Predicting drug resistance of the HIV-1 protease using molecular interaction energy components

Drug resistance significantly impairs the efficacy of AIDS therapy. Therefore, precise prediction of resistant viral mutants is particularly useful for developing effective drugs and designing therapeutic regimen. In this study, we applied a structure-based computational approach to predict mutants of the HIV-1 protease resistant to the seven FDA approved drugs. We analyzed the energetic pattern of the protease-drug interaction by calculating the molecular interaction energy components (MIECs) between the drug and the protease residues. Support vector machines (SVMs) were trained on MIECs to classify protease mutants into resistant and nonresistant categories. The high prediction accuracies for the test sets of cross-validations suggested that the MIECs successfully characterized the interaction interface between drugs and the HIV-1 protease. We conducted a proof-of-concept study on a newly approved drug, darunavir (TMC114), on which no drug resistance data were available in the public domain. Compared with amprenavir, our analysis suggested that darunavir might be more potent to combat drug resistance. To quantitatively estimate binding affinities of drugs and study the contributions of protease residues to causing resistance, linear regression models were trained on MIECs using partial least squares (PLS). The MIEC-PLS models also achieved satisfactory prediction accuracy. Analysis of the fitting coefficients of MIECs in the regression model revealed the important resistance mutations and shed light into understanding the mechanisms of these mutations to cause resistance. Our study demonstrated the advantages of characterizing the protease-drug interaction using MIECs. We believe that MIEC-SVM and MIEC-PLS can help design new agents or combination of therapeutic regimens to counter HIV-1 protease resistant strains.     

Improving Detection of Arrhythmia Drug-Drug Interactions in Pharmacovigilance Data through the Implementation of Similarity-Based Modeling

Identification of Drug-Drug Interactions (DDIs) is a significant challenge during drug development and clinical practice. DDIs are responsible for many adverse drug effects (ADEs), decreasing patient quality of life and causing higher care expenses. DDIs are not systematically evaluated in pre-clinical or clinical trials and so the FDA U. S. Food and Drug Administration relies on post-marketing surveillance to monitor patient safety. However, existing pharmacovigilance algorithms show poor performance for detecting DDIs exhibiting prohibitively high false positive rates. Alternatively, methods based on chemical structure and pharmacological similarity have shown promise in adverse drug event detection. We hypothesize that the use of chemical biology data in a post hoc analysis of pharmacovigilance results will significantly improve the detection of dangerous interactions. Our model integrates a reference standard of DDIs known to cause arrhythmias with drug similarity data. To compare similarity between drugs we used chemical structure (both 2D and 3D molecular structure), adverse drug side effects, chemogenomic targets, drug indication classes, and known drug-drug interactions. We evaluated the method on external reference standards. Our results showed an enhancement of sensitivity, specificity and precision in different top positions with the use of similarity measures to rank the candidates extracted from pharmacovigilance data. For the top 100 DDI candidates, similarity-based modeling yielded close to twofold precision enhancement compared to the proportional reporting ratio (PRR). Moreover, the method helps in the DDI decision making through the identification of the DDI in the reference standard that generated the candidate.     

Human teratogens: update 2010

A wide variety of human teratogens have been identified. The characteristics of human teratogens can be used in the assessment of apparent “new” teratogens, when postulated. Information is available through online databases, such as TERIS and Reprotox, telephone‐based counseling resources (e.g., Organization of Teratogen Information Systems [OTIS] and European Network Teratology Information Services [ENTIS]), reference books, annual meetings of the Teratology Society, and published articles. There are significant deficiencies in the information available: (1) lack of knowledge about the molecular and cellular basis for most teratogenic effects; (2) the inability to genetically identify more susceptible women before pregnancy; (3) little information is available on dermal and airborne exposures during pregnancy; and (4) most clinicians receive little, if any, training in the identification of or counseling for exposure to potential teratogens. There are many current dilemmas in counseling about exposures in pregnancy, including: (1) Is exposure to specific drugs, such as selected serotonin re‐uptake inhibitors (SSRIs) and the inhibitors of tumor necrosis factor‐alpha, teratogenic in the first trimester of pregnancy? (2) Are the increased risks of birth defects associated with assisted reproductive technology due, in part, to epigenetic effects? (3) What are the “safe” levels of exposure to the plasticizers phthalates during pregnancy? (4) How do we convince busy physicians, nurses, and pharmacists not to use the drug categories A, B, C, D, and X in counseling and to use more accurate sources? There is a need for a national advisory center for pregnancy registries to provide guidance when new registries are being developed. Birth Defects Research (Part A), 2011. © 2011 Wiley‐Liss, Inc.     

Quantitative analysis on the characteristics of targets with FDA approved drugs

Accumulated knowledge of genomic information, systems biology, and disease mechanisms provide an unprecedented opportunity to elucidate the genetic basis of diseases, and to discover new and novel therapeutic targets from the wealth of genomic data. With hundreds to a few thousand potential targets available in the human genome alone, target selection and validation has become a critical component of drug discovery process. The explorations on quantitative characteristics of the currently explored targets (those without any marketed drug) and successful targets (targeted by at least one marketed drug) could help discern simple rules for selecting a putative successful target. Here we use integrative in silico (computational) approaches to quantitatively analyze the characteristics of 133 targets with FDA approved drugs and 3120 human disease genes (therapeutic targets) not targeted by FDA approved drugs. This is the first attempt to comparatively analyze targets with FDA approved drugs and targets with no FDA approved drug or no drugs available for them. Our results show that proteins with 5 or fewer number of homologs outside their own family, proteins with single-exon gene architecture and proