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Dihydrofolate reductase (DHFR) is ubiquitously present in all living organisms and plays a crucial role in the growth of the fungal pathogen R.solani. Sequence alignment confirmed the evolutionary conservation of the essential lid domain, with the amino acid 'P' within the PEKN lid domain appearing with a frequency of 89.5% in higher organisms and 11.8% in lower organisms. Consequently, a K65P variant was introduced into R.solani DHFR (rDHFR). Subsequent enzymatic kinetics assays were conducted for human DHFR (hDHFR), rDHFR, E. coli DHFR (eDHFR), and the K65P variant. hDHFR exhibited the highest k cat of 0.95 s -1 , followed by rDHFR with 0.14 s -1 , while eDHFR displayed the lowest k cat of 0.09 s -1 . Remarkably, the K65P variant induced a significant reduction in K m , resulting in a 1.8-fold enhancement in catalytic efficiency (k cat /K m ) relative to the wild type. Differential scanning fluorimetry and binding free energy calculations confirmed the enhanced substrate affinity for both folate and NADPH in the K65P variant. These results suggest that the K65P mutation enhances substrate affinity and catalytic efficiency in DHFR, highlighting the evolutionary and functional importance of the K65 residue., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Gene therapies that chronically suppress vascular endothelial growth factor (VEGF) represent a new approach for managing retinal vascular leakage and neovascularization. However, constitutive suppression of VEGF in the eye may have deleterious side effects. Here, we developed a novel strategy to introduce Flt23k, a decoy receptor that binds intracellular VEGF, fused to the destabilizing domain (DD) of Escherichia coli dihydrofolate reductase (DHFR) into the retina. The expressed DHFR(DD)-Flt23k fusion protein is degraded unless "switched on" by administering a stabilizer; in this case, the antibiotic trimethoprim (TMP). Cells transfected with the DHFR(DD)-Flt23k construct expressed the fusion protein at levels correlated with the TMP dose. Stabilization of the DHFR(DD)-Flt23k fusion protein by TMP was able to inhibit intracellular VEGF in hypoxic cells. Intravitreal injection of self-complementary adeno-associated viral vector (scAAV)-DHFR(DD)-Flt23k and subsequent administration of TMP resulted in tunable suppression of ischemia-induced retinal neovascularization in a rat model of oxygen-induced retinopathy (OIR). Hence, our study suggests a promising novel approach for the treatment of retinal neovascularization. Schematic diagram of the tunable system utilizing the DHFR(DD)-Flt23k approach to reduce VEGF secretion. a The schematic shows normal VEGF secretion. b Without the ligand TMP, the DHFR(DD)-Flt23k protein is destabilized and degraded by the proteasome. c In the presence of the ligand TMP, DHFR(DD)-Flt23k is stabilized and sequestered in the ER, thereby conditionally inhibiting VEGF. Green lines indicate the intracellular and extracellular distributions of VEGF. Blue lines indicate proteasomal degradation of the DHFR(DD)-Flt23k protein. Orange lines indicate the uptake of cell-permeable TMP. TMP, trimethoprim; VEGF, vascular endothelial growth factor; ER, endoplasmic reticulum.

The enzyme dihydrofolate reductase (DHFR) catalyzes NADPH dependent reduction of dihydrofolate to tetrahydrofolate. It plays a crucial role in the DNA synthesis. The investigation of evolution of DHFR generates immense curiosity. It aids in predicting how the enzyme has adapted to the surroundings of various cell types. In spite of great similarity in the structure of E. coli DHFR and human DHFR, their primary sequences are divergent to a great extent, which is evident in variations in the kinetics mechanism of their catalysis. In presence of physiological levels of ligands, they possess distinct kinetics and different rate limiting steps. We have reviewed the process of their unfolding and refolding, their behaviour in denaturing conditions and in presence of various chaperones. Although there is structural similarity between these two homologous enzymes yet they have established distinct mechanisms to accomplish the coequal functions.

Dihydrofolate (DHF) reductase coded by a plasmid of the extremely halophilic archaeon Haloarcula japonica strain TR-1 (HjDHFR P1) shows moderate halophilicity on enzymatic activity at pH 6.0, although there is no significant effect of NaCl on its secondary structure. To elucidate the salt-activation and -inactivation mechanisms of this enzyme, we investigated the effects of pH and salt concentration, deuterium isotope effect, steady-state kinetics, and rapid-phase ligand-binding kinetics. Enzyme activity was increased eightfold by the addition of 500 mM NaCl at pH 6.0, fourfold by 250 mM at pH 8.0, and became independent of salt concentration at pH 10.0. Full isotope effects observed at pH 10.0 under 0-1000 mM NaCl indicated that the rate of hydride transfer, which was the rate-determining step at the basic pH region, was independent of salt concentration. Conversely, rapid-phase ligand-binding experiments showed that the amplitude of the DHF-binding reaction increased and the tetrahydrofolate (THF)-releasing rate decreased with increasing NaCl concentration. These results suggested that the salt-activation mechanism of HjDHFR P1 is via the population change of the anion-unbound and anion-bound conformers, which are binding-incompetent and -competent conformations for DHF, respectively, while that of salt inactivation is via deceleration of the THF-releasing rate, which is the rate-determining step at the neutral pH region.

