Rafael Andrade Caceres

CDK9 a potential target for drug development.

The family of Cyclin-Dependent Kinases (CDKs) can be subdivided into two major functional groups based on their roles in cell cycle and/or transcriptional control. CDK9 is the catalytic subunit of positive transcription elongation factor b (P-TEFb). CDK9 is the kinase of the TAK complex (Tat-associated kinase complex), and binds to Tat protein of HIV, suggesting a possible role for CDK9 in AIDS progression. CDK9 complexed with its regulatory partner cyclin T1, serves as a cellular mediator of the transactivation function of the HIV Tat protein. P-TEFb is responsible for the phosphorylation of the carboxyl-terminal domain of RNA Pol II, resulting in stimulation of transcription. Furthermore, the complexes containing CDK9 induce the differentiation in distinct tissue. The CDK9/cyclin T1 complex is expressed at higher level in more differentiated primary neuroectodermal and neuroblastoma tumors, showing a correlation between the kinase expression and tumor differentiation grade. This may have clinical and therapeutical implications for these tumor types. Among the CDK inhibitors two have shown to be effective against CDK9: Roscovitine and Flavopiridol. These two inhibitors prevented the replication of human immunodeficiency virus (HIV) type 1 by blocking Tat transactivation of the HIV type 1 promoter. These compounds inhibit CDKs by binding to the catalytic domain in place of ATP, preventing transfer of a phosphate group to the substrate. More sensitive therapeutic agents of CDK9 can be designed, and structural studies can add information in the understanding of this kinase. The major features related to CDK9 inhibition will be reviewed in this article.

Shikimate kinase: A potential target for development of novel antitubercular agents

Tuberculosis (TB) remains the leading cause of mortality due to a bacterial pathogen, Mycobacterium tuberculosis. However, no new classes of drugs for TB have been developed in the past 30 years. Therefore there is an urgent need to develop faster acting and effective new antitubercular agents, preferably belonging to new structural classes, to better combat TB, including MDR-TB, to shorten the duration of current treatment to improve patient compliance, and to provide effective treatment of latent tuberculosis infection. The enzymes in the shikimate pathway are potential targets for development of a new generation of antitubercular drugs. The shikimate pathway has been shown by disruption of aroK gene to be essential for the Mycobacterium tuberculosis. The shikimate kinase (SK) catalyses the phosphorylation of the 3-hydroxyl group of shikimic acid (shikimate) using ATP as a co-substrate. SK belongs to family of nucleoside monophosphate (NMP) kinases. The enzyme is an alpha/beta protein consisting of a central sheet of five parallel beta-strands flanked by alpha-helices. The shikimate kinases are composed of three domains: Core domain, Lid domain and Shikimate-binding domain. The Lid and Shikimate-binding domains are responsible for large conformational changes during catalysis. More recently, the precise interactions between SK and substrate have been elucidated, showing the binding of shikimate with three charged residues conserved among the SK sequences. The elucidation of interactions between MtSK and their substrates is crucial for the development of a new generation of drugs against tuberculosis through rational drug design.

Protein Kinases as Targets for Antiparasitic Chemotherapy Drugs

Parasitic protozoa infecting humans have a great impact on public health, especially in the developing countries. In many instances, the parasites have developed resistance against available chemotherapeutic agents, making the search for alternative drugs a priority. In line with the current interest in Protein Kinase (PK) inhibitors as potential drugs against a variety of diseases, the possibility that PKs may represent targets for novel anti-parasitic agents is being explored. Research into parasite PKs has benefited greatly from genome and EST sequencing projects, with the genomes from a few species fully sequenced (notably that from the malaria parasite Plasmodium falciparum) and several more under way, the structural features that are important to design specific inhibitors against these PKs will be reviewed in the present work.

Linear Interaction Energy (LIE) Method in Lead Discovery and Optimization

Currently, in order to accelerate the process of drug development and also reduce costs, many of the experimental assays related to lead discovery and lead optimization processes are being replaced by computational, in silico, methods. In this context, the LIE (linear interaction energy) method has been used to calculate binding free energies for widely different compounds by averaging interaction energies obtained from molecular dynamics (MD) or Monte Carlo (MC) simulations. In particular, the combination of docking and affinity predictions with the LIE method can thus save valuable resources in lead discovery and optimization projects. This review presents a description of LIE methodology and some recent studies that illustrate the importance and utility of the method in the field of pharmaceutical research.

Drug-binding databases.

Recent developments in computer power and chemoinformatics methodology make possible that a huge amount of data become available through internet. These databases are devoted to a wide spectrum of scientific fields. Here we are concerned with databases related to protein-drug interactions. More specifically, databases where potential new molecules could be accessed to be used in virtual screening initiatives. In the past decade several databases have been developed where molecules to be used in the virtual screening could be easily identified, downloaded and even purchased. This review describes and summarizes the recent advances in the development of these databases, and also the main applications related to virtual screening projects.

