Current Drug Targets - Volume 11, Issue 3, 2010

Development of a successful drug is the result of a combination of biological activity and drug-like properties. Both features can be estimated by in silico methodologies in the initial stages of drug discovery and development. Application of molecular docking simulations to scan a library of small-molecules to identify a potential inhibitor for a protein target is a methodology referred to as structure-based virtual screening (SBVS). This computational methodology has been employed in pharmaceutical research and development for over thirty years [1]. Application of SBVS opened the possibility to test millions of smallmolecules compounds against important targets for drug design. This computer simulation process involves using known threedimensional structure of a protein target to identify potential ligands [2-4]. The main requirements for SBVS are the following: 1) Availability of three-dimensional structure of a validated protein target [5], 2) a virtual library of small molecules to be used in the screening process [6], and 3) an efficient molecular docking algorithm to predict protein-ligand complex. Further steps may be added to include molecular dynamics simulations in order to evaluate protein-ligand interaction using a more robust and accurate methodology [7-9]. Molecular docking is a computer simulation approach able to predict the structure of a receptor-ligand complex, where the receptor is a protein target [10]. It can be defined as a simulation process where a ligand position is determined in a predicted or pre-defined binding site. Molecular docking simulation is capable of reproducing experimental data through docking validation algorithms (redocking), where protein-ligand or protein-protein conformations are obtained in silico and compared to structures obtained from X-ray crystallography or nuclear magnetic resonance. It has been shown for a large number of drug targets that the detailed structure of the protein, as obtained from experimental techniques, can be used to design or modify the structure of a small molecule docked to the target structure [2]. Most of the drugs act via non-covalent interactions. Therefore, methods to evaluate such interactions are necessary. The present volume of Current Drug Targets brings reviews focused on recent development of structure-based virtual screening methodologies, including reviews on modern computational approaches to molecular docking and evaluation of ligand binding affinity, application of molecular docking to identify new drugs. Special attention is devoted to state-of-art methodologies dedicated to molecular docking simulations. There is also a review focused on de novo protein design, also referred to as the inverse protein folding problem, which is the determination of an amino acid sequence, or a set of sequences, that will fold into a given three-dimensional protein template, and its application to four protein systems. This methodology has a broad spectrum of applications, from enhanced design of inhibitors and new sequences with better stability to the design of catalytic sites of enzymes and drug discovery [11]. One key point in the development of docking algorithms is the accuracy of docking simulation. The accuracy may vary depending on what target is being tested and what kind of molecules composes the screening library. Highest speed and highest accuracy are ideal, although opposite features for virtual screening through docking simulations. Methods which are more complex, considering many physicochemical and thermodynamic properties tend to present higher accuracy. However, these methods consume more CPU time. This is exactly the case when we use molecular dynamics simulations to evaluate ligandbiding affinity [7-9]. Likewise, methods which take into account simpler parameters, such as evolutionary algorithms, are able to predict docking conformations in fast speed, however at lower accuracy rate. Recent developments in the application of evolutionary algorithms [12,13] to docking will be reviewed in this volume. We may define evolutionary algorithms as a group of computational approaches based on the concepts of Darwin's theory of evolution that are designed to find optimal solution to problems [14]. Regardless of its definition, evolutionary algorithms are heuristic algorithms. They tend to find the best or one of the best solutions, but they can also be trapped in the local optimal solutions, unable to find the global best result. We can say that in evolutionary algorithms, the evolutionary course is simplified, and consequently it has very little in common with genuine world evolution. Furthermore, applications of structure-based virtual screening to identify new lead compounds for protein targets are also discussed. Important protein targets such as, cyclin-dependent kinase 2, purine nucleoside phosphorylase, shikimate kinase, human immunodeficiency virus 1, ubiquitin specific protease 7, and influenza A neuraminidase are reviewed here. Several recent applications of SBVS have identified new drugs, which serve as incentives for the development of new methodologies and also for extending the application to a wide range of protein targets and diseases [14-22]. In conclusion, one of the most defying challenges in the post-genomic era is the understanding of structural features of the protein-drug interaction. Information obtained from structural studies of protein targets [23-30] together with molecular docking simulations will pave the way for discovery and development of a new generation of drugs. Finally, I would like to express gratitude to the authors for their important contribution to this special issue, which hopefully will be of value to researchers dedicated to structure-based virtual screening projects.

This paper provides an overview of computational de novo protein design methods, highlighting recent advances and successes. Four protein systems are described that are important targets for drug design: human immunodeficiency virus 1, purine nucleoside phosphorylase, ubiquitin specific protease 7, and histone demethylases. Target areas for drug design for each protein are described, along with known inhibitors, focusing on peptidic inhibitors, but also describing some small-molecule inhibitors. Computational design methods that have been employed in elucidating these inhibitors for each protein are outlined, along with steps that can be taken in order to apply computational protein design to a system that has mainly used experimental methods to date.