Protein-ligand interaction is often characterized using polarization transfer by the intermolecular nuclear Overhauser effect (NOE). For such NOE experiments, hyperpolarization of nuclear spins presents the opportunity to increase the spin magnetization, which is transferred, by several orders of magnitude. Here, folic acid, a ligand of dihydrofolate reductase (DHFR), was hyperpolarized on (1)H spins using dissolution dynamic nuclear polarization (D-DNP). Mixing hyperpolarized ligand with protein resulted in observable increases in protein (1)H signal predominantly in the methyl group region of the spectra. Using (13)C single quantum selection in a series of one-dimensional spectra, the carbon chemical shift ranges of the corresponding methyl groups can be elucidated. Signals observed in these hyperpolarized spectra could be confirmed using 3D isotope filtered NOESY spectra, although the hyperpolarized spectra were obtained in single scans. By further correlating the signal intensities observed in the D-DNP experiments with the occurrence of short distances in the crystal structure of the protein-ligand complex, the observed methyl proton signals could be matched to the chemical shifts of six amino acids in the active site of DHFR-folic acid binary complex. These data demonstrate that (13)C chemical shift selection of protein resonances, combined with the intrinsic selectivity towards magnetization originating from the initially hyperpolarized spins, can be used for site specific characterization of protein-ligand interactions.

Occasionally, a mutation in an exposed loop region causes a significant change in protein function and/or stability. A single mutation Gly67Val of E. coli dihydrofolate reductase (DHFR) in the exposed CD loop is such an example. We have carried out the chemical shift assignments for H(N), N(H), C(α) and C(β) atoms of the Gly67Val mutant of E. coli DHFR complexed with folate at pH 7.0, 35 °C, and then evaluated the H(N), N(H), C(α) and C(β) chemical shift changes caused by the mutation. The result indicates that, while the overall secondary structure remains the same, the single mutation Gly67Val causes site-specific conformational changes of the polypeptide backbone restricted around the adenosine-binding subdomain (residues 38-88) and not in the distant catalytic domain.

The effects of salt on the structure, stability, and enzymatic function of a novel dihydrofolate reductase (HjDHFR P1) from a hyperhalophilic archaeon, Haloarcula japonica strain TR-1 living in a Japanese saltern, were studied using ultraviolet absorption, circular dichroism (CD), and fluorescence spectroscopy. HjDHFR P1 had a partial structure at pH 8.0 in the absence of NaCl, and the addition of NaCl (0-500 mM concentration) induced significant structural formation to HjDHFR P1. The addition of NADPH, which is a coenzyme for its catalytic reaction, and lowering the pH from 8 to 6 also induced the same CD change, indicating the formation of the NADPH-binding site in HjDHFR P1. The NaCl dependence of thermal and urea-induced unfolding measurements suggested that protein stability increased depending on NaCl concentration regardless of structural formation, and HjDHFR P1 achieved the same stability as Escherichia coli DHFR at 750 mM NaCl. Halophilic characteristics were also observed for enzymatic function, although its structure had already formed under the conditions that enzymatic activity was measured at due to the presence of NADPH. These results suggest that the halophilic mechanism on structural stability and function was caused by factors other than structural formation, which are suggested to be the contributions of preferential interactions between the protein and salt ions and the specific binding of salt ions.

In order to elucidate the molecular adaptation mechanisms of enzymes to the high hydrostatic pressure of the deep sea, we cloned, purified, and characterized more than ten dihydrofolate reductases (DHFRs) from bacteria living in deep-sea and ambient atmospheric pressure environments. The nucleotide and amino acid sequences of these DHFRs indicate the deep-sea bacteria are adapted to their environments after the differentiation of their genus from ancestors inhabiting atmospheric pressure environments. In particular, the backbone structure of the deep-sea DHFR from Moritella profunda (mpDHFR) almost overlapped with the normal homolog from Escherichia coli (ecDHFR). Thus, those of other DHFRs would also overlap on the basis of their sequence similarities. However, the structural stability of both DHFRs was quite different: compared to ecDHFR, mpDHFR was more thermally stable but less stable against urea and pressure unfolding. The smaller volume changes due to unfolding suggest that the native structure of mpDHFR has a smaller cavity and/or enhanced hydration compared to ecDHFR. High hydrostatic pressure reduced the enzymatic activity of many DHFRs, but three deep-sea DHFRs and the D27E mutant of ecDHFR exhibited pressure-dependent activation. The inverted activation volumes from positive to negative values indicate the modification of their structural dynamics, conversion of the rate-determining step of the enzymatic reaction, and different contributions of the cavity and hydration to the transition-state structure. Since the cavity and hydration depend on amino acid side chains, DHFRs would adapt to the deep-sea environment by regulating the cavity and hydration by substituting their amino acid side chains without altering their backbone structure. The results of this study clearly indicate that the cavity and hydration play important roles in the adaptation of enzymes to the deep-sea environment.

Human dihydrofolate reductase-like 1 (DHFRL1) has been identified as a second human dihydrofolate reductase (DHFR) enzyme. Although DHFRL1 have high sequence homology with human DHFR, dihydrofolate (DHF) exhibits a lowered binding affinity to DHFRL1 and the corresponding molecular mechanism is still unknown. To address this question, we studied the binding of DHF to DHFRL1 and DHFR by using molecular dynamics simulation. Moreover, to investigate the role the 24th residue of DHFR/DHFRL1 plays in DHF binding, R24W DHFRL1 mutant was also studied. The van der Waals interaction are more crucial for the total DHF binding energies, while the difference between the DHF binding energies of human DHFR and DHFRL1 can be attributed to the electrostatic interaction and the polar desolvation free energy.More specifically, lower DHF affinity to DHFRL1 can be mainly attributed to the reduction of net electrostatic interactions of residues Arg32 and Gln35 of DHFRL1 with DHF as being affected by Arg24. The side chain of Arg24 in DHFRL1 can extend deeply into the binding sites of DHF and NADPH, and disturb the DHF binding by steric effect, which rarely happens in human DHFR and R24W DHFRL1 mutant. Additionally, the conformation of loop I in DHFRL1 was also studied in this work. Interestingly, the loop conformation resemble to normal closed state of Escherichia coli DHFR other than the closed state of human DHFR. We hope this work will be useful to understand the general characteristics of DHFRL1.

