Abstract
The study of molecular behavior at high levels of theoretical accuracy has entered into a new age in computational drug discovery where quantum mechanical (QM) methods are becoming increasingly popular. Theoretically rigorous calculations can be prohibitively computationally expensive and time consuming. These two factors have necessitated the development of faster methods, and the fragment molecular orbital method (FMO) is one such method that has been used for efficient and accurate QM calculations in drug design. In this chapter, the use of FMO is described in detail for predicting geometry, estimating the binding energy of the ligands, conformational sampling, analysis of molecular interactions, deriving partial charges, and generating quantitative structure-activity relationship (QSAR) models.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Amari S, Aizawa M, Zhang J, Fukuzawa K, Mochizuki Y, Iwasawa Y, Nakata K, Chuman H, Nakano T (2006) VISCANA: visualized cluster analysis of protein-ligand interaction based on the ab initio fragment molecular orbital method for virtual ligand screening. J Chem Inf Model 46(1):221–230
Raha K, Merz KM (2004) A quantum mechanics-based scoring function: study of zinc ion-mediated ligand binding. J Am Chem Soc 126(4):1020–1021
Raha K, Merz KM (2005) Large-scale validation of a quantum mechanics based scoring function: predicting the binding affinity and the binding mode of a diverse set of protein-ligand complexes. J Med Chem 48(14):4558–4575
Mazanetz MP, Ichihara O, Law RJ, Whittaker M (2011) Prediction of cyclin-dependent kinase 2 inhibitor potency using the fragment molecular orbital method. J Cheminform 3(1):2
He X, Fusti-Molnar L, Cui G, Merz KM (2009) Importance of dispersion and electron correlation in ab initio protein folding. J Phys Chem B 113(15):5290–5300
Faver JC, Zheng Z, Merz KM (2011) Model for the fast estimation of basis set superposition error in biomolecular systems. J Chem Phys 135:144110
Fischer B, Fukuzawa K, Wenzel W (2008) Receptor-specific scoring functions derived from quantum chemical models improve affinity estimates for in-silico drug discovery. Proteins 70(4):1264–1273
Yoshida T, Fujita T, Chuman H (2009) Novel quantitative structure-activity studies of HIV-1 protease inhibitors of the cyclic urea type using descriptors derived from molecular dynamics and molecular orbital calculations. Curr Comput Aided Drug Des 5(1):38–55
Hitaoka S, Matoba H, Harada M, Yoshida T, Tsuji D, Hirokawa T, Itoh K, Chuman H (2011) Correlation analyses on binding affinity of sialic acid analogues and antiinfluenza drugs with human neuraminidase using ab Initio MO calculations on their complex structures-LERE-QSAR analysis (IV). J Chem Inf Model 51:2706–2716
Brunger AT, Adams PD (2002) Molecular dynamics applied to X-ray structure refinement. Acc Chem Res 35(6):404–412
Brooks BR, Brooks C, Mackerell A, Nilsson L, Petrella R, Roux B, Won Y, Archontis G, Bartels C, Boresch S, Caflisch A, Caves L, Cui Q, Dinner AR, Feig M, Fischer S, Gao J, Hodoscek M, Im W, Kuczera K, Lazaridis T, Ma J, Ovchinnikov V, Paci E, Pastor RW, Post CB, Pu JZ, Schaefer M, Tidor B, Venable RM, Woodcock HL, Wu X, Yang W, York DM, Karplus M (2009) CHARMM: the biomolecular simulation program. J Comput Chem 30(10):1545–1614
Vanommeslaeghe K, Hatcher E, Acharya C, Kundu S, Zhong S, Shim J, Darian E, Guvench O, Lopes P, Vorobyov I, Mackerell ADJ (2010) CHARMM general force field: a force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields. J Comput Chem 31(4):671–690
Pearlman DA, Case DA, Caldwell JW, Ross WS, Cheatham TE, DeBolt S, Ferguson D, Seibel G, Kollman P (1995) AMBER, a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to simulate the structural and energetic properties of molecules. Comput Phys Commun 91(1):1–41
Engh RA, Huber R (1991) Accurate bond and angle parameters for X-ray protein structure refinement. Acta Crystallogr A 47(4):392–400
