The theory of interceptor-protector action of DNA binding drugs.

The review discusses the theory of interceptor-protector action (the IPA theory) as the new self-consistent biophysical theory establishing a quantitative interrelation between parameters measured in independent physico-chemical experiment and in vitro biological experiment for the class of DNA binding drugs. The elements of the theory provide complete algorithm of analysis, which may potentially be applied to any system of DNA targeting aromatic drugs. Such analytical schemes, apart from extension of current scientific knowledge, are important in the context of rational drug design for managing drug's response by changing the physico-chemical parameters of molecular complexation.

Natural Products based P-glycoprotein Activators for Improved ß-amyloid Clearance in Alzheimer's Disease: An in silico Approach.

Alzheimer's disease is an age related disorder and is defined to be progressive, irreversible neurodegenerative disease. The potential targets which are associated with the Alzheimer's disease are cholinesterases, N-methyl-D-aspartate receptor, Beta secretase 1, Pregnane X receptor (PXR) and P-glycoprotein (Pgp). P-glycoprotein is a member of the ATP binding cassette (ABC) transporter family, which is an important integral of the blood-brain, blood-cerebrospinal fluid and the blood-testis barrier. Reports from the literature provide evidences that the up-regulation of the efflux pump is liable for a decrease in ß -amyloid intracellular accumulation and is an important hallmark in Alzheimer's disease (AD). Thus, targeting ß-amyloid clearance by stimulating Pgp could be a useful strategy to prevent Alzheimer's advancement. Currently available drugs provide limited effectiveness and do not assure to cure Alzheimer's disease completely. On the other hand, the current research is now directed towards the development of synthetic or natural based therapeutics which can delay the onset or progression of Alzheimer's disease. Since ancient time medicinal plants such as Withania somnifera, Bacopa monieri, Nerium indicum have been used to prevent neurological disorders including Alzheimer's disease. Till today around 125 Indian medicinal plants have been screened on the basis of ethnopharmacology for their activity against neurological disorders. In this paper, we report bioactives from natural sources which show binding affinity towards the Pgp receptor using ligand based pharmacophore development, virtual screening, molecular docking and molecular dynamics simulation studies for the bioactives possessing acceptable ADME properties. These bioactives can thus be useful to treat Alzheimer's disease.

Screening of direct thrombin inhibitors from Radix Salviae Miltiorrhizae by a peak fractionation approach.

Thrombin plays a significant role in thromboembolic disease. In this work, a peak fractionation approach combined with an activity assay method was used to screen direct thrombin inhibitors from Radix Salviae Miltiorrhizae (RSM), a famous herbal remedy for the treatment of cardiovascular diseases in China. A total of 91 fractions were collected from the RSM extract, and 19 fractions out of them showed thrombin inhibitory effects with dose-effect relationship. Among them, three compounds were unambiguously identified as 15, 16-dihydrotanshinone I, cryptotanshinone and tanshinone IIA with IC50 values of 29.39, 81.11 and 66.60µM, respectively. The three compounds were reported with direct thrombin inhibition activities for the first time and their ligand-thrombin interactions were explored by a molecular docking research. These results may contribute to explain the medical benefit of RSM for the prevention and treatment of cardiovascular diseases.

Revisiting de novo drug design: receptor based pharmacophore screening.

De novo drug design methods such as receptor or protein based pharmacophore modeling present a unique opportunity to generate novel ligands by employing the potential binding sites even when no explicit ligand information is known for a particular target. Recent developments in molecular modeling programs have enhanced the ability of early programs such as LUDI or Pocket that not only identify the key interactions or hot spots at the suspected binding site, but also and convert these hot spots into three-dimensional search queries and virtual screening of the property filtered synthetic libraries. Together with molecular docking studies and consensus scoring schemes they would enrich the lead identification processes. In this review, we discuss the ligand and receptor based de novo drug design approaches with selected examples.

Fragment informatics and computational fragment-based drug design: an overview and update.

