© in This Web Service Cambridge University

Cambridge University Press 978-0-521-88723-6 - Drug Design: Structure- and Ligand-Based Approaches Edited by Kenneth M. Merz, Dagmar Ringe and Charles H. Reynolds Index More information

Index

absolute free energies, 73–76 ligand binding in, 73–74 BACE inhibitors, 187–189 FKBP binding calculations for, 75 T4 lysozyme ligand binding, 74–75 ligand binding affinity and, 184–186 ligand binding in, 73–74 water binding and, 74 solubility in, 191 T4 lysozyme ligand binding, 74–75 negative results from, 76–77 BAR. See Bennett Acceptance Ratio negative results for, 74–75 predictive tests for, 76 BBB penetration. See blood-brain barrier water binding and, 74 relative binding free, 72–73 (BBB) penetration, in ADME absorption/distribution/metabolism/ estrogen receptors and, 73 models excretion (ADME) software, 1, 5–7. for fructose 1, 6 bisphosphatase, 73 Bennett Acceptance Ratio (BAR), 68 See also intestinal absorption, in HIV-1 and, 72, 73 MBAR, 68 ADME models; metabolism, in for neutrophil elastase inhibitors, BIEs. See binding isotope effects ADME models; P-glycoprotein 73 binding affinity calculations, 129–130 effluxes, in ADME models; solvation free, 76 linear scaling and, 130–131 solubility, in ADME models studies on, 77 binding isotope effects (BIEs), 238–239, 240 BBB penetration and, 169–170 with GCMC techniques, 77 Biochemical and Organic Model Builder celecoxib, 6–7 alchemical methods, for SBDD, 66 (BOMB), for lead generation, 1, 2–3 for drug discovery, 165–173 explicit water simulations in, 66 core binding sites, 2 administration routes for, 166 free energy perturbation as, 66 docking, 3–4 clearance in, 172 Lennard-Jones parameters for, 69 protein hosts, 2–3 computational models in, 165 pathways for, 68–69 results, 3 drug-likeness measures in, 165–166 WHAM as, 68 PDB file, 3 formulation problems with, 165 Zwanzig relationship, 66 scoring function, 3 intestinal absorption and, 168–169 allosteric inhibitors, 94 small group scans, 10 metabolism in, 172–173 enzyme binding sites for, 94 substituent library, 2 P-glycoprotein effluxes and, 170–171 monomer cores as target for, 94 blood-brain barrier (BBB) penetration, in plasma protein binding and, 171–172 protease dimer interfaces in, 94 ADME models, 169–170 proteomic families and, 166 AMBER force fields, 126 P-glycoprotein effluxes and, 170–171 solubility in, 166–168 AMP sites, HGLP and, 259–261 BOMB. See Biochemical and Organic Model tissue distribution and, 172 AmpC ␤-lactamase inhibitors, QSAR Builder (BOMB), for lead QIKPROP, 5–7 models for, 161 generation required input, 5 classification of, 161 bound pose prediction, with docking, submission to, 5–6 amprenavir, 87 105–114 rofecoxib, 6 analogs, docking scores and, 99 with JNK3 proteins, 108–113 “rule-of-three,” 6 ␤2-andrenergic receptors, 249 aminopyrimidines, 109–110 violations, 7 ligand-binding sites in, 249–250 compound classes in, 109 achiral immucillins, 242 anticancer agents, QSAR models for, oximes, 110–111 acyclic immucillins, 241–242 161 p38 inhibitors, 110 DATMe, 241–242 anticonvulsive compounds, QSAR models public structures in, 108–109 ADME software. See absorption/ for, 159–161 pyrazole placement in, 111–113 distribution/metabolism/ Maybridge HitFinder library and, 161 with SAMPL challenge, 105 excretion software APEX-3D method, 139 manual vs. automated, 113–114 affinity distribution models, for SBDD, pharmacore scoring by, 144 with SAMPL challenge, 105–107 62–63 applicability domains, in QSAR models, JNK3 structures and, 105 basic equations for, 64 154–155 manual process for, 106 Agenerase. See amprenavir confidence index for, 155 semi-automated process for, 106 AIM theory. See atoms-in-molecules (AIM) definition of, 155 small-molecule conformations in, theory Aptivus. See tipranavir 106–107 ALADDIN method, 139 atazanavir, 87 with urokinase plasminogen activators, alchemical free-energy calculations, for atoms-in-molecules (AIM) theory, 107–108 SBDD, 66, 72–76 133 ligand docking and, 107 absolute free, 73–76 azidothymidine (AZT), 87 public structures in, 107 FKBP binding calculations for, 75 AZT. See azidothymidine RMSD-DPI and, 107

265

© in this web service Cambridge University Press www.cambridge.org Cambridge University Press 978-0-521-88723-6 - Drug Design: Structure- and Ligand-Based Approaches Edited by Kenneth M. Merz, Dagmar Ringe and Charles H. Reynolds Index More information