Ryde U (2007) Accurate metal-site structures in proteins obtained by combining experimental data and quantum chemistry. Dalton Trans 6:607–625
Cramer CJ (2004) Essentials of computational chemistry: theories and models, 2nd edn. John Wiley & Sons Inc, Chichester
Stone JE, Phillips JC, Freddolino PL, Hardy DJ, Trabuco LG, Schulten K (2007) Accelerating molecular modeling applications with graphics processors. J Comput Chem 28(16):2618–2640
Götz AW, Williamson MJ, Xu D, Poole D, Le Grand S, Walker RC (2012) Routine microsecond molecular dynamics simulations with AMBER on GPUs. 1. Generalized born. J Chem Theory Comput 8(5):1542–1555
Salomon-Ferrer R, Götz AW, Poole D, Le Grand S, Walker RC (2013) Routine microsecond molecular dynamics simulations with AMBER on GPUs. 2. Explicit solvent particle mesh Ewald. J Chem Theory Comput 9(9):3878–3888
Luehr N, Ufimtsev IS, Martínez TJ (2011) Dynamic precision for electron repulsion integral evaluation on graphical processing units (GPUs). J Chem Theory Comput 7(4):949–954
Asadchev A, Gordon MS (2012) New multithreaded hybrid CPU/GPU approach to Hartree–Fock. J Chem Theory Comput 8(11):4166–4176
Stone JE, Hardy DJ, Ufimtsev IS, Schulten K (2010) GPU-accelerated molecular modeling coming of age. J Mol Graph Model 29(2):116–125
Kozakov D, Brenke R, Comeau SR, Vajda S (2006) PIPER: an FFT-based protein docking program with pairwise potentials. Proteins 65(2):392–406
Kantardjiev AA (2012) Quantum. Ligand. Dock: protein–ligand docking with quantum entanglement refinement on a GPU system. Nucleic Acids Res 40(W1):W415–W422
Korb O, Stützle T, Exner TE (2011) Accelerating molecular docking calculations using graphics processing units. J Chem Inf Model 51(4):865–876
Zhang X, Wong SE, Lightstone FC (2013) Message passing interface and multithreading hybrid for parallel molecular docking of large databases on petascale high performance computing machines. J Comput Chem 34(11):915–927
Hagiwara Y, Ohno K, Orita M, Koga R, Endo T, Akiyama Y, Sekijima M (2013) Accelerating quantum chemistry calculations with graphical processing units-toward in high-density (HD) silico drug discovery. Curr Comput Aided Drug Des 9(3):396–401
Ilatovskiy AV, Abagyan R, Kufareva I (2013) Quantum mechanics approaches to drug research in the era of structural chemogenomics. Int J Quantum Chem 113(12):1669–1675
Scuseria GE (1999) Linear scaling density functional calculations with Gaussian orbitals. J Phys Chem A 103(25):4782–4790
Zalesny R, Papadopoulos MG, Mezey PG, Leszczynski J (eds) (2011) Linear-scaling techniques in computational chemistry and physics: methods and applications, vol 13. Springer Science & Business Media, Berlin
Reimers JR (ed) (2011) Computational methods for large systems: electronic structure approaches for biotechnology and nanotechnology. John Wiley & Sons, New York, NY
Otto P, Ladik J (1975) Investigation of the interaction between molecules at medium distances: I. SCF LCAO MO supermolecule, perturbational and mutually consistent calculations for two interacting HF and CH2O molecules. J Chem Phys 8(1):192–200
Gao J (1997) Toward a molecular orbital derived empirical potential for liquid simulations. J Phys Chem B 101(4):657–663
Gordon MS, Pruitt SR, Fedorov DG, Slipchenko LV (2012) Fragmentation methods: a route to accurate calculations on large systems. Chem Rev 112(1):632–672
Pruitt SR, Bertoni C, Brorsen KR, Gordon MS (2014) Efficient and accurate fragmentation methods. Acc Chem Res 47(9):2786–2794
Wang B, Yang KR, Xu X, Isegawa M, Leverentz HR, Truhlar DG (2014) Quantum mechanical fragment methods based on partitioning atoms or partitioning coordinates. Acc Chem Res 47(9):2731–2738
He X, Zhu T, Wang X, Liu J, Zhang JZ (2014) Fragment quantum mechanical calculation of proteins and its applications. Acc Chem Res 47(9):2748–2757
