In silico identification and characterization of protein-ligand binding sites

Protein–ligand binding site prediction methods aim to predict, from amino acid sequence, protein–ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein–ligand interactions has become extremely important to help determine a protein’s functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein–ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein–ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein–ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.

Studies towards the identification of putative bioactive conformation of potent vasodilator arylidene N-acylhydrazone derivatives

In this report we disclose the synthesis, vasodilatory activity, and identification of bioactive conformation of new N-acylhydrazone and N-methyl-N-acylhydrazone derivatives, structurally designed by bioisosteric replacements of previously described cardioactive compounds LASSBio-294 and its N-methyl derivative LASSBio-785. Some of these novel derivatives presented improved vasorelaxant properties, being new cardiovascular drug candidates. (C) 2009 Elsevier Masson SAS. All rights reserved.

Identification of genes associated with local aggressiveness and metastatic behavior in soft tissue tumors

Soft tissue tumors represent a group of neoplasia with different histologic and biological presentations varying from benign, locally confined to very aggressive and metastatic tumors. The molecular mechanisms responsible for such differences are still unknown. The understanding of these molecular alterations mechanism will be critical to discriminate patients who need systemic treatment from those that can be treated only locally and could also guide the development of new drugs` against this tumors. Using 102 tumor samples representing a large spectrum of these tumors, we performed expression profiling and defined differentially expression genes that are likely to be involved in tumors that are locally aggressive and in tumors with metastatic potential. We described a set of 12 genes (SNRPD3, MEGF9, SPTAN-1, AFAP1L2, ENDOD1, SERPIN5, ZWINTAS, TOP2A, UBE2C, ABCF1, MCM2, and ARL6IP5) showing opposite expression when these two conditions were compared. These genes are mainly related to cell-cell and cell-extracellular matrix interactions and cell proliferation and might represent helpful tools for a more precise classification and diagnosis as well as potential drug targets.

Computerized identification of motor complications in Parkinson's disease

Objective: To investigate whether spirography-based objective measures are able to effectively characterize the severity of unwanted symptom states (Off and dyskinesia) and discriminate them from motor state of healthy elderly subjects. Background: Sixty-five patients with advanced Parkinson’s disease (PD) and 10 healthy elderly (HE) subjects performed repeated assessments of spirography, using a touch screen telemetry device in their home environments. On inclusion, the patients were either treated with levodopa-carbidopa intestinal gel or were candidates for switching to this treatment. On each test occasion, the subjects were asked trace a pre-drawn Archimedes spiral shown on the screen, using an ergonomic pen stylus. The test was repeated three times and was performed using dominant hand. A clinician used a web interface which animated the spiral drawings, allowing him to observe different kinematic features, like accelerations and spatial changes, during the drawing process and to rate different motor impairments. Initially, the motor impairments of drawing speed, irregularity and hesitation were rated on a 0 (normal) to 4 (extremely severe) scales followed by marking the momentary motor state of the patient into 2 categories that is Off and Dyskinesia. A sample of spirals drawn by HE subjects was randomly selected and used in subsequent analysis. Methods: The raw spiral data, consisting of stylus position and timestamp, were processed using time series analysis techniques like discrete wavelet transform, approximate entropy and dynamic time warping in order to extract 13 quantitative measures for representing meaningful motor impairment information. A principal component analysis (PCA) was used to reduce the dimensions of the quantitative measures into 4 principal components (PC). In order to classify the motor states into 3 categories that is Off, HE and dyskinesia, a logistic regression model was used as a classifier to map the 4 PCs to the corresponding clinically assigned motor state categories. A stratified 10-fold cross-validation (also known as rotation estimation) was applied to assess the generalization ability of the logistic regression classifier to future independent data sets. To investigate mean differences of the 4 PCs across the three categories, a one-way ANOVA test followed by Tukey multiple comparisons was used. Results: The agreements between computed and clinician ratings were very good with a weighted area under the receiver operating characteristic curve (AUC) coefficient of 0.91. The mean PC scores were different across the three motor state categories, only at different levels. The first 2 PCs were good at discriminating between the motor states whereas the PC3 was good at discriminating between HE subjects and PD patients. The mean scores of PC4 showed a trend across the three states but without significant differences. The Spearman’s rank correlations between the first 2 PCs and clinically assessed motor impairments were as follows: drawing speed (PC1, 0.34; PC2, 0.83), irregularity (PC1, 0.17; PC2, 0.17), and hesitation (PC1, 0.27; PC2, 0.77). Conclusions: These findings suggest that spirography-based objective measures are valid measures of spatial- and time-dependent deficits and can be used to distinguish drug-related motor dysfunctions between Off and dyskinesia in PD. These measures can be potentially useful during clinical evaluation of individualized drug-related complications such as over- and under-medications thus maximizing the amount of time the patients spend in the On state.