Dihydrofolate reductase from the deep-sea bacterium Moritella profunda (MpDHFR) has been (13)C/(15)N isotopically labelled and purified. Here, we report the aliphatic (1)H, (13)C and (15)N resonance assignments of MpDHFR in complex with NADP(+) and folate. The spectra of MpDHFR suggest considerably greater conformational heterogeneity than is seen in the closely related DHFR from Escherichia coli.

Klebsiella pneumoniae strain DF12SA (HQ114261) was isolated from diabetic foot wounds. The strain showed resistance against ampicillin, kanamycin, gentamicin, streptomycin, spectinomycin, trimethoprim, tetracycline, meropenem, amikacin, piperacillin/tazobactam, augmentin, co-trimoxazole, carbapenems, penicillins and cefoperazone, and was sensitive to clindamycin. Molecular characterization of the multidrug-resistance phenotype revealed the presence of a class 1 integron containing two genes, a dihydrofolate reductase (DHFR) (PF00186), which confers resistance to trimethoprim; and aminoglycoside adenyltransferase (AadA) (PF01909), which confers resistance to streptomycin and spectinomycin. A class 1 integron in K. pneumoniae containing these two genes was present in eight (18.18%) out of 44 different diabetic foot ulcer (DFU) patients. Hence, there is a need to develop therapeutics that inhibit growth of multidrug resistant K. pneumoniae in DFU patients and still achieve amputation control. Am attempt was made to create a 3D model and find a suitable inhibitor using an in silico study. Rational drug design/testing requires crystal structures for DHFR and AadA. However, the structures of DHFR and AadA from K. pneumoniae are not available. Modelling was performed using Swiss Model Server and Discovery Studio 3.1. The PDBSum server was used to check stereo chemical properties using Ramachandran plot analysis of modeled structures. Clindamycin was found to be suitable inhibitor of DHFR and AadA. A DockingServer based on Autodock & Mopac was used for docking calculations. The amino acid residues Ser(32), Ile(46), Glu(53), Gln(54), Phe(57), Thr(72), Met(76), Val(78), Leu(79), Ser(122), Tyr(128), Ile(151) in case of DHFR and Phe(34), Asp(60), Arg(63), Gln(64), Leu(68), Glu(87), Thr(89), Val(90) for AadA were found to be responsible for positioning clindamycin into the active site. The study identifies amino acid residues crucial to 'DHFR and AadA -drug' and 'DHFR and AadA -inhibitor' interactions that might be useful in the ongoing search for a versatile DHFR and AadA -inhibitor.

Leishmaniasis, a multi-faceted ethereal disease is considered to be one of the World's major communicable diseases that demands exhaustive research and control measures. The substantial data on these protozoan parasites has not been utilized completely to develop potential therapeutic strategies against Leishmaniasis. Dihydrofolate reductase thymidylate synthase (DHFR-TS) plays a major role in the infective state of the parasite and hence the DHFR-TS based drugs remains of much interest to researchers working on Leishmaniasis. Although, crystal structures of DHFR-TS from different species including Plasmodium falciparum and Trypanosoma cruzi are available, the experimentally determined structure of the Leishmania major DHFR-TS has not yet been reported in the Protein Data Bank. A high quality three dimensional structure of L.major DHFR-TS has been modeled through the homology modeling approach. Carefully refined and the energy minimized structure of the modeled protein was validated using a number of structure validation programs to confirm its structure quality. The modeled protein structure was used in the process of structure based virtual screening to figure out a potential lead structure against DHFR TS. The lead molecule identified has a binding affinity of 0.51 nM and clearly follows drug like properties.

Nanoparticle (NP)-based targeted drug delivery involves cell-specific targeting followed by a subsequent therapeutic action from the therapeutic carried by the NP system. NPs conjugated with methotrexate (MTX), a potent inhibitor of dihydrofolate reductase (DHFR) localized in cytosol, have been under investigation as a delivery system to target cancer cells to enhance the therapeutic index of methotrexate, which is otherwise non-selectively cytotoxic. Despite improved therapeutic activity from MTX-conjugated NPs in vitro and in vivo, the therapeutic action of these conjugates following cellular entry is poorly understood; in particular it is unclear whether the therapeutic activity requires release of the MTX. This study investigates whether MTX must be released from a nanoparticle in order to achieve the therapeutic activity. We report herein light-controlled release of methotrexate from a dendrimer-based conjugate and provide evidence suggesting that MTX still attached to the nanoconjugate system is fully able to inhibit the activity of its enzyme target and the growth of cancer cells.

The E28D variant of dihydrofolate reductase from Moritella profunda was generated and found to have the same K (i) (within error) for the competitive inhibitor trimethoprim as the wild type enzyme. Contrary to a previous claim in the literature, Glu 28 is therefore not the cause of the reduced affinity for trimethoprim relative to dihydrofolate reductase from Escherichia coli.

Design and discovery of new potential inhibitors of Plasmodium falciparum dihydrofolate reductase (PfDHFR), equally active against both the wild-type and mutant strains, is urgently needed. In this study, a computer-aided molecular design approach that involved ab initio molecular orbital and density functional theory calculations, along with molecular electrostatic potential analysis, and molecular docking studies was employed to design 15 1H-imidazole-2,4-diamine derivatives as potential inhibitors of PfDHFR enzyme. Visual inspection of the binding modes of the compounds demonstrated that they all interact, via H-bond interactions, with key amino acid residues (Asp54, Ileu/Leu164, Asn/Ser108 and Ile14) similar to those of WR99210 (3) in the active site of the enzymes used in the study. These interactions are known to be essential for enzyme inhibition. These compounds showed better or comparable binding affinities to that of the bound ligand (WR99210). In silico toxicity predictions, carried out using TOPKAT software, also indicated that the compounds are non-toxic.

