Inhibition of human dihydrofolate reductase by 4,6-diamino-1,2-dihydro-2,2-dimethyl-1-(substituted-phenyl)-s-triazine s. A quantitative structure-activity relationship analysis

Chemical space of Escherichia coli dihydrofolate reductase inhibitors: New approaches for discovering novel drugs for old bugs

Escherichia coli Dihydrofolate reductase is an important enzyme that is essential for the survival of the Gram-negative microorganism. Inhibitors designed against this enzyme have demonstrated application as antibiotics. However, either because of poor bioavailability of the small-molecules resulting from their inability to cross the double membrane in Gram-negative bacteria or because the microorganism develops resistance to the antibiotics by mutating the DHFR target, discovery of new antibiotics against the enzyme is mandatory to overcome drug-resistance. This review summarizes the field of DHFR inhibition with special focus on recent efforts to effectively interface computational and experimental efforts to discover novel classes of inhibitors that target allosteric and active-sites in drug-resistant variants of EcDHFR.

Ligand binding studies, preliminary structure-activity relationship and detailed mechanistic characterization of 1-phenyl-6,6-dimethyl-1,3,5-triazine-2,4-diamine derivatives as inhibitors of Escherichia coli dihydrofolate reductase

Gram-negative bacteria are implicated in the causation of life-threatening hospital-acquired infections. They acquire rapid resistance to multiple drugs and available antibiotics. Hence, there is the need to discover new antibacterial agents with novel scaffolds. For the first time, this study explores the 1,3,5-triazine-2,4-diamine and 1,2,4-triazine-2,4-diamine group of compounds as potential inhibitors of Escherichia coli DHFR, a pivotal enzyme in the thymidine and purine synthesis pathway. Using differential scanning fluorimetry, DSF, fifteen compounds with various substitutions on either the 3rd or 4th positions on the benzene group of 6,6-dimethyl-1-(benzene)-1,3,5-triazine-2,4-diamine were shown to bind to the enzyme with varying affinities. Then, the dose dependence of inhibition by these compounds was determined. Preliminary quantitative structure-activity relationship analysis and docking studies implicate the alkyl linker group and the sulfonyl fluoride group in increasing the potency of inhibition. 4-[4-[3-(4,6-diamino-2,2-dimethyl-1,3,5-triazin-1-yl)phenyl]butyl]benzenesulfonyl fluoride (NSC120927), the best hit from the study and a molecule with no reported inhibition of E. coli DHFR, potently inhibits the enzyme with a Ki value of 42.50 ± 5.34 nM, followed by 4-[6-[4-(4,6-diamino-2,2-dimethyl-1,3,5-triazin-1-yl)phenyl]hexyl]benzenesulfonyl fluoride (NSC132279), with a Ki value of 100.9 ± 12.7 nM. Detailed kinetic characterization of the inhibition brought about by five small-molecule hits shows that these inhibitors bind to the dihydrofolate binding site with preferential binding to the NADPH-bound binary form of the enzyme. Furthermore, in search of novel diaminotriazine scaffolds, it is shown that lamotrigine, a 1,2,4-triazine-3,5-diamine and a sodium-ion channel blocker class of antiepileptic drug, also inhibits E. coli DHFR. This is the first comprehensive study on the binding and inhibition brought about by diaminotriazines of a gram-negative prokaryotic enzyme and provides valuable insights into the SAR as an aid to the discovery of novel antibiotics.

CoMFA analysis of tgDHFR and rlDHFR based on antifolates with 6-5 fused ring system using the all-orientation search (AOS) routine and a modified cross-validated r(2)-guided region selection (q(2)-GRS) routine and its initial application

