Kinetics and crystal structure of human purine nucleoside phosphorylase in complex with 7-methyl-6-thio-guanosine

Databases of ligand-binding pockets and protein-ligand interactions

Many research groups and institutions have created a variety of databases curating experimental and predicted data related to protein-ligand binding. The landscape of available databases is dynamic, with new databases emerging and established databases becoming defunct. Here, we review the current state of databases that contain binding pockets and protein-ligand binding interactions. We have compiled a list of such databases, fifty-three of which are currently available for use. We discuss variation in how binding pockets are defined and summarize pocket-finding methods. We organize the fifty-three databases into subgroups based on goals and contents, and describe standard use cases. We also illustrate that pockets within the same protein are characterized differently across different databases. Finally, we assess critical issues of sustainability, accessibility and redundancy.

How Docking Programs Work

Protein-ligand docking simulations are of central interest for computer-aided drug design. Docking is also of pivotal importance to understand the structural basis for protein-ligand binding affinity. In the last decades, we have seen an explosion in the number of three-dimensional structures of protein-ligand complexes available at the Protein Data Bank. These structures gave further support for the development and validation of in silico approaches to address the binding of small molecules to proteins. As a result, we have now dozens of open source programs and web servers to carry out molecular docking simulations. The development of the docking programs and the success of such simulations called the attention of a broad spectrum of researchers not necessarily familiar with computer simulations. In this scenario, it is essential for those involved in experimental studies of protein-ligand interactions and biophysical techniques to have a glimpse of the basics of the protein-ligand docking simulations. Applications of protein-ligand docking simulations to drug development and discovery were able to identify hits, inhibitors, and even drugs. In the present chapter, we cover the fundamental ideas behind protein-ligand docking programs for non-specialists, which may benefit from such knowledge when studying molecular recognition mechanism.

Docking with GemDock

GEMDOCK is a protein-ligand docking software that makes use of an elegant biologically inspired computational methodology based on the differential evolution algorithm. As any docking program, GEMDOCK has two major features to predict the binding of a small-molecule ligand to the binding site of a protein target: the search algorithm and the scoring function to evaluate the generated poses. The GEMDOCK scoring function uses a piecewise potential energy function integrated into the differential evolutionary algorithm. GEMDOCK has been applied to a wide range of protein systems with docking accuracy similar to other docking programs such as Molegro Virtual Docker, AutoDock4, and AutoDock Vina. In this chapter, we explain how to carry out protein-ligand docking simulations with GEMDOCK. We focus this tutorial on the protein target cyclin-dependent kinase 2.

SAnDReS: A Computational Tool for Docking

Since the early 1980s, we have witnessed considerable progress in the development and application of docking programs to assess protein-ligand interactions. Most of these applications had as a goal the identification of potential new binders to protein targets. Another remarkable progress is taking place in the determination of the structures of protein-ligand complexes, mostly using X-ray diffraction crystallography. Considering these developments, we have a favorable scenario for the creation of a computational tool that integrates into one workflow all steps involved in molecular docking simulations. We had these goals in mind when we developed the program SAnDReS. This program allows the integration of all computational features related to modern docking studies into one workflow. SAnDReS not only carries out docking simulations but also evaluates several docking protocols allowing the selection of the best approach for a given protein system. SAnDReS is a free and open-source (GNU General Public License) computational environment for running docking simulations. Here, we describe the combination of SAnDReS and AutoDock4 for protein-ligand docking simulations. AutoDock4 is a free program that has been applied to over a thousand receptor-ligand docking simulations. The dataset described in this chapter is available for downloading at https://github.com/azevedolab/sandres.

Van der Waals Potential in Protein Complexes

Van der Waals forces are determinants of the formation of protein-ligand complexes. Physical models based on the Lennard-Jones potential can estimate van der Waals interactions with considerable accuracy and with a computational complexity that allows its application to molecular docking simulations and virtual screening of large databases of small organic molecules. Several empirical scoring functions used to evaluate protein-ligand interactions approximate van der Waals interactions with the Lennard-Jones potential. In this chapter, we present the main concepts necessary to understand van der Waals interactions relevant to molecular recognition of a ligand by the binding pocket of a protein target. We describe the Lennard-Jones potential and its application to calculate potential energy for an ensemble of structures to highlight the main features related to the importance of this interaction for binding affinity.

Homology Modeling of Protein Targets with MODELLER

Homology modeling is a computational approach to generate three-dimensional structures of protein targets when experimental data about similar proteins are available. Although experimental methods such as X-ray crystallography and nuclear magnetic resonance spectroscopy successfully solved the structures of nearly 150,000 macromolecules, there is still a gap in our structural knowledge. We can fulfill this gap with computational methodologies. Our goal in this chapter is to explain how to perform homology modeling of protein targets for drug development. We choose as a homology modeling tool the program MODELLER. To illustrate its use, we describe how to model the structure of human cyclin-dependent kinase 3 using MODELLER. We explain the modeling procedure of CDK3 apoenzyme and the structure of this enzyme in complex with roscovitine.