Fragment-based drug design (FBDD) is a promising approach for the discovery and optimization of lead compounds. Despite its successes, FBDD also faces some internal limitations and challenges. FBDD requires a high quality of target protein and good solubility of fragments. Biophysical techniques for fragment screening necessitate expensive detection equipment and the strategies for evolving fragment hits to leads remain to be improved. Regardless, FBDD is necessary for investigating larger chemical space and can be applied to challenging biological targets. In this scenario, cheminformatics and computational chemistry can be used as alternative approaches that can significantly improve the efficiency and success rate of lead discovery and optimization. Cheminformatics and computational tools assist FBDD in a very flexible manner. Computational FBDD can be used independently or in parallel with experimental FBDD for efficiently generating and optimizing leads. Computational FBDD can also be integrated into each step of experimental FBDD and help to play a synergistic role by maximizing its performance. This review will provide critical analysis of the complementarity between computational and experimental FBDD and highlight recent advances in new algorithms and successful examples of their applications. In particular, fragment-based cheminformatics tools, high-throughput fragment docking, and fragment-based de novo drug design will provide the focus of this review. We will also discuss the advantages and limitations of different methods and the trends in new developments that should inspire future research.

Receptor-based pharmacophore and pharmacophore key descriptors for virtual screening and QSAR modeling.

The intuitive nature of the pharmacophore concept has made it widely accepted by the medicinal chemistry community, evidenced by the past 3 decades of development and application of computerized pharmacophore modeling tools. On the other hand, shape complementarity has been recognized as a critical factor in molecular recognition between drugs and their receptors. Recent development of fast and accurate shape comparison tools has facilitated the wide spread use of shape matching technologies in drug discovery. However, pharmacophore and shape technologies, if used separately, often lead to high false positive rate. Thus, integrating pharmacophore matching and shape matching technologies into one program has the potential to reduce the false positive rates in virtual screening. Other issues of current pharmacophore technologies include sometimes high false negative rate and non-quantitative prediction. In this article, we first focus on a recently implemented method (Shape4) that combines receptor based shape matching and pharmacophore comparison in a single algorithm to create shape pharmacophore models for virtual screening. We also examine a recent example that utilizes multi-complex information to develop receptor-based pharmacophore models that promises to reduce false negative rate. Finally, we review several methods that employ receptor-based pharmacophore map and pharmacophore key descriptors for QSAR modeling. We conclude by emphasizing the concept of receptor-based shape pharmacophore and its roles in future drug discovery.

Development of multiplexed microarray binding assays for high-throughput drug discovery.

The ability to combine primary hit identification assays with target profiling would significantly streamline the current drug discovery process. Working towards this end, we report here the development of a microarray-based ligand binding assay that supports multiplexed analysis of G protein-coupled receptor systems in a 96-well microplate format that is compatible with the equipment and infrastructure typical of high-throughput screening laboratories. A prototype microarray was generated by pin-printing seven different receptors within the wells of a specially coated glass-bottom microplate and assaying with a cocktail of fluorescent ligands. Development of the multiplexed system included optimization of methods for depositing receptor membrane proteins and establishing a generic set of assay conditions that simultaneously satisfied the pharmacology requirements of all of the receptor systems included on the array. The multiplexed system is shown to produce valid pharmacological results as evidenced by its ability to report K(i) values for receptor-specific fluorescent ligands and rank ordered potencies for diagnostic displacing compounds comparable to values generated by conventional simplexed assays. Moreover, the results of a 40-compound mini-screen confirmed that the assay accurately identifies valid hits. The results suggest the assay may be immediately suitable for routine profiling tasks and demonstrate the potential of the format for high-throughput multiplexed drug discovery.

Evaluation of different virtual screening programs for docking in a charged binding pocket.

Virtual screening of small molecules against a protein target often identifies the correct pose, but the ranking in terms of binding energy remains a difficult problem, resulting in unacceptable numbers of false positives and negatives. To investigate this problem, the performance of three docking programs, FRED, QXP/FLO, and GLIDE, along with their five different scoring functions, was evaluated with the engineered cavity in cytochrome c peroxidase (CCP). This small cavity is negatively charged and completely buried from solvent. A test set of 60 molecules, experimentally identified as 43 "binders" and 17 "non-binders", were tested with the CCP binding site. The docking methods' performance is quantified by the ROC curve and their reproduction of crystal poses. The effects from generation of different ligand tautomers and inclusion of water molecule in the cavity are also discussed.

Using molecular docking, 3D-QSAR, and cluster analysis for screening structurally diverse data sets of pharmacological interest.

In this study, we propose a drug design approach which includes docking, molecular fingerprints based cluster analysis, and 'induced' descriptors based receptor-dependent 3D-QSAR. The method was shown to be very useful for screening and modeling structurally diverse data sets of pharmacological interest. Different from other receptor-dependent 3D-QSAR, no ambiguous alignments are required for the construction of the models, and the computational cost is relatively lower. Moreover, 'induced' descriptors were shown to be very powerful in "capturing" ligand-receptor intermolecular interactions. The methodology was validated for eight data sets sampled from the literature and from public databases: human sex hormone-binding globulin, human corticosteroid-binding globulin, anthrax lethal factor, HIV-1 reverse transcriptase, neuraminidase A, thrombin, trypsin, and Pneumocystis carinii dihydrofolate reductase data sets. The resulting models were interpretable; the constructed QSAR equations have high statistical significance and predictive strength; and the drug design solutions were shown to be useful for guiding ligand modification for the development of new inhibitors for a broad range of molecular targets.