Dihydrofolate reductase (DHFR) has been used successfully as a drug target in the area of anti-bacterial, anti-cancer and anti-malarial therapy. It also acts as a drug target for Leishmaniasis. Inhibition of DHFR leads to cell death through lack of thymine (nucleotide metabolism). Although the crystal structures of Leishmania major and Trypanosoma cruzi DHFR-thymidylate synthase (TS) have been resolved, to date there is no three-dimensional (3D)-structural information on DHFR-TS of Leishmania donovani chagasi, which causes visceral leishmaniasis. Our aim in this study was to model the 3D structure of L. donovani chagasi DHFR-TS, and to investigate the structural requirements for its inhibition. In this paper we describe a highly refined homology model of L. donovani chagasi DHFR-TS based on available crystallographic structures by using the Homology module of Insight II. Structural refinement and minimization of the generated L. donovani chagasi DHFR-TS model employed the Discover 3 module of Insight II and molecular dynamic simulations. The model was further validated through use of the PROCHECK, Verify_3D, PROSA, PSQS and ERRAT programs, which confirm that the model is reliable. Superimposition of the model structure with the templates L. major A chain, L. major B chain And T. cruzi A chain showed root mean square deviations of 0.69 A, 0.71 A and 1.11 A, respectively. Docking analysis of the L. donovani chagasi DHFR-TS model with methotrexate enabled us to identify specific residues, viz. Val156, Val30, Lys95, Lys75 and Arg97, within the L. donovani chagasi DHFR-TS binding pocket, that play an important role in ligand or substrate binding. Docking studies clearly indicated that these five residues are important determinants for binding as they have strong hydrogen bonding interactions with the ligand.

Comparative molecular field analysis (CoMFA) and quantum chemical calculations were performed on cycloguanil (Cyc) derivatives of the wild type and the quadruple mutant (Asn51Ile, Cys59Arg, Ser108Asn, Ile164Leu) of Plasmodium falciparum dihydrofolate reductase (PfDHFR). The represented CoMFA models of wild type (r(2) = 0.727 and r(2) = 0.985) and mutant type (r(2) = 0.786 and r(2) = 0.979) can describe the differences of the Cyc structural requirements for the two types of PfDHFR enzymes and can be useful to guide the design of new inhibitors. Moreover, the obtained particular interaction energies between the Cyc and the surrounding residues in the binding pocket indicated that Asn108 of mutant enzyme was the cause of Cyc resistance by producing steric clash with p-Cl of Cyc. Consequently, comparing the energy contributions with the potent flexible WR99210 inhibitor, it was found that the key mutant residue, Asn108, demonstrates attractive interaction with this inhibitor and some residues, Leu46, Ile112, Pro113, Phe116, and Leu119, seem to perform as second binding site with WR99210. Therefore, quantum chemical calculations can be useful for investigating residue interactions to clarify the cause of drug resistance.

We established a novel strategy for preparing uniformly stable isotope-labeled proteins by using suspension-cultured plant cells and an inducible virus vector encoding the research target. By using this new method, we demonstrated the expression of three proteins, namely, Escherichia coli dihydrofolate reductase (DHFR), chicken calmodulin (CaM), and porcine protein kinase C-dependent protein phosphatase-1 inhibitor with a molecular mass of 17-kDa (CPI-17). In addition, we successfully expressed bovine pancreatic trypsin inhibitor (BPTI), which contains three pairs of disulfide bonds, as the soluble form. In the most efficient case, as little as 50 ml culture yielded 3-4 mg (15)N-labeled protein suitable for NMR experiments. The (1)H-(15)N HSQC spectra of all of these proteins clearly indicated that their structures were identical to those of their counterparts reported previously. Thus, the present results suggest that our novel protocol is a potential method for NMR sample preparation.

This study employed surface-based properties for use in the superimposition of three series of molecules. The properties used were derived from semiempirical molecular orbital calculations and can be related to the physics of intermolecular interactions. In each case, the superimposition of the compounds was within 0.6 A of the experimental overlay. The superimposition cases presented differing levels of involvement of electrostatic interactions, and in only one case did shape similarity provide the best overlay. Two test compounds were applied to an example exploring non-nucleoside HIV-1 reverse transcriptase inhibitors and only one of these compounds overlaid in the same manner as their crystal structure complexes. This served to highlight the need for molecules to occupy the same region of space when employing this technique. Nevertheless, the method can be used to generate pharmacophores and ultimately could be used to interrogate databases for molecules that match the key surface properties, thus allowing scaffold hopping.

A better understanding of how salt affects enzyme activity can be gained via NMR studies of binary hvDHFR1:folate complex. Chemical shift assignments of the 17.9 kDa enzyme with bound substrate prepare the way for ongoing research of the effects of salt on enzyme flexibility through relaxation studies.

Elucidation of the molecular basis of the stability of enzymes from extremophilic organisms is of fundamental importance for various industrial applications. Due to the wealth of structural data from various species, dihydrofolate reductase (DHFR, EC 1.5.1.3) provides an excellent model for systematic investigations. In this report, DHFR from alkaliphilic Bacillus halodurans C-125 was cloned and expressed in E. coli. Functional analyses revealed that BhDHFR exhibits the most alkali-stable phenotype of DHFRs characterized so far. Optimal enzyme activity was observed in a slightly basic pH region ranging from 7.25 to 8.75. Alkali-stability is associated with a remarkable resistance to elevated temperatures (half-life of 60 min at 52.5 degrees C) and to high concentrations of urea (up to 3 M). Although the secondary structure shows distinct similarities to those of mesophilic DHFR molecules, BhDHFR exhibits molecular features contributing to its alkaliphilic properties. Interestingly, the unique phenotype is diminished by C-terminal addition of a His-tag sequence. Therefore, His-tag-derivatized BhDHFR offers the opportunity to obtain deeper insights into the specific mechanisms of alkaliphilic adaption by comparison of the three dimensional structure of both BhDHFR molecules.

