Quantitative Evaluation of Dissociation Mechanisms in Phenolphthalein and the Related Compounds

Technical Paper Quantitative Evaluation of Dissociation Mechanisms in Phenolphthalein and the Related Compounds

Toshihiko Hanai

Health Research Foundation, Research Institute for Production Development 4F, 15 Shimogamo-morimoto-cho, Sakyo-ku, Kyoto 606-0805, Japan e-mail: [email protected]

(Received: October 11, 2015; Accepted for publication: April 14, 2016; Online publication: May 6, 2016)

Computational chemistry programs were evaluated as aids to teaching qualitative analytical chemistry. Compu- tational chemical calculations can predict absorption spectra, thus enabling the modeling of indicator dissociation mechanisms by different computational chemical programs using a personal computer. An updated MNDO program among 51 programs was found to be the best predictor to explain the dissociation mechanisms of isobenzofuranones and sulfonephthaleins. Unknown dissociation constants were predicted from atomic partial charges instead of Ham- mett's constants. Keywords: Quantitative analysis of dissociation mechanisms, Isobenzofuranone, Sulfonephthalein, Computational chemistry

1 Introduction the absorption wavelength and electron density changes were not well described. The dissociation mechanisms, maximum How to quantitatively teach qualitative analytical chemistry is wavelengths, and electron density maps of isobenzofuranones a very important subject for analytical chemists. Previously, a and sulfonephthaleins were, therefore, evaluated by in silico method to teach molecular interaction mechanisms in chroma- analysis despite the anticipated poor precision. The experimen- tography was quantitatively achieved using molecular mechan- tally measured dissociation of phenolphthalein is described ics and MOPAC programs [1]. Furthermore, the reaction mech- using four dissociation structures, where the ionization of two anisms of highly sensitive detections were also quantitatively phenolic hydroxyl groups converts the neutral molecular form described [2,3]. Further study was carried out for simple detec- into the red quinoid form. Further dissociation from the quinoid tion, indicator's color changes by using updated computational structure to the alcoholic form eliminates the color. The disso- chemical programs. ciation mechanisms can also be described using three structures Color indicators have been the backbone of simple pH tests without the need for a transition structure [8]. and titration analyses. The spectrophotometric determination There are many color indicators having chemical structures of hydrogen ion concentrations by using color indicators was similar to phenolphthalein; these indicators should have similar described [4]. The precision of indicator dissociation constants dissociation mechanisms. The differences in their dissociation was evaluated and the dissociation mechanisms (pKa) were de- constants depend on the inductive effects of the substituents. scribed in detail. The pKa values were found to vary according The associated four dissociation structures were constructed to salt, temperature, and the laboratories where the work was and their spectra and HOMO and LUMO electron density maps conducted [5,6]. The effects of salts and proteins on the spectra were calculated. The unreported dissociation constants were of some dyes and indicators were studied [7]. The dissociation predicted from atomic partial charge calculated using an empir- processes were described in detail by Kolthoff [5]. However, ical program PM6. There still remains the limitation that com-

DOI: 10.2477/jccj.2015-0055 13 putational chemistry programs can estimate the spectra only in phenyl)-7,7-dioxo-8-oxa-7λ6-thiabicyclo[4.3.0]nona- the absence of solvents. 1,3,5-trien-9-yl]-5-methyl-2-propane-2-yl-phenol