Cell cycle deregulation is one of the first steps that transform normal cells into tumor cells. CDKs are a family of proteins devoted to controlling cell cycle entry, progression and exit. Studies from animal models show a tissuespecific essentiality of the single CDKs. In cancer cells, mis-regulation of CDK function is a common event. For this reason the pioneer compound Flavopiridol was developed and many new drugs are currently under development. ATP and the last generation of non-ATP competitive inhibitors are now emerging as one of the most potentially powerful target therapies. Many clinical trials are ongoing, as either a single agent or in combination with the classical cytotoxic agents. In this review, we discuss new strategies and methods to design more potent, selective and specific CDK inhibitors, starting from evidence emerging from animal and cancer cell models.

Poor therapeutic outcomes and serious side effects, together with acquired resistance to multiple drugs, are common problems of current cancer therapies. Therefore, there is an urgent need for new cancer-targeted drugs, which has led (inter alia) to the development of molecules that can specifically inhibit cyclin-dependent kinases (CDKs). In addition to their cell cycle regulatory functions, CDKs, especially CDK7 and CDK9, play important roles in the regulation of RNA polymerase II-mediated transcription. Here, we report on progress in the preclinical development of CDK inhibitors and their anticancer activities. Special attention is paid to the action mechanisms of the pan-specific CDK inhibitors flavopiridol and roscovitine, which have already entered phase II clinical trials as treatments for various tumours. The links between their ability to inhibit transcription and sensitisation of some types of cancer to apoptosis, mechanisms leading to p53 activation, and their synergistic cooperation with common DNA damaging drugs are also discussed. It has been demonstrated that drug-resistant cancer cells can arise during therapeutic application of small molecule protein kinase inhibitors. Clinical resistance to CDK inhibitors has not yet been described, but by comparing CDKs to other kinases, and CDK inhibitors to other clinically used protein kinase inhibitors, we also discuss possible mechanisms that could lead to resistance to CDK inhibitors.

A significant number of drugs and drug candidates in clinical development are halogenated structures. For a long time, insertion of halogen atoms on hit or lead compounds was predominantly performed to exploit their steric effects, through the ability of these bulk atoms to occupy the binding site of molecular targets. However, halogens in drug - target complexes influence several processes rather than steric aspects alone. For example, the formation of halogen bonds in ligand-target complexes is now recognized as a kind of intermolecular interaction that favorably contributes to the stability of protein-ligand complexes. This paper is aimed at introducing the fascinating versatility of halogen atoms. It starts summarizing the prevalence of halogenated drugs and their structural and pharmacological features. Next, we discuss the identification and prediction of halogen bonds in protein-ligand complexes, and how these bonds should be exploited. Interesting results of halogen insertions during the processes of hit-to-lead or lead-to-drug conversions are also detailed. Polyhalogenated anesthetics and protein kinase inhibitors that bear halogens are analyzed as cases studies. Thereby, this review serves as a guide for the virtual screening of libraries containing halogenated compounds and may be a source of inspiration for the medicinal chemists.

Since 2003, highly pathogenic H5N1 influenza viruses have been the cause of large-scale death in poultry and the subsequent infection and death of over 140 humans. At present, there are only three licensed anti-Influenza drugs namely Relenza (Zanamivir - ZMV), Tamiflu (Oseltamivir - OTV) and Amantadine/Rimantadine. The latter targets the M2 ion channel whereas the other compounds target neuraminidase (NA) and were designed through structure-based enzyme inhibitor programmes. Some structural knowledge of the Influenza neuraminidase is now known, due to remarkable advances in crystallographic techniques. The structure of H5N1 NA is particularly attractive because it offers new opportunities for drug design. Besides a profound impact that structural biology has had on understanding the Influenza virus and the rational design of antivirals, computational methods are now a viable partner to experiment in designing NA inhibitors. We herein discuss the development of current neuraminidase inhibitors, the emergence of resistance to them and recent research progress towards the development of new inhibitors.

Molecular docking is a simulation process where the binding of a small molecule is identified in the structure of a protein target. There are several different computational approaches to solve this problem. Here it is described recent developments in application of evolutionary algorithms to molecular docking simulations. Evolutionary algorithms are classified as a group of computational techniques based on the concepts of Darwin's theory of evolution that are designed to find the best possible solution to optimization problems. A successfully implementation of this algorithm can be found in the program MolDock. The main features of MolDock are reviewed here. We also describe application of MolDock to purine nucleoside phosphorylase, shikimate kinase and cyclin-dependent kinase 2.