266 Index

bovine PNP,transition-state structure of, consensus prediction, in QSAR models, NOEs and, 48–49 221–226 156–159 sensitivity of, 48 immucillins and, 226, 227 Critical Assessment of PRedicted dimethyl sulfoxide (DMSO), 166, 167–168 crystal structures of, 227–229 Interactions (CAPRI), 79 DISCO method. See DIStance COmparisons inhibitions of, 227 Critical Assessment of Structure Prediction (DISCO) method KIEs in, 222–223 (CASP), 79 DIStance COmparisons (DISCO) method, inosine arsenolysis interpretation and, Critical Assessment of Techniques for Free 138 223–224, 226, 230, 238 Energy Evaluation (CATFEE), 79 in pharmacore identification, 142 labeled substrate synthesis in, 221–222 Crixivan. See indinavir docking, 98–114.Seealsobound pose V/K KIEs and, 223 crystal packing, 168 prediction, with docking crystal structures, 17 bound pose prediction with, 105–114 CAPRI. See Critical Assessment of diffraction of, 18 with JNK3 proteins, 108–113 PRedicted Interactions electron density map and, 21 manual vs. automated, 113–114 Carbo´ similarity index (CSI), 133 patterns for, 18–20 with SAMPL challenge, 105–107 CASP. See Critical Assessment of Structure docking and, 99 with urokinase plasminogen activators, Prediction in GPCRs, 248–250 107–108 CATALYST method, 138–139 of human PNP, 234 censuses for pharmacore scoring with, 143, 144 of immucillins, 227–229 analysis of, 100–102 CATFEE. See Critical Assessment of in proposed molecular mechanisms of inhibitors in, 104 Techniques for Free Energy resistance, for HIV-1, 92–93 potent hits and, 103–104 Evaluation proteins as, 17 recommendations for, 102 CAVEAT method, 139 cloned, 17 of screens, 99–100 Celebrex. See celecoxib docking and, 99 Wilcoxon-Mann-Whitney celecoxib, 6–7 homologous, 17 nonparametric rank order tests charge transfers, 128 mammalian, 17 and, 101–102 chemical shift perturbations (CSP), truncation for, 17 computer-aided drug design with, 123–124 scattered beams and, 18 183–184 CHEM-X method, 139 CSI. See Carbo´ similarity index free-energy calculations and, 98, 99 pharmacore fingerprinting with, 146 CSP. See chemical shift perturbations future applications for, 114 clearance, in drug discovery, 172 cytochrome analysis, 173 for GPCRs, 251–252 cloned proteins, crystallization of, 17 fast, 251–252 combinatorial libraries, for SBDD, 61 DADMe immucillins, 232–234 manual, 251–252 CoMFA. See comparative molecular field enantiomers of, 234–237 virtual screening for, 251–252 analysis human PNP and, 232, 234 of HGLP, 257–258, 259–261 comparative molecular field analysis pharmacological applications of, lead discovery with, 99–102 (CoMFA), 132 239–241 methods for SBDD, 61 disadvantages in, 133 synthesis of, 232–233 in pharmacore methods, 140 comparative molecular similarity indices in vivo studies of, 241 receptor-based, 144 analysis (CoMSIA), 132 DANTE method, 139 protein configuration integrals and, competitive binding methods, of NMR, pharmacore scoring with, 143 99 49–50 darunavir, 87 protein crystal structures and, 99 computer-aided drug design, 181–193 data collection, for x-ray crystallography, in relative proton potential, 128–129 BACE optimization in, 187–189 18–20 scores, 99 solubility and, 191 diffraction and, 18 affinity for analogs and, 99 challenges in, 181–182 patterns for, 18–20 as theory, 98–99 with accuracy, 181 quality of, 19–20 virtual screening for, 3–4, 99–100, with protein/ligand binding affinities, as three-dimensional, 18–19 104–105 181 units in, 18 Zwanzig relationship and, 98–99 sampling as, 181–182 resolution of, 20 docking screens, census for, 99–100 development of, 181 with scattered beams, 18 double electron-electron resonance with docking, 183–184 DATMe immucillins, 241–242 (DEER), 89 ligand binding affinity in, 184–185, DEER. See double electron-electron drug design.Seealsocomputer-aided drug 187 resonance design; drug discovery and BACE inhibitors and, 184–186 delavirdine, 87 optimization; HIV-1 protease, with FEP, 184 density functional theory (DFT), 124 drug design for; purine nucleoside LIE calculations for, 184 DFG-out binding pocket, 201–202 phosphorylase (PNP), drug design rules for, 189 access to, 201–202 for; structure-based drug design modeling approaches for, 182 DFT. See density functional theory computer-aided, 181–193 potency and, 189–193 diabetes, HGLP for, 257 BACE optimization in, 187–189 hERG modeling and, 190–192, 193 diffraction, of crystals, 18 challenges in, 181–182 with protein structures, 182, 183 electron density map and, 21 development of, 181 geometry optimization for, 183 patterns for, 18–20 with docking, 183–184 protonation state determination with, quality of, 19–20 ligand binding affinity in, 184–187 182–183 as three-dimensional, 18–19 modeling approaches for, 182 scoring with, 183–184 units in, 18 potency and, 189–193 CoMSIA. See comparative molecular diffusion-based methods, of NMR, 48–49 with protein structures, 182–183 similarity indices analysis longitudinal relaxation rates of, 48–49 scoring with, 183–184

267 Index

for HIV-1 protease, 87–95 ligand efficiency in, 44 mapping features for, 141–142 allosteric inhibitors in, 94 linkage in, 45 model development for, 139 for HCV, 212 NMR in, 41–50, 55 receptor-based, 144–145 proposed molecular mechanisms of principles of, 42–44 SCAMPI, 139 resistance and, 92–94 screening in, 41–42 scoring of, 143–144 simulations of, 88–91 searching efficiency of fragments in, 3D chemical features in, 137 structure of, 87–88 43–44 3D database screening in, 146–148 unbound structures in, 91–92 validation of fragments in, 44–45 torsion angles in, 137–138 viral inhibitors for, 87 fragment-based structure-guided, 30–39 QSAR in, 151–162 LBDD, 120 advantages of, 31 applicability domains in, 154–155 QSAR methods for, 120 fragment engineering in, 30 combinatorial criteria for, 155–156 quantum mechanics and, 131 fragment libraries for, 31 criticism of, 151–152 for PNP, 220–239 fragment linkage in, 30 development of, 151 binding isotope effects and, 238–239, history of, 30 Hansch approach to, 152 240 HTS libraries and, 30–31 mechanistic models for, 154 bovine, transition-state structure of, SGX FAST, 31–39 methodologies for, 152–153 221–226 GPCRs, 1 model validation in, 153–154 human, transition-state structure of, for HIV-1 protease, 87–95 modern data sets in, 152 230–234 allosteric inhibitors in, 94 multiple descriptors in, 152–153 immucillins and, 226–230 proposed molecular mechanisms of PAHs and, 154 kinetic mechanisms for, 220–221 resistance and, 92–94 target properties for, 153 mechanistic implications of, 234–239 simulations of, 88–91 SAR, 1 remote interactions for, 237–238 structure of, 87–88 SBDD and, 17 third-generation, 241–242 unbound structures in, 91–92 SGX FAST, 31–39 SBDD, 17 viral inhibitors for, 87 aromatic bromine and, 32 catalysis and, 128 HTS, 1 biochemical assays for, 35 combinatorial libraries for, 61 lead generation, 1–5 complementary biophysical screening, free energy calculations in, 61–79 BOMB, 1, 2–3 35 ITC for, 61 GLIDE program, 1 deliverable properties for, 32 linear scaling in, 130–131 HIV-RT, 1 end game for, 32, 37 molecular profiles for, 61 virtual screening, 3–4 fragment library design in, 31–32, 37 parameters of, 120 lead optimization, 7–12 fragment x-ray screening in, 32, 34–35 physics-based models for, 61 complex modeling, 7 future prospects for, 38–39 quantum mechanics in, 120–127, conversions, 7 leadlike properties in, 31–32 128–129, 131, 133 FEP calculations, 7–11 protein kinases in, 37 screening methods for, 61 heterocycle scans, 8–10 SAR optimization in, 35–37 SPR for, 61 linker refinement, 11 selectivity in, 37 transition-state analog, 215–243 logistics, 11–12 SMERGE program for, 37 drug discovery and optimization, 1–12.See molecular design calculations, SPR screening for, 35 also fragment-based lead 7–8 target enabling in, 32, 33–34 discovery; fragment-based protocols, 12 X-ray screening in, 35 structure-guided drug discovery; small group scans, 10–11 siRNA, 1 HIV-1 protease, drug design for; ligand-based design, 1 structure-based design, 1 pharmacore methods; SGX FAST with MM-PBSA, 71–72 x-ray crystallography and, 17–28 fragment-based structure-guided pharmacore methods for, 137–148 advantages of, 24–25 drug discovery active analog approach in, 137 basic requirements for, 17 ADME properties in, 165–173 ALADDIN, 139 data collection for, 18–20 administration routes for, 166 APEX-3D, 139 disadvantages of, 25 clearance in, 172 automated perception, from ligand electron density map for, 20, 21–22 computational models in, 165 structures, 139–140 phasing in, 20–21 drug-likeness measures in, 165–166 CATALYST, 138–139 quantum mechanics in, 120–123 formulation problems with, 165 CAVEAT, 139 refinement of, 22–24 intestinal absorption and, 168–169 CHEM-X, 139 surface mapping in, 25–28 metabolism in, 172–173 common identification for, 142 for water molecules, 26–27 P-glycoprotein effluxes and, 170–171 DANTE, 139 drug potency, computer-aided drug design plasma protein binding and, 171–172 definition of, 137 and, 189–193 proteomic families and, 166 DISCO, 138 hERG modeling and, 190–193 solubility in, 166–168 ensemble distance geometry, 138 drug resistance, HIV-1 protease and, tissue distribution and, 172 evolution of, 137–139 87–95 FBLD excluded volumes in, 145 allosteric inhibitors in, 94 advantages of, 42 fingerprints, 146 proposed molecular mechanisms of binding efficiency of fragments in, 44 GALAHAD, 139 resistance and, 92–94 chemical efficiency of fragments in, GASP, 138–139 simulations of, 88–91 42–43 HIPHOP, 138–139 structure of, 87–88 development of, 41 history of, 137–139 unbound structures in, 91–92 fragment definition in, 41–42 ligand preparation in, 140–141 viral inhibitors for, 87 hit-to-lead process in, 44–45 manual construction for, 139 ␭-dynamics, as SBDD methodology, 70