2 Experimental 3 Results and Discussion

The computers used were PowerMac G3 and Dell Optiplex The basic structures of isobenzofuranones and the dissoci- running on ChemIntosh® from SoftShell (SanDiego, CA) and ated phenolphthalein molecules drawn using Chemintosh® are CAChe® and SciGress® programs from Fujitsu (Tokyo, Japan). shown in Figures 1 and 2, respectively. There are many com- The spectra were measured in aqueous solutions using a Shi- putational chemistry programs available to create electronic madzu UV1200 (Tokyo, Japan). Indicators used are listed be- spectra. The programs used are summarized in Table 2. The low. The SciGress program provides different programs to cal- spectra of phenolphthalein structure 3, shown in Figure 3, were culate electronic spectra, including MNDO, AM1, PM3, PM5, calculated to compare MM2 and MM3 using programs 3, 4, PM6, RM1, PDDG/MNDO, PDDG/PM3, DFT, ZINDO/S, and 25 (a, b). Structure 3 was initially optimized using MM2 INDO/S, CNDO/S, CNDO/S2, CNDO/S3, CNDO/2, CI, RPA, for programs 3 and 25 (a), and MM3 for programs 4 and 25 (b). ZINDO, and MO-S. The dissociation spectra of phenolphtha- Programs 3 and 4 are ZINDO and program 25 is MO-S MNDO. lein structures were calculated using these programs and used The basic geometries can be optimized using molecular me- to evaluate the accuracy of the programs. The properties of the chanics, either MM2 or MM3. MM3 was found to show weak indicators are summarized in Table 1. The abbreviations of absorption spectra, and did not provide definite information computational chemical programs are summarized later. about the maximum absorption wavelengths. Structures optimized using MM3 exhibited weak molar absorptivities and red 2.1 List of Indicators shift. The intensity was about half of that of calculated using o-Cresolphthalein:3,3-bis(4-hydroxy-3-methylphenyl)-iso- MM2 as shown in Figure 3, and semi-empirical combinations benzofuran-1(3H)-one did not work in many cases, with computer error messages be- α-Naphtholphthalein:3,3-bis(4-hydroxynaphthalene-1-yl)-2- ing generated. Therefore, MM2 was chosen as the initial pro- benzofuran-1-one gram, and the spectra of dissociated phenolphthaleins were cal- Phenolphthalein:3,3-bis(4-hydroxyphenyl)isobenzofuran- culated using SciGress programs. The results are summarized 1(3H)-one Thymolphthalein:3,3-bis(4-hydroxy-2-methyl-5-propane- in Table 3, where some absorption wavelengths are given fol- 2-ylphenyl)-2-benzofuran-1-one lowing their absorption strength. The three dimensional struc- Bromocresolgreen;2,6-Dibromo-4-[7-(3,5-dibromo- tures of phenolphthalein optimized using the MM2 program are 4-hydroxy-2-methyl-phenyl)-9,9-dioxo-8-oxa-9λ6- shown in Figure 4 with HOMO and LUMO electron density thiabicyclo[4.3.0]nona-1,3,5-triene-7-yl]-3-methylphenol maps optimized using semi-empirical programs (PM6). Bromocresolpurple:4,4'-(1,1-dioxido-3H-2,1-benzoxathi- The estimated wavelength of structure 3 representing the red ole-3,3-diyl)bis(2-bromo-6-methylphenol) color varied from 310 to 813 nm. Absorption spectra are gener- Bromophenolblue:4,4'-(1,1-dioxido-3H-2,1-benzoxathiole-3,3-diyl)bis(2,6-dibromophenol) ally shifted to lower wavelength in polar solution. Therefore, Bromothymolblue:4,4'-(1,1-dioxido-3H-2,1-benzoxathi- the calculated wavelengths should be higher than the measured ole-3,3-diyl)bis(2-bromo-6-isopropyl-3-methylphenol) wavelength of 550 nm. Programs 2, 3, 14–16, 18–21, 25, 27, Chlorophenolred:2-chloro-4-[3-(3-chloro-4-hydroxyphenyl)- 28, 32–35, 37, 42, 49, and 50 were acceptable candidates for 1,1-dioxobenzo(c)oxathiol-3-yl]phenol further study. Therefore, the spectra of structures 1 and 4 were Cresolred:4,4'-(1,1-dioxido-3H-2,1-benzoxathiole-3,3-diyl) calculated using these programs. bis(2-methylphenol) The evolution of computational chemistry programs should Cresolpurple:4,4'-(1,1-dioxido-3H-2,1-benzoxathiol-3-yl- dine)bis(3-methylphenol) improve the precision of predicted spectra. However, these re- Phenolred:4,4'-(3H-2,1-benzoxathiole-3-ylidene)bisphenol sults indicate that no single program accurately predicts spectra Thymolblue:4-[9-(4-hydroxy-2-methyl-5-propane-2-yl- for all types of compounds. By comparison of the configuration