Raghavachari K, Saha A (2015) Accurate composite and fragment-based quantum chemical models for large molecules. Chem Rev 115(12):5643–5677
Collins MA, Bettens RP (2015) Energy-based molecular fragmentation methods. Chem Rev 115(12):5607–5642
Akimov AV, Prezhdo OV (2015) Large-scale computations in chemistry: a bird’s eye view of a vibrant field. Chem Rev 115(12):5797–5890
Kitaura K, Ikeo E, Asada T, Nakano T, Uebayasi M (1999) Fragment molecular orbital method: an approximate computational method for large molecules. Chem Phys Lett 313(3-4):701–706
Fedorov DG, Kitaura K (2007) Extending the power of quantum chemistry to large systems with the fragment molecular orbital method. J Phys Chem A 111(30):6904–6914
Fedorov D, Kitaura K (eds) (2009) The fragment molecular orbital method: practical applications to large molecular systems. CRC Press, Boca Raton, FL
Fedorov DG, Nagata T, Kitaura K (2012) Exploring chemistry with the fragment molecular orbital method. Phys Chem Chem Phys 14:7562–7577
Tanaka S, Mochizuki Y, Komeiji Y, Okiyama Y, Fukuzawa K (2014) Electron-correlated fragment-molecular-orbital calculations for biomolecular and nano systems. Phys Chem Chem Phys 16(22):10310–10344
Okiyama Y, Tsukamoto T, Watanabe C, Fukuzawa K, Tanaka S, Mochizuki Y (2013) Modeling of peptide–silica interaction based on four-body corrected fragment molecular orbital (FMO4) calculations. Chem Phys Lett 566:25–31
Kato K, Fukuzawa K, Mochizuki Y (2015) Modeling of hydroxyapatite-peptide interaction based on fragment molecular orbital method. Chem Phys Lett 629:58–64
Taguchi N, Mochizuki Y, Nakano T, Amari S, Fukuzawa K, Ishikawa T, Sakurai M, Tanaka S (2009) Fragment molecular orbital calculations on red fluorescent proteins (DsRed and mFruits). J Phys Chem B 113(4):1153–1161
Fukuzawa K, Watanabe C, Kurisaki I, Taguchi N, Mochizuki Y, Nakano T, Tanaka S, Komeiji Y (2014) Accuracy of the fragment molecular orbital (FMO) calculations for DNA: total energy, molecular orbital, and inter-fragment interaction energy. Comput Theor Chem 1034:7–16
Suenaga M (2008) Development of GUI for GAMESS/FMO calculation. J Comput Chem Jpn 7:33–53
Fedorov DG, Ishida T, Kitaura K (2005) Multilayer formulation of the fragment molecular orbital method (FMO). J Phys Chem A 109(11):2638–2646
Nishimoto Y, Fedorov DG, Irle S (2015) Third-order density-functional tight-binding combined with the fragment molecular orbital method. Chem Phys Lett 636:90–96
Nakano T, Mochizuki Y, Fukuzawa K, Amari S, Tanaka S (2006) Developments and applications of ABINIT-MP software based on the fragment molecular orbital method. In: Starikov EB, Lewis JP, Tanaka S (eds) Modern methods for theoretical physical chemistry of biopolymers. Elsevier, Amsterdam, pp 39–52
Okamoto T, Ishikawa T, Koyano Y, Yamamoto N, Kuwata K, Nagaoka M (2013) A minimal implementation of the AMBER-PAICS interface for ab initio FMO-QM/MM-MD simulation. Bull Chem Soc Jpn 86(2):210–222
Schmidt MW, Baldridge KK, Boatz JA, Elbert ST, Gordon MS, Jensen JH, Koseki S, Matsunaga N, Nguyen KA, Su S, Windus TL, Dupuis M, Montgomery JAJ (1993) General atomic and molecular electronic structure system. J Comput Chem 14(11):1347–1363. doi:10.1002/jcc.540141112
Nakata H, Nagata T, Fedorov DG, Yokojima S, Kitaura K, Nakamura S (2013) Analytic second derivatives of the energy in the fragment molecular orbital method. J Chem Phys 138(16):164103
Alexeev Y, Fedorov DG, Shvartsburg AA (2014) Effective ion mobility calculations for macromolecules by scattering on electron clouds. J Phys Chem A 118(34):6763–6772. doi:10.1021/jp505012c
Alexeev Y, Mazanetz M, Ichihara O, Fedorov DG (2012) GAMESS as a free quantum-mechanical platform for drug research. Curr Top Med Chem 12(18):2013–2033
Mazanetz MP (2013) Quantum mechanical applications in drug discovery. In: In silico drug discovery and design. Future Science Ltd., London, pp 64–79. doi:10.4155/9781909453012
