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.     

Separation of Dihydrofolate Reductase Inhibitors by RP-HPLC and Comparison with Capillary Zone Electrophoresis

The dihydrofolate reductase inhibitors (DHFRIs) are a group of antibiotic compounds with closely related chemical structures. A previous attempt to separate the eight compounds by CZE was successful, but only at low pH (2.1) and high buffer concentration (250mM phosphate). As a result, baseline noise was high. Additionally, baseline resolution was not quite achieved and the separation took 25 minutes. However, the size-based separation indicated that reversed-phase HPLC might be a good alternative. A three-dimensional overlapping resolution mapping (OR_sM) scheme utilised pH, flow rate and percentage organic modifier (for both methanol and acetonitrile). Clear generalised outcomes were observed under isocratic conditions. At higher pHs, where the analytes were largely unionised, retention was excessive. At higher percentages of MeOH or ACN, the more-difficult-to-separate components were poorly resolved. On the other hand, low pHs (2.5 in 50mM phosphate) with low percentages of the organic modifiers (7% ACN or 11% MeOH) but high flow rates (2.3mLmin^–1) yielded better than baseline resolution in 17 minutes. A partially optimised gradient run (at pH 6.5) again yielded far better than baseline resolution in 12 minutes, but required 4 minutes re-equilibration. Hence, the HPLC separations are superior to the CZE separation in all of runtime (40%), resolution and limit of detection (down by 6).     

Identification and energetic ranking of possible docking sites for pterin on dihydrofolate reductase

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.     

Efforts Toward the Direct Experimental Characterization of Enzyme Microenvironments: Tyrosine100 in Dihydrofolate Reductase

State secrets : Site‐specific deuteration and FTIR studies reveal that Tyr100 in dihydrofolate reductase plays an important role in catalysis, with a strong electrostatic coupling occuring between Tyr100 and the charge that develops in the hydride‐transfer transition state (see picture, NADP⁺ purple, Tyr100 green). However, relaying correlated motions that facilitate catalysis from distal sites of the protein to the hydride donor may also be involved.

     

Refinement of modelled structures by knowledge-based energy profiles and secondary structure prediction: Application to the human procarboxypeptidase A2

Knowledge-based energy profiles combined with secondary structure prediction have been applied to molecular modelling refinement. To check the procedure, three different models of human procarboxypeptidase A2 (hPCPA2) have been built using the 3D structures of procarboxypeptidase A1 (pPCPA1) and bovine procarboxypeptidase A (bPCPA) as templates. The results of the refinement can be tested against the X-ray structure of hPCPA2 which has been recently determined. Regions miss-modelled in the activation segment of hPCPA2 were detected by means of pseudo-energies using Prosa II and modified afterwards according to the secondary structure prediction. Moreover, models obtained by automated methods as COMPOSER, MODELLER and distance restraints have also been compared, where it was found possible to find out the best model by means of pseudo-energies. Two general conclusions can be elicited from this work: (1) on a given set of putative models it is possible to distinguish among them the one closest to the crystallographic structure, and (2) within a given structure it is possible to find by means of pseudo-energies those regions that have been defectively modelled.     

Heuristic lipophilicity potential for computer-aided rational drug design: Optimizations of screening functions and parameters

In this research we test and compare three possible atom-basedscreening functions used in the heuristic molecular lipophilicity potential(HMLP). Screening function 1 is a power distance-dependent function, b , screening function 2is an exponential distance-dependent function, b_iexp( , and screening function 3 is aweighted distance-dependent function, For every screening function, the parameters ( ,d₀, and are optimized using 41 common organic molecules of 4 types of compounds:aliphatic alcohols, aliphatic carboxylic acids, aliphatic amines, andaliphatic alkanes. The results of calculations show that screening function3 cannot give chemically reasonable results, however, both the powerscreening function and the exponential screening function give chemicallysatisfactory results. There are two notable differences between screeningfunctions 1 and 2. First, the exponential screening function has largervalues in the short distance than the power screening function, thereforemore influence from the nearest neighbors is involved using screeningfunction 2 than screening function 1. Second, the power screening functionhas larger values in the long distance than the exponential screeningfunction, therefore screening function 1 is effected by atoms at longdistance more than screening function 2. For screening function 1, thesuitable range of parameter d₀ is 1.5 < d₀ < 3.0, and d₀ = 2.0 is recommended. HMLP developed in this researchprovides a potential tool for computer-aided three-dimensional drugdesign.     