268 Index

Ehrlich, Paul, 137 fragment-based lead discovery (FBLD).See free-energy calculations, in SBDD, 61–79. electron density map, 20, 21–22 also nuclear magnetic resonance See also alchemical free-energy diffraction studies and, 21 (NMR), with FBLD calculations, for SBDD; alchemical display for, 22 advantages of, 42 methods, for SBDD; Molecular interpretation of, 21–22 binding efficiency of fragments in, 44 Mechanics with Poisson occupancies in, 22 chemical efficiency of fragments in, Boltzmann and Surface Area; solvent flattening and, 21 42–43 partition function computation surface mapping and, 25–26 development of, 41 accuracy of, 62–63 electrostatic potential (ESP) maps, fragment definition in, 41–42 for affinity distribution models, 62–63 127–131 for hydrogen bond acceptors, 41 for binding affinity, 62 relative proton potential and, 127–131 for hydrogen bond donors, 41 alchemical, 66, 72–76 catalysis and, 128 molecular classification for, 41 absolute free, 73–76 charge transfers in, 128 molecular weight in, 41 for fructose 1, 6 bisphosphatase, 73 docking programs in, 128–129 hit-to-lead process in, 44–45 negative results from, 76–77 interaction energy decomposition in, ligand efficiency in, 44 predictive tests for, 76 131 linkage in, 45 relative binding free, 72–73 linear scaling in, 130–131 NMR in, 41–50, 55 solvation free, 76 point charge models in, 127–128 applications of, 50–55 studies on, 77 polarization in, 128 competitive binding methods of, docking and, 98, 99 proton affinity in, 128 49–50 future applications for, 77–79 ZINC database and, 129 development of, 41 with CASP, 79 energetically restrained refinement (EREF) diffusion-based methods of, 48–49 with GAFF, 78 formalism, 121–122 ligand binding in, 45–46 for HIV-1 protease drug design, 93 ensemble distance geometry, 138 ligand-directed methods of, 47–50 ligand binding calculations, 70–77 enzymatic transition-state formation, relaxation-based methods of, 48–49 for MM-PBSA, 70–72 215–216 saturation transfer difference methods methodologies for, 63–70 dynamic coupling in, 216 of, 47 alchemical methods, 66 ground-state destabilization in, 215 surface mapping and, 27–28 for basic equations, 64 NACs and, 216 target-directed methods of, 45–47 expanded ensemble as, 70 substrate conformation and, 215–216 WaterLOGSY method in, 47–48 Hamiltonian exchanges as, 70 EREF formalism. See energetically principles of, 42–44 Jarzynski’s relationship, 67–68 restrained refinement (EREF) property ranges in, 42 ␭-dynamics, 70 formalism screening in, 41–42 MM-PBSA, 64–65 ESP maps. See electrostatic potential (ESP) HTS, 42 multiple intermediates, 66–67 maps searching efficiency of fragments in, multiple ligand simulations, 70 estrogen receptors, 73 43–44 partition function computation, 65–66 expanded ensemble, as SBDD validation of fragments in, 44–45 pulling methods, 69 methodology, 70 fragment-based structure-guided drug umbrella sampling, 69–70 explicit water simulations, 66 discovery, 30–39 simulation codes for, 78 advantages of, 31 free-energy perturbation (FEP), 66 FBLD. See fragment-based lead discovery fragment engineering in, 30 with ligand binding affinity, 184 feature dictionary, for pharmacore features, fragment libraries for fructose 1, 6 bisphosphatase, 73 141 HTS libraries vs., 31 fused heterocyclics, 199–201 FEP. See free-energy perturbation ligand efficiency in, 31 FEP calculations, 7–11 fragment linkage in, 30 GAFF. See Generalized Amber Force Field azines as NNRTIs, 8 history of, 30 GALAHAD method, 139 heterocycle scans, 8–10 HTS libraries and, 30–31 GASP method. See Genetic Algorithm five-membered heterocyclic core, 205–206 fragment libraries vs., 31 Superposition Program method FKBP binding calculations, 75 SGX FAST, 31–39 gas-phase potential energies, 64 Fortovase. See saquinavir soft gel aromatic bromine and, 32 GCMC techniques. See Grand canonical fosamprenavir, 87 biochemical assays for, 35 Monte Carlo (GCMC) techniques fragment dictionary, 141–142 complementary biophysical screening, Generalized Amber Force Field (GAFF), 78 fragment fusion, 51 35 Genetic Algorithm Superposition Program fragment libraries deliverable properties for, 32 (GASP) method, 138–139 ligand efficiency in, 31 end game for, 32, 37 GLIDE program, for lead generation, 1 for SGX FAST, 31–32 fragment library design in, 31–32, 37 filtering, 4 chemical diversity of, 33 fragment x-ray screening in, 32, virtual screening, 3, 4–5 design of, 31–32, 37 34–35 GLUE docking program, 173 properties of, 32–33 future prospects for, 38–39 GPCRs. See G-protein-coupled receptors size of, 32–33 leadlike properties in, 31–32 G-protein-coupled receptors (GPCRs), 1 for structure-guided drug discovery, HTS protein kinases in, 37 ␤2-andrenergic, 249 libraries v., 31 SAR optimization in, 35–37 ligand-binding sites in, 249–250 potency for, 31 selectivity in, 37 crystal structures in, 248–250 fragment X-ray screening, 32, 34–35 SMERGE program for, 37 docking studies for, 251–252 LIMS and, 34–35 SPR screening for, 35 fast, 251–252 sensitivity of, 35 target enabling in, 32, 33–34 manual, 251–252 visualization clarity of, 35 x-ray screening in, 35 virtual screening for, 251–252