14 J. Comput. Chem. Jpn., Vol. 15, No. 1 (2016) Table 1. Properties of indicators

interaction (CI) and analogous random-phase approximation structure 3. The combination of RPA and a semi-empirical ge- (RPA) using MM2 geometry, MO-S, RPA, MM2, and AM1, ometry such as AM1, PM3, PM5, or RM1 gave higher wave- or PM3 or PM5 combinations predicted greater red shifts lengths than that of a CI and semi-empirical combination, but than MO-S, CI, MM2, and AM1, or PM3 or PM5 combina- the calculated wavelength were still relatively short. PDDD tions. CNDO/2, CNDO/S2, CNDO/S3, and RPA combinations and MNDO combinations worked fine with CI; however, a were not suitable for phenolphthalein structure 3, but CNDO/2, combination of PDDG/MNDO and RPA showed increased red CNDO/S2, CNDO/S3, and CI combinations estimated the red shifts. In general, CI was better than RPA that gave weak visible shift wavelength quite well. CNDO/S and CI or RPA combina- wavelengths, as well as than RM1. As described in reference 8, tions worked well, but INDO/S and CI or RPA combinations CI was much more accurate than RPA and even predicted the gave overly strong red shift. However, ZINDO gave a relatively wavelength difference. The long calculation times for CI have better wavelength prediction. A Zerner modification seemed to been reduced by the development of fast personal computers. improve the original INDO performance for phenolphthalein These results differed from those of six carotenoids [17]. In

DOI: 10.2477/jccj.2015-0055 15 Figure 1. Chemical structures of isobenzofurans. Figure 2. Dissociation scheme of phenolphthalein. calculations of the electronic wavelength spectra of carotenoids in conjugated molecules, INDO/S, provided the best agree- semi-empirical geometries (AM1, PM3, PM5, PM6, or RM1) ment with the experiment. AM1 and PM3 values were very demonstrated lower absorption wavelengths than with either similar with a small shift of PM3 energies toward the blue light. MM2 or MM3 geometries. MO-S with a semi-empirical pro- Compared with INDO/S, AM1 and PM3 results were shifted gram with MM2 or MM3 geometries showed higher absorption either to the blue or red, depending on the molecules chosen. wavelengths. INDO gave higher red shift than MNDO. MNDO and MINDO/3 gave energies generally red-shifted MO-S, CI, and MNDO combinations at MNDO geometry compared to those of INDO/S [8]. Vertical excitation energies showed the most reasonable wavelength, and PDDG/MNDO computed with INDO/S showed the best agreement with the combination produced the best result. AM1, PM3, PM5, and experiment. However, this approximation was not adequate RM1 geometries showed blue shift. However, this approxima- for ground-state molecules. On the other hand, the electronic tion was not adequate for the ground state compounds. On the spectra showed reasonable agreement with experiment and other hand, AM1, PM3, and PM5 showed reasonable agree- reproduced the basic trends [17], though MNDO was the best ment with the experiment for the ground state spectra. The es- for phenolphthalein. The small wavelength difference cannot timated spectra of phenolphthalein structure 1 indicated strong be justified because the solvent effect was not included in the absorption at lower wavelengths; however some programs calculation. Combinations of CNDO and RPA showed strong showed weak visible absorption. If the weak absorption cannot blue shift, except for CNDO/S. Despite these programs having be neglected, programs 42, 43, 49, and 50 are not suitable for been basically evolved from NDDO, the order of development this study. The calculated spectra of phenolphthalein structure 4 is NDDO < CNDO < INDO < MINDO < MNDO < AM1 < also indicated visible absorption using programs 14, 15, 25, 26, DFT

16 J. Comput. Chem. Jpn., Vol. 15, No. 1 (2016) Table 2. Comparison of UV-Vis spectra of dissociated phenolphthalein structures using different programs

Absorption wavelength nm Structure1*1 Structure 3*1 Structure 4*1 No Programs Strong absorption Reference Strong absorption wavelength nm 549-553 wavelength nm

