Multiple ligand-binding modes in bacterial R67 dihydrofolate reductase

Summary R67 dihydrofolate reductase (DHFR), a bacterial plasmid-encoded enzyme associated with resistance to the drug trimethoprim, shows neither sequence nor structural homology with the chromosomal DHFR. It presents a highly symmetrical toroidal structure, where four identical monomers contribute to the unique central active-site pore. Two reactants (dihydrofolate, DHF), two cofactors (NADPH) or one of each (R67•DHF•NADPH) can be found simultaneously within the active site, the last one being the reactive ternary complex. As the positioning of the ligands has proven elusive to empirical determination, we addressed the problem from a theoretical perspective. Several potential structures of the ternary complex were generated using the docking programs AutoDock and FlexX. The variability among the final poses, many of which conformed to experimental data, prompted us to perform a comparative scoring analysis and molecular dynamics simulations to assess the stability of the complexes. Analysis of ligand–ligand and ligand–protein interactions along the 4 ns trajectories of eight different structures allowed us to identify important inter-ligand contacts and key protein residues. Our results, combined with published empirical data, clearly suggest that multipe binding modes of the ligands are possible within R67 DHFR. While the pterin ring of DHF and the nicotinamide ring of NADPH assume a stacked endo-conformation at the centre of the pore, probably assisted by V66, Q67 and I68, the tails of the molecules extend towards opposite ends of the cavity, adopting multiple configurations in a solvent rich-environment where hydrogen-bond interactions with K32 and Y69 may play important roles.     

Light activates reduction of methotrexate by NADPH in the ternary complex with Escherichia coli dihydrofolate reductase

Methotrexate (MTX), a strong inhibitor of dihydrofolate reductase (DHFR), has been widely used for chemotherapy for many types of cancer as well as for juvenile rheumatoid arthritis. It mimics folate substrates and binds tightly to the active site of DHFR, perhaps in a conformation close to the transition state of the folate catalyzed reaction. Absorption, fluorescence and ultrasensitive Raman difference spectroscopies show that light-activated MTX reacts with NADPH in the enzyme active site, producing 5,8-dihydromethotrexate (5,8-dihydro-MTX) and NADP+. The reaction, which proceeds with a hydride transfer between C4 (pro-R side) of the nicotinamide ring and N5 of the pteridine ring, is similar to that between folate and NADPH except that the hydride is transferred to C6 in this case. Hence, MTX is catalytically competent in its excited state. Most experiments were performed on the Escherichia coli enzyme, but preliminary studies show that the reaction also occurs with human DHFR.     

A proposed model of Mycobacterium avium complex dihydrofolate reductase and its utility for drug design

A homology model of Mycobacterium avium complex dihydrofolate reductase (MAC DHFR) was constructed on the basis of the X-ray crystal structure of Mycobacterium tuberculosis (Mtb) DHFR. The homology searching of the MAC DHFR resulted in the identification of the Mtb DHFR structure (PDB 1DF7) as the template for the model building. The MAC enzyme sequence was aligned to that of the Mtb counterpart using a modified Needleman and Wunsch methodology. The initial geometry to be modeled was copied from the template, either fully or partially depending on whether the residues were conserved or not, respectively. Using a randomized modeling procedure, 10 independent models of the target protein were built. The cartesian average of all the model structures was then refined using molecular mechanics. The resulting model was assessed for stereochemical quality using a Ramachandran plot and by analyzing the consistency of the model with the experimental data. The structurally and functionally important residues were identified from the model. Further, 5-deazapteridines recently reported as inhibitors of MAC DHFR were docked into the active site of the developed model. All the seven inhibitors used in the docking study have a similar docking mode at the active site. The network of hydrogen bonds around the 2,4-diamino-5-deazapteridine ring was found to be crucial for the binding of the inhibitors with the active site residues. The 5-methyl group of the inhibitors was located in a narrow hydrophobic pocket at the bottom of the active site. The relative values of the three torsion angles of the inhibitors were found to be important for the proper orientation of the inhibitor functional groups into the active site.     