Drug-herb interactions: eliminating toxicity with hard drug design.

By searching the literatures, it was found that a total of 32 drugs interacting with herbal medicines in humans. These drugs mainly include anticoagulants (warfarin, aspirin and phenprocoumon), sedatives and antidepressants (midazolam, alprazolam and amitriptyline), oral contraceptives, anti-HIV agents (indinavir, ritonavir and saquinavir), cardiovascular drug (digoxin), immunosuppressants (cyclosporine and tacrolimus) and anticancer drugs (imatinib and irinotecan). Most of them are substrates for cytochrome P450s (CYPs) and/or P-glycoprotein (PgP) and many of which have narrow therapeutic indices. However, several drugs including acetaminophen, carbamazepine, mycophenolic acid, and pravastatin did not interact with herbs. Both pharmacokinetic (e.g. induction of hepatic CYPs and intestinal PgP) and/or pharmacodynamic mechanisms (e.g. synergistic or antagonistic interaction on the same drug target) may be involved in drug-herb interactions, leading of altered drug clearance, response and toxicity. Toxicity arising from drug-herb interactions may be minor, moderate, or even fatal, depending on a number of factors associated with the patients, herbs and drugs. Predicting drug-herb interactions, timely identification of drugs that interact with herbs, and therapeutic drug monitoring may minimize toxic drug-herb interactions. It is likely to predict pharmacokinetic herb-drug interactions by following the pharmacokinetic principles and using proper models that are used for predicting drug-drug interactions. Identification of drugs that interact with herbs can be incorporated into the early stages of drug development. A fourth approach for circumventing toxicity arising from drug-herb interactions is proper design of drugs with minimal potential for herbal interaction. So-called ”hard drugs” that are not metabolized by CYPs and not transported by PgP are believed not to interact with herbs due to their unique pharmacokinetic properties. More studies are needed and new approached are required to minimize toxicity arising from drug-herb interactions.

Identifying targets for drug discovery using bioinformatics

Drug discovery is the process of discovering and designing drugs, which includes target identification, target validation, lead identification, lead optimization and introduction of the new drugs to the public. This process is very important, involving analyzing the causes of the diseases and finding ways to tackle them. Objective: The problems we must face include: i) that this process is so long and expensive that it might cost millions of dollars and take a dozen years; and ii) the accuracy of identification of targets is not good enough, which in turn delays the process. Introducing bioinformatics into the drug discovery process could contribute much to it. Bioinformatics is a booming subject combining biology with computer science. It can explore the causes of diseases at the molecular level, explain the phenomena of the diseases from the angle of the gene and make use of computer techniques, such as data mining, machine learning and so on, to decrease the scope of analysis and enhance the accuracy of the results so as to reduce the cost and time. Methods: Here we describe recent studies about how to apply bioinformatics techniques in the four phases of drug discovery, how these techniques improve the drug discovery process and some possible difficulties that should be dealt with. Results: We conclude that combining bioinformatics with drug discovery is a very promising method although it faces many problems currently.

The self-reported personal wellbeing of a sample of Australian injecting drug users

Aims To examine the self-reported personal wellbeing of a sample of Australian injecting drug users (IDU) using a standardized instrument and determine the key correlates of variations in self-reported personal wellbeing.