Hydrogen Bonds in Protein-Ligand Complexes

Fast and reliable evaluation of the hydrogen bond potential energy has a significant impact in the drug design and development since it allows the assessment of large databases of organic molecules in virtual screening projects focused on a protein of interest. Semi-empirical force fields implemented in molecular docking programs make it possible the evaluation of protein-ligand binding affinity where the hydrogen bond potential is a common term used in the calculation. In this chapter, we describe the concepts behind the programs used to predict hydrogen bond potential energy employing semi-empirical force fields as the ones available in the programs AMBER, AutoDock4, TreeDock, and ReplicOpter. We described here the 12-10 potential and applied it to evaluate the binding affinity for an ensemble of crystallographic structures for which experimental data about binding affinity are available.

Functional and Structural Characterization of Purine Nucleoside Phosphorylase from Kluyveromyces lactis and Its Potential Applications in Reducing Purine Content in Food

Consumption of foods and beverages with high purine content increases the risk of hyperuricemia, which causes gout and can lead to cardiovascular, renal, and other metabolic disorders. As patients often find dietary restrictions challenging, enzymatically lowering purine content in popular foods and beverages offers a safe and attractive strategy to control hyperuricemia. Here, we report structurally and functionally characterized purine nucleoside phosphorylase (PNP) from Kluyveromyces lactis (KlacPNP), a key enzyme involved in the purine degradation pathway. We report a 1.97 Å resolution crystal structure of homotrimeric KlacPNP with an intrinsically bound hypoxanthine in the active site. KlacPNP belongs to the nucleoside phosphorylase-I (NP-I) family, and it specifically utilizes 6-oxopurine substrates in the following order: inosine > guanosine > xanthosine, but is inactive towards adenosine. To engineer enzymes with broad substrate specificity, we created two point variants, KlacPNP^N256D and KlacPNP^N256E, by replacing the catalytically active Asn256 with Asp and Glu, respectively, based on structural and comparative sequence analysis. KlacPNP^N256D not only displayed broad substrate specificity by utilizing both 6-oxopurines and 6-aminopurines in the order adenosine > inosine > xanthosine > guanosine, but also displayed reversal of substrate specificity. In contrast, KlacPNP^N256E was highly specific to inosine and could not utilize other tested substrates. Beer consumption is associated with increased risk of developing gout, owing to its high purine content. Here, we demonstrate that KlacPNP and KlacPNP^N256D could be used to catalyze a key reaction involved in lowering beer purine content. Biochemical properties of these enzymes such as activity across a wide pH range, optimum activity at about 25°C, and stability for months at about 8°C, make them suitable candidates for food and beverage industries. Since KlacPNP^N256D has broad substrate specificity, a combination of engineered KlacPNP and other enzymes involved in purine degradation could effectively lower the purine content in foods and beverages.

N-phosphonocarbonylpyrrolidine derivatives of guanine: a new class of bi-substrate inhibitors of human purine nucleoside phosphorylase

A complete series of pyrrolidine nucleotides, (3R)- and (3S)-3-(guanin-9-yl)pyrrolidin-1-N-ylcarbonylphosphonic acids and (3S,4R)-, (3R,4S)-, (3S,4S)-, and (3R,4R)-4-(guanin-9-yl)-3-hydroxypyrrolidin-1-N-ylcarbonylphosphonic acids, were synthesized and evaluated as potential inhibitors of purine nucleoside phosphorylase (PNP) isolated from peripheral blood mononuclear cells (PBMCs) and cell lines of myeloid and lymphoid origin. Two compounds, (S)-3-(guanin-9-yl)pyrrolidin-1-N-ylcarbonylphosphonic acid (2a) and (3S,4R)-4-(guanin-9-yl)-3-hydroxypyrrolidin-1-N-ylcarbonylphosphonic acid (6a), were recognized as nanomolar competitive inhibitors of PNP isolated from cell lines with K(i) values within the ranges of 16-100 and 10-24 nM, respectively. The low (MESG)K(i) and (Pi)K(i) values of both compounds for PNP isolated from PBMCs suggest that these compounds could be bisubstrate inhibitors that occupy both the phosphate and nucleoside binding sites of the enzyme.

Crystal structure and molecular dynamics studies of human purine nucleoside phosphorylase complexed with 7-deazaguanine

In humans, purine nucleoside phosphorylase (HsPNP) is responsible for degradation of deoxyguanosine, and genetic deficiency of this enzyme leads to profound T-cell mediated immunosuppression. HsPNP is a target for inhibitor development aiming at T-cell immune response modulation. Here we report the crystal structure of HsPNP in complex with 7-deazaguanine (HsPNP:7DG) at 2.75 A. Molecular dynamics simulations were employed to assess the structural features of HsPNP in both free form and in complex with 7DG. Our results show that some regions, responsible for entrance and exit of substrate, present a conformational variability, which is dissected by dynamics simulation analysis. Enzymatic assays were also carried out and revealed that 7-deazaguanine presents a lower inhibitory activity against HsPNP (K(i)=200 microM). The present structure may be employed in both structure-based design of PNP inhibitors and in development of specific empirical scoring functions.