Z-DNA, the alternative form of double-stranded DNA involved in a variety of nucleotide metabolism, is recognized and stabilized by specific Z-DNA binding proteins (ZBPs). Three ZBPs known in vertebrates --ADAR1, DAI and PKZ-- modulate innate immunity, particularly, the IFN-induced immune response. The E3L protein of vaccinia virus appears to compete with the host ZBP for Z-DNA binding, thereby suppressing the host immune system. ZBPs are, therefore, considered to be attractive therapeutic targets for infectious and immune diseases. Recent advances in computer-aided drug development combined with the high-resolution crystal and NMR structures of ZBPs have enabled us to discover novel candidates for ZBP inhibitors. In this study, we present an overview of Z-DNA and known ZBPs as drug targets, and summarize recent progress in the structure-based identification of ZBP inhibitors.

RNA interference (RNAi) is a phenomenon of sequence-specific gene silencing in mammalian cells and its discovery has lead to its wide application as a powerful tool in post-genomic research. Recently, short interfering RNA (siRNA), which induces RNAi, has been experimentally introduced as a cancer therapy and is expected to be developed as a nucleic acid-based medicine. Selection of appropriate gene targets is an important parameter in the potential success of siRNA cancer therapies. Candidate targets include genes associated with cell proliferation, metastasis, angiogenesis, and drug resistance. Importantly, silencing of such genes must not affect the functions of normal cells. Development of suitable drug delivery systems (DDSs) is also an important issue. Numerous methods to transfect siRNAs into cells have been developed, and the use of non-viral DDSs is preferred because it offers greater safety for clinical application than does the use of viral DDSs. Currently, atelocollagen and cationic liposomes represent the most advantageous non-viral DDSs available. In this article, we briefly review the mechanism of RNAi and non-viral DDSs. Next we discuss in detail some of the most recent findings concerning the administration of potential nucleic acid-based drugs against polo-like kinase-1 (PLK-1), which regulates the mitotic process in mammalian cells. These promising results demonstrate that PLK-1 is a suitable target for cancer therapy. Finally, several current clinical trials of RNAi therapies against cancers are discussed. Results of current studies and clinical trials demonstrate that manipulation of RNAi mechanism by use of targeted siRNA offers promising strategies for cancer therapies.

Valproic acid (VPA) has been used for epilepsy treatment since the 1970s. Recently, it was demonstrated that it inhibits histone deacetylases (HDAC), modulates cell cycle, induces tumor cell death and inhibits angiogenesis in various tumor models. The exact anticancer mechanisms of VPA remains unclear, but HDAC inhibition, extracellular-regulated kinase activation, protein kinase C inhibition, Wnt-signaling activation, proteasomal degradation of HDAC, possible downregulation of telomerase activity and DNA demethylation participate in its anticancer effect. Hyperacetylation of histones, as a result of HDAC inhibition, seems to be the most important mechanism of VPA's antitumor action. Preclinical data suggest that the anticancer effect of chemotherapy is augmented when VPA is used in combination with cytostatics. Besides the effects of pretreatment with HDAC inhibitors, which increases the efficiency of 5-aza-2'- deoxycytidine, VP-16, ellipticine, doxorubicin and cisplatin, pre-exposure to VPA increases the cytotoxicity of topoisomerase II inhibitors. There are two suggested cell death mechanisms caused by potentiation of anticancer drugs by HDAC inhibitors that are neither exclusive nor synergistic. The first involves apoptosis and can be both p53 dependent or independent; the second involves mechanisms other than apoptosis. In resistant chronic myeloid leukemia (CML), VPA restores sensitivity to imatinib. We have demonstrated the synergistic effects of VPA and cisplatin in neuroblastoma cells. VPA can be taken orally, crosses the blood brain barrier and can be used for extended periods. Clinical trials in patients with malignancies are being conducted. The use of VPA prior to or together with anticancer drugs may thus prove a beneficial treatment.

Thrombus formation at a site of arterial injury (eg, rupture of an atherosclerotic plaque in a carotid artery), a crucial step in the pathogenesis of cerebral ischemia, is initiated by the adhesion of platelets to the arterial wall. In vivo, activated platelets release adenosine diphosphate (ADP), whose binding to the platelet P2Y12 receptor elicits progressive and sustained platelet aggregation. As a result, this receptor has been a target for the development of clinically effective antiplatelet agents, such as the thienopyridines ticlopidine and, more recently, clopidogrel, the only two currently FDAapproved P2Y12 antagonists. Clopidogrel has a well-established role as an antithrombotic agent in the setting of ischemic stroke. However, several challenges remain, including the relatively slow onset of action of this drug and the phenomenon of clopidogrel response variability or “resistance”. A number of novel P2Y12 antagonists are therefore under investigation to determine whether they can result in better or more rapid antithrombotic effects than clopidogrel, without an unacceptable increase in hemorrhagic (or other) side effects. These include 1) prasugrel, an orally-administered thienopyridine prodrug, 2) ticagrelor (AZD6140), an ATP analog reversible P2Y12 antagonist, 3) cangrelor, an intravenously-administered reversible P2Y12 antagonist, and 4) PRT060128. Whether the promising pharmacological profile of these drugs will be translated into clinical benefit for stroke patients will be determined by the results of clinical trials.