269 Index

as drug target, 248 in vitro activity in, 212 immucillins, transition-stage analog design features of, 248 proposed molecular mechanisms of for, 226–230 fragment-based methods for, 253–254 resistance and, 92–94 achiral, 242 future applications of, 254 binding affinity in, 93 acyclic, 241–242 modeling for, 248–254 crystal packing in, 92–93 DATMe, 241–242 3D, 250–251 entropy change in, 93 BIEs and, 238–239 molecular dynamic simulations for, free-energy calculations for, 93 bovine PNP and, 226, 227 252–253 microcalorimetric measurements in, crystal structures in, 227–229 bilayer and solvent models, 252–253 93 inhibition of, 227 model building for, 253 wide-open structure for, 92 clinical trials with, 240 rhodopsin, 248–249 simulations of, 88–91 DADMe, 232–234 ligand-binding sites in, 249–250 with DEER, 89 human PNP and, 232, 234 SBDD and, 248 dihedral angle space constraints in, 91 pharmacological applications of, 3D modeling for, 250–251 with EPR method, 89 239–241 with de novo structure prediction, 251 flap flexibility and, 88–91 synthesis of, 232–233 fragment-based methods for, 253–254 with implicit solvent models, 90–91 in vivo studies of, 241 with homologies, 250–251 with multiscale models, 89–90 dissociation constants in, 227, 236, 237, Grand canonical Monte Carlo (GCMC) with NMR, 88–89 239 techniques, 77 structure of, 87–88 enantiomers of, 234–237 GRIND descriptors, 170 flap formation, 87, 88 human PNP inhibition by, 231 Gund, Peter, 137 semi-open, 87, 88, 90 DADMe immucillins and, 232–234 unbound vs. bound, 88 pharmacological applications of, Hamiltonian exchanges, as SBDD wide-open, 87–88, 91, 92 239–241 methodology, 70 unbound structures in, 91–92 protein dynamics with, 229–230 Hamming, Richard, 165 bound vs., 88 stoichiometry of, 227 Hansch QSAR approach, 152 NOESY for, 92 synthesis of, 226–227 hepatitis C virus (HCV) simulations of, 91–92 in vivo studies on, 239–240 HIV-1 protease drug design for, 209–213 viral inhibitors for, 87 for human T cells, 239–240 lead optimization in, 211 protease disruption in, 87 for mouse T cells, 240 modeling for, 209–210 receptor binding in, 87 indinavir, 87 pharmokinetic profiles in, 212 reverse transcription processes for, indoles, 204 proof of concept in, 211 87 Industrial Fluid Properties Simulation targets for, 209 HIV-1 reverse transcriptase (HIV-RT), 1 Collective (IFPSC), 79 virtual medium for, 210 relative binding free energies and, 72, inosine arsenolysis interpretation, 223–224, in vitro activity in, 212 73 226, 230, 238 incidence rates for, 209 HIV-RT. See HIV-1 reverse transcriptase computational modeling for, 225 SVR for, 209 HTS. See high-throughput screening intestinal absorption, in ADME models, hERG. See human ether-a-go-go` related human ether-a-go-go` related gene (hERG), 168–169 gene 190–192, 193 classification regression tree, 168 heterocycle scans, 8–10 human glycogen phosphorylase (HGLP), computational models in, 169 polycyclic, 9 SBDD for, 257–262 descriptors in, 168 HGLP. See human glycogen phosphorylase AMP sites and, 259–261 intramolecular hydrogen bonds in, (HGLP), SBDD for design of, 261–262 168–169 high-throughput screening (HTS), 1 for diabetes, 257 PAMPA permeabilities and, 169 in FBLD, 42 docking of, 257–258, 259–261 Invirase. See saquinavir hard gel for fragment-based structure-guided x-ray crystal structures and, 262 ionization identification, in pharmacore drug discovery, 30–31 energy calculations for, 262 methods, 140 compliance issues with, 31 features of, 257 isothermal calorimetry (ITC), for SBDD, disadvantages of, 30 phenyl diacid compounds and, 258, 262 61 fragment libraries vs., 31 putative binding pocket prediction for, molecule size and, 30–31 258–259 Jarzynski’s relationship, 67–68 for SBDD, 61 characterization of, 261 BAR in, 68 HIPHOP method, 138–139 hydrogen bond contour map and, 261 MBAR in, 68 features of, 138 synthesis of, 261–262 WHAM in, 68 pharmacore scoring with, 143, 144 human muscle glycogen phosphorylase JNK3 proteins, 108–113 HIV-1 protease, drug design for, 87–95 (HMGP), SBDD for, 257 aminopyrimidines, 109–110 allosteric inhibitors in, 94 human PNP,transition-state structure of, compound classes in, 109 enzyme binding sites for, 94 230–234 oximes, 110–111 monomer cores as target for, 94 crystal structure of, 234 p38 inhibitors, 110 protease dimer interfaces in, 94 DADMe immucillins and, 232, 234 public structures in, 108–109 for HCV, 209–213 features of, 230–231 pyrazol placement in, 111–113 lead optimization in, 211 hydrogen bond acceptors, 41 with SAMPL challenge, 105 modeling for, 209–210 hydrogen bond contour map, 261 Journal of Information and Modeling, 151, pharmokinetic profiles in, 212 hydrogen bond donors, 41 153 proof of concept in, 211 targets for, 209 IFPSC. See Industrial Fluid Properties Kaletra. See lopinavir-ritonavir virtual medium for, 210 Simulation Collective KIEs. See kinetic isotope effects