We report the development of CoMFA analysis models that correlate the 3D chemical structures of 80 compounds with 6-5 fused ring system synthesized in our laboratory and their inhibitory potencies against tgDHFR and rlDHFR. In addition to conventional CoMFA analysis, we used two routines available in the literature aimed at the optimization of CoMFA: all-orientation search (AOS) and cross-validated r(2)-guided region selection (q(2)-GRS) to further optimize the models. During this process, we identified a problem associated with q(2)-GRS routine and modified using two strategies. Thus, for the inhibitory activity against each enzyme (tgDHFR and rlDHFR), five CoMFA models were developed using the conventional CoMFA, AOS optimized CoMFA, the original q(2)-GRS optimized CoMFA and the modified q(2)-GRS optimized CoMFA using the first and the second strategy. In this study, we demonstrate that the modified q(2)-GRS routines are superior to the original routine. On the basis of the steric contour maps of the models, we designed four new compounds in the 2,4-diamino-5-methyl-6-phenylsulfanyl-substituted pyrrolo[2,3-d]pyrimidine series. As predicted, the new compounds were potent and selective inhibitors of tgDHFR. One of them, 2,4-diamino-5-methyl-6-(2',6'-dimethylphenylthio)pyrrolo[2,3-d]pyrimidine, is the first 6-5 fused ring system compound with nanomolar tgDHFR inhibitory activity. The HCl salt of this compound was also prepared to increase solubility. Both forms of the drug were tested in vivo in a Toxoplasma gondii infection mouse model. The results indicate that both forms were active with the HCl salt significantly more potent than the free base.

Structure-activity relationship and comparative docking studies for cycloguanil analogs as PfDHFR-TS inhibitors

Drug resistance acquired by Plasmodium falciparum (Pf) is a major problem in the treatment and control of malaria. One of the major examples of drug resistance is that caused by mutations in the active site of dihydrofolate reductase (DHFR) of Pf (PfDHFR-TS). A double mutation, A16V+S108T, is specific for resistance to the marketed drug cycloguanil. In this study, we used 58 cycloguanil (2,4-diamino-1,6-dihydro-1,3,5-triazine) derivatives to explore the relationship between various physicochemical properties and reported binding affinity data on wild-type and mutant-type A16V+S108T. Using the Hansch 2D-quantitative structure-activity relationship method, we obtained a parabolic relationship of hydrophobicity of substituents at the N1-phenyl ring with the wild-type binding affinity data. Hydrophobicity being a key property for wild-type binding affinity data, we found steric factors to be crucial for A16V+S108T mutant resistance. We investigated FlexX, GOLD, Glide and Molegro virtual docking programs and 13 different scoring functions on 10 of the cycloguanil derivatives to evaluate which program was best for reproducing the experimental binding mode and correlating the docking scores with the reported binding affinity data. We identified GOLD, using its GoldScore fitness function, as the most accurate docking program for predicting binding affinity data of cycloguanil derivatives to DHFR and Molegro virtual docker, with its template docking algorithm and MolDock [GRID] scoring function, as most accurate for reproducing the experimental binding mode of a reference ligand that is structurally similar to the cycloguanil derivatives studied. We also report an interaction index which best describes the structure-activity relationships exhibited by these analogs in terms of PfDHFR-TS active site interactions.

Synthesis and in vitro evaluation of 2,4-diamino-1,3,5-triazine derivatives as neuronal voltage-gated sodium channel blockers

Neuronal sodium channels blockers interfere with ion flux and have been used for managing neuropathic pain, epilepsy, and cerebral ischemic disorders. In the current study, four groups of 2,4-diamino-1,3,5-triazine derivatives were synthesized and investigated for their neuronal sodium channels binding activity. 5-Aryl-1,3,5-triazaspiro[5.5]undeca-1,3-diene-2,4-diamines (4a-4j) were found to have the best neuronal sodium binding activity among the four groups of triazines evaluated. Derivatives 4a-4j blocked the sodium channels with IC50 values ranged from 4.0 to 14.7 microM. The result from this study showed that analogues of 2,4-diamino-1,3,5-triazines could be used as leads for the discovery of neuronal sodium channels blockers for managing central nervous system related disorders.

CoMFA and CoMSIA Analyses of Pneumocystis carinii Dihydrofolate Reductase, Toxoplasma gondii Dihydrofolate Reductase, and Rat Liver Dihydrofolate Reductase

In a continuing effort to develop potent and selective dihydrofolate reductase (DHFR) inhibitors against opportunistic pathogens, we developed three-dimensional quantitative structure-activity relationship (3D QSAR) models for the inhibitory activity against Pneumocystis carinii (pc) DHFR, Toxoplasma gondii (tg) DHFR, and rat liver DHFR, using a data set of 179 structurally diverse compounds. To ensure a balanced distribution of more potent and less potent drugs in the training set, three different 90-compound training sets taken from the main data set were used, one for each enzyme, while the remaining 89 compounds in the main data set in each case were used as the test set. Three methods, namely, conventional CoMFA, all orientation search (AOS) CoMFA, and CoMSIA were applied to the training sets. While the AOS CoMFA models gave the best internal predictions (cross-validated r(2) values from the training sets), which are satisfactory, CoMSIA models gave the best external predictions (predictive r(2) values from the test sets). Both AOS CoMFA and CoMSIA analyses were used to construct stdev*coefficient contour maps which can be used to design new compounds in an interactive fashion.