Towards understanding the origins of the different specificities of binding the reduced (NADPH) and oxidised (NADP+) forms of nicotinamide adenine dinucleotide phosphate coenzyme to dihydrofolate reductase

Lactobacillus casei dihydrofolate reductase (DHFR) binds more than a thousand times tighter to NADPH than to NADP⁺. The origins of the difference in binding affinity to DHFR between NADPH and NADP⁺ are investigated in the present study using experimental NMR data and hybrid density functional, B3LYP, calculations. Certain protein residues (Ala 6, Gln 7, Ile 13 and Gly 14) that are directly involved in hydrogen bonding with the nicotinamide carboxamide group show consistent differences in ¹H and ¹⁵N chemical shift between NADPH and NADP⁺ in a variety of ternary complexes. B3LYP calculations in model systems of protein-coenzyme interactions show differences in the H-bond geometry and differences in charge distribution between the oxidised and reduced forms of the nicotinamide ring. GIAO isotropic nuclear shieldings calculated for nuclei in these systems reproduce the experimentally observed trends in magnitudes and signs of the chemical shifts. The experimentally observed reduction in binding of NADP⁺ compared with NADPH results partly from NADP⁺ having to change its nicotinamide amide group from a cis- to a trans-conformation on binding and partly from the oxidised nicotinamide ring of NADP⁺ being unable to take up its optimal hydrogen bonding geometry in its interactions with protein residues.     

Automated flexible ligand docking method and its application for database search

We have developed a new docking program that explores ligand flexibility. This program can be applied to database searches. The program is similar in concept to earlier efforts, but it has been automated and improved. The algorithm begins by selecting an anchor fragment of a ligand. This fragment is protonated, as needed, and then placed in the receptor by the DOCK algorithm, followed by minimization using a simplex method. Finally, the conformations of the remaining parts of the putative ligands are searched by a limited backtrack method and minimized to get the most stable conformation. To test the efficiency of this method, the program was used to regenerate ten ligand–protein complex structures. In all cases, the docked ligands basically reproduced the crystallographic binding modes. The efficiency of this method was further tested by a database search. Ten percent of molecules from the Available Chemicals Directory (ACD) were docked to a dihydrofolate reductase structure. Most of the top-ranking molecules (7 of the top 13 hits) are dihydrofolate or methotrexate derivatives, which are known to be DHFR inhibitors, demonstrating the suitability of this program for screening molecular databases. © 1997 John Wiley & Sons, Inc. J Comput Chem 18 : 1812–1825, 1997     

Dihydrofolate reductase: structural aspects of mechanisms of enzyme catalysis and inhibition

The mechanism of catalytic reduction of folic and dihydrofolic acids to tetrahydrofolate, which proceeds under the action of dihydrofolate reductase and the coenzyme NADPH, is considered. The roles of the enzyme active site, the coenzyme, individual amino acid residues of the enzyme, and water molecules in the catalytic reaction are discussed. Interactions of the enzyme with competitive inhibitors many of which are widely used in medicine as antitumor and antibacterial drugs are examined. The factors controlling the selectivity of inhibitor binding to bacterial forms of the enzyme are analyzed. The results of X-ray diffraction and NMR spectroscopic studies of the structures of the enzyme and its complexes with the substrate and inhibitors are surveyed. The role of specific interactions and molecular motions of the protein and ligands in the mechanism of catalysis and in the binding of the ligands to the enzyme is discussed.     

Docking-based comparative intermolecular contacts analysis as new 3-D QSAR concept for validating docking studies and in silico screening: NMT and GP inhibitors as case studies

The significant role played by docking algorithms in drug discovery combined with their serious pitfalls prompted us to envisage a novel concept for validating docking solutions, namely, docking-based comparative intermolecular contacts analysis (dbCICA). This novel approach is based on the number and quality of contacts between docked ligands and amino acid residues within the binding pocket. It assesses a particular docking configuration on the basis of its ability to align a set of ligands within a corresponding binding pocket in such a way that potent ligands come into contact with binding site spots distinct from those approached by low-affinity ligands and vice versa. In other words, dbCICA evaluates the consistency of docking by assessing the correlation between ligands' affinities and their contacts with binding site spots. Optimal dbCICA models can be translated into valid pharmacophore models that can be used as 3-D search queries to mine structural databases for new bioactive compounds. dbCICA was implemented to search for new inhibitors of candida N-myristoyl transferase as potential antifungal agents and glycogen phosphorylase (GP) inhibitors as potential antidiabetic agents. The process culminated in five selective micromolar antifungal leads and nine GP inhibitory leads.     