270 Index

kinetic isotope effects (KIEs), 217–220 MSE values for, 70–71 MM-PBSA. See Molecular Mechanics with in bovine PNP, 222–223 positive/negative partitioning in, 71 Poisson Boltzmann and Surface inosine arsenolysis interpretation and, scores for, 71 Area 223–224, 226, 230, 238 ligand preparation, in pharmacore molecular design calculations, 7–11 V/K KIEs and, 223 methods, 140–141 molecular dynamic simulations, for GPCRs, computational modeling for, 219–220 docking and, 140 252–253 features of, 218 ionization identification for, 140 bilayer and solvent models inhibitor design approach to, 220 with MCMM, 140 explicit, 252–253 for inosine arsenolysis interpretation, with MMFF, 140 implicit, 253 223–224, 226, 230, 238 model development in, 140 model building for, 253 as intrinsic, 219 with OPLS, 140 Molecular Mechanics with Poisson kinetic mechanisms, for PNP drug design, sampling methods for, 140 Boltzmann and Surface Area 220–221 tautomerization in, 140 (MM-PBSA), 64–65 ligand-based drug design (LBDD), 120 bound/unbound stimulation and, 64–65 laboratory information management QSAR methods for, 120 coordinate sampling in, 64 system (LIMS), 33 quantum mechanics and, 131 in drug discovery, 71–72 fragment X-ray screening and, 34–35 with QSAR, 131–132 dynamic trajectory analysis in, 65 LBDD. See ligand-based drug design ligand-directed methods, of NMR, 47–50 entropic costs with, 65 lead generation, 1–5 advantages of, 47 gas-phase potential energies in, 64 BOMB, 1, 2–3 disadvantages of, 47 as ligand binding calculation, 70–72 core binding sites, 2 ligands, in drug discovery and optimization computational costs of, 70 docking, 3–4 design for, 1 MSE values for, 70–71 protein hosts, 2–3 in FBLD, 44 solute entropy change in, 64 results, 3 NMR and, 45–46 solvation energy term in, 64–65 scoring function, 3 in fragment libraries, efficiency of, 31 structure generation in, 64 substituent library, 2 quantum mechanics and, 123–125 molecular quantum similarity, 133 GLIDE program, 1 SAR optimization and, 36 molecular replacement, 20 filtering, 4 LIGANDSCOUT model, 144–145 Monte Carlo Multiple Model (MCMM), virtual screening, 3, 4–5 LIMS. See laboratory information 140 HIV-RT, 1 management system MOZYME program, 130 virtual screening, 3–4 linear interaction energy (LIE) calculations, multiple intermediates, as SBDD docking, 3–4 184 methodology, 66–67 GLIDE program, 3, 4–5 linear scaling, 130–131 double-wide sampling in, 67 NNRTIs, 3–4 MOZYME program for, 130 thermodynamic integration in, 67 ZINC database, 4 technology development for, 130–131 curvature from, 67 lead optimization, 7–12 with water molecules, 130 slow growth simulation in, 67 complex modeling, 7 Lipinski’s rules, 31 Zwanzig relationship expansion in, conversions, 7 lopinavir-ritonavir, 87 67 FEP calculations, 7–11 LUDI interaction map, 144 multistate Bennett Acceptance Ratio azines as NNRTIs, 8 (MBAR), 68 heterocycle scans, 8–10 mammalian proteins, crystallization of, in HCV drug design, 211 17 NACs. See near-attack conformers macrocyclization approach to, mapping.Seealsosurface mapping near-attack conformers (NACs), 216 212–213 of pharmacore features, 141–142 neutrophil elastase inhibitors, 73 heterocycle scans, 8–10 feature dictionary for, 141 nevirapin, 87 linker refinement, 11 fragment dictionary for, 141–142 NNRTIs logistics, 11–12 of interaction sites, 141 FEP calculations, 8 molecular design calculations, 7–8 of ionic groups, 141 virtual screening, 3–4 FEP, 7–11 Martin, Yvonne, 138 NOEs. See nuclear Overhauser effects protocols, 12 matched molecular pairs analysis, 167 NOESY. See nuclear Overhauser effect small group scans, 10–11 Maybridge HitFinder library, 4 spectroscopy BOMB, 10 anticonvulsive models and, 161 Norvir. See ritonavir Lennard-Jones parameters, for SBDD, 69 MBAR. See multistate Bennett Acceptance nuclear magnetic resonance (NMR), with Lexiva. See fosamprenavir Ratio FBLD, 41–50, 55 libraries. See combinatorial libraries, for MCMM. See Monte Carlo Multiple Model applications of, 50–55 SBDD; fragment libraries Merck Molecular Force Field (MMFF), 140 fragment fusion in, 51 LIE calculations. See linear interaction metabolism, in ADME models, 172–173 fragment linking in, 51–52 energy calculations aromatic hydroxylation extraction and, variation and elaboration in, 53–55 ligand binding affinity, 184–185, 187 172 competitive binding methods of, 49–50 BACE inhibitors and, 184–186 cytochrome analysis and, 173 diffusion-based methods of, 48–49 with FEP, 184 GLUE docking program for, 173 for HIV-1 protease, 88–89 LIE calculations for, 184 MetaSite program for, 173 ligand binding in, 45–46 ligand binding calculations, for SBDD, QSAR models, 173 ligand-directed methods of, 47–50 70–77 quantum mechanics and, 172 advantages of, 47 absolute free energies and, 73–74 MetaSite program, 173 disadvantages of, 47 MM-PBSA as, 70–72 Mining Minima method, 66 quantum mechanics in, 123–125 computational costs of, 70 MMFF. See Merck Molecular Force Field CSP in, 123–124

