Brominated trimetrexate analogues as inhibitors of pneumocystis carinii and toxoplasma gondii dihydrofolate reductase

Five previously undescribed trimetrexate analogues with bulky 2′-bromo substitution on the phenyl ring were synthesized in order to assess the effect of this structure modification on dihydrofolate reductase inhibition. Condensation of 2-[2-(2-bromo-3,4,5-trimethoxyphenyl)ethyl]-1,l-dicyanopropene with sulfur in the presence of N,N-diethylamine afforded 2-amino-5-(2′-bromo-3′,4′,5′-trimethoxybenzyl)-4-methyl-thiophene-3-carbonitrile ( 15 ) and 2-amino-4-[2-(2′-bromo-3′,4′,5′-trimethoxyphenyl)ethyl]thiophene-3-car-bonitrile ( 16 ). Further reaction with chloroformamidine hydrochloride converted 15 and 16 into 2,4-diamino-5-(2′-bromo-3′,4′,5′-trimethoxybenzyl)-4-methylthieno[2,3-d]pyrimidine ( 8a ) and 2,4-diamino-4-[2-(2′-bromo-3′,4′,5′-trimethoxyphenyl)ethylthieno[2,3-d]pyrimidine ( 12 ) respectively. Other analogues, obtained by reductive coupling of the appropriate 2,4-diaminoquinazoline-6(or 5)-carbonitriles with 2-bromo-3,4,5-trimethoxyaniline, were 2,4-diamino-6-(2′-bromo-3′,4′,5′-trimethoxyanilinomethyl)-5-chloro-quinazoline ( 9a ), 2,4-diamino-5-(2′-bromo-3′,4′,5′-trimethoxyanilinomethyl)quinazoline ( 10 ), and 2,4-diamino-6-(2′-bromo-3′,4′,5′-trimethoxyanilinomethyl)quinazoline ( 11 ). Enzyme inhibition assays revealed that space-filling 2′-bromo substitution in this limited series of dicyclic 2,4-diaminopyrimidines with a 3′,4′,5′-trimethoxyphenyl side chain and a CH₂, CH₂CH₂, or CH₂NH bridge failed to improve species selectivity against either P. carinii or T. gondii dihydrofolate reductase relative to rat liver dihydrofolate reductase.     

Drug design of human dihydrofolate reductase (hDHFR) inhibitors with deep learning

Human dihydrofolate reductase (hDHFR) inhibitors have been a popular research object designed as anti-cancer, anti-malarial, and antibacterial drugs for decades. Besides quantitative structure-activity relationship (QSAR), artificial intelligence (AI) has recently been introduced in numerous professional biological researches, such as molecular drug design and biological activity prediction. In this study, we construct a deep-learning workflow for designing novel hDHFR inhibitors. This workflow mainly includes two networks, as described in the following: The first one is the artificial neural network trained by the molecules selected from the ChEMBL database with experimental hDHFR inhibitions as the label to evaluate the bioactivity of the designed molecular structures constructed from the second network. The second network utilizes conditional generative and adversarial networks (cGAN) to generate candidate molecules with the desired properties. Finally, the obtained candidate molecules with high hDHFR inhibition are subjected to a molecular docking process to verify their binding patterns and affinity strengths inside the active site of hDHFR. In the end, we have successfully identified several novel drug-like compounds with hDHFR inhibition comparable to those currently used in clinics. We present a new tool to effectively design new drug-like compounds through an AI approach.     