Sawada T, Fedorov DG, Kitaura K (2010) Role of the key mutation in the selective binding of avian and human influenza hemagglutinin to sialosides revealed by quantum-mechanical calculations. J Am Chem Soc 132:16862–16872
Sawada T, Fedorov DG, Kitaura K (2010) Binding of influenza A virus hemagglutinin to the sialoside receptor Is not controlled by the homotropic allosteric effect. J Phys Chem B 114:15700–15705
Komeiji Y, Mori H, Nakano T, Mochizuki Y (2012) Recent advances in fragment molecular orbital-based molecular dynamics (FMO-MD) simulations. In: Wang L (ed) Molecular dynamics - theoretical developments and applications in nanotechnology and energy. Rijeka, Croatia: INTECH, pp 3–24
Sato M, Yamataka H, Komeiji Y, Mochizuki Y, Ishikawa T, Nakano T (2008) How does an SN2 reaction take place in solution? Full ab initio MD simulations for the hydrolysis of the methyl diazonium ion. J Am Chem Soc 130(8):2396–2397
Sato M, Yamataka H, Komeiji Y, Mochizuki Y (2012) FMO-MD simulations on the hydration of formaldehyde in water solution with constraint dynamics. Chemistry 18(31):9714–9721
Nakata H, Fedorov DG, Zahariev F, Schmidt MW, Kitaura K, Gordon MS, Nakamura S (2015) Analytic second derivative of the energy for density functional theory based on the three-body fragment molecular orbital method. J Chem Phys 142(12):124101
Nakata H, Fedorov DG, Nagata T, Kitaura K, Nakamura S (2015) Simulations of chemical reactions with the frozen domain formulation of the fragment molecular orbital method. J Chem Theory Comput 11(7):3053–3064. doi:10.1021/acs.jctc.5b00277
Fedorov DG, Kitaura K, Li H, Jensen JH, Gordon MS (2006) The polarizable continuum model (PCM) interfaced with the fragment molecular orbital method (FMO). J Comput Chem 27(8):976–985
Li H, Fedorov DG, Nagata T, Kitaura K, Jensen JH, Gordon MS (2010) Energy gradients in combined fragment molecular orbital and polarizable continuum model (FMO/PCM) calculation. J Comput Chem 31(4):778–790
Nagata T, Fedorov D, Li H, Kitaura K (2012) Analytic gradient for second order Møller-Plesset perturbation theory with the Polarizable Continuum Model based on the Fragment molecular Orbital method. J Chem Phys 136:204112
Nakata H, Fedorov DG, Kitaura K, Nakamura S (2015) Extension of the fragment molecular orbital method to treat large open-shell systems in solution. Chem Phys Lett 635:86–92
Watanabe H, Okiyama Y, Nakano T, Tanaka S (2010) Incorporation of solvation effects into the fragment molecular orbital calculations with the Poisson–Boltzmann equation. Chem Phys Lett 500(1):116–119
Yoshida N (2014) Efficient implementation of the three-dimensional reference interaction site model method in the fragment molecular orbital method. J Chem Phys 140(21):214118
Nagata T, Fedorov DG, Kitaura K, Gordon MS (2009) A combined effective fragment potential–fragment molecular orbital method. I. The energy expression and initial applications. J Chem Phys 131:024101
Nakanishi I, Fedorov DG, Kitaura K (2007) Molecular recognition mechanism of FK506 binding protein: an all-electron fragment molecular orbital study. Proteins 68(1):145–158
Murata K, Fedorov DG, Nakanishi I, Kitaura K (2009) Cluster hydration model for binding energy calculations of protein–ligand complexes. J Phys Chem B 113(3):809–817
Fedorov DG, Ishida T, Uebayasi M, Kitaura K (2007) The fragment molecular orbital method for geometry optimizations of polypeptides and proteins. J Phys Chem A 111(14):2722–2732
Fedorov DG, Kitaura K (2014) Use of an auxiliary basis set to describe the polarization in the fragment molecular orbital method. Chem Phys Lett 597:99–105
Nagata T, Fedorov DG, Ishimura K, Kitaura K (2011) Analytic energy gradient for second-order Møller-Plesset perturbation theory based on the fragment molecular orbital method. J Chem Phys 135:044110
Nakata H, Fedorov DG, Yokojima S, Kitaura K, Nakamura S (2014) Simulations of Raman spectra using the fragment molecular orbital method. J Chem Theory Comput 10(9):3689–3698