Discovery of novel inhibition site centered on 114-bit tryptophan of Thioredoxin reductase 1 through computer-aided drug design

Thioredoxin reductase 1 (TrxR1) is an oxidoreductase playing the important role in the tumor cells. It is a new type of drug therapy target. Most of the existing TrxR1 inhibitors act directly covalently on the active sites. Herein, molecular docking-based virtual screening approach was used to screen inhibitors with new binding site of TrxR1 from the SPECS database. After experimental test, compound 22 was identified as the reversibility inhibitor of TrxR1 U498C mutant (It has similar structure and function to replace the wild-type TrxR1 which is difficult to express) with IC₅₀ value of 15.31 ± 0.57 μM. The molecular docking results showed that the interaction between compound 22 and TrxR1 was centered on inactive site Trp¹¹⁴. Furthermore, phenazine compounds 24–30 with similar structures as 22 were also screened out from our phenazine database. Compounds 24–27 had longer chain structures and better inhibitory activity than compound 22, while compounds 28–30 were the opposite. Compounds 24–27 can be more stably bound in the protein cavity on Trp¹¹⁴ than compounds 28–30. Then we verified amino acids centered on Trp¹¹⁴ can regulate TrxR1 activity by amino acids mutation. Taken together, A new inhibition site are found that can regulate TrxR1 U498C mutant activity by acting on amino acids sequence at inactive sites centered on Trp¹¹⁴ and can provide ideas for the discovery and research of new TrxR1 inhibitors.     

DNA G-quadruplex and its potential as anticancer drug target

G-quadruplex secondary structures are four-stranded globular nucleic acid structures form in the specific DNA and RNA G-rich sequences with biological significance such as human telomeres,oncogene-promoter regions,replication initiation sites,and 5′and 3′-untranslated(UTR)regions.The non-canonical G-quadruplex secondary structures can readily form under physiologically relevant ionic conditions and are considered to be new molecular target for cancer therapeutics.This review discusses the essential progress in our lab related to the structures and functions of biologically relevant DNA G-quadruplexes in human gene promoters and telomeres,and the opportunities presented for the development of G-quadruplex-targeted smallmolecule drugs.     

Development of non-peptide ACE inhibitors as novel and potent cardiovascular therapeutics: An in silico modelling approach

Angiotensin-converting enzyme (ACE) inhibitors have been acknowledged as first-line agents for the treatment of hypertension and a variety of cardiovascular disorders. In this context, quantitative structure–activity relationship (QSAR) models for a series of non-peptide compounds as ACE inhibitors are developed based on Simplified Molecular Input-Line Entry System (SMILES) notation and local graph invariants. Three random splits into the training and test sets are used. The Monte Carlo method is applied for model development. Molecular docking studies are used for the final assessment of the developed QSAR model and the design of novel inhibitors. The statistical quality of the developed model is good. Molecular fragments responsible for the increase/decrease of the studied activity are calculated. The computer-aided design of new compounds, as potential ACE inhibitors, is presented. The predictive potential of the applied approach is tested, and the robustness of the model is proven using different methods. The results obtained from molecular docking studies are in excellent correlation with the results from QSAR studies. The presented study may be useful in the search for novel cardiovascular therapeutics based on ACE inhibition.     

AstexViewer: a visualisation aid for structure-based drug design

AstexViewer is a Java molecular graphics program that can be used for visualisation in many aspects of structure-based drug design. This paper describes its functionality, implementation and examples of its use. The program can run as an Applet in a web browser allowing structures to be displayed without installing additional software. Applications of its use are described for visualisation and as part of a structure based design platform. The software is being made freely available to the community and may be downloaded from http://www.astex-technology.com/AstexViewer.     

Rotamer decomposition and protein dynamics: Efficiently analyzing dihedral populations from molecular dynamics

Molecular mechanics methods have matured into powerful methods to understand the dynamics and flexibility of macromolecules and especially proteins. As multinanosecond to microsecond length molecular dynamics (MD) simulations become commonplace, advanced analysis tools are required to generate scientifically useful information from large amounts of data. Some of the key degrees of freedom to understand protein flexibility and dynamics are the amino acid residue side chain dihedral angles. In this work, we present an easily automated way to summarize and understand the relevant dihedral populations. A tremendous reduction in complexity is achieved by describing dihedral timeseries in terms of histograms decomposed into Gaussians. Using the familiar and widely studied protein lysozyme, it is demonstrated that our approach captures essential properties of protein structure and dynamics. A simple classification scheme is proposed that indicates the rotational state population for each dihedral angle of interest and allows a decision if a given side chain or peptide backbone fragment remains rigid during the course of an MD simulation, adopts a converged distribution between conformational substates or has not reached convergence yet. © 2012 Wiley Periodicals, Inc.     

Balancing target flexibility and target denaturation in computational fragment‐based inhibitor discovery

Accounting for target flexibility and selecting “hot spots” most likely to be able to bind an inhibitor continue to be challenges in the field of structure‐based drug design, especially in the case of protein–protein interactions. Computational fragment‐based approaches using molecular dynamics (MD) simulations are a promising emerging technology having the potential to address both of these challenges. However, the optimal MD conditions permitting sufficient target flexibility while also avoiding fragment‐induced target denaturation remain ambiguous. Using one such technology (Site Identification by Ligand Competitive Saturation, SILCS), conditions were identified to either prevent denaturation or identify and exclude trajectories in which subtle but important denaturation was occurring. The target system used was the well‐characterized protein cytokine IL‐2, which is involved in a protein–protein interface and, in its unliganded crystallographic form, lacks surface pockets that can serve as small‐molecule binding sites. Nonetheless, small‐molecule inhibitors have previously been discovered that bind to two “cryptic” binding sites that emerge only in the presence of ligand binding, highlighting the important role of IL‐2 flexibility. Using the above conditions, SILCS with hydrophobic fragments was able to identify both sites based on favorable fragment binding while avoiding IL‐2 denaturation. An important additional finding was that acetonitrile, a water‐miscible fragment, fails to identify either site yet can induce target denaturation, highlighting the importance of fragment choice. © 2012 Wiley Periodicals, Inc.     