Design, setting and participants Cross-sectional survey of 881 Australian IDU.

Measurements Self-reported personal wellbeing collected using the Personal Wellbeing Index (PWI).

Findings IDU scored significantly lower than the general Australian population on the PWI and all subscales. Lower PWI scores were associated with a range of socio-demographic, drug use and other health and social characteristics. Across all PWI subscales, lower personal wellbeing scores were associated with unemployment, past 6-month mental health problems and more frequent injecting (all P < 0.05).

Conclusions The PWI is sufficiently sensitive to distinguish between IDU and the general population, and to identify key correlates of PWI among IDU. Some domains canvassed within the scale, such as health, standard of living and life achievements, are well within the scope of current intervention strategies, such as pharmacotherapy maintenance treatment and housing and employment support services. This suggests that the PWI could be useful in clinical settings by allowing structured identification of the areas of a person's life to be addressed as a part of a treatment regimen. In order to inform targeted prevention and intervention efforts, longitudinal studies of PWI and its correlates among IDU are required.

Implementation and evaluation of brief depression and anxiety screening in clients contacting a drug and alcohol service

Introduction and Aims. High prevalence mental health (HPMH) comorbidity is common in clients seeking alcohol and other drug (AOD) treatment yet can remain undetected. Although research has reported on the introduction of screening into AOD services, little research has reported on the processes surrounding the introduction or evaluated its effectiveness.This study reports on the implementation and evaluation of brief anxiety and depression screening within a specialised, publicly funded AOD service in South-East Victoria.
Design and Methods. Study one examined the implementation of standardised HPMH screening with 114 adult clients (Mean age = 35.49, SD = 9.53; 64% male) telephoning an AOD service over a 5 week period. Measures included severity of HPMH problems,AOD use, care plans and referrals. Study two used semistructured interviews with nine staff/managers to evaluate the effectiveness of screening and its impact on service delivery.
Results. Ninety-four per cent of clients were identified at risk of anxiety or depression. Most care plans incorporated counselling, and concurrent referrals commonly involved a general practitioner. Staff and management found systematic screening increased identification and understanding of comorbid issues and enhanced client interaction but impacted on resource requirements.
Discussion and Conclusions. Most AOD treatment seekers were identified HPMH comorbid and care plans generally included counselling.Adjunctive referrals were more common for severely depressed clients. Screening was effective and enhanced client rapport.Evaluations revealed low confidence in treating HPMH issues in-house.Training may increase worker confidence in managing mental health interventions with subclinical cases, enhancing services’ ability to move towards dual diagnosis capability.

Identification and characterization of a new class of cognitive enhancers based on inhibition of insulin-regulated aminopeptidase

Approximately one-quarter of people over the age of 65 are estimated to suffer some form of cognitive impairment, underscoring the need for effective cognitive-enhancing agents. Insulin-regulated aminopeptidase (IRAP) is potentially an innovative target for the development of cognitive enhancers, as its peptide inhibitors exhibit memory-enhancing effects in both normal and memory-impaired rodents. Using a homology model of the catalytic domain of IRAP and virtual screening, we have identified a class of nonpeptide, small-molecule inhibitors of IRAP. Structure-based computational development of an initial "hit" resulted in the identification of two divergent families of compounds. Subsequent medicinal chemistry performed on the highest affinity compound produced inhibitors with nanomolar affinities (Ki 20–700 nM) for IRAP. In vivo efficacy of one of these inhibitors was demonstrated in rats with an acute dose (1 nmol in 1 µl) administered into the lateral ventricles, improving performance in both spatial working and recognition memory paradigms. We have identified a family of specific IRAP inhibitors that is biologically active which will be useful both in understanding the physiological role of IRAP and potentially in the development of clinically useful cognitive enhancers. Notably, this study also provides unequivocal proof of principal that inhibition of IRAP results in memory enhancement.

Randomised controlled trials and 'unexpected' adverse events associated with newly released drugs : improvements in pharmacovigilance systems are necessary for real-time identification of patient safety risks

Adverse drug events are one of the major causes of morbidity in developed countries, yet the drugs involved in these events have been trialled and approved on the basis of randomised controlled trials (RCTs), regarded as the study design that will produce the best evidence.