Sawada T, Fedorov DG, Kitaura K (2009) Structural and interaction analysis of helical heparin oligosaccharides with the fragment molecular orbital method. Int J Quantum Chem 109(9):2033–2045
Tsukamoto T, Mochizuki Y, Watanabe N, Fukuzawa K, Nakano T (2012) Partial geometry optimization with FMO-MP2 gradient: application to TrpCage. Chem Phys Lett 535:157–162
Ishikawa T, Yamamoto N, Kuwata K (2010) Partial energy gradient based on the fragment molecular orbital method: application to geometry optimization. Chem Phys Lett 500(1):149–154
Fedorov DG, Alexeev Y, Kitaura K (2011) Geometry optimization of the active site of a large system with the fragment molecular orbital method. J Phys Chem Lett 2(4):282–288. doi:10.1021/jz1016894
Steinmann C, Fedorov DG, Jensen JH (2013) Mapping enzymatic catalysis using the effective fragment molecular orbital method: towards all ab initio biochemistry. PLoS One 8(4):e60602
Christensen AS, Steinmann C, Fedorov DG, Jensen JH (2014) Hybrid RHF/MP2 geometry optimizations with the effective fragment molecular orbital method. PLoS One 9(2):e88800
Mazanetz M, Law R, Whittaker M (2013) Hit and Lead Identification from fragments. In: Schneider G (ed) De novo molecular design. Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, pp 143–200. doi:10.1002/9783527677016.ch6
Ponder JW, Richards FM (1987) An efficient Newton-like method for molecular mechanics energy minimization of large molecules. J Comput Chem 8(7):1016–1024
Maseras F, Morokuma K (1995) IMOMM: a new integrated ab initio molecular mechanics geometry optimization scheme of equilibrium structures and transition states. J Comput Chem 16(9):1170–1179
Shoemaker JR, Burggraf LW, Gordon MS (1999) SIMOMM: an integrated molecular orbital/molecular mechanics optimization scheme for surfaces. J Phys Chem A 103(17):3245–3251
Fedorov DG, Asada N, Nakanishi I, Kitaura K (2014) The use of many-body expansions and geometry optimizations in fragment-based methods. Acc Chem Res 47(9):2846–2856
Nakano T, Kaminuma T, Sato T, Fukuzawa K, Akiyama Y, Uebayasi M, Kitaura K (2002) Fragment molecular orbital method: use of approximate electrostatic potential. Chem Phys Lett 351(5-6):475–480
Ishida T, Fedorov DG, Kitaura K (2006) All electron quantum chemical calculation of the entire enzyme system confirms a collective catalytic device in the chorismate mutase reaction. J Phys Chem B 110(3):1457–1463
Jensen JH, Willemoës M, Winther JR, De Vico L (2014) In silico prediction of mutant HIV-1 proteases cleaving a target sequence. PLoS One 9(5):e95833
Ito M, Brinck T (2014) Novel approach for identifying key residues in enzymatic reactions: proton abstraction in ketosteroid isomerase. J Phys Chem B 118(46):13050–13058
Hediger MR, Steinmann C, De Vico L, Jensen JH (2013) A computational method for the systematic screening of reaction barriers in enzymes: searching for Bacillus circulans xylanase mutants with greater activity towards a synthetic substrate. PeerJ 1:e111
Nishimoto Y, Fedorov DG, Irle S (2014) Density-functional tight-binding combined with the fragment molecular orbital method. J Chem Theory Comput 10(11):4801–4812
Sugiki SI, Kurita N, Sengoku Y, Sekino H (2003) Fragment molecular orbital method with density functional theory and DIIS convergence acceleration. Chem Phys Lett 382(5):611–617
Fedorov DG, Kitaura K (2012) Energy decomposition analysis in solution based on the fragment molecular orbital method. J Phys Chem A 116:704–719
Fedorov DG, Kitaura K (2007) Pair interaction energy decomposition analysis. J Comput Chem 28(1):222–237
Green MC, Fedorov DG, Kitaura K, Francisco JS, Slipchenko LV (2013) Open-shell pair interaction energy decomposition analysis (PIEDA): formulation and application to the hydrogen abstraction in tripeptides. J Chem Phys 138(7):074111