Dithiol proteins as guardians of the intracellular redox milieu in parasites: old and new drug targets in trypanosomes and malaria-causing plasmodia

Parasitic diseases such as sleeping sickness, Chagas' heart disease, and malaria are major health problems in poverty-stricken areas. Antiparasitic drugs that are not only active but also affordable and readily available are urgently required. One approach to finding new drugs and rediscovering old ones is based on enzyme inhibitors that paralyze antioxidant systems in the pathogens. These antioxidant ensembles are essential to the parasites as they are attacked in the human host by strong oxidants such as peroxynitrite, hypochlorite, and H2O2. The pathogen-protecting system consists of some 20 thiol and dithiol proteins, which buffer the intraparasitic redox milieu at a potential of -250 mV. In trypanosomes and leishmania the network is centered around the unique dithiol trypanothione (N1,N8-bis(glutathionyl)spermidine). In contrast, malaria parasites have a more conservative dual antioxidative system based on glutathione and thioredoxin. Inhibitors of antioxidant enzymes such as trypanothione reductase are, indeed, parasiticidal but they can also delay or prevent resistance against a number of other antiparasitic drugs.     

Virtual screening for compounds that mimic protein-protein interface epitopes

Modulation of protein-protein interactions (PPI) has emerged as a new concept in rational drug design. Here, we present a computational protocol for identifying potential PPI inhibitors. Relevant regions of interfaces (epitopes) are predicted for three-dimensional protein models and serve as queries for virtual compound screening. We present a computational screening protocol that incorporates two different pharmacophore models. One model is based on the mathematical concept of autocorrelation vectors and the other utilizes fuzzy labeled graphs. In a proof-of-concept study, we were able to identify serine protease inhibitors using a predicted trypsin epitope as query. Our virtual screening framework may be suited for rapid identification of PPI inhibitors and suggesting bioactive tool compounds.     

Application and limitations of X-ray crystallographic data in structure-based ligand and drug design

Structure-based design usually focuses upon the optimization of ligand affinity. However, successful drug design also requires the optimization of many other properties. The primary source of structural information for protein-ligand complexes is X-ray crystallography. The uncertainties introduced during the derivation of an atomic model from the experimentally observed electron density data are not always appreciated. Uncertainties in the atomic model can have significant consequences when this model is subsequently used as the basis of manual design, docking, scoring, and virtual screening efforts. Docking and scoring algorithms are currently imperfect. A good correlation between observed and calculated binding affinities is usually only observed only when very large ranges of affinity are considered. Errors in the correlation often exceed the range of affinities commonly encountered during lead optimization. Some structure-based design approaches now involve screening libraries by using technologies based on NMR spectroscopy and X-ray crystallography to discover small polar templates, which are used for further optimization. Such compounds are defined as leadlike and are also sought by more traditional high-throughput screening technologies. Structure-based design and HTS technologies show important complementarity and a degree of convergence.     

PRO_SELECT: Combining structure-based drug design and combinatorial chemistry for rapid lead discovery. 1. Technology

This paper describes a novel methodology, PRO_SELECT, which combines elements of structure-based drug design and combinatorial chemistry to create a new paradigm for accelerated lead discovery. Starting with a synthetically accessible template positioned in the active site of the target of interest, PRO_SELECT employs database searching to generate lists of potential substituents for each substituent position on the template. These substituents are selected on the basis of their being able to couple to the template using known synthetic routes and their possession of the correct functionality to interact with specified residues in the active site. The lists of potential substituents are then screened computationally against the active site using rapid algorithms. An empirical scoring function, correlated to binding free energy, is used to rank the substituents at each position. The highest scoring substituents at each position can then be examined using a variety of techniques and a final selection is made. Combinatorial enumeration of the final lists generates a library of synthetically accessible molecules, which may then be prioritised for synthesis and assay. The results obtained using PRO_SELECT to design thrombin inhibitors are briefly discussed.     

Comparative molecular field analysis and energy interaction studies of thrombin-inhibitor complexes

A Comparative Molecular Field Analysis (CoMFA) and an interaction energy-based method were applied on a database holding the 3D structures of 29 thrombin-inhibitor complexes. Several parameters were optimized in both methods in order to obtain the best correlation between theoretical and experimentally determined binding (Ki) data. CoMFA, which only uses the information of the inhibitors, performed best (r = 0.99, q2 = 0.46, N = 29) when HF 6-31G charges were used in combination with a pharmacophore-based alignment. Inclusion of hydrophobic fields did not lead to improvements. The interaction energy-based approach uses the information of the whole thrombin-inhibitor complex. A statistically significant correlation (r = 0.74, N = 14) could only be obtained for a subset of the database containing the high resolution structures. Geometry optimization of the ligand only in combination with downscaled electrostatics performed best.