We introduce PHASE, a highly flexible system for common pharmacophore identification and assessment, 3D QSAR model development, and 3D database creation and searching. The primary workflows and tasks supported by PHASE are described, and details of the underlying scientific methodologies are provided. Using results from previously published investigations, PHASE is compared directly to other ligand-based software for its ability to identify target pharmacophores, rationalize structure-activity data, and predict activities of external compounds.

Alignment of multiple ligands based on shared pharmacophoric and pharmacosteric features is a long-recognized challenge in drug discovery and development. This is particularly true when the spatial overlap between structures is incomplete, in which case no good template molecule is likely to exist. Pair-wise rigid ligand alignment based on linear assignment (the LAMDA algorithm) has the potential to address this problem (Richmond et al. in J Mol Graph Model 23:199-209, 2004). Here we present the version of LAMDA embodied in the GALAHAD program, which carries out multi-way alignments by iterative construction of hypermolecules that retain the aggregate as well as the individual attributes of the ligands. We have also generalized the cost function from being purely atom-based to being one that operates on ionic, hydrogen bonding, hydrophobic and steric features. Finally, we have added the ability to generate useful partial-match 3D search queries from the hypermolecules obtained. By running frozen conformations through the GALAHAD program, one can utilize the extended version of LAMDA to generate pharmacophores and pharmacosteres that agree well with crystal structure alignments for a range of literature datasets, with minor adjustments of the default parameters generating even better models. Allowing for inclusion of partial match constraints in the queries yields pharmacophores that are consistently a superset of full-match pharmacophores identified in previous analyses, with the additional features representing points of potentially beneficial interaction with the target.

A method is presented for enumerating a large number of isosteric analogues of a ligand from a known protein-ligand complex structure and then rapidly calculating an estimate of their binding energies. This approach takes full advantage of the observed crystal structure, by reusing the atomic co-ordinates determined experimentally for one ligand, to approximate those of similar compounds that have approximately the same shape. By assuming that compounds with similar shapes adopt similar binding poses, and that entropic and protein flexibility effects are approximately constant across such an isosteric series ("the frozen ligand approximation"), it is possible to order their binding affinities relatively accurately. Additionally, the constraint that the atomic coordinates are invariant allows for a dramatic simplification in the Poisson-Boltzmann method used to calculation the electrostatic component of the binding energy. This algorithmic improvement allows for the calculation of tens of thousands of binding energies per second for drug-like molecules, enabling this technique to be used in screening large virtual libraries of isosteric analogues. Most significantly, this procedure is shown to be able to reproduce SAR effects of subtle medicinal chemistry substitutions. Finally, this paper reports the results of the proposed methodology on seven model systems; dihydrofolate reductase, Lck kinase, ribosome inactivating protein, L: -arabinose binding protein, neuraminidase, HIV-1 reverse transcriptase and COX-2.

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.

The popular model-free approach to analyze NMR relaxation measurements has been examined using artificial amide (15)N relaxation data sets generated from a 10 nanosecond molecular dynamics trajectory of a dihydrofolate reductase ternary complex in explicit water. With access to a detailed picture of the underlying internal motions, the efficacy of model-free analysis and impact of model selection protocols on the interpretation of NMR data can be studied. In the limit of uncorrelated global tumbling and internal motions, fitting the relaxation data to the model-free models can recover a significant amount of quantitative information on the internal dynamics. Despite a slight overestimation, the generalized order parameter is quite accurately determined. However, the model-free analysis appears to be insensitive to the presence of nanosecond time scale motions with relatively small magnitude. For such cases, the effective correlation time can be significantly underestimated. As a result, proteins appear to be more rigid than they really are. The model selection protocols have a major impact on the information one can reliably obtain. The commonly employed protocol based on step-up hypothesis testing has severe drawbacks of oversimplification and underfitting. The consequences are that the order parameter is more severely overestimated and the correlation time more severely underestimated. Instead, model selection based on Bayesian Information Criteria (BIC), recently introduced to the model-free analysis by d'Auvergne and Gooley (2003), provides a better balance between bias and variance. More appropriate models can be selected, leading to improved estimate of both the order parameter and correlation time. In addition, the computational cost is significantly reduced and subjective parameters such as the significance level are unnecessary.

A general method for stable-isotope labeling of large proteins is introduced and applied for studies of the E. coli GroE chaperone proteins by solution NMR. In addition to enabling the residue-specific (15)N-labeling of proteins on a highly deuterated background, it is also an efficient approach for uniform labeling. The method meets the requirements of high-level deuteration, minimal cross-labeling and high protein yield, which are crucial for NMR studies of structures with sizes above 150 kDa. The results obtained with the new protocol are compared to other strategies for protein labeling, and evaluated with regard to the influence of external factors on the resulting isotope labeling patterns. Applications with the GroE system show that these strategies are efficient tools for studies of structure, dynamics and intermolecular interactions in large supramolecular complexes, when combined with TROSY- and CRINEPT-based experimental NMR schemes.

FLEXX-PHARM, an extended version of the flexible docking tool FLEXX, allows the incorporation of information about important characteristics of protein-ligand binding modes into a docking calculation. This information is introduced as a simple set of constraints derived from receptor-based type pharmacophore features. The constraints are determined by selected FLEXX interactions and inclusion volumes in the receptor active site. They guide the docking process to produce a set of docking solutions with particular properties. By applying a series of look-ahead checks during the flexible construction of ligand fragments within the active site, FLEXX-PHARM determines which partially built docking solutions can potentially obey the constraints. Solutions that will not obey the constraints are deleted as early as possible, often decreasing the calculation time and enabling new docking solutions to emerge. FLEXX-PHARM was evaluated on various individual protein-ligand complexes where the top docking solutions generated by FLEXX had high root mean square deviations (RMSD) from the experimentally observed binding modes. FLEXX-PHARM showed an improvement in the RMSD of the top solutions in most cases, along with a reduction in run time. We also tested FLEXX-PHARM as a database screening tool on a small dataset of molecules for three target proteins. In two cases, FLEXX-PHARM missed one or two of the active molecules due to the constraints selected. However, in general FLEXX-PHARM maintained or improved the enrichment shown with FLEXX, while completing the screen in considerably less run time.

