand entropy. A quantitative structure-activity relationship (QSAR) model obtained by Partial Least Squares projection to latent structures (PLS) analysis of the ligand potencies and the calculated terms showed a strong correlation (r2 = 0.939, q2 = 0.896) for the 14 molecule test set which had a Pearson rank order correlation of 0.97. A training set of a further 14 molecules was well predicted (r2 = 0.842), and could be used to obtain meaningful estimations of the binding free energy.ConclusionsOur results show that binding energies calculated with the FMO method correlate well with published data. Analysis of the terms used to derive the FMO energies adds greater understanding to the binding interactions than can be gained by MM methods. Combining this...

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Section: Resultsmentioning

confidence: 99%

Prediction of cyclin-dependent kinase 2 inhibitor potency using the fragment molecular orbital method

et al. 2011

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“…Yoshida et al 556 applied FMO/RHF/6-31G to QSAR studies of the binding affinity of substituted benzenesulfonamides with carbonic anhydrase, noting the difficulties in modeling Zn 2+ -containing systems. Hitaoka et al 557 used FMO/ MP2/6-31G in QSAR studies of the binding affinity of sialic acid analogues with influenza virus neuraminidase-1, where they divided the protein into three binding pockets and used the sums of PIEs for these subsystems as separate descriptors.…”

Section: δEmentioning

confidence: 99%

Fragmentation Methods: A Route to Accurate Calculations on Large Systems

et al. 2011

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Theoretical chemists have always strived to perform quantum mechanics (QM) calculations on larger and larger molecules and molecular systems, as well as condensed phase species, that are frequently much larger than the current state-of-the-art would suggest is possible. The desire to study species (with acceptable accuracy) that are larger than appears to be feasible has naturally led to the development of novel methods, including semiempirical approaches, reduced scaling methods, and fragmentation methods. The focus of the present review is on fragmentation methods, in which a large molecule or molecular system is made more computationally tractable by explicitly considering only one part (fragment) of the whole in any particular calculation. If one can divide a species of interest into fragments, employ some level of ab initio QM to calculate the wave function, energy, and properties of each fragment, and then combine the results from the fragment calculations to predict the same properties for the whole, the possibility exists that the accuracy of the outcome can approach that which would be obtained from a full (nonfragmented) calculation. It is this goal that drives the development of fragmentation methods. Disciplines Chemistry CommentsReprinted (adapted) with permission from Chemical Reviews 112 (2012): 632,

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“…Consequently, E disp governs ΔG obs in complex formation of N1-NA with Set I compounds. 17) Conversely, Fig. 7(b) for hNEU2-Set II compounds shows that the contribution of E disp is considerably smaller than that of the electrostatic energy contribution in Eq.…”

Section: Rism 27mentioning

confidence: 86%

“…We previously proposed a novel QSAR procedure called linear expression by representative energy terms (LERE)-QSAR [17][18][19][20][21] involving molecular calculations such as an ab initio fragment molecular orbital (FMO) one.…”

Section: Formulation Of the Lere-qsar Equationmentioning

confidence: 99%

“…This instructive case study demonstrates that LERE-QSAR has a considerable advantage over the traditional QSAR, although there is no logical conflict between the two. 17,19) Neuraminidases (NAs) are ubiquitous exoglycohydrolases that hydrolyze the terminal sialic acids of glycoproteins and glycolipids and are widely distributed in nature, from viruses, microorganisms, and fungi to higher animals and humans. 42) Among them, influenza virus NAs have been studied extensively as a target for influenza disease, and anti-influenza drugs have been developed.…”

Section: Case Studies Of Lere-qsar Applicationsmentioning

confidence: 99%

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Revisiting the Hansch–Fujita approach and development of a fundamental QSAR

Hitaoka

Chuman

2013

J. Pestic. Sci.

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This review paper is based on the lecture presented in Kyoto on August 25th, 2012, by one of the authors (HC) in the Memorial Symposium for the 50th Anniversary of the Hansch-Fujita Approach; however, several parts have been added. The current paper contains (I) a formulation of an extended one of the well-known Hansch-Fujita QSAR analysis, but a new promising one (called linear expression by representative energy terms (LERE)-QSAR), which can consider ligand-protein interactions explicitly by using modern molecular calculations on a whole ligand-protein complex, and (II) applications of the LERE-QSAR analysis to several cases.

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Correlation Analyses on Binding Affinity of Sialic Acid Analogues with Influenza Virus Neuraminidase-1 Using ab Initio MO Calculations on Their Complex Structures

Cited by 45 publications

References 90 publications

Prediction of cyclin-dependent kinase 2 inhibitor potency using the fragment molecular orbital method

Prediction of cyclin-dependent kinase 2 inhibitor potency using the fragment molecular orbital method

Fragmentation Methods: A Route to Accurate Calculations on Large Systems

Revisiting the Hansch–Fujita approach and development of a fundamental QSAR

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