Flexible ligand docking using a genetic algorithm

Summary Two computational techniques have been developed to explore the orientational and conformational space of a flexible ligand within an enzyme. Both methods use the Genetic Algorithm (GA) to generate conformationally flexible ligands in conjunction with algorithms from the DOCK suite of programs to characterize the receptor site. The methods are applied to three enzyme-ligand complexes: dihydrofolate reductase-methotrexate, thymidylate synthase-phenolpthalein and HIV protease-thioketal haloperidol. Conformations and orientations close to the crystallographically determined structures are obtained, as well as alternative structures with low energy. The potential for the GA method to screen a database of compounds is also examined. A collection of ligands is evaluated simultaneously, rather than docking the ligands individually into the enzyme.Abbreviations GA genetic algorithm; dhfr, dihydrofolate reductase - mtx methotrexate - ts thymidylate synthase - fen phenolphalein - HIV human immune deficiency virus - hivp HIV protease - thk thioketal haloperidol     

A molecular model of the folate binding site of Pneumocystis carinii dihydrofolate reductase

Summary The inhibition of Pneumocystis carinii dihydrofolate reductase (DHFR) continues to be the major treatment strategy for P. carinii pneumonia (PCP). The design of new anti-pneumocystis agents would be significantly enhanced by the availability of a 3D model of the methotrexate (MTX) binding site of the P. carinii DHFR. However, an X-ray crystal structure of the P. carinii DHFR is not yet available. Alignment of the amino acid sequences of P. carinii and Lactobacillus casei DHFRs indicates that the two proteins show approximately 80% homology among MTX binding-site residues. This high level of homology suggests that the L. casei DHFR MTX binding-site structure could serve as a structural template in developing a model of the P. carinii DHFR MTX binding site. Therefore, the X-ray crystal structure of L. casei DHFR was used to develop a 3D model of the methotrexate binding site of P. carinii DHFR. The molecular modeling and dynamics software QUANTA/CHARMm was used. Amino acid residue mutations and deletions were performed using QUANTA and macromolecular minimizations were achieved with CHARMm. The MTX binding-site residues of L. casei DHFR were mutated to the corresponding residues of the P. carinii DHFR sequence. The resulting structure was extensively minimized. The resulting P. carinii MTX binding-site model showed significant differences in hydrogen-bonding patterns from the L. casei MTX binding site. Also, the P. carinii site is more hydrophobic than the corresponding L. casei site. Analysis of atom-to-atom close contacts between methotrexate and protein binding-site residues indicates that the P. carinii MTX binding-site complex is primarily stabilized by hydrophobic interactions, while the L. casei complex is mostly stabilized by electrostatic interactions. The model is consistent with the observed increased sensitivity of P. carinii DHFR to lipid-soluble inhibitors and provides a rational basis for the design of new anti-pneumocystis agents.     

Stretching exercises — flexibility in dihydrofolate reductase catalysis

As an enzyme, dihydrofolate reductase performs two tasks: transformation of its substrate dihydrofolate or folate to tetrahydrofolate, using NADPH as a cofactor, and regeneration of the enzyme for a subsequent round of catalysis. Studies discussed in this review highlight the role of conformational flexibility in both of these enzymatic functions.     

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.     