1 ZINDO INDO/MM3(standard) 189>225>284 581&719 193>256>316 2 ZINDO CI current geometry (INDO/S, MM2) error 640 193>254>307 3 ZINDO CI MM2 (ZINDO/S MM2) (ZINDO INDO/S) 192>226>292 660 193>254>307 4 ZINDO CI MM3 (ZINDO using INDO/S MM3) 189>225>283 660(weak) 193>256>316 5 ZINDO CI at INDO/I using MM3 188>238>299 500 - 6 ZINDO CI at AM1 184>233>284 470 - 7 ZINDO CI at PM3 187>230>286 474 - 8 ZINDO CI at PM5 187>231>283 467 - 9 ZINDO CI at PM6 188>231>282 483 - 10 ZINDO CI at RM1 187>227>286 467 - 11 ZINDO CI at DFT B88-PW91 geometry*2 - 476, - 12 ZINDO CI at DFT B88-LYP geometry*2 - 481, - 13 ZINDO CI at DFT D-VWV geometry*2 - 459, - 14 MO-S AM1 using CI at current geometry 219>>301 633 225>305>362 15 MO-S PM3 using CI at current geometry 218>>293 662 226>248>303>360 16 MO-S PM5 using CI at current geometry 225>>318 654 232>258>314 17 MO-S CNDO/2 using CI at current 2 geometry - 334 - 18 MO-S CNDO/S2 using CI at current geometry 196>229>280 787 197>244>288 19 MO-S CNDO/S3 using CI at current geometry 196>229>285 787 195>245>286 20 MO-S CNDO/S using CI at current geometry 190>227>285 658 193>245>277 21 MO-S INDO/S using CI at current geometry 193>226>293 758 194>254>293 22 MO-S PDDD/MNDO using CI at current geometry - 301 - 23 MO-S PDDG/PM3 at current geometry error 24 MO-S RM1 using CI at current geometry - 301 - 25 MO-S MNDO using CI at current geometry 232>>339 629 240>266>329>395 26 MO-S AM1 using RPA at current geometry 233>>303 649 237>308>374 27 MO-S PM3 using RPA at current geometry 233>>291 658 237>305>372 28 MO-S PM5 using RPA at current geometry 245>>321 680 245>316>358 29 MO-S CNDO/2 using RPA at current geometry - 340 - 30 MO-S CNDO/S2 using RPA at current geometry - 301 - 31 MO-S CNDO/S3 using RPA at current geometry - 301 - 32 MO-S CNDO/S using RPA at current geometry 204>231>288 673 195>248>278 33 MO-S INDO/2 using RPA at current geometry 211>230>297 813 199>258>294 34 MO-S PDDG/MNDO using RPA at current geometry 260>>369 718 266>353>445 35 MO-S PDDG/PM3 using RPA at current geometry 233>>294 690 236>303>369 36 MO-S RM1 using RPA at current geometry - 478 - 37 MO-S MNDO using RPA at current geometry 249>>341 680 255>333>412 38 MO-S AM1 using CI at AM1 geometry - 490 - 39 MO-S PM3 using CI at PM3 geometry - 493 - 40 MO-S PM5 using CI at PM5 geometry - 490 - 41 MO-S RM1 using CI at RM1 geometry - 478 - 42 MO-S MNDO using CI at MNDO geometry 233>>359 529 237>267>>337 43 MO-S PDDG/MNDO using CI at PDDG/MNDO geometry 243>>371 549 243>283>348> >356>433 44 MO-S PDDG/PM3 using CI at POOD/PM3 geometry - 503 - 45 MO-S AM1 using RPA at AM1 geometry - 508 - 46 MO-S PM3 using RPA at PM3 geometry - 508 - 47 MO-S PM5 using RPA at PM5 geometry - 503 - 48 MO-S RM1 using RPA at RM1 geometry - 490 - 49 MO-S MNDO using RPA at MNDO geometry 252>>352 546 248>342>420 50 MO-S PDDG/MNDO using RPA at PDDG/MNDO geometry 262>>375 568 262>361>459 51 MO-S PDDG/PM3 using RPA at PDDG/PM3 geometry - 518 229>307>375

Current geometry: MM2 geometry was used; Multi wavelength is given for structures 1 and 4. The order is based on molar absorptivity strength. Typical wavelengths are listed in order to their absorption strength;*1: Structures 1, 3 and 4 explained in Figure 2; *2: Can read all spectra from 11 to 13; however, the calculation costs more than 14 hrs.

DOI: 10.2477/jccj.2015-0055 17 Table 3. Typical absorption wavelengths measured using different computational programs