Bandyopadhyay P, Gordon MS, Mennucci B, Tomasi J (2002) An integrated effective fragment - polarizable continuum approach to solvation: theory and application to glycine. J Chem Phys 116:5023
Nagata T, Fedorov DG, Sawada T, Kitaura K (2012) Analysis of solute–solvent interactions in the fragment molecular orbital method interfaced with effective fragment potentials: theory and application to a solvated griffithsin–carbohydrate complex. J Phys Chem A 116(36):9088–9099
Ishikawa T, Ishikura T, Kuwata K (2009) Theoretical study of the prion protein based on the fragment molecular orbital method. J Comput Chem 30(16):2594–2601
Okiyama Y, Fukuzawa K, Yamada H, Mochizuki Y, Nakano T, Tanaka S (2011) Counterpoise-corrected interaction energy analysis based on the fragment molecular orbital scheme. Chem Phys Lett 509(1):67–71
Watanabe C, Fukuzawa K, Okiyama Y, Tsukamoto T, Kato A, Tanaka S, Mochizuki Y, Nakano T (2013) Three-and four-body corrected fragment molecular orbital calculations with a novel subdividing fragmentation method applicable to structure-based drug design. J Mol Graph Model 41:31–42
Asada N, Fedorov DG, Kitaura K, Nakanishi I, Merz KM Jr (2012) An efficient method to evaluate intermolecular interaction energies in large systems using overlapping multicenter ONIOM and the fragment molecular orbital method. J Phys Chem Lett 3(18):2604–2610
Tanaka S, Watanabe C, Okiyama Y (2013) Statistical correction to effective interactions in the fragment molecular orbital method. Chem Phys Lett 556:272–277
Mochizuki Y, Fukuzawa K, Kato A, Tanaka S, Kitaura K, Nakano T (2005) A configuration analysis for fragment interaction. Chem Phys Lett 410(4):247–253
Ishikawa T, Mochizuki Y, Amari S, Nakano T, Tokiwa H, Tanaka S, Tanaka K (2007) Fragment interaction analysis based on local MP2. Theor Chem Acc 118(5-6):937–945
Ishikawa T, Kuwata K (2009) Interaction analysis of the native structure of prion protein with quantum chemical calculations. J Chem Theory Comput 6(2):538–547
Hitaoka S, Harada M, Yoshida T, Chuman H (2010) Correlation analyses on binding affinity of sialic acid analogues with influenza virus Neuraminidase-1 using ab Initio MO calculations on their complex structures. J Chem Inf Model 50(10):1796–1805
Dedachi K, Hirakawa T, Fujita S, Khan MTH, Sylte I, Kurita N (2011) Specific interactions and binding free energies between thermolysin and dipeptides: molecular simulations combined with Ab initio molecular orbital and classical vibrational analysis. J Comput Chem 32(14):3047–3057
Suenaga M (2005) Facio: new computational chemistry environment for PC GAMESS. J Comput Chem Jpn 4(1):25–32
Durant JL, Leland BA, Henry DR, Nourse JG (2002) Reoptimization of MDL keys for use in drug discovery. J Chem Inf Comput Sci 42(6):1273–1280
Kohonen T (2001) Self-organizing maps, vol 30, 3rd edn, Information sciences. Springer, Berlin
Hefner R (1959) Book review: Warren S. Torgerson, Theory and methods of scaling. New York: John Wiley and Sons, Inc. 1958. Syst Res Behav Sci 4(3):245–247
Kurauchi R, Watanabe C, Fukuzawa K, Tanaka S (2015) Novel type of virtual ligand screening on the basis of quantum-chemical calculations for protein–ligand complexes and extended clustering techniques. Comput Theor Chem 1061:12–22
Verkhivker GM, Bouzida D, Gehlhaar DK, Rejto PA, Arthurs S, Colson AB, Freer ST, Larson V, Luty BA, Marrone T (2000) Deciphering common failures in molecular docking of ligand-protein complexes. J Comput Aided Mol Des 14(8):731–751
Neumann L, Von König K, Ullmann D (2011) HTS reporter displacement assay for fragment screening and fragment evolution toward leads with optimized binding kinetics, binding selectivity, and thermodynamic signature. Methods Enzymol 493:299–320
Williams DH, Stephens E, O’Brien DP, Zhou M (2004) Understanding noncovalent interactions: ligand binding energy and catalytic efficiency from ligand-induced reductions in motion within receptors and enzymes. Angew Chem Int Ed 43(48):6596–6616