Pseudoreceptor models in drug design: bridging ligand- and receptor-based virtual screening.

Rational drug design is based on explicit or implicit structure-activity relationship models. Typically, receptor-based or ligand-based strategies are pursued, depending on the information available about known ligands and the receptor structure. Pseudoreceptor models combine the advantages of these two strategies and represent a unifying concept for both receptor mapping and ligand matching. They can provide an entry point for structure-based modelling in drug discovery projects that lack a high-resolution structure of the target. Here, we review the field of pseudoreceptor modelling techniques along with recent hit and lead finding applications, and critically discuss prerequisites, advantages and limitations of the various approaches.

Screening for positive allosteric modulators: assessment of modulator concentration-response curves as a screening paradigm.

Targeting allosteric binding sites represents a powerful mechanism for selectively modulating receptor function. The advent of functional assays as the screening method of choice is leading to an increase in the number of allosteric modulators identified. These include positive allosteric modulators that can increase the affinity of the orthosteric agonist and potentiate the evoked response. A common method for screening for positive allosteric modulators is to examine a concentration-response (C/R) curve to the putative modulator in the presence of a single, low concentration of agonist. The study reported here has used data simulations for positive allosteric modulators according to the allosteric ternary complex model to generate modulator C/R curves. The results are then compared to the mechanistic parameters used to simulate the data. It is clear from the simulations that the potency of a positive modulator C/R curve in a screening assay is the product of both its affinity and positive cooperativity. However, it is often difficult to tell which parameter dominates the response; not knowing the actual affinity or cooperativity of a ligand may have consequences for receptor selectivity. Further modeling demonstrates that the use and choice of single agonist concentration, as well as changes in the agonist curve Hill slope, can have significant effects on the modulator C/R curve. Finally, the quantitative relationship between modulator C/R curves and the allosteric ternary complex model is explored. These simulations emphasize the importance of careful interpretation of screening data and of conducting full mechanism of action studies for positive allosteric modulators.

Evaluation of 3-carboxy-4(1H)-quinolones as inhibitors of human protein kinase CK2.

Due to the emerging role of protein kinase CK2 as a molecule that participates not only in the development of some cancers but also in viral infections and inflammatory failures, small organic inhibitors of CK2, besides application in scientific research, may have therapeutic significance. In this paper, we present a new class of CK2 inhibitors-3-carboxy-4(1H)-quinolones. This class of inhibitors has been selected via receptor-based virtual screening of the Otava compound library. It was revealed that the most active compounds, 5,6,8-trichloro-4-oxo-1,4-dihydroquinoline-3-carboxylic acid (7) (IC(50) = 0.3 microM) and 4-oxo-1,4-dihydrobenzo[h]quinoline-3-carboxylic acid (9) (IC(50) = 1 microM), are ATP competitive (K(i) values are 0.06 and 0.28 microM, respectively). Evaluation of the inhibitors on seven protein kinases shows considerable selectivity toward CK2. According to theoretical calculations and experimental data, a structural model describing the key features of 3-carboxy-4(1H)-quinolones responsible for tight binding to CK2 active site has been developed.

A comprehensive in vitro screening of d-, l-, and dl-threo-methylphenidate: an exploratory study.