Three-dimensional quantitative structure-activity and structure-selectivity relationships of dihydrofolate reductase inhibitors

Three-dimensional quantitative structure-activity relationship (3D-QSAR) modelling using comparative molecular similarity indices analysis (CoMSIA) was applied to a series of 406 structurally diverse dihydrofolate reductase (DHFR) inhibitors from Pneumocystis carinii (pc) and rat liver (rl). X-ray crystal structures of three inhibitors bound to pcDHFR were used for defining the alignment rule. For pcDHFR, a QSAR model containing 6 components was selected using leave-10%-out cross-validation (n= 240, q2 = 0.65), while a 4-component model was selected for rlDHFR (n= 237, q2 = 0.63); both include steric, electrostatic and hydrophobic contributions. The models were validated using a large test set, designed to maximise its diversity and to verify the predictive accuracy of models for extrapolation. The pcDHFR model has r2 = 0.60 and mean absolute error (MAE) = 0.57 for the test set after removing 4 outliers, and the rlDHFR model has r2 = 0.60 and MAE = 0.69 after removing 4 test set outliers. In addition, classification models predicting selectivity for pcDHFR over rlDHFR were developed using soft independent modelling by class analogy (SIMCA), with a selectivity ratio of 2 (IC50,rlDHFR/ IC50,pcDHFR) used for delimiting classes. A 5-component model including steric and electrostatic contributions has cross-validated and test set classification rates of 0.67 and 0.68 for selective inhibitors, and 0.85 and 0.72 for unselective inhibitors. The predictive accuracy of models, together with the identification of important contributions in QSAR and classification models, offer the possibility of designing potent selective inhibitors and estimating their activity prior to synthesis.     

Carbon-deuterium bonds as probes of dihydrofolate reductase

Much effort has been directed toward understanding the contributions of electrostatics and dynamics to protein function and especially to enzyme catalysis. Unfortunately, these studies have been limited by the absence of direct experimental probes. We have been developing the use of carbon-deuterium bonds as probes of proteins and now report the application of the technique to the enzyme dihydrofolate reductase, which catalyzes a hydride transfer and has served as a paradigm for biological catalysis. We observe that the stretching absorption frequency of (methyl- d 3) methionine carbon-deuterium bonds shows an approximately linear dependence on solvent dielectric. Solvent and computational studies support the empirical interpretation of the stretching frequency in terms of local polarity. To begin to explore the use of this technique to study enzyme function and mechanism, we report a preliminary analysis of (methyl- d 3) methionine residues within dihydrofolate reductase. Specifically, we characterize the IR absorptions at Met16 and Met20, within the catalytically important Met20 loop, and Met42, which is located within the hydrophobic core of the enzyme. The results confirm the sensitivity of the carbon-deuterium bonds to their local protein environment, demonstrate that dihydrofolate reductase is electrostatically and dynamically heterogeneous, and lay the foundation for the direct characterization protein electrostatics and dynamics and, potentially, their contribution to catalysis.     

Synthesis and biological evaluation of 5-arylfuro[2,3-d]pyrimidines as novel dihydrofolate reductase inhibitors

A series of about fifty novel 5-arylfuro[2,3-d]pyrimidine derivatives were synthesized as potential inhibitors of dihydrofolate reductase (DHFR) arising from different species. Weak enzyme inhibition was observed for most of the compounds, with only a few reaching IC50 values less than 30 microM. With regards to antibacterial and anti-malarial potency, only seven compounds showed a modest in vitro activity against some bacteria strains and only three products proved significantly active against P. falciparum.     

Molecular orbital study of the ring nitrogen basicity of various dihydrofolate reductase inhibitors

We present molecular orbital (CNDO /2) calculations on the key fragments of different dihydrofolate reductase inhibitors. Distance geometry analysis, physicochemical parameter dependent QSAR , and molecular shape analysis raised some questions regarding the basicity of the ring nitrogen (N1) in these inhibitors and the effect of the various substituents on the basicity. We show that the ring nitrogen N1 of methotrexate has a considerably higher tendency to be protonated compared to that of folic acid. However, not all 2,4-diamino inhibitors are equally basic. Even 2-amino-4-hydroxyquinazoline is sufficiently basic to be protonated, but not the 2,4-diamino-5-sulfonyl derivatives. The pyrimidinium ion seems to be highly solvated, since in spite of its high protonation energy it is strongly basic. Triazines were found to be the most basic of all the classes studied.     