Though the focus on adverse drug events has been primarily on processes and outcomes associated with the use of these approved drugs, attention needs to be directed to the way in which the RCT study design is structured. The implementation of controls to achieve internal validity in RCTs may be the very controls that reduce external validity, and contribute to the levels of adverse drug events associated with the release of a new drug to the wider patient population.

An examination of these controls, and the effects they can have on patient safety, underscore the importance of knowing about how the clinical trials of a drug are undertaken, rather than relying only on the recorded outcomes.

As the majority of new drugs are likely to be prescribed to older patients who have one or more comorbidities in addition to that targeted by a new drug, and as the RCTs of those drugs typically under-represent the elderly and exclude patients with multiple comorbidities, timely assessment of drug safety signals is essential.

It is unlikely that regulatory jurisdictions will undertake a reassessment of safety issues for drugs that are already approved. Instead, reliance has been placed on adverse drug event reporting systems. Such systems have a very low reporting rate, and most adverse drug events remain unreported, to the eventual cost to patients and healthcare systems.

This makes it essential for near real-time systems that can pick up safety signals as they occur, so that modifications to the product information (or removal of the drug) can be implemented.

Efflux pumps of Mycobacterium tuberculosis play a significant role in antituberculosis activity of potential drug candidates

Active efflux of drugs mediated by efflux pumps that confer drug resistance is one of the mechanisms developed by bacteria to counter the adverse effects of antibiotics and chemicals. To understand these efflux mechanisms in Mycobacterium tuberculosis, we generated knockout (KO) mutants of four efflux pumps of the pathogen belonging to different classes. We measured the MICs and kill values of two different compound classes on the wild type (WT) and the efflux pump (EP) KO mutants in the presence and absence of the efflux inhibitors verapamil and L-phenylalanyl-L-arginyl-β-naphthylamide (PAβN). Among the pumps studied, the efflux pumps belonging to the ABC (ATP-binding cassette) class, encoded by Rv1218c, and the SMR (small multidrug resistance) class, encoded by Rv3065, appear to play important roles in mediating the efflux of different chemical classes and antibiotics. Efflux pumps encoded by Rv0849 and Rv1258c also mediate the efflux of these compounds, but to a lesser extent. Increased killing is observed in WT M. tuberculosis cells by these compounds in the presence of either verapamil or PAβN. The efflux pump KO mutants were more susceptible to these compounds in the presence of efflux inhibitors. We have shown that these four efflux pumps of M. tuberculosis play a vital role in mediating efflux of different chemical scaffolds. Inhibitors of one or several of these efflux pumps could have a significant impact in the treatment of tuberculosis. The identification and characterization of Rv0849, a new efflux pump belonging to the MFS (major facilitator superfamily) class, are reported.

Herb-drug interactions and mechanistic and clinical considerations

Herbal medicines are often used in combination with conventional drugs, and this may give rise to the potential of harmful herb-drug interactions. This paper updates our knowledge on clinical herb-drug interactions with an emphasis of the mechanistic and clinical consideration. In silico, in vitro, animal and human studies are often used to predict and/or identify drug interactions with herbal remedies. To date, a number of clinically important herb-drug interactions have been reported, but many of them are from case reports and limited clinical observations. Common herbal medicines that interact with drugs include St John's wort (Hypericum perforatum), ginkgo (Ginkgo biloba), ginger (Zingiber officinale), ginseng (Panax ginseng), and garlic (Allium sativum). For example, St John's wort significantly reduced the area under the plasma concentration-time curve (AUC) and blood concentrations of cyclosporine, midazolam, tacrolimus, amitriptyline, digoxin, indinavir, warfarin, phenprocoumon and theophylline. The common drugs that interact with herbal medicines include warfarin, midazolam, digoxin, amitriptyline, indinavir, cyclosporine, tacrolimus and irinotecan. Herbal medicines may interact with drugs at the intestine, liver, kidneys, and targets of action. Importantly, many of these drugs have very narrow therapeutic indices. Most of them are substrates for cytochrome P450s (CYPs) and/or P-glycoprotein (P-gp). The underlying mechanisms for most reported herb-drug interactions are not fully understood, and pharmacokinetic and/or pharmacodynamic mechanisms are implicated in many of these interactions. In particular, enzyme induction and inhibition may play an important role in the occurrence of some herbdrug interactions. Because herb-drug interactions can significantly affect circulating levels of drug and, hence, alter the clinical outcome, the identification of herb-drug interactions has important implications.