R67 dihydrofolate reductase (DHFR) is a novel enzyme that confers resistance to the antibiotic trimethoprim. The crystal structure of R67 DHFR displays a toroidal structure with a central active-site pore. This homotetrameric protein exhibits 222 symmetry, with only a few residues from each chain contributing to the active site, so related sites must be used to bind both substrate (dihydrofolate) and cofactor (NADPH) in the productive R67 DHFR.NADPH.dihydrofolate complex. Whereas the site of folate binding has been partially resolved crystallographically, an interesting question remains: how can the highly symmetrical active site also bind and orient NADPH for catalysis? To model this ternary complex, we employed DOCK and SLIDE, two methods for docking flexible ligands into proteins using quite different algorithms. The bound pteridine ring of folate (Fol I) from the crystal structure of R67 DHFR was used as the basis for docking the nicotinamide-ribose-Pi (NMN) moiety of NADPH. NMN was positioned by both DOCK and SLIDE on the opposite side of the pore from Fol I, where it interacts with Fol I at the pore's center. Numerous residues serve dual roles in binding. For example, Gln 67 from both the B and D subunits has several contacts with the pteridine ring, while the same residue from the A and C subunits has several contacts with the nicotinamide ring. The residues involved in dual roles are generally amphipathic, allowing them to make both hydrophobic and hydrophilic contacts with the ligands. The result is a 'hot spot' binding surface allowing the same residues to co-optimize the binding of two ligands, and orient them for catalysis.

Genetic algorithms have properties which make them attractive in de novo drug design. Like other de novo design programs, genetic algorithms require a method to reduce the enormous search space of possible compounds. Most often this is done using information from known ligands. We have developed the ADAPT program, a genetic algorithm which uses molecular interactions evaluated with docking calculations as a fitness function to reduce the search space. ADAPT does not require information about known ligands. The program takes an initial set of compounds and iteratively builds new compounds based on the fitness scores of the previous set of compounds. We describe the particulars of the ADAPT algorithm and its application to three well-studied target systems. We also show that the strategies of enhanced local sampling and re-introducing diversity to the compound population during the design cycle provide better results than conventional genetic algorithm protocols.

A general method is presented for magnetic field alignment of proteins in solution. By tagging a target protein with calmodulin saturated with paramagnetic lanthanide ions it is possible to measure substantial residual dipolar couplings (RDC) whilst minimising the effects of pseudocontact shifts on the target protein. A construct was made consisting of a calmodulin-binding peptide (M13 from sk-MLCK) attached to a target protein, dihydrofolate reductase in this case. The engineered protein binds tightly to calmodulin saturated with terbium, a paramagnetic lanthanide ion. By using only a short linker region between the M13 and the target protein, some of the magnetic field alignment induced in the CaM(Tb3+)4 is effectively transmitted to the target protein (DHFR). 1H-15N HSQC IPAP experiments on the tagged complex containing 15N-labelled DHFR-M13 protein and unlabelled CaM(Tb3+)4 allow one to measure RDC contributions in the aligned complex. RDC values in the range +4.0 to -7.4 Hz were measured at 600 MHz. Comparisons of 1H-15N HSQC spectra of 15N-DHFR-M13 alone and its complexes with CaM(Ca2+)4 and CaM(Tb3+)4 indicated that (i) the structure of the target protein is not affected by the complex formation and (ii) the spectra of the target protein are not seriously perturbed by pseudocontact shifts. The use of a relatively large tagging group (CaM) allows us to use a lanthanide ion with a very high magnetic susceptibility anisotropy (such as Tb3+) to give large alignments while maintaining relatively long distances from the target protein nuclei (and hence giving only small pseudocontact shift contributions).

Free energy force field (FEFF) 3D-QSAR analysis was used to construct ligand-receptor binding models for a set of 18 structurally diverse antifolates including pyrimethamine, cycloguanil, methotrexate, aminopterin and trimethoprim, and 13 pyrrolo[2,3-d]pyrimidines. The molecular target ('receptor') used was a 3D-homology model of a specific mutant type of Plasmodium falciparum (Pf) dihydrofolate reductase (DHFR). The dependent variable of the 3D-QSAR models is the IC50 inhibition constant for the specific mutant type of PfDHFR. The independent variables of the 3D-QSAR models (the descriptors) are scaled energy terms of a modified first-generation AMBER force field combined with a hydration shell aqueous solvation model and a collection of 2D-QSAR descriptors often used in QSAR studies. Multiple temperature molecular dynamics simulation (MDS) and the genetic function approximation (GFA) were employed using partial least square (PLS) and multidimensional linear regressions as the fitting functions to develop FEFF 3D-QSAR models for the binding process. The significant FEFF energy terms in the best 3D-QSAR models include energy contributions of the direct ligand-receptor interaction. Some changes in conformational energy terms of the ligand due to binding to the enzyme are also found to be important descriptors. The FEFF 3D-QSAR models indicate some structural features perhaps relevant to the mechanism of resistance of the PfDHFR to current antimalarials. The FEFF 3D-QSAR models are also compared to receptor-independent (RI) 4D-QSAR models developed in an earlier study and subsequently refined using recently developed generalized alignment rules.