271 Index

DFT and, 124 with 3D database screening, 146 computer-aided drug design with, 182, NOE in, 123 for triplet sets, 146 183 screening methods for, 123 GALAHAD, 139 geometry optimization for, 183 relaxation-based methods of, 48–49 GASP, 138–139 protonation state determination with, saturation transfer difference methods of, HIPHOP, 138–139 182–183 47 features of, 138 configuration integrals for, 99 with spectroscopy, 47 history of, 137–139 crystallization of, 17 surface mapping and, 27–28 ligand preparation in, 140–141 cloned, 17 target-directed methods of, 45–47 docking and, 140 docking and, 99 chemical shift perturbation in, 46 ionization identification for, 140 homologous, 17 ligand binding in, 45–46 with MCMM, 140 mammalian, 17 WaterLOGSY method in, 47–48 with MMFF, 140 refinement data for, 26 nuclear Overhauser effect spectroscopy model development in, 140 truncation for, 17 (NOESY), 92 with OPLS, 140 JNK3, 108–113 nuclear Overhauser effects (NOEs), 48–49, sampling methods for, 140 aminopyrimidines, 109–110 123 tautomerization in, 140 compound classes in, 109 manual construction for, 139 oximes, 110–111 OPLS. See Optimized Potential for Liquid with Seeman model, 139 p38 inhibitors, 110 Simulation mapping features for, 141–142 public structures in, 108–109 Optimized Potential for Liquid Simulation feature dictionary for, 141 pyrazole placement in, 111–113 (OPLS), 140 fragment dictionary for, 141–142 with SAMPL challenge, 105 of interaction sites, 141 phasing and, 21 PAHs. See polycyclic aromatic of ionic groups, 141 quantum mechanics and, structure hydrocarbons model development for, 139 modeling of, 125–127 PAMPA. See parallel artificial membrane for P-glycoprotein effluxes, 170 AMBER force fields in, 126 permeability assay receptor-based, 144–145 geometry validation in, 125 parallel artificial membrane permeability development of, 144 native discrimination in, 126–127 assay (PAMPA), 169 docking in, 144 semiempirical geometry partition function computation, 65–66 with LIGANDSCOUT model, 144–145 approximations in, 125–126 Mining Minima method, 66 with LUDI interaction map, 144 protein configuration integrals, 99 mode integration in, 66 SCAMPI, 139 Protein Data Bank (PDB) file, 3 Patchett, Arthur, 165 scoring of, 143–144 in SGX FAST, 33 Pauling, Linus, 215 with APEX-3D, 144 p38, SBDD for, 197–206 PDB file. See Protein Data Bank (PDB) file with CATALYST, 143, 144 DFG-out binding pocket and, 201–202 Pearlman, David, 72 with DANTE, 143 access to, 201–202 P-glycoprotein effluxes, in ADME models, with HIPHOP, 143, 144 five-membered heterocyclic core, 170–171 with PHASE method, 143, 144 205–206 BBB penetration and, 170–171 with SCAMPI, 144 trisubstituted imidazole, 205 pharmacores for, 170 3D chemical features in, 137 fused heterocyclics and, 199–201 QSAR models for, 170 3D database screening in, 146–148 indoles and, 204 3D-QSAR for, 170 automated perception in, 147 with pyrazolopyrimidines, 202 GRIND descriptors in, 170 hits in, 146 with pyrimidines, 197–199 TOPS-MODE descriptors in, 170 information returns with, 148 with thiazoles, 202–204 pharmacore methods, 137–148 partial matching in, 147 with triazines, 197–199 active analog approach in, 137 as point-based, 147 purine nucleoside phosphorylase (PNP), ALADDIN, 139 precomputed conformers in, 146 drug design for, 220–239.Seealso APEX-3D, 139 torsion angles in, 137–138 immucillins, transition-stage automated perception, from ligand PHASE method, pharmacore scoring by, analog design for structures, 139–140 143, 144 binding isotope effects and, 238–239, 240 CATALYST, 138–139 phasing, in x-ray crystallography, 20–21 bovine, transition-state structure of, CAVEAT, 139 electron density map for, 20, 21–22 221–226 CHEM-X, 139 molecular replacement and, 20 immucillins and, 226, 227 common identification for, 142 structure determination from, 20–21 KIEs and, 222–223 with DISCO, 142 for protein models, 21 labeled substrate synthesis in, 221–222 DANTE, 139 waves and, 20 V/K KIEs and, 223 definition of, 137 phenyl diacid compounds, 258, 262 human, transition-state structure of, DISCO, 138 plasma protein binding, 171–172 230–234 ensemble distance geometry, 138 PNP. See purine nucleoside phosphorylase crystal structure of, 234 evolution of, 137–139 (PNP), drug design for features of, 230–231 excluded volumes in, 145 point charge models, 127–128 immucillin inhibition of, 231 crystallographic receptor structure as, polycyclic aromatic hydrocarbons (PAHs), immucillins and, 226–230 145 154 achiral, 242 inactive structures and, 145 polycyclic heterocycle scans, 9 acyclic, 241–242 shrink-wrap method for, 145 predictive tests, 76 BIEs and, 238–239 fingerprints, 146 Prezista. See darunavir bovine PNP and, 226, 227 with CHEM-X software, 146 protease dimer interfaces, 94 clinical trials with, 240 creation of, 146 protein(s) DADMe, 232–234