Barker JJ, Barker O, Courtney SM, Gardiner M, Hesterkamp T, Ichihara O, Mather O, Montalbetti CAGN, Müller A, Varasi M (2010) Discovery of a novel Hsp90 inhibitor by fragment linking. ChemMedChem 5(10):1697–1700
Ferenczy GG, Keseru GM (2012) Thermodynamics of fragment binding. J Chem Inf Model 52(4):1039–1045
Abel R, Young T, Farid R, Berne BJ, Friesner RA (2008) Role of the active-site solvent in the thermodynamics of factor Xa ligand binding. J Am Chem Soc 130(9):2817–2831
Huggins DJ, Sherman W, Tidor B (2012) Rational approaches to improving selectivity in drug design. J Med Chem 55(4):1424–1444
Wyatt PG, Woodhead AJ, Berdini V, Boulstridge JA, Carr MG, Cross DM, Davis DJ, Devine LA, Early TR, Feltell RE (2008) Identification of N-(4-piperidinyl)-4-(2, 6-dichlorobenzoylamino)-1 H-pyrazole-3-carboxamide (AT7519), a novel cyclin dependent kinase inhibitor using fragment-based X-Ray crystallography and structure based drug design. J Med Chem 51(16):4986–4999
Hartshorn MJ, Murray CW, Cleasby A, Frederickson M, Tickle IJ, Jhoti H (2005) Fragment-based lead discovery using X-ray crystallography. J Med Chem 48(2):403–413
Imai YN, Inoue Y, Nakanishi I, Kitaura K (2009) Cl–π Interactions in protein–ligand complexes. QSAR Comb Sci 28(8):869–873
Ozawa T, Okazaki K (2008) CH/π hydrogen bonds determine the selectivity of the Src homology 2 domain to tyrosine phosphotyrosyl peptides: an ab initio fragment molecular orbital study. J Comput Chem 29(16):2656–2666
Anzaki S, Watanabe C, Fukuzawa K, Mochizuki Y, Tanaka S (2014) Interaction energy analysis on specific binding of influenza virus hemagglutinin to avian and human sialosaccharide receptors: importance of mutation-induced structural change. J Mol Graph Model 53:48–58
Yoshioka A, Fukuzawa K, Mochizuki Y, Yamashita K, Nakano T, Okiyama Y, Nobusawa E, Nakajima K, Tanaka S (2011) Prediction of probable mutations in influenza virus hemagglutinin protein based on large-scale ab initio fragment molecular orbital calculations. J Mol Graph Model 30:110–119
Okiyama Y, Watanabe H, Fukuzawa K, Nakano T, Mochizuki Y, Ishikawa T, Tanaka S, Ebina K (2007) Application of the fragment molecular orbital method for determination of atomic charges on polypeptides. Chem Phys Lett 449(4):329–335
Okiyama Y, Watanabe H, Fukuzawa K, Nakano T, Mochizuki Y, Ishikawa T, Ebina K, Tanaka S (2009) Application of the fragment molecular orbital method for determination of atomic charges on polypeptides. II. Towards an improvement of force fields used for classical molecular dynamics simulations. Chem Phys Lett 467(4):417–423
Chang L, Ishikawa T, Kuwata K, Takada S (2013) Protein-specific force field derived from the fragment molecular orbital method can improve protein–ligand binding interactions. J Comput Chem 34(14):1251–1257
Cramer RD, Patterson DE, Bunce JD (1988) Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. J Am Chem Soc 110(18):5959–5967
Klebe G, Abraham U, Mietzner T (1994) Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity. J Med Chem 37(24):4130–4146
Zhang Q, Yang J, Liang K, Feng L, Li S, Wan J, Xu X, Yang G, Liu D, Yang S (2008) Binding interaction analysis of the active site and its inhibitors for neuraminidase (N1 subtype) of human influenza virus by the integration of molecular docking, FMO calculation and 3D-QSAR CoMFA modeling. J Chem Inf Model 48(9):1802–1812
Zhang Q, Yu C, Min J, Wang Y, He J, Yu Z (2011) Rational questing for potential novel inhibitors of FabK from Streptococcus pneumoniae by combining FMO calculation, CoMFA 3D-QSAR modeling and virtual screening. J Mol Model 17(6):1483–1492
Yoshida T, Yamagishi K, Chuman H (2008) QSAR study of cyclic urea type HIV-1 PR inhibitors using ab initio MO calculation of their complex structures with HIV-1 PR. QSAR Comb Sci 27(6):694–703
Yoshida T, Munei Y, Hitaoka S, Chuman H (2010) Correlation analyses on binding affinity of substituted benzenesulfonamides with carbonic anhydrase using ab initio MO calculations on their complex structures. J Chem Inf Model 50(5):850–860