Indicators Program S1 S2 S3 S4 No Phenol- 3 292 578 660 307 phthalein 9 282 329 483 329 25 339 580 629 395 42 359 353 529 400 o-Cresol- 3 290 577 630 315 phthalein 9 286 324 492 320 25 344 578 645 400 42 355 327 529 407 Thymol- 3 302 489>414 621 308 phthalein 9 209 333 508 328 25 350 590 650 406 42 357 304 556 415 Figure 3. Comparison of ZINO and MO-W, MNDO using CI α-Naphthol- 3 323 600 650 343 phthalein 9 309 348 620 373 at MM2 and MM3 geometry of phenolphthalein structure 3. 25 384 677 744 430 42 383 374 585 448 Bromocresol 3 280 585 617 320 green 9 284 293 498 322 phosphoric acid), structure 1 should absorb at 230 nm. Pro- 25 352 600 662 419 grams 53 and 75 demonstrated high absorption but programs 42 312 346 525 335 Bromocresol 3 283 453 684 311 3 and 9 showed weak absorption, and the maximum absorption purple 9 271 324 516 322 wavelength was lower than 200 nm. Other isobenzofuranones, 25 350 457 492>400 407 42 317 315>343 400>550 416 o-cresolphthalein, thymolphthalein, and α−naphthylphthalein Bromophenol 3 266 548 676 309 blue 9 277 320 498 456 showed results similar to those obtained for phenolphthalein. 25 348 447>651 394>651 382 Structure 2 optimized by MM2 showed strong visible absorp- 42 316 357 393>328 392 Bromothymol 3 290 570 670 315 tion. The best visible absorption was obtained by program 42; blue 9 287 323 516 324 25 346 585 685 416 however structures 1, 2, and 4 showed weak visible-light ab- 42 425 300 522 425 sorption. Structures optimized using PM6 (program 9) showed Chlorophenol 3 277 364 478 318 red 9 284 319 501 326 the best wavelength selectivity, but the structure 3 wavelength 25 340 390 530 405 showed blue shift. 42 321 354 529 406 Cresol purple 3 197> 592 515 340 The ZINDO-DFT combination did not deliver reasonable 9 287 292 530 330 25 335 615 602 400 wavelengths, even with calculation times of longer than 14 42 324 351 575 406 hours. Therefore, this was not used further. RM1 was also not Cresol red 3 282 546 515 318 9 282 324 512 333 suitable for phenolphthalein. The ADF program was listed but 25 340 570 546 400 42 319 344 533 405 not included in this SciGress program. Phenol red 3 282 556 675 323 Since phenolphthalein was discovered in 1871, many similar 9 281 306 489 325 25 330 567 687 395 compounds have been synthesized and used as color indica- 42 327 351 531 399 tors (Table 1). Because their dissociation mechanisms must be Thymol blue 3 286 593 746 325 9 291 313 522 336 the same as that of phenolphthalein, their spectra and electron 25 337 627 730 405 42 311 350 560 413 density maps have been calculated. Their structures are sum- S1, S2, S3, S4: structure 1-4 in Figure 1, Double peaks are marized in Figure 5, and the estimated dissociated structures indicated based on the absorption strength (>). are shown in Figure 6, with chlorophenol red as an example.

The spectra of dissociated compounds are summarized in Table color. Structures 2 and 3 spectra should be visible but several 3, where these spectra were calculated using programs 5, 9, 25, calculated wavelengths did not demonstrate their visible spec- and 42. Structures 1 and 4 spectra should be non-color, there- tra. fore only their longest wavelengths are listed to indicate their These programs were selected based on the results of phe-

18 J. Comput. Chem. Jpn., Vol. 15, No. 1 (2016) Figure 4. HOMO and LUMO electron density maps of phenolphthalein dissociation. structures 1-4.

Figure 6. Dissociation scheme of chlorophenol red.

sults were obtained for bromo-substituted sulfonephthaleins. In particular, bromocresol purple and bromophenol blue showed very poor performance. Their structures optimized using PM6 or MNDO did not show reasonable visible absorption spectra, which may be because of poor properties of bromine that has a strongly negative inductive effect. This in silico analysis quantitatively demonstrated the dissociation mechanisms together with their HOMO and LUMO electron distributions, as shown in Figure 4. In the ionization process, the LUMO indicated the resonance form that caused the red shift. The increased π-electron delocalization in the an- ion produces a smaller HOMO-LUMO gap and increased absorption wavelength [14]. The dissociation constants were af- fected by the inductive effects of substituents. Alkyl groups (+I effect) produce higher dissociation constant shift, and halogens Figure 5. Chemical structure of sulfonephthaleins. (-I effect) provide lower dissociation constant shift, similar to the dissociation constants of phenolic compounds where their nolphthalein. The MNDO element of PDDG/MNDO gave an dissociation constants were predicted from their oxygen atomic error message for phenylsulfonephthalein because the original partial charges [19]. The atomic partial charges (apc) of oxygen MNDO cannot handle sulfur. MNDO in programs 42 and 49 calculated using MOPAC-PM5 are summarized in Table 1. The appears to have been updated. Alkyl-substituted sulfonephtha- dissociation of two hydroxyl groups is the main mechanism, leins gave results similar to those of isobenzofuranones. The and both have the same chance of dissociation. Therefore, the visible absorption of structures 1, 2, and 4, optimized with sum of these oxygen atomic partial charges of structure 3 was MNDO or PM6, was weak, and structure 2 optimized with used to predict unknown pKa values. The reference pKa values MM2 showed strong visible absorption. Chloro-substituted iso- from reference 18 were used as the standard values. The pre- benzofuranones showed results similar to isobenzosulfones and dicted pKa values were calculated from the following equation: alkyl-substituted sulfonephthaleins. The most complicated re- pKa = −29.966 (pKa reference) − 37.079 giving r = 0.972 (n =