272 Index

purine nucleoside phosphorylase (cont.) quantitative structure/activity relationship R factor, 23 dissociation constants in, 227, 236, 237, (QSAR) models, 157 RBDD 239 acceptability criteria for, 155–156 linear scaling in, 130–131 enantiomers of, 234–237 for AmpC ␤-lactamase inhibitors, 161 quantum mechanics in human PNP inhibition by, 231 classification of, 161 qualitative uses of, 127 pharmacological applications of, for anticancer agents, 161 ESP maps and, 127–131 239–241 for anticonvulsive compounds, 159–161 quantitative uses of, 128–129 protein dynamics with, 229–230 Maybridge HitFinder library and, 161 relative proton potential and, 127–131 stoichiometry of, 227 applicability domains in, 154–155 receptor-based pharmacore methods, synthesis of, 226–227 confidence index for, 155 144–145 in vivo studies on, 239–240 definition of, 155 development of, 144 kinetic mechanisms for, 220–221 consensus prediction in, 156–159 docking in, 144 mechanistic implications of, 234–239 future research for, 161–162 with LIGANDSCOUT model, 144–145 enantiomers as, 234–237 good practices in, 156–159 with LUDI interaction map, 144 transition-state discrimination as, mechanistic, 154 recursive partitioning, in ADME models, 234 for metabolism, in ADME models, 173 167 remote interactions for, 237–238 for P-glycoprotein effluxes, 170 relative binding free energies, 72–73 third-generation, 241–242 predictive workflow, 159 estrogen receptors and, 73 pyrazolopyrimidines, 202 for lead optimization, 159–161 for fructose 1, 6 bisphosphatase, 73 pyrimidines, 197–199 statistical figures of merit for, 156–157 HIV-1 and, 72, 73 pyrazolopyrimidines, 202 toxicity results for, 158 for neutrophil elastase inhibitors, 73 validation of, 153–154 relative proton potential, 127–131 QIKPROP, 5–7 virtual screening for, 159 catalysis and, 128 required input, 5 quantum mechanics, in SBDD, 120–131, charge transfers in, 128 submission to, 5–6 133.Seealsoelectrostatic potential docking programs in, 128–129 QSAR. See quantitative structure/activity (ESP) maps interaction energy decomposition in, 131 relationship catalysis and, 128 linear scaling in, 130–131 QSM. See quantum similarity measure CoMFA method in, 132 MOZYME program for, 130 QTMS. See quantum topological molecular disadvantages in, 133 technology development for, 130–131 similarity CoMSIA method in, 132 with water molecules, 130 quantitative structure/activity relationship ESP maps and, 127–131 point charge models in, 127–128 (QSAR).Seealsoquantitative relative proton potential and, 127–131 polarization in, 128 structure/activity relationship interaction energy decomposition in, 131 proton affinity in, 128 (QSAR) models LBDD and, 131 ZINC database and, 129 in drug discovery, 151–162 with QSAR, 131–132 relaxation-based methods, of NMR, 48–49 applicability domains in, 154–155 linear scaling in, 130–131 Reviews in Computational Chemistry, 151 combinatorial criteria for, 155–156 MOZYME program for, 130 Reyataz. See atazanavir criticism of, 151–152 technology development for, 130–131 rhodopsin, 248–249 development of, 151 with water molecules, 130 ligand-binding sites in, 249–250 Hansch approach to, 152 metabolism and, 172 ritonavir, 87 mechanistic models for, 154 molecular quantum similarity and, 133 rofecoxib, 6 methodologies for, 152–153 AIM theory and, 133 model validation in, 153–154 in NMR refinement, 123–125 SAMPL. See Statistical Assessment of the modern data sets in, 152 CSP in, 123–124 Modeling of Proteins and Ligands multiple descriptors in, 152–153 DFT and, 124 saquinavir hard gel, 87 PAHs and, 154 NOE in, 123 saquinavir soft gel, 87 target properties for, 153 screening methods for, 123 SAR. See structure/activity relationships LBDD and, 120, 131–132 protein structure modeling with, 125–127 saturation transfer difference methods, of models for, 157 AMBER force fields in, 126 NMR, 47 acceptability criteria for, 155–156 geometry validation in, 125 with spectroscopy, 47 for AmpC ␤-lactamase inhibitors, 161 native discrimination in, 126–127 SBDD. See structure-based drug design for anticancer agents, 161 semiempirical geometry Scaffold MErging via Recursive Graph for anticonvulsive compounds, approximations in, 125–126 Exploration (SMERGE) program, 159–161 QSAR and, 131–132 37 applicability domains in, 154–155 QSM for, 133 SCAMPI. See Statistical Classification of consensus prediction in, 156–159 spectroscopic, 132 Activities of Molecules for future research for, 161–162 3D model, 131–132 Pharmacore Identification good practices in, 156–159 QTMS and, 133 scans mechanistic, 154 in RBDD heterocycle, 8–10 predictive workflow, 159 qualitative uses of, 127 small group, 10–11 statistical figures of merit for, 156–157 quantitative uses of, 128–129 BOMB, 10 toxicity results for, 158 in x-ray refinement, 120–123 scattered beams, crystal structures and, 18 validation of, 153–154 EREF formalism for, 121–122 Science, 7 virtual screening for, 159 quantum similarity measure (QSM), 133 scoring, with computer-aided drug design, quantum mechanics and, 131–132 CSI for, 133 183–184 3D model, 131–132 quantum topological molecular similarity screening spectroscopic, 132 (QTMS), 133 for docking, censuses for, 99–100