Pathways to new drug discovery in neuropsychiatry

There is currently a crisis in drug discovery for neuropsychiatric disorders, with a profound, yet unexpected drought in new drug development across the spectrum. In this commentary, the sources of this dilemma and potential avenues to redress the issue are explored. These include a critical review of diagnostic issues and of selection of participants for clinical trials, and the mechanisms for identifying new drugs and new drug targets. Historically, the vast majority of agents have been discovered serendipitously or have been modifications of existing agents. Serendipitous discoveries, based on astute clinical observation or data mining, remain a valid option, as is illustrated by the suggestion in the paper by Wahlqvist and colleagues that treatment with sulfonylurea and metformin reduces the risk of affective disorder. However, the identification of agents targeting disorder-related biomarkers is currently proving particularly fruitful. There is considerable hope for genetics as a purist, pathophysiologically valid pathway to drug discovery; however, it is unclear whether the science is ready to meet this promise. Fruitful paradigms will require a break from the orthodoxy, and creativity and risk may well be the fingerprints of success.

Zebrafish as a genetic model in pre-clinical drug testing and screening

The traditional drug discovery pipeline for the identification and development of compounds that selectively target specific molecules to ameliorate disease remains a major focus for medical research. However, the zebrafish is increasingly providing alternative strategies for various components of this pipeline. Zebrafish and their embryos are small, easily accessible and relatively low cost, making them applicable to high-throughput, small molecule screening. Zebrafish can also be manipulated by a range of forward and reverse genetics techniques to facilitate gene discovery and functional studies. Moreover, their physiological and developmental complexity provides accurate models of human disease to underpin mechanism of action and in vivo validation studies. Finally, several of these biological characteristics make zebrafish eminently suitable for toxicity testing, including eco-toxicology. Here we review the application of zebrafish to preclinical drug development and toxicity testing, including recent advances in mutant generation, drug screening and toxicology that serve to further enhance the capabilities of this valuable model organism in drug discovery.

Identification of unprecedented anticancer properties of high molecular weight biomacromolecular complex containing bovine lactoferrin (HMW-bLf)

With the successful clinical trials, multifunctional glycoprotein bovine lactoferrin is gaining attention as a safe nutraceutical and biologic drug targeting cancer, chronic-inflammatory, viral and microbial diseases. Interestingly, recent findings that human lactoferrin oligomerizes under simulated physiological conditions signify the possible role of oligomerization in the multifunctional activities of lactoferrin molecule during infections and in disease targeting signaling pathways. Here we report the purification and physicochemical characterization of high molecular weight biomacromolecular complex containing bovine lactoferrin (≥250 kDa), from bovine colostrum, a naturally enriched source of lactoferrin. It showed structural similarities to native monomeric iron free (Apo) lactoferrin (∼78-80 kDa), retained anti-bovine lactoferrin antibody specific binding and displayed potential receptor binding properties when tested for cellular internalization. It further displayed higher thermal stability and better resistance to gut enzyme digestion than native bLf monomer. High molecular weight bovine lactoferrin was functionally bioactive and inhibited significantly the cell proliferation (p<0.01) of human breast and colon carcinoma derived cells. It induced significantly higher cancer cell death (apoptosis) and cytotoxicity in a dose-dependent manner in cancer cells than the normal intestinal cells. Upon cellular internalization, it led to the up-regulation of caspase-3 expression and degradation of actin. In order to identify the cutting edge future potential of this bio-macromolecule in medicine over the monomer, its in-depth structural and functional properties need to be investigated further.