Molecular dynamics studies of a hexameric purine nucleoside phosphorylase

Purine nucleoside phosphorylase (PNP) (EC.2.4.2.1) is an enzyme that catalyzes the cleavage of N-ribosidic bonds of the purine ribonucleosides and 2-deoxyribonucleosides in the presence of inorganic orthophosphate as a second substrate. This enzyme is involved in purine-salvage pathway and has been proposed as a promising target for design and development of antimalarial and antibacterial drugs. Recent elucidation of the three-dimensional structure of PNP by X-ray protein crystallography left open the possibility of structure-based virtual screening initiatives in combination with molecular dynamics simulations focused on identification of potential new antimalarial drugs. Most of the previously published molecular dynamics simulations of PNP were carried out on human PNP, a trimeric PNP. The present article describes for the first time molecular dynamics simulations of hexameric PNP from Plasmodium falciparum (PfPNP). Two systems were simulated in the present work, PfPNP in ligand free form, and in complex with immucillin and sulfate. Based on the dynamical behavior of both systems the main results related to structural stability and protein-drug interactions are discussed.

Conservation of structure and activity in Plasmodium purine nucleoside phosphorylases

BACKGROUND

Purine nucleoside phosphorylase (PNP) is central to purine salvage mechanisms in Plasmodium parasites, the causative agents of malaria. Most human malaria results from infection either by Plasmodium falciparum (Pf), the deadliest form of the parasite, or by the widespread Plasmodium vivax (Pv). Whereas the PNP enzyme from Pf has previously been studied in detail, despite the prevalence of Pv little is known about many of the key metabolic enzymes from this parasite, including PvPNP.

RESULTS

The crystal structure of PvPNP is described and is seen to have many features in common with the previously reported structure of PfPNP. In particular, the composition and conformations of the active site regions are virtually identical. The crystal structure of a complex of PfPNP co-crystallised with inosine and arsenate is also described, and is found to contain a mixture of products and reactants - hypoxanthine, ribose and arsenate. The ribose C1' in this hybrid complex lies close to the expected point of symmetry along the PNP reaction coordinate, consistent with a conformation between the transition and product states. These two Plasmodium PNP structures confirm the similarity of structure and mechanism of these enzymes, which are also confirmed in enzyme kinetic assays using an array of substrates. These reveal an unusual form of substrate activation by 2'-deoxyinosine of PvPNP, but not PfPNP.

CONCLUSION

The close similarity of the Pf and Pv PNP structures allows characteristic features to be identified that differentiate the Apicomplexa PNPs from the human host enzyme. This similarity also suggests there should be a high level of cross-reactivity for compounds designed to inhibit either of these molecular targets. However, despite these similarities, there are also small differences in the activities of the two Plasmodium enzymes.

Molecular modeling, dynamics and docking studies of purine nucleoside phosphorylase from Streptococcus pyogenes

Purine Nucleoside Phosphorylase (PNP) catalyzes the reversible phosphorolysis of N-glycosidic bonds of purine nucleosides and deoxynucleosides, except for adenosine, to generate ribose 1-phosphate and the purine base. PNP has been submitted to intensive structural studies. This work describes for the first time a structural model of PNP from Streptococcus pyogenes (SpPNP). We modeled the complexes of SpPNP with six different ligands in order to determine the structural basis for specificity of these ligands against SpPNP. Molecular dynamics (MD) simulations were performed in order to evaluate the overall stability of SpPNP model. The analysis of the MD simulation was assessed mainly by principal component analysis (PCA) to explore the trimeric structure behavior. Structural comparison, between SpPNP and human PNP, was able to identify the main features responsible for differences in ligand-binding affinities, such as mutation in the purine-binding site and in the second phosphate-binding site. The PCA analysis suggests a different behavior for each subunit in the trimer structure.

Humanized ADEPT comprised of an engineered human purine nucleoside phosphorylase and a tumor targeting peptide for treatment of cancer

Immunogenicity caused by the use of nonhuman enzymes in antibody-directed enzyme prodrug therapy has limited its clinical application. To overcome this problem, we have developed a mutant human purine nucleoside phosphorylase, which, unlike the wild-type enzyme, accepts (deoxy)adenosine-based prodrugs as substrates. Among the different mutants of human purine nucleoside phosphorylase tested, a double mutant with amino acid substitutions E201Q:N243D (hDM) is the most efficient in cleaving (deoxy)adenosine-based prodrugs. Although hDM is capable of using multiple prodrugs as substrates, it is most effective at cleaving 2-fluoro-2'-deoxyadenosine to a cytotoxic drug. To target hDM to the tumor site, the enzyme was fused to an anti-HER-2/neu peptide mimetic (AHNP). Treatment of HER-2/neu-expressing tumor cells with hDM-AHNP results in cellular localization of enzyme activity. As a consequence, harmless prodrug is converted to a cytotoxic drug in the vicinity of the tumor cells, resulting in tumor cell apoptosis. Unlike the nonhuman enzymes, the hDM should have minimal immunogenicity when used in antibody-directed enzyme prodrug therapy, thus providing a novel promising therapeutic agent for the treatment of tumors.