273 Index

for drug discovery and optimization siRNA. See small interfering RNA energy calculations for, 262 in FBLD, 41–42 small group scans, 10–11 features of, 257 for lead generation, 3–4 BOMB, 10 phenyl diacid compounds and, 258, with fragment X-rays, 32, 34–35 small interfering RNA (siRNA), 1 262 LIMS and, 34–35 SMERGE program. See Scaffold MErging via putative binding pocket prediction for, sensitivity of, 35 Recursive Graph Exploration 258–259 for GLIDE program, for lead generation, (SMERGE) program synthesis of, 261–262 3, 4–5 solubility, in ADME models, 166–168 for HMGP, 257 HTS, 1, 42 in BACE ligands, 191 ITC for, 61 in FBLD, 42 crystal packing and, 168 linear scaling in, 130–131 for fragment-based structure-guided in DMSO stock, 166, 167–168 molecular profiles for, 61 drug discovery, 30–31 Gaussian process for, 167 HST screening for, 61 for SBDD, 61 matched molecular pairs analysis and, for p38, 197–206 for NNRTIs, 3–4 167 DFG-out binding pocket and, 201–202 for SGX FAST minimum accepted level for, 167 five-membered heterocyclic core, complementary biophysical screening, prediction of, 167 205–206 35 recursive partitioning in, 167 fused heterocyclics and, 199–201 fragment x-ray screening in, 32, solute entropy change, 64 indoles and, 204 34–35 solvation energy terms, 64–65 pyrazolopyrimidines and, 202 with fragment x-rays, 32, 34–35 free, 76 with pyrimidines, 197–199 with SPR, 35 solvent flattening, 21 with thiazoles, 202–204 with x-rays, 35 spectroscopic 3D-QSAR, 132 with triazines, 197–199 with SPR, 35 SPR. See surface plasmon resonance parameters of, 120 virtual Statistical Assessment of the Modeling of physics-based models for, 61 for docking, 3–4, 99–100, 104–105 Proteins and Ligands (SAMPL), quantum mechanics in, 120–127, GLIDE program and, 3, 4–5 79 128–129, 131, 133 ZINC database in, 4 docking and, 105–107 catalysis and, 128 Seeman model, 139 JNK3 structures and, 105 CoMFA method in, 132 SGX FAST fragment-based structure-guided manual process for, 106 CoMSIA method in, 132 drug discovery semi-automated process for, 106 ESP maps and, 127–131 aromatic bromine and, 32 small-molecule conformations in, interaction energy decomposition in, biochemical assays for, 35 106–107 131 complementary biophysical screening, Statistical Classification of Activities of LBDD and, 131 35 Molecules for Pharmacore linear scaling in, 130–131 with SPR, 35 Identification (SCAMPI), 139 molecular quantum similarity and, deliverable properties for, 32 pharmacore scoring by, 144 133 end game for, 32, 37 structure/activity relationships (SAR), 1 in NMR refinement, 123–125 fragment library design in, 31–32, 37 ligand efficiency and, 36 protein structure modeling with, chemical diversity of, 33 QSAR, LBDD and, 120 125–127 Lipinski’s rules and, 31 in SGX FAST fragment-based QSAR and, 131–132 properties of, 32–33 structure-guided drug discovery, QTMS and, 133 size of, 32–33 35–37 in x-ray refinement, 120–123 fragment x-ray screening in, 32, 34–35 binding sites in, 36, 38 screening methods for LIMS and, 34–35 fragment choice in, 36 docking, 61 sensitivity of, 35 fragment engineering in, 36 with HST, 61 visualization clarity of, 35 goals for, 36 SPR for, 61 future prospects for, 38–39 ligand efficiency in, 36 surface mapping, 25–28 leadlike properties in, 31–32 in target enabling, 32 electron density in, 25–26 protein kinases in, 37 structure-based drug design (SBDD), 17. molecular binding in, 27 SAR optimization in, 35–37 See also free energy calculations, in NMR and, 27–28 binding sites in, 36, 38 SBDD; quantum mechanics, in regional association in, 27–28 fragment choice in, 36 SBDD substructure decomposition and, 27 fragment engineering in, 36 catalysis and, 128 for water molecules, 26–27 goals for, 36 combinatorial libraries for, 61 surface plasmon resonance (SPR), 35 ligand efficiency in, 36 free-energy calculations in, 61–79 with complementary biophysical in target enabling, 32 accuracy of, 62–63 screening, 35 selectivity in, 37 alchemical, 66, 72–76 for SBDD, 61 SMERGE program for, 37 future applications for, 77–79 sustained virologic response (SVR), for HCV, SPR screening for, 35 ligand binding calculations, 70–77 209 with complementary biophysical methodologies for, 63–70 SVR. See sustained virologic response (SVR), screening, 35 simulation codes for, 78 for HCV target enabling in, 32, 33–34 GPCRs and, 248 LIMS in, 33 for HGLP, 257–262 T4 lysozyme ligand binding, 74–75 modular robotics in, 33–34 AMP sites and, 259–261 negative results for, 77 PDB domains in, 33 design of, 261–262 target-directed methods, of NMR, 45–47 SAR optimization in, 32 for diabetes, 257 chemical shift perturbation in, 46 x-ray screening in, 35 docking of, 257–258, 259–261 ligand binding in, 45–46

274 Index

tautomerization, in pharmacore methods, mimicry in, 217 advantages of, 24–25 140 for PNP, 220–239 basic requirements for, 17 thermodynamic integration, in SBDD, 67 triazines, 197–199 for proteins, 17 curvature from, 67 trisubstituted imidazole, 205 data collection for, 18–20 slow growth simulation in, 67 diffraction and, 18 Zwanzig relationship expansion in, 67 umbrella sampling, for SBDD, 69–70 resolution of, 20 thiazoles, 202–204 urokinase plasminogen activators, 107–108 with scattered beams, 18 3D database screening, in pharmacore ligand docking and, 107 disadvantages of, 25 method, 146–148 public structures in, 107 strategies against, 25 automated perception in, 147 RMSD-DPI and, 107 electron density map for, 20, 21–22 hits in, 146 diffraction studies and, 21 information returns with, 148 Vioxx. See rofecoxib display for, 22 partial matching in, 147 Viracept, 87 interpretation of, 21–22 for pharmacore fingerprinting, 146 virtual screening occupancies in, 22 as point-based, 147 for docking, 3–4, 99–100, 104–105 solvent flattening and, 21 precomputed conformers in, 146 GLIDE program, 3, 4–5 with HGLP, 262 3D quantitative structure/activity for GPCRs, 251–252 phasing in, 20–21 relationship (3D-QSAR), NNRTIs, 3–4 electron density map for, 20 131–132 for QSAR models, 159 molecular replacement and, 20 descriptor categories of, 131–132 ZINC database, 4 structure determination from, 20–21 for P-glycoprotein effluxes, 170 waves and, 20 spectroscopic, 132 water binding free energy, 74 quantum mechanics in, 120–123 3D-QSAR. See 3D quantitative water molecules, in x-ray crystallography, EREF formalism for, 121–122 structure/activity relationship 23–24 refinement of, in SBDD, 22–24, 123 tipranavir, 87 surface mapping for, 26–27 misinterpretation measures and, 24 topological substructural molecular design Water/Ligand Observed via Gradient protein data and, 24–26 (TOPS-MODE) descriptors, 170 SpectroscopY (WaterLOGSY) quantum mechanics and, 120–123 TOPS-MODE descriptors. See topological method, in NMR, 47–48 R factor in, 23 substructural molecular design WaterLOGSY method. See Water/Ligand surface mapping in, 25–28 (TOPS-MODE) descriptors Observed via Gradient electron density in, 25–26 transition-state analog drug design, SpectroscopY (WaterLOGSY) molecular binding in, 27 215–243 method, in NMR NMR and, 27–28 enzymatic formation in, 215–216 weighted histogram analysis method regional association in, 27–28 dynamic coupling in, 216 (WHAM), 68 substructure decomposition and, 27 ground-state destabilization in, 215 WHAM. See weighted histogram analysis for water molecules, 26–27 NACs and, 216 method water molecules and, 23–24 substrate conformation and, 215–216 Wilcoxon-Mann-Whitney nonparametric surface mapping for, 26–27 KIEs and, 217–220 rank-order tests, 101–102 computational modeling for, 219–220 William the Conqueror, 98 ZINC database, 129 features of, 218 Zwanzig relationship, 66 inhibitor design approach to, 220 x-ray crystallography, drug discovery and, docking and, 98–99 as intrinsic, 219 17–28 in thermodynamic integration, 67