DOI: 10.2477/jccj.2015-0055 19 9). The predicted pKa values are listed in Table 1. MNDO was AM1: Austin Model 1-semi-empirical method for the quan- the best program to calculate these spectra, but the apc values tum calculation of molecular electronic structure in com- calculated using MNDO were not suitable for pKa prediction. putational chemistry based on NDDO [20–22]. CEO: Collective Electronic Oscillators [17,22] In addition, this method can be used to design better reagents CI: Configuration Interaction [23,24] those have improved wavelength selectivity and absorption in- CNDO: Complete Neglect of Differential Overlap [25–29] tensity. CNDO/S: CNDO for Spectroscopy The comparison of calculated spectra indicates that a selec- DFT: Density Functional Theory [30,31] tion of program set was not easy for a variety of compounds. DFT B88: DFT Becke88- pure GGA [32,33] This is a tedious process to find the best program set to obtain GGA: Generalized Gradient Approximation [32,34] an identical spectrum with the measured spectrum. However, LYP: GGA correlation functional from Lee, Yang and Parr functional [32,33] we have to recognize the estimated spectra were calculated in INDO: Intermediate Neglect of Differential Overlap vacua, but the experimental spectra were measured in pH con- [17,23,24,35] trolled aqueous solution, This means that chemically estimated INDO/S: INDO for Spectroscopy [17,36] computational spectra should be used as the relative informa- MNDO: Modified NDDO; does not take intra-account delo- tion to study the color indicator mechanisms. calization effect, uses only s and p orbital sets [18,21,37– 39]. 4 Summary MNDO/d: MINDO with d-orbital [40] MINDO/3: version up product of INDO; Modified Neglect Computational chemical analysis can help to teach qualita- of Diatomic Differential Overlap [24,35,40] tive analytical chemistry better. For spectral predictions and MO-S: Molecular Orbital package to calculate Spectroscopic the visualization of the electron-transfer mechanisms of color properties of a molecule [SciGress, Fujitsu] indicators, combinations of MO-S or MNDO with CI seemed NDDO: Neglect of Diatomic Differential Overlap [21,24] PDDG: Pairwise Distance Directed Gaussian modification of to give the best results for isobenzofuranones and sulfonephtha- NDDO provides good description of the van der Waals at- leins (structure 3). The MO-S and CI combination was suitable traction between atoms [38]. for the ground-state structure of isobenzofuranones and sul- PM3: Parametric Model 3; Reparametrization of MNDO fonephthaleins (structures 1 and 4). The precision of computa- with core-core repulsion term similar to those of AM1 tional chemical programs has been improved for protein analy- [20,21,38]. sis; however, the above results demand further improvement PM5: Parametric Model 5; Version-up program of PM3 [21] for small molecules. 51 programs are collected, some programs PM6: Version-up program of PM5, however, PM6 can handle more elements compared to PM5 according to James included water for the calculation; however, estimation of sol- Stewart [21,41]. vent effects remains as a challenge. Above results will help to PW91: Perdew-Wang 1991 functional [32–34,42,43] improve the precision of up-dated programs to predict spectra RM1: Recife Model 1, Semi-empirical methods, Reparam- of a variety of compounds with a program selection guide. etrization of AM1 for H, C, N, O, P, S, F, Cl, Br, and I 4.1 Abbreviations of computational chemi- [21,41,44]. cal programs RPA: reference 22 SAOP: Statistical Average of Orbital Potentials [42] The following programs are listed in SciGress programs, TZP: Triple-Zquality augmented by one set of Polarization functions [32] however, the selection guide is not available. First, constructed ZINDO: reference 23 structures were mainly optimized by MM2; then their spectra ZORA: Zero-Order Regular Approximation [42] were calculated using the following programs. ADF: Amsterdam Density Functional (DFT-Density Func- tional Theory- for molecules, heavy elements, transition metals) [18]

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