A non-covalent interaction force field model derived from the partition coefficient of 1-octanol/water solubility is described. This model, HINT for Hydropathic INTeractions, is shown to include, in very empirical and approximate terms, all components of biomolecular associations, including hydrogen bonding, Coulombic interactions, hydrophobic interactions, entropy and solvation/desolvation. Particular emphasis is placed on: (1) demonstrating the relationship between the total empirical HINT score and free energy of association, deltaGinteraction; (2) showing that the HINT hydrophobic-polar interaction sub-score represents the energy cost of desolvation upon binding for interacting biomolecules; and (3) a new methodology for treating constrained water molecules as discrete independent small ligands. An example calculation is reported for dihydrofolate reductase (DHFR) bound with methotrexate (MTX). In that case the observed very tight binding, deltaGinteraction < or = -13.6 kcal mol(-1), is largely due to ten hydrogen bonds between the ligand and enzyme with estimated strength ranging between -0.4 and -2.3 kcal mol(-1). Four water molecules bridging between DHFR and MTX contribute an additional -1.7 kcal mol(-1) stability to the complex. The HINT estimate of the cost of desolvation is +13.9 kcal mol(-1).

Model-free analysis has been extensively used to extract information on motions in proteins over a wide range of timescales from NMR relaxation data. We present a detailed analysis of the effects of rotational anisotropy on the model-free analysis of a ternary complex for dihydrofolate reductase (DHFR). Our findings show that the small degree of anisotropy exhibited by DHFR (Dparallel/Dperpendicular = 1.18) introduces erroneous motional models, mostly exchange terms, to over 50% of the NH spins analyzed when isotropic tumbling is assumed. Moreover, there is a systematic change in S2, as large as 0.08 for some residues. The significant effects of anisotropic rotational diffusion on model-free motional parameters are in marked contrast to previous studies and are accentuated by lowering of the effective correlation time using isotropic tumbling methods. This is caused by the preponderance of NH vectors aligned perpendicular to the principal diffusion tensor axis and is readily detected because of the high quality of the relaxation data. A novel procedure, COPED (COmparison of Predicted and Experimental Diffusion tensors) is presented for distinguishing genuine motions from the effects of anisotropy by comparing experimental relaxation data and data predicted from hydrodynamic analyses. The procedure shows excellent agreement with the slow motions detected from the axially symmetric model-free analysis and represents an independent procedure for determining rotational diffusion and slow motions that can confirm or refute established procedures that rely on relaxation data. Our findings show that neglect of even small degrees of rotational diffusion anisotropy can introduce significant errors in model-free analysis when the data is of high quality. These errors can hinder our understanding of the role of internal motions in protein function.

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 deltaE 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.

A new method is proposed for docking ligands into proteins in cases where an NMR-determined solution structure of a related complex is available. The method uses a set of experimentally determined values for protein-ligand, ligand-ligand, and protein-protein restraints for residues in or near to the binding site, combined with a set of protein-protein restraints involving all the other residues which is taken from the list of restraints previously used to generate the reference structure of a related complex. This approach differs from ordinary docking methods where the calculation uses fixed atomic coordinates from the reference structure rather than the restraints used to determine the reference structure. The binding site residues influenced by replacing the reference ligand by the new ligand were determined by monitoring differences in 1H chemical shifts. The method has been validated by showing the excellent agreement between structures of L. casei dihydrofolate reductase trimetrexate calculated by conventional methods using a full experimentally determined set of restraints and those using this new restraint docking method based on an L. casei dihydrofolate reductase methotrexate reference structure.

This paper investigates a computational procedure for the determination of the atom types on the vertices of a molecular skeleton to optimize interaction with the receptor site whilst maintaining a synthetically reasonable structure. The connectivity of the skeleton is analysed and appropriate atom types are compiled for each vertex. Receptor ionization and conformational states are generated by varying the positions of hydrogen atoms and electron lone pairs in the carboxyl, rotatable hydroxyl and amino groups. The structure is divided into small non-overlapping substructures. Atom types are assigned exhaustively onto each of the substructures using a depth-first search method; chemical rules are applied to reject unacceptable atom combinations early on. An empirical interaction score is calculated and the representatives of each partial structure are stored in ascending order according to their scores. The branch-and-bound procedure is then used to find the structures with the lowest scores. The method is illustrated using five protein-ligand complexes.

The reliability of new methodology for detecting sites for ligand binding on the surfaces of proteins has been tested using a range of dihydrofolate reductase (DHFR) crystal structures. Docking of the pterin molecule to ten such DHFR structures has been examined. Initial docking sites were selected using the VDW-FFT method we have developed recently. This procedure was followed by rigid geometry optimization and solvation energy calculations using our parametrized reaction field multipoles (PRFM) method and the finite difference solution of the Poisson equation (FDPB) method. Two different sets of MM parameters, from the OPLS and Amber94 force fields, have been used. In eight cases the energy of the complexes with pterin bound at the active site was the lowest with the recent Amber94 parameters. In one case the spurious first-ranked site was only 1.8 kcal/mol lower in energy compared with the active site. The other 'failure' of the method may, in fact, represent a valid initial binding site. The calculations with the old OPLS parameters gave slightly worse results.

Dihydrofolate reductase has successfully been used as a drug target in the area of anti-cancer, anti-bacterial and anti-malarial chemotherapy. Little has been done to evaluate it as a drug target for treatment of the trypanosomiases and leishmaniasis. A crystal structure of Leishmania major dihydrofolate reductase has been published. In this paper, we describe the modelling of Trypanosoma cruzi and Trypanosoma brucei dihydrofolate reductases based on this crystal structure. These structures and models have been used in the comparison of protozoan, bacterial and human enzymes in order to highlight the different features that can be used in the design of selective anti-protozoan agents. Comparison has been made between residues present in the active site, the accessibility of these residues, charge distribution in the active site, and the shape and size of the active sites. Whilst there is a high degree of similarity between protozoan, human and bacterial dihydrofolate reductase active sites, there are differences that provide potential for selective drug design. In particular, we have identified a set of residues which may be important for selective drug design and identified a larger binding pocket in the protozoan than the human and bacterial enzymes.