Munei Y, Shimamoto K, Harada M, Yoshida T, Chuman H (2011) Correlation analyses on binding affinity of substituted benzenesulfonamides with carbonic anhydrase using ab initio MO calculations on their complex structures (II). Bioorg Med Chem Lett 21(1):141–144
Mashima A, Kurahashi M, Sasahara K, Yoshida T, Chuman H (2014) Connecting classical QSAR and LERE analyses using modern molecular calculations, LERE-QSAR (VI): hydrolysis of substituted hippuric acid phenyl esters by trypsin. Mol Inform 33(11-12):802–814
Hitaoka S, Chuman H, Yoshizawa K (2015) A QSAR study on the inhibition mechanism of matrix metalloproteinase-12 by arylsulfone analogs based on molecular orbital calculations. Org Biomol Chem 13(3):793–806
Baker NA, Sept D, Joseph S, Holst MJ, McCammon JA (2001) Electrostatics of nanosystems: application to microtubules and the ribosome. Proc Natl Acad Sci U S A 98(18):10037–10041
Li L, Li C, Sarkar S, Zhang J, Witham S, Zhang Z, Wang L, Smith N, Petukh M, Alexov E (2012) DelPhi: a comprehensive suite for DelPhi software and associated resources. BMC Biophys 5(1):9
Watanabe T, Inadomi Y, Fukuzawa K, Nakano T, Tanaka S, Nilsson L, Nagashima U (2007) DNA and estrogen receptor interaction revealed by fragment molecular orbital calculations. J Phys Chem B 111(32):9621–9627
Fedorov DG, Olson RM, Kitaura K, Gordon MS, Koseki S (2004) A new hierarchical parallelization scheme: generalized distributed data interface (GDDI), and an application to the fragment molecular orbital method (FMO). J Comput Chem 25(6):872–880
Alexeev Y, Mahajan A, Leyffer S, Fletcher GD, Fedorov DG Heuristic static load-balancing algorithm applied to the Fragment Molecular Orbital method. In: Proceedings of the ACM/IEEE Supercomputing 2012 Conference, Salt Lake City, 2012. IEEE, pp 1–13
Acknowledgments
Dmitri G. Fedorov has been supported by the Next Generation Super Computing Project, Nanoscience Program (MEXT, Japan) and Computational Materials Science Initiative (CMSI, Japan). This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357.
The submitted manuscript has been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory (“Argonne”). Argonne, a US Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. The US Government retains for itself, and others acting on its behalf, a paid-up nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the government.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Glossary
- AMBER
-
Assisted Model Building with Energy Refinement
- CADD
-
Computer-Aided Drug Design
- CHARMM
-
Chemistry at HARvard Macromolecular Mechanics
- EFP
-
Effective Fragment Potential
- ESP
-
Electrostatic Potential
- FD
-
Frozen Domain
- FDD
-
Frozen Domain and Dimers
- FMO
-
Fragment Molecular Orbital
- GAMESS
-
General Atomic and Molecular Electronic Structure System
- LAMMPS
-
Large-scale Atomic/Molecular Massively Parallel Simulator
- MD
-
Molecular Dynamics
- MM
-
Molecular Mechanics
- PB
-
Poisson–Boltzmann
- PCM
-
Polarizable Continuum Model
- PIE
-
Pair Interaction Energy
- PIEDA
-
PIE Decomposition Analysis
- QM
-
Quantum Mechanical
- QSAR
-
Quantitative SAR
- SAR
-
Structure-Activity Relationship
- SBDD
-
Structure Based Drug Design
Rights and permissions
Copyright information
© 2015 Springer Science+Business Media New York
About this protocol
Cite this protocol
Mazanetz, M.P., Chudyk, E., Fedorov, D.G., Alexeev, Y. (2015). Applications of the Fragment Molecular Orbital Method to Drug Research. In: Zhang, W. (eds) Computer-Aided Drug Discovery. Methods in Pharmacology and Toxicology. Humana Press, New York, NY. https://doi.org/10.1007/7653_2015_59
Download citation
DOI: https://doi.org/10.1007/7653_2015_59
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-3519-2
Online ISBN: 978-1-4939-3521-5
eBook Packages: Springer Protocols