Synthesis, dihydrofolate reductase inhibition, anti-proliferative testing, and saturation transfer difference ¹H-NMR study of some new 2-substituted-4,6-diaminopyrimidine derivatives

A series of 2-substituted-4,6-diaminipyrimidine derivatives were synthesized and evaluated for their dihydrofolate reductase (DHFR) inhibitory activity. Saturation transfer difference (STD) (1)H-NMR experiments were used to probe the binding characteristics of the compounds with human DHFR enzyme. The most potent molecules, 12 and 15, in enzyme assay study showed the best results in STD experiments indicating their intimate interaction with the receptor. The docking studies were followed to explain the structural basis for the observed interaction between the ligands and DHFR. All the compounds were also assayed in vitro for their growth inhibitory activity on MCF-7, HepG2, SKHep1, and Hela tumor cell lines. Compounds 16, 17, and 22 demonstrated the most potent in vitro anti-proliferative activity among the others.     

荧光光度法二氢叶酸还原酶抑制剂筛选模型的建立和应用

本文应用二氢叶酸(DHFA)和辅酶Ⅱ(NADPH)的荧光性质,建立了二氢叶酸还原酶(DHFR)活力测定的反应体系,并对酸度等反应条件进行了优化。在该体系中,用双倒数作图法分别测定了二氢叶酸还原酶对二氢叶酸和辅酶Ⅱ的表观米氏常数。将所建立的体系应用于氨甲喋呤,甲氧苄氨嘧啶等已知抑制剂的抑制率的测定,结果满意。     

Fast drug-receptor mapping by site-directed distances: a novel method of predicting new pharmacological leads

The searching and characterization of large chemical databases has recently provoked much interest, particularly with respect to the question of whether any of the compounds in the database could serve as new leads to a compound of pharmacological interest. This paper introduces a fast and novel method of determining whether any of a given series of compounds are able, on geometrical grounds, to interact with an active site of interest. The C program written to implement the method is able to make a qualitative prediction for a given compound in about 1 s per structure (for drug-sized molecules), while still permitting the compound complete conformational freedom. However, the algorithm is sufficiently flexible to permit distance constraints to be placed on the molecules while docking. The test system studied was a family of Baker's triazines docking into the active site of dihydrofolate reductase (DHFR), as defined by a methotrexate/NADPH complex.     

Incorporating dynamics in E. coli dihydrofolate reductase enhances structure-based drug discovery

Escherichia coli dihydrofolate reductase (DHFR) is a long-standing target for enzyme studies. The influence of protein motion on its catalytic cycle is significant, and the conformation of the M20 loop is of particular interest. We present receptor-based pharmacophore models-an equivalent of solvent-mapping of binding hotspots-based on ensembles of protein conformations from molecular dynamics simulations of DHFR.NADPH in both the closed and open conformation of the M20 loop. The optimal models identify DHFR inhibitors over druglike non-inhibitors; furthermore, high-affinity inhibitors of E. coli DHFR are preferentially identified over general DHFR inhibitors. As expected, models resulting from simulations with DHFR in the productive conformation with a closed M20 loop have better performance than those from the open-loop simulations. Model performance improves with increased dynamic sampling, indicating that including a greater degree of protein flexibility can enhance the quest for potent inhibitors. This was compared to the limited conformational sampling seen in crystal structures, which were suboptimal for this application.     

The use of docking-based comparative intermolecular contacts analysis to identify optimal docking conditions within glucokinase and to discover of new GK activators

Glucokinase (GK) is involved in normal glucose homeostasis and therefore it is a valid target for drug design and discovery efforts. GK activators (GKAs) have excellent potential as treatments of hyperglycemia and diabetes. The combined recent interest in GKAs, together with docking limitations and shortages of docking validation methods prompted us to use our new 3D-QSAR analysis, namely, docking-based comparative intermolecular contacts analysis (dbCICA), to validate docking configurations performed on a group of GKAs within GK binding site. dbCICA assesses the consistency of docking by assessing the correlation between ligands’ affinities and their contacts with binding site spots. Optimal dbCICA models were validated by receiver operating characteristic curve analysis and comparative molecular field analysis. dbCICA models were also converted into valid pharmacophores that were used as search queries to mine 3D structural databases for new GKAs. The search yielded several potent bioactivators that experimentally increased GK bioactivity up to 7.5-folds at 10 μM.     