dl-Methylphenidate (MPH) has been widely used to treat attention-deficit/hyperactivity disorder (ADHD) for the last half century. It had been exclusively available in the racemic form, i.e., a 50:50 mixture of d- and l-isomers. However, a single enantiomer formulation, d-MPH (dexmethylphenidate), became available for general clinical use in 2002. For this reason, the intrinsic pharmacological differences in the effects of d- and l-MPH have recently come under intense investigation. The primary therapeutic effects of MPH are generally recognized to reside in the d-isomer. The present investigation provides quantitative values for a broad range of receptor-level interactions of the individual MPH isomers to better characterize the distinction between dl-MPH versus d-MPH versus l-MPH as it relates to binding affinity at sites associated with relevant central nervous system (CNS) pharmacology, as well as peripheral physiology. Overall, there were few differences in binding affinities between d-MPH and the racemate whereas there were more apparent differences between d-MPH and l-MPH. d-MPH exhibited prominent affinity at the norepinephrine transporter (NET) site, even exceeding such affinity at the dopamine transporter (DAT). These results further demonstrate that affinity for catecholaminergic sites largely resides in the d-MPH isomer. Although binding affinity was not demonstrable at the serotonin (5-HT) transporter site (SERT), novel findings of the study included affinity for the 5-HT1A and 5-HT2B receptor sites for both d- and l-MPH, with d-MPH exerting by far the most predominant effects at these sites. Thus, the emerging data of favorable therapeutic effects of ADHD treatment with d-MPH (and dl-MPH) may be underpinned by affinity and potential pharmacologic effects at NET and DAT sites, as well as sites relevant to serotonergic neurotransmission that may modulate mood, cognition, and motor behavior. However, the present exploratory studies reflect receptor binding affinities only. The specific pharmacological activities (i.e., agonism vs. antagonism) of these compounds await further exploration.

Development and evaluation of a pharmacophore model for inhibitors of aldosterone synthase (CYP11B2).

Recently, we proposed inhibition of aldosterone synthase (CYP11B2) as a novel strategy for the treatment of congestive heart failure and myocardial fibrosis and synthesized a large number of inhibitors. In this work, a pharmacophore model for CYP11B2 inhibitors was developed by superimposition of active and non-active compounds. This model was confirmed by the synthesis of two pyridyl substituted acenaphthene derivatives (A,B). This new class of compounds as well as the pharmacophore could be helpful for the discovery of novel inhibitors.

Target-related affinity profiling: Telik's lead discovery technology.

Target-Related Affinity Profiling (TRAP) is a computational drug discovery technology that is based on 'affinity fingerprints', which are molecular descriptors derived from the protein binding preferences of small molecules. The underlying concepts of TRAP are reviewed. Affinity fingerprints are compared to molecular descriptors derived from chemical structures and shown to be a useful alternative for lead discovery. The TRAP screening process is described and two example applications are presented: I. the discovery of novel inhibitors of human intestinal carboxylesterase, and II. the discovery of novel inhibitors of cyclooxygenase-1 through the use of the affinity fingerprints of known cyclooxygenase-1 inhibitors. A summary of the complementary advantages of TRAP screening technology compared to traditional approaches to drug lead discovery concludes the review.

Current perspectives on the therapeutic utility of VR1 antagonists.

This review gives a brief overview of the expression patterns, molecular pharmacology and physiological roles of the vanilloid receptor 1 (VR1). Particular emphasis is given to the therapeutic utility of VR1 modulators. Small molecule agonists of VR1, including capsaicin and RTX, are currently utilized for a number of clinical syndromes, including intractable neuropathic pain, spinal detrusor hyperreflexia, and bladder hypersensitivity; however, antagonists of VR1 have yet to reach the clinic. While the classic VR1 antagonist, capsazepine has proven a useful tool for unraveling the molecular pharmacology of VR1, in vivo studies with this compound have had limited success due to poor pharmacokinetic properties and species selectivity issues. With the cloning of VR1 in 1997, the pharmaceutical community has been provided a molecular target for high throughput screening and small molecule lead discovery and optimization. As a result, resurgence in the interest of VR1 antagonists has given way to many new pharmacological agents that may provide better tools to probe VR1 physiology, and ultimately yield promising therapeutic agents.

Interaction between protein kinase Cmu and the vanilloid receptor type 1.

The capsaicin receptor VR1 is a polymodal nociceptor activated by multiple stimuli. It has been reported that protein kinase C plays a role in the sensitization of VR1. Protein kinase D/PKCmu is a member of the protein kinase D serine/threonine kinase family that exhibits structural, enzymological, and regulatory features distinct from those of the PKCs, with which they are related. As part of our effort to optimize conditions for evaluating VR1 pharmacology, we found that treatment of Chinese hamster ovary (CHO) cells heterologously expressing rat VR1 (CHO/rVR1) with butyrate enhanced rVR1 expression and activity. The expression of PKCmu and PKCbeta1, but not of other PKC isoforms, was also enhanced by butyrate treatment, suggesting the possibility that these two isoforms might contribute to the enhanced activity of rVR1. In support of this hypothesis, we found the following. 1) Overexpression of PKCmu enhanced the response of rVR1 to capsaicin and low pH, and expression of a dominant negative variant of PKCmu reduced the response of rVR1. 2) Reduction of endogenous PKCmu using antisense oligonucleotides decreased the response of exogenous rVR1 expressed in CHO cells as well as of endogenous rVR1 in dorsal root ganglion neurons. 3) PKCmu localized to the plasma membrane when overexpressed in CHO/rVR1 cells. 4) PKCmu directly bound to rVR1 expressed in CHO cells as well as to endogenous rVR1 in dorsal root ganglia or to an N-terminal fragment of rVR1, indicating a direct interaction between PKCmu and rVR1. 5) PKCmu directly phosphorylated rVR1 or a longer N-terminal fragment (amino acids 1-118) of rVR1 but not a shorter one (amino acids 1-99). 6) Mutation of S116A in rVR1 blocked both the phosphorylation of rVR1 by PKCmu and the enhancement by PKCmu of the rVR1 response to capsaicin. We conclude that PKCmu functions as a direct modulator of rVR1.