Evaluation of molecular docking using polynomial empirical scoring functions.

Molecular docking simulations are of pivotal importance for analysis of protein-ligand interactions and also an essential resource for virtual-screening initiatives. In molecular docking simulations several possible docked structures are generated, which create an ensemble of structures representing binary complexes. Therefore, it is crucial to find the best solution for the simulation. One approach to this problem is to employ empirical scoring function to identify the best docked structure. It is expected that scoring functions show a descriptive funnel-shaped energy surface without many false minima to impair the efficiency of conformational sampling. We employed this methodology against a test set with 300 docked structures. Docking simulations of these ligands against enzyme binding pocket indicated a funnel-shaped behavior of the complexation for this system. This review compares a set of recently proposed polynomial empirical scoring functions, implemented in a program called POLSCORE, with two popular scoring function programs (XSCORE and DrugScore). Overall comparison indicated that POLSCORE works better to predict the correct docked position, for the ensemble of docked structures analyzed in the present work.

Structural studies of human purine nucleoside phosphorylase: towards a new specific empirical scoring function.

Human purine nucleoside phosphorylase (HsPNP) is a target for inhibitor development aiming at T-cell immune response modulation. In this work, we report the development of a new set of empirical scoring functions and its application to evaluate binding affinities and docking results. To test these new functions, we solved the structure of HsPNP and 2-mercapto-4(3H)-quinazolinone (HsPNP:MQU) binary complex at 2.7A resolution using synchrotron radiation, and used these functions to predict ligand position obtained in docking simulations. We also employed molecular dynamics simulations to analyze HsPNP in two conditions, as apoenzyme and in the binary complex form, in order to assess the structural features responsible for stability. Analysis of the structural differences between systems provides explanation for inhibitor binding. The use of these scoring functions to evaluate binding affinities and molecular docking results may be used to guide future efforts on virtual screening focused on HsPNP.

Molecular modeling and dynamics studies of cytidylate kinase from Mycobacterium tuberculosis H37Rv

Bacterial cytidylate kinase or cytidine monophosphate kinase (CMP kinase) catalyses the phosphoryl transfer from ATP to CMP and dCMP, resulting in the formation nucleoside diphosphates. In eukaryotes, CMP/UMP kinase catalyses the conversion of UMP and CMP to, respectively, UDP and CDP with high efficiency. This work describes for the first time a model of bacterial cytidylate kinase or cytidine monophosphate kinase (CMP kinase) from mycobacterium tuberculosis (MtCMPK). We modeled MtPCMPK in apo form and in complex with cytidine 5′-monophosphate (CMP) to try to determine the structural basis for specificity. Comparative analysis of the model of MtCMPK allowed identification of structural features responsible for ligand affinities. Analysis of the molecular dynamics simulations of these two systems indicates the structural features responsible for the stability of the structure, and may help in the identification of new inhibitors for this enzyme.

Molecular modeling and dynamics simulations of PNP from Streptococcus agalactiae

This work describes for the first time a structural model of purine nucleoside phosphorylase from Streptococcus agalactiae (SaPNP). PNP 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 a potential target for the development of antibacterial drugs. We modeled the complexes of SaPNP with 15 different ligands in order to determine the structural basis for the specificity of these ligands against SaPNP. The application of a novel empirical scoring function to estimate the affinity of a ligand for a protein was able to identify the ligands with high affinity for PNPs. The analysis of molecular dynamics trajectory for SaPNP indicates that the functionally important motifs have a very stable structure. This new structural model together with a novel empirical scoring function opens the possibility to explorer larger library of compounds in order to identify the new inhibitors for PNPs in virtual screening projects.

Crystal structure and molecular dynamics studies of purine nucleoside phosphorylase from Mycobacterium tuberculosis associated with acyclovir

Consumption has been a scourge of mankind since ancient times. This illness has charged a high price to human lives. Many efforts have been made to defeat Mycobacterium tuberculosis (Mt). The M. tuberculosis purine nucleoside phosphorylase (MtPNP) is considered an interesting target to pursuit new potential inhibitors, inasmuch it belongs to the purine salvage pathway and its activity might be involved in the mycobacterial latency process. Here we present the MtPNP crystallographic structure associated with acyclovir and phosphate (MtPNP:ACY:PO(4)) at 2.10 Å resolution. Molecular dynamics simulations were carried out in order to dissect MtPNP:ACY:PO(4) structural features, and the influence of the ligand in the binding pocket stability. Our results revealed that the ligand leads to active site lost of stability, in agreement with experimental results, which demonstrate a considerable inhibitory activity against MtPNP (K(i) = 150 nM). Furthermore, we observed that some residues which are important in the proper ligands anchor into the human homologous enzyme do not present the same importance to MtPNP. Therewithal, these findings contribute to the search of new specific inhibitors for MtPNP, since peculiarities between the mycobacterial and human enzyme binding sites have been identified, making a structural-based drug design feasible.