Evaluation of docking/scoring approaches: A comparative study based on MMP3 inhibitors

An increasing number of docking/scoring programs are available that use different sampling and scoring algorithms. A reliable scoring function is the crucial element of such approaches. Comparative studies are needed to evaluate their current capabilities. DOCK4 with force field and PMF scoring as well as FlexX were used to evaluate the predictive power of these docking/scoring approaches to identify the correct binding mode of 61 MMP-3 inhibitors in a crystal structure of stromelysin and also to rank them according to their different binding affinities. It was found that DOCK4/PMF scoring performs significantly better than FlexX and DOCK4/FF in both ranking ligands and predicting their binding modes. Most notably, DOCK4/PMF was the only scoring/docking approach that found a significant correlation between binding affinity and predicted score of the docked inhibitors. However, comparing only those cases where the correct binding mode was identified (scoring highest among sampled poses), FlexX showed the best `fine tuning' (lowest rmsd) in predicted binding modes. The results suggest that not so much the sampling procedure but rather the scoring function is the crucial element of a docking program.     

SAMPL4 & DOCK3.7: lessons for automated docking procedures

The SAMPL4 challenges were used to test current automated methods for solvation energy, virtual screening, pose and affinity prediction of the molecular docking pipeline DOCK 3.7. Additionally, first-order models of binding affinity were proposed as milestones for any method predicting binding affinity. Several important discoveries about the molecular docking software were made during the challenge: (1) Solvation energies of ligands were five-fold worse than any other method used in SAMPL4, including methods that were similarly fast, (2) HIV Integrase is a challenging target, but automated docking on the correct allosteric site performed well in terms of virtual screening and pose prediction (compared to other methods) but affinity prediction, as expected, was very poor, (3) Molecular docking grid sizes can be very important, serious errors were discovered with default settings that have been adjusted for all future work. Overall, lessons from SAMPL4 suggest many changes to molecular docking tools, not just DOCK 3.7, that could improve the state of the art. Future difficulties and projects will be discussed.     

Computational algorithmic and molecular dynamics study of functional and structural impacts of non-synonymous single nucleotide polymorphisms in human DHFR gene

Human dihydrofolate reductase (DHFR) is a conserved enzyme that is central to folate metabolism and is widely targeted in pathogenic diseases as well as cancers. Although studies have reported the fact that genetic mutations in DHFR leads to a rare autosomal recessive inborn error of folate metabolism and drug resistance, there is a lack of an extensive study on how the deleterious non-synonymous SNPs (nsSNPs) disrupt its phenotypic effects. In this study, we aim at discovering the structural and functional consequences of nsSNPs in DHFR by employing a combined computational approach consisting of ten recently developed in silico tools for identification of damaging nsSNPs and molecular dynamics (MD) simulation for getting deeper insights into the magnitudes of damaging effects. Our study revealed the presence of 12 most deleterious nsSNPs affecting the native phenotypic effects, with three (R71T, G118D, Y122D) identified in the co-factor and ligand binding active sites. MD simulations also suggested that these three SNPs particularly Y122D, alter the overall structural flexibility and dynamics of the native DHFR protein which can provide more understandings into the crucial roles of these mutants in influencing the loss of DHFR function.     

Modeling the evolution of drug resistance in malaria

Plasmodium falciparum, the causal agent of malaria, continues to evolve resistance to frontline therapeutics such as chloroquine and sulfadoxine-pyrimethamine. Here we study the amino acid replacements in dihydrofolate reductase (DHFR) that confer resistance to pyrimethamine while still binding the natural DHFR substrate, 7,8-dihydrofolate, and cofactor, NADPH. The chain of amino acid replacements that has led to resistance can be inferred in a computer, leading to a broader understanding of the coevolution between the drug and target. This in silico approach suggests that only a small set of specific active site replacements in the proper order could have led to the resistant strains in the wild today. A similar approach can be used on any target of interest to anticipate likely pathways of future resistance for more effective drug development.