A central problem in forming accurate regression equations in QSAR studies is the selection of appropriate descriptors for the compounds under study. We describe a novel procedure for using inductive logic programming (ILP) to discover new indicator variables (attributes) for QSAR problems, and show that these improve the accuracy of the derived regression equations. ILP techniques have previously been shown to work well on drug design problems where there is a large structural component or where clear comprehensible rules are required. However, ILP techniques have had the disadvantage of only being able to make qualitative predictions (e.g. active, inactive) and not to predict real numbers (regression). We unify ILP and linear regression techniques to give a QSAR method that has the strength of ILP at describing steric structure, with the familiarity and power of linear regression. We evaluated the utility of this new QSAR technique by examining the prediction of biological activity with and without the addition of new structural indicator variables formed by ILP. In three out of five datasets examined the addition of ILP variables produced statistically better results (P < 0.01) over the original description. The new ILP variables did not increase the overall complexity of the derived QSAR equations and added insight into possible mechanisms of action. We conclude that ILP can aid in the process of drug design.

A genetic algorithm (GA) is described which is used to compare the solvent-accessible surfaces of two proteins or fragments of proteins, represented by a dot surface calculated using the Connolly algorithm. The GA is used to move one surface relative to the other to locate the most similar surface region between the two. The matching process is enhanced by the use of the surface normals and shape terms provided by the Connolly program and also by a simple hydrogen-bonding descriptor and an additional shape descriptor. The algorithm has been tested in applications ranging from the comparison of small surface patches to the comparison of whole protein surfaces, and it has performed correctly in all cases. Examples of the matches are given and a quantitative analysis of the quality of the matches is performed. A number of possible future enhancements to the program are described which would allow the GA to be used for more complex surface comparisons.

We present an efficient algorithm for the structural alignment of medium-sized organic molecules. The algorithm has been developed for applications in 3D QSAR and in receptor modeling. The method assumes one of the molecules, the reference ligand, to be presented in the conformation that it adopts inside the receptor pocket. The second molecule, the test ligand, is considered to be flexible, and is assumed to be given in an arbitrary low-energy conformation. Ligand flexibility is modeled by decomposing the test ligand into molecular fragments, such that ring systems are completely contained in a single fragment. Conformations of fragments and torsional angles of single bonds are taken from a small finite set, which depends on the fragment and bond, respectively. The algorithm superimposes a distinguished base fragment of the test ligand onto a suitable region of the reference ligand and then attaches the remaining fragments of the test ligand in a step-by-step fashion. During this process, a scoring function is optimized that encompasses bonding terms and terms accounting for steric overlap as well as for similarity of chemical properties of both ligands. The algorithm has been implemented in the FLEXS system. To validate the quality of the produced results, we have selected a number of examples for which the mutual superposition of two ligands is experimentally given by the comparison of the binding geometries known from the crystal structures of their corresponding protein-ligand complexes. On more than two-thirds of the test examples the algorithm produces rms deviations of the predicted versus the observed conformation of the test ligand below 1.5 A. The run time of the algorithm on a single problem instance is a few minutes on a common-day workstation. The overall goal of this research is to drastically reduce run times, while limiting the inaccuracies of the model and the computation to a tolerable level.

This paper describes the implementation and comparison of four heuristic search algorithms (genetic algorithm, evolutionary programming, simulated annealing and tabu search) and a random search procedure for flexible molecular docking. To our knowledge, this is the first application of the tabu search algorithm in this area. The algorithms are compared using a recently described fast molecular recognition potential function and a diverse set of five protein-ligand systems. Statistical analysis of the results indicates that overall the genetic algorithm performs best in terms of the median energy of the solutions located. However, tabu search shows a better performance in terms of locating solutions close to the crystallographic ligand conformation. These results suggest that a hybrid search algorithm may give superior results to any of the algorithms alone.

We describe an algorithm for the automated generation of molecular structures subject to geometric and connectivity constraints. The method relies on simulated annealing and simplex optimization of a penalty function that contains a variety of conditions and can be useful in structure-based drug design projects. The procedure controls the diversity and complexity of the generated molecules. Structure selection filters are an integral part and drive the algorithm. Several procedures have been developed to achieve reliable control. A number of template sets can be defined and combined to control the range of molecules which are searched. Ring systems are predefined. Normally, the ring-system complexity is on of the most elusive and difficult factors to control when fusion-, bridge- and spiro-structures are built by joining templates. Here this is not an issue; the decision about which systems are acceptable, and which are not, is made before the run is initiated. Queries for inclusion and exclusion spheres are incorporated into the objective function, and, by using a flexible notation, the structure generation can be directed and more focused. Simulated annealing is a reliable optimizer and converges asymptotically to the global minimum. The objective functions used here are degenerate, so it is likely that each run will produce a different set of good solutions.

Water is known to play an important role in the recognition and stabilization of the interaction between a ligand and its site. This has important implications for drug design. Analyses of 19 high-resolution crystal structures of protein-ligand complexes reveal the multiple hydrogen-bonding feature of water molecules mediating protein-ligand interactions. Most of the water molecules (nearly 80%) involved in bridging the protein and the ligand can make three or more hydrogen bonds when distance and bond angles are used as criteria to define hydrogen-bonding interactions. Isotropic B-factors have been used to take into account the mobility of water molecules. The water molecules at binding sites bridge the protein and ligand, and interact with other water molecules to form a complex network of interconnecting hydrogen bonds. Some water molecules at the site do not directly bridge between the protein and the ligand, but may contribute indirectly to the stability of the complex by holding bridging water molecules in the right position through a network of hydrogen bonds. These water networks are probably crucial for the stability of the protein-ligand complex and are important for any site-directed drug design strategies.