Abstract
We developed a new structure-based in-silico screening method using a negative image of a ligand-binding pocket and a multi-protein–compound interaction matrix. Based on the structure of the ligand pocket of the target protein, we designed a negative image, which consists of virtual atoms whose radii are close to those of carbon atoms. The virtual atoms fit the pocket ideally and achieve an optimal Coulomb interaction. A protein–compound docking program calculates the protein–compound interaction matrix for many proteins and many compounds including the negative image, which can be treated as a virtual compound. With specific attention to a vector of docking scores for a single compound with many proteins, we selected a compound whose score vector was similar to that of the negative image as a candidate hit compound. This method was applied to representative target proteins and showed high database enrichment with a relatively quick procedure.
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Acknowledgements
This work was supported by grants from the New Energy and Industrial Technology Development Organization of Japan (NEDO) and the Ministry of Economy, Trade, and Industry (METI) of Japan.
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Appendices
Appendix 1
The following PDB identifier list of complexes was used: 12asy, 1a28, 1a42, 1a4g, 1a4q, 1ady, 1aer, 1ai5, 1aoe, 1apt, 1apu, 1aqw, 1aszy, 1atl, 1aux, 1b58, 1b76, 1b9v, 1bdg, 1bma, 1byb, 1byg, 1c1e, 1c5c, 1c83, 1cbs, 1cbx, 1cdg, 1ckp, 1com, 1coy, 1cps, 1cqez, 1csny, 1cvu, 1cx2z, 1d0l, 1d3h, 1dd7, 1dg5, 1dhf, 1dog, 1dr1, 1eed, 1efv, 1ejn, 1epb, 1epo, 1eqg, 1eqh, 1ets, 1f0r, 1f0s, 1fen, 1fkg, 1fki, 1fl3, 1gol, 1gtr, 1hck, 1hdc, 1hfc, 1hos, 1hpv, 1hsb, 1htf, 1hyt, 1ida, 1ivb, 1jap, 1lcp, 1lic, 1lna, 1mbi, 1mdr, 1gcz, 1mld, 1mmq, 1mmu, 1mrg, 1mts, 1nco, 1ngp, 1nks, 1okl, 1phd, 1phg, 1poc, 1ppc, 1pph, 1pso, 1pxx, 1pyg, 1qbr, 1qbu, 1qh7, 1qpq, 1rds, 1rne, 1rnt, 1rob, 1s2a, 1s2c, 1ses, 1snc, 1so0, 1tlp, 1tmn, 1tng, 1tnh, 1tni, 1tnl, 1tyl, 1xid, 1xie, 1yee, 2aac, 2aad, 2ack, 2ada, 2cmd, 2cpp, 2fox, 2ifb, 2pk4, 2qwk, 2tmd, 2tmn, 3cla, 3cpa, 3erd, 3ert, 3pgh, 3r1r, 3tpi, 4cox, 4est, 4lbd, 4phv, 5cpp, 5er1, 6cox, 6rnt, and 7tim. For 1htf and 1s2c, two receptor pockets were prepared, since these proteins both bind two ligands each.
Appendix 2
The names of the COX-2 inhibitors used in the present study are suprofen, flubiprofen, indomethacin, ketoprofen, naproxen, etodolac, nimesulide, rofecoxib, diclofenac and Sc-558 (1-phenylsulfonamide-3- trifluoromethyl-5-parabromophenylpyrazole).
Appendix 3
The names of the thermolysin inhibitors used in the present study are the following, in which the PDB code in parentheses is the complex structure from which the compound originated, also the Ki values are supplied when the value is available [27]: l-benzylsuccinate (1hyt: Ki = 3.8 nM), phenylalanine phosphinic acid-deamino-methyl-phenylalanine (1os0), (6-methyl-3,4-dihydro-2H-chromen-2-Yl) methylphosphonate (1pe5), 2-(4-methylphenoxy) ethylphosphonate-3-methylbutan-1-amine (1pe7), 2-ethoxyethylphosphonate-3-methylbutan-1-amine (1pe8), (2-sulfanyl-3-phenylpropanoyl)-Phe-Tyr (1qf0:Ki = 42 nM), [2(R,S)-2-sulfanylheptanoyl]-Phe-Ala (1qf1:Ki = 48 nM), [(2S)-2-sulfanyl-3-phenylpropanoyl]-Gly-(5-phenylproline) (1qf2:Ki = 1200 nM), n-(1-(2(R, S)-carboxy-4-phenylbutyl) cyclopentylcarbonyl)-(S)-tryptophan (1thl), (R)-retrothiorphan (1z9g), (S)-thiorphan (1zdp), hydroxamic acid (4tln:Ki = 190 µM), phenylalanine phosphinic acid (4tmn:Ki = 68 pM), Honh-benzylmalonyl-l-alanylglycine-P-nitroanilide (5tln), Cbz-GlyP-Leu-Leu (ZgPLl) (5tmn:Ki = 9.1 nM), Cbz-GlyP-(O)-Leu-Leu (ZgP(O)Ll) (6tmn:Ki = 9 µM), CH2CO(N–OH)Leu-OCH3 (7tln), benzyloxycarbonyl-d-Ala (1kto), benzyloxycarbonyl-l-Ala (1kl6), benzyloxycarbonyl-d-Thr (1kro), benzyloxycarbonyl-l-Thr (1kj0), benzyloxycarbonyl-d-Asp (1ks7), benzyloxycarbonyl-l-Asp (1kkk), benzyloxycarbonyl-d-Glu (1kr6) and benzyloxycarbonyl-l-Glu (1kjp).
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Fukunishi, Y., Kubota, S., Kanai, C. et al. A Virtual Active Compound Produced from the Negative Image of a Ligand-binding Pocket, and its Application to in-silico Drug Screening. J Comput Aided Mol Des 20, 237–248 (2006). https://doi.org/10.1007/s10822-006-9047-1
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DOI: https://doi.org/10.1007/s10822-006-9047-1