Molecular determinants of vanilloid sensitivity in TRPV1.

Vanilloid receptor 1 (TRPV1), a membrane-associated cation channel, is activated by the pungent vanilloid from chili peppers, capsaicin, and the ultra potent vanilloid from Euphorbia resinifera, resiniferatoxin (RTX), as well as by physical stimuli (heat and protons) and proposed endogenous ligands (anandamide, N-arachidonyldopamine, N-oleoyldopamine, and products of lipoxygenase). Only limited information is available in TRPV1 on the residues that contribute to vanilloid activation. Interestingly, rabbits have been suggested to be insensitive to capsaicin and have been shown to lack detectable [(3)H]RTX binding in membranes prepared from their dorsal root ganglia. We have cloned rabbit TRPV1 (oTRPV1) and report that it exhibits high homology to rat and human TRPV1. Like its mammalian orthologs, oTRPV1 is selectively expressed in sensory neurons and is sensitive to protons and heat activation but is 100-fold less sensitive to vanilloid activation than either rat or human. Here we identify key residues (Met(547) and Thr(550)) in transmembrane regions 3 and 4 (TM3/4) of rat and human TRPV1 that confer vanilloid sensitivity, [(3)H]RTX binding and competitive antagonist binding to rabbit TRPV1. We also show that these residues differentially affect ligand recognition as well as the assays of functional response versus ligand binding. Furthermore, these residues account for the reported pharmacological differences of RTX, PPAHV (phorbol 12-phenyl-acetate 13-acetate 20-homovanillate) and capsazepine between human and rat TRPV1. Based on our data we propose a model of the TM3/4 region of TRPV1 bound to capsaicin or RTX that may aid in the development of potent TRPV1 antagonists with utility in the treatment of sensory disorders.

The FlexX database docking environment--rational extraction of receptor based pharmacophores.

We present an integrated docking environment that allows for iterative and interactive detailed analysis of many docking solutions. All docking information is stored in an ORACLE database. New scoring schemes (e.g. target-specific scoring functions) as well as various types of filters can be easily defined and tested within this environment. As an example application we investigated the validity of the following hypothesis: If a docking procedure can lead to enrichments significantly better than random then a bias towards (partially) correct placements should be detectable. Such bias in terms of a preference for certain interacting groups within the active site can be used to select a set of receptor-based pharmacophore constraints, which in turn might be used to enhance the docking procedure. As a proof of concept for this approach we performed docking studies on three targets: thrombin, the cyclin-dependent kinase 2 (CDK2) and the angiotensin converting enzyme (ACE). We docked a set of known active compounds with standard FlexX and derived three sets of target-specific receptor-based pharmacophore constraints by statistical analysis of the predicted placements. Applying these receptor-based constraints in a virtual screening protocol utilizing FlexX-Pharm led to significantly improved enrichments.

Strategies for compound selection.

In-house pharmaceutical collections are no longer sufficient for sampling chemical spaces. As novel bioactive chemotypes are successfully identified by virtual and high -throughput screening, the ability to rapidly sift through large numbers of chemicals prior to acquisition or experiment is required. Strategies for compound selection include some of the following steps: 1.) database assembly ('in silico' inventory); 2a.) structural integrity verification (keep unique structures only); 2b.) limited exploration of alternative chemical representations for the uniques (stereoisomers, tautomers, ionization states); 3.) property and structural filtering (remove unwanted structures); 4.) 3D-structure generation (for virtual screening or 3D-based similarity); 5a.) clustering or statistical design for selection; 5b.) similarity-based selection (if bioactives are known); 5c.) receptor-based selection (if target binding site is known); 6.) add a random subset to the final list.