Abstract
A series of twenty-two novel N-(disubstituted-phenyl)-3-hydroxynaphthalene- 2-carboxamide derivatives was synthesized and characterized as potential antimicrobial agents. N-[3,5-bis(trifluoromethyl)phenyl]- and N-[2-chloro-5-(trifluoromethyl)phenyl]-3-hydroxy- naphthalene-2-carboxamide showed submicromolar (MICs 0.16–0.68 µM) activity against methicillin-resistant Staphylococcus aureus isolates. N-[3,5-bis(trifluoromethyl)phenyl]- and N-[4-bromo-3-(trifluoromethyl)phenyl]-3-hydroxynaphthalene-2-carboxamide revealed activity against M. tuberculosis (both MICs 10 µM) comparable with that of rifampicin. Synergistic activity was observed for the combinations of ciprofloxacin with N-[4-bromo-3-(trifluoromethyl)phenyl]- and N-(4-bromo-3-fluorophenyl)-3-hydroxynaphthalene-2-carboxamides against MRSA SA 630 isolate. The similarity-related property space assessment for the congeneric series of structurally related carboxamide derivatives was performed using the principal component analysis. Interestingly, different distribution of mono-halogenated carboxamide derivatives with the –CF3 substituent is accompanied by the increased activity profile. A symmetric matrix of Tanimoto coefficients indicated the structural dissimilarities of dichloro- and dimetoxy-substituted isomers from the remaining ones. Moreover, the quantitative sampling of similarity-related activity landscape provided a subtle picture of favorable and disallowed structural modifications that are valid for determining activity cliffs. Finally, the advanced method of neural network quantitative SAR was engaged to illustrate the key 3D steric/electronic/lipophilic features of the ligand-site composition by the systematic probing of the functional group.
Highlights
The comprehensive specification of the target-ligand interaction content in the rational drug design is a computationally intense issue that requires at least four German G’s: Geschick, Geduld, Geld, and Glück [1]
The biological screening of all the compounds was performed against the reference and quality control strain Staphylococcus aureus ATCC 29213, three clinical isolates of methicillin-resistant S. aureus (MRSA) [41], and against Mycobacterium tuberculosis H37Ra ATCC 25177
N-[3,5-bis(trifluoromethyl)phenyl]-3-hydroxynaphthalene-2-carboxamide (13) and N-[2-chloro-5(trifluoromethyl)phenyl]-3-hydroxynaphthalene-2-carboxamide (20) demonstrated high activity against methicillin-resistant S. aureus isolates in the range of minimum inhibitory concentrations (MICs) from 0.16 to 0.68 μM
Summary
The comprehensive specification of the target-ligand interaction content in the rational drug design is a computationally intense issue that requires at least four German G’s: Geschick (skill), Geduld (patience), Geld (money), and Glück (luck) [1]. Whenever no structure or model of the target molecule is accessible at the atomic level the pharmacophore-guided concept can be employed for mapping of the binding/active site [4]. The straightforward tenet of substituent interchangeability and complementarity inherently favors the similarity principle, especially in structure-activity (SAR) modeling, where congeneric series of molecules should exhibit similar pharmacological profile [6]. In this context, validation is one of those words . M[38o,r3e9o]v. eMr, othreeoqvuearn, titthaetivqeusaanmtiptalitnivgeosfasmimpillainrigtyorfelsaitmedilaacrittivyitryellaanteddscaacpteivpitryovliadneddsacaspuebtlperpoivcitduerde oaf fFsaaucivntbioavtrllielatyybp, licetchltiaufenfrsdceo[do4m0fis]fpa.allFveloioxnwraaaelbpldylpe,srttaorhnauedcchctduoiromsafalpltmllhoeewoxdaemipdfiapcscarthortiiuaonccnethuslortehafalartmthnaeionrmdegivafuiaccshlaiiidntnigoefonlnrseedatuhrenrataeitnlramgnreieuntvswiiannlogigdrtknhfeoewuraradcastelitveneimretymtpwcilnlooiiffyrnkesgdw[4th0aine]s. qemuapnltoityaetdiveinSAqRuatontsiptaetciivfey tShAe Rpottoentsipaellcyifvyaltihde3-pdoimteenntisailolnyalvsatleidric3/e-ldeicmtreonnsicio/ nliaplopstheirliicc/feeleactutrroensiocf/ tlihpeolpighailnicd-freeacteupretosrocfotmhepolisgiatinodn-rbeycethpetosrycsotemmpaotsicitsioanmbpylinthgeosfythsteemfuantcictiosanmalpglrinogupofretshueltfiunngcitniotnhael pgrrooduupcrteiosunlotifnagninavthereapgreoddsuecleticotnioonf-darnivaevnerpahgaerdmsaecleocpthioonre-dpraivtteenrnph[2a6r]m. acophore pattern [26]
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