Prediction of dihydrofolate reductase inhibition and selectivity using computational neural networks and linear discriminant analysis

A data set of 345 dihydrofolate reductase inhibitors was used to build QSAR models that correlate chemical structure and inhibition potency for three types of dihydrofolate reductase (DHFR): rat liver (rl), Pneumocystis carinii (pc), and Toxoplasma gondii (tg). Quantitative models were built using subsets of molecular structure descriptors being analyzed by computational neural networks. Neural network models were able to accurately predict log IC(50) values for the three types of DHFR to within +/-0.65 log units (data sets ranged approximately 5.5 log units) of the experimentally determined values. Classification models were also constructed using linear discriminant analysis to identify compounds as selective or nonselective inhibitors of bacterial DHFR (pcDHFR and tgDHFR) relative to mammalian DHFR (rlDHFR). A leave-N-out training procedure was used to add robustness to the models and to prove that consistent results could be obtained using different training and prediction set splits. The best linear discriminant analysis (LDA) models were able to correctly predict DHFR selectivity for approximately 70% of the external prediction set compounds. A set of new nitrogen and oxygen-specific descriptors were developed especially for this data set to better encode structural features, which are believed to directly influence DHFR inhibition and selectivity.

Inhibitors of dihydrofolate reductase in Leishmania and trypanosomes

The protozoan diseases leishmaniasis, Chagas' disease and African trypanosomiasis are major health problems in many countries, particularly developing countries, and there are few drugs available to treat these diseases. Dihydrofolate reductase (DHFR) inhibitors have been used successfully in the treatment of a number of other diseases such as cancer, malaria and bacterial infections; however they have not been used for the treatment of these diseases. This article summarises studies on leishmanial and trypanosomal DHFR inhibitor development and evaluation. Possible mechanisms of resistance to DHFR inhibitors are also discussed.

Ab initio studies of 2,4-diamino triazine and its complexes with ligands: a model for inhibitor-active site interactions of dihydrofolate reductase

The protonation energies of 2,4-diamino triazine, an inhibitor of the therapeutic target dihydrofolate reductase, has been calculated using ab initio (Hartree-Fock) calculations. It is found that N1 (see Fig. 1) exhibits the highest proton affinity (261.6 kcal/mol) by comparison with other inhibitor protonation sites. The energies of binding of the formate ion and formamide (as models for the amino acid residues in the active site of dihydrofolate reductase) to neutral and protonated 2,4-diamino triazine are also obtained. The highest binding energies are featured by the complex formed from a formate attached to the N4 and N1 protonated forms of the triazine. However, as N4 has a comparatively low proton affinity (195.0 kcal/mol), it is unlikely that an interaction of this nature would prevail. On the other hand, the formate-protonated N1 interaction is similar to the structures identified by X-ray crystallography of enzyme-triazine complexes.

A molecular shape analysis and quantitative structure-activity relationship investigation of some triazine-antifolate inhibitors of Leishmania dihydrofolate reductase

Molecular shape analysis (MSA) is used to develop quantitative structure-activity relationships (QSARs) for a set of 45 4,6-diamino-1,2-dihydro-2,2-dimethyl-1-(3-substituted-phenyl)-s-triazine inhibitors of Leishmania major dihydrofolate reductase (DHFR). The MSA-QSARs are equally significant to a QSAR developed by R. G. Booth et al. [1987) J. Med. Chem. 30, 1218) using linear free energy descriptors. However, the MSA-QSARs have the same general form as all other QSARs developed for DHFR inhibitors using MSA. Molecular shape, as represented by common overlap steric volume of each inhibitor with a shape reference standard triazine from the set of 45 compounds, and relative lipophilicity account for the large majority of the variance in inhibition potency as a function of substituent choice. A general method of evaluating the impact of different conformational states of flexible substituents upon the form and significance of MSA-QSARs is developed. The results of applying this method to the 45 triazines indicate that the MSA-QSARs are relatively independent of the type of conformation assigned to the large flexible substituents. It is important to note, however, that the types of substituent conformations used in this analysis cannot necessarily be related to an "active" substituent conformation.