Effect of the structural characteristics of dihydrofolate reductase inhibitors on their metabolic properties

The orientation of dihydropyrimidine derivatives containing podand chains is determined in the model receptor using the CiS algorithm. The orientation of compounds with podand chains is compared with the location of compounds without podand chains in the model receptor. The pharmacophore and antipharmacophore parts of the compounds are analyzed. Amino acid residues responsible for the effective interactions of the compounds with podand chains with the binding site of dihydrofolate reductase (DHFR) are identified using the X-ray diffraction data. The mechanism of the action of tuberculostatic compounds with podand chains in their composition is proposed, which assumes the studied molecules to undergo metabolism by cytochrome P450 isoform 3A4 forming metabolites. The most active are the metabolites without the fragments of podand chains, which interact with DHFR. Therefore, the compounds containing podand chains are prodrugs.     

Synthesis of 5-(4-substituted benzyl)-2,4-diaminoquinazolines as inhibitors of candida albicans dihydrofolate reductase

Several 5-(4-substituted benzyl)-2,4-diaminoquinazolines were prepared as potentially selective inhibitors of Candida albicans dihydrofolate reductase. These compounds were synthesized by a novel route, which included as a key step the displacement of a fluoro group in 2,6-difluorobenzonitrile by the anions of ethyl or methyl 4-substituted phenylacetates. The resultant diarylacetates were saponified and decarboxylated to the 2-fluoro-6-(4-substituted phenyl)benzonitriles. Ring closure of these benzonitriles with guanidine carbonate gave the 5-(4-substituted benzyl)-2,4-diaminoquinazolines.     

毛细管电泳法研究中草药有效成分对二氢叶酸还原酶的抑制作用

利用已建立的二氢叶酸还原酶抑制剂的毛细管电泳法筛选模型,研究了10种中草药有效成分对二氢叶酸还原酶的抑制作用.经实验测定发现木樨草素、表儿荼素、紫杉醇和槲皮素对二氢叶酸还原酶(DHFR)有抑制作用,且抑制效果为木樨草素>紫杉醇>表儿荼素>槲皮素.通过对产物NADP(氧化型辅酶Ⅱ)峰面积的定量测定,计算了4种抑制剂的抑制率.     

Selectivity analysis of 5-(arylthio)-2,4-diaminoquinazolines as inhibitors of Candida albicans dihydrofolate reductase by molecular dynamics simulations

A series of 5-(arylthio)-2,4-diaminoquinazolines are known as selective inhibitors of dihydrofolate reductase (DHFR) from Candida albicans. We have performed docking and molecular dynamics simulations of these inhibitors with C. albicans and human DHFR to understand the basis for selectivity of these agents. Study was performed on a selected set of 10 compounds with variation in structure and activity. Molecular dynamics simulations were performed at 300 K for 45 ps with equilibration for 10 ps. Trajectory data was analyzed on the basis of hydrogen bond interactions, energy of binding and conformational energy difference. The results indicate that hydrogen bonds formed between the compound and the active site residues are responsible for inhibition and higher potency. The selectivity index, i.e the ratio of I₅₀ against human DHFR to I₅₀ against fungal DHFR, is mainly determined by the conformation adapted by the compounds within the active site of two enzymes. Since the human DHFR active site is rigid, the compound is trapped in a higher energy conformation. This energy difference between the two conformations E mainly governs the selectivity against fungal DHFR. The information generated from this analysis of potency and selectivity should be useful for further work in the area of antifungal research.     

Designing specific inhibitors against dihydrofolate reductase of W. bancrofti towards drug discovery for lymphatic filariasis

Structural Chemistry - Lymphatic filariasis (LF) is one among the leading neglected diseases caused by mosquitoe-borne parasite Wuchereria bancrofti to humans. Though drugs are available for the...     

Effect of mutation on enzyme motion in dihydrofolate reductase

Hybrid quantum-classical molecular dynamics simulations of a mutant Escherichia coli dihydrofolate reductase enzyme are presented. Although residue 121 is on the exterior of the enzyme, experimental studies have shown that the mutation of Gly-121 to valine reduces the rate of hydride transfer by a factor of 163. The simulations indicate that the decrease in the hydride transfer rate for the G121V mutant is due to an increase in the free energy barrier. The calculated free energy barrier is higher for the mutant than for the wild-type enzyme by an amount that is consistent with the experimentally observed rate reduction. The calculated transmission coefficients are comparable for the wild-type and mutant enzymes. The simulations suggest that this mutation may interrupt a network of coupled promoting motions proposed to play an important role in DHFR catalysis. This phenomenon has broad implications for protein engineering and drug design.     

Simulations of remote mutants of dihydrofolate reductase reveal the nature of a network of residues coupled to hydride transfer

Recent experimental and theoretical studies have proposed that enzymes involve networks of coupled residues throughout the protein that participate in motions accompanying chemical barrier crossing. Here, we have examined portions of a proposed network in dihydrofolate reductase (DHFR) using quantum mechanics/molecular mechanics simulations. The simulations use a hybrid quantum mechanics‐molecular mechanics approach with a recently developed semiempirical AM1‐SRP Hamiltonian that provides accurate results for this reaction. The simulations reproduce experimentally determined catalytic rates for the wild type and distant mutants of E. coli DHFR, underscoring the accuracy of the simulation protocol. Additionally, the simulations provide detailed insight into how residues remote from the active site affect the catalyzed chemistry, through changes in the thermally averaged properties along the reaction coordinate. The mutations do not greatly affect the structure of the transition state near the bond activation, but we observe differences somewhat removed from the point of C? H cleavage that affect the rate. The mutations have global effects on the thermally averaged structure that propagate throughout the enzyme and the current simulations highlight several interactions that appear to be particularly important. © 2014 Wiley Periodicals, Inc.     

Design,synthesis, and evaluation of gluten peptide analogs as selective inhibitors of human tissue transglutaminase

Recent studies have implicated a crucial role for tissue transglutaminase (TG2) in the pathogenesis of Celiac Sprue, a disorder of the small intestine triggered in genetically susceptible individuals by dietary exposure to gluten. Proteolytically stable peptide inhibitors of human TG2 were designed containing acivicin or alternatively 6-diazo-5-oxo-norleucine (DON) as warheads. In biochemical and cell-based assays, the best of these inhibitors, Ac-PQP-(DON)-LPF-NH(2), was considerably more potent and selective than other TG2 inhibitors reported to date. Selective pharmacological inhibition of extracellular TG2 should be useful in exploring the mechanistic implications of TG2-catalyzed modification of dietary gluten, a phenomenon of considerable relevance in Celiac Sprue.     

Protein flexibility and species specificity in structure-based drug discovery: dihydrofolate reductase as a test system

In structure-based drug discovery, researchers would like to identify all possible scaffolds for a given target. However, techniques that push the boundaries of chemical space could lead to many false positives or inhibitors that lack specificity for the target. Is it possible to broadly identify the appropriate chemical space for the inhibitors and yet maintain target specificity? To address this question, we have turned to dihydrofolate reductase (DHFR), a well-studied metabolic enzyme of pharmacological relevance. We have extended our multiple protein structure (MPS) method for receptor-based pharmacophore models to use multiple X-ray crystallographic structures. Models were created for DHFR from human and Pneumocystis carinii. These models incorporate a fair degree of protein flexibility and are highly selective for known DHFR inhibitors over drug-like non-inhibitors. Despite sharing a highly conserved active site, the pharmacophore models reflect subtle differences between the human and P. carinii forms, which identify species-specific, high-affinity inhibitors. We also use structures of DHFR from Candida albicans as a counter example. The available crystal structures show little flexibility, and the resulting models give poorer performance in identifying species-specific inhibitors. Therapeutic success for this system may depend on achieving species specificity between the related human host and these key fungal targets. The MPS technique is a promising advance for structure-based drug discovery for DHFR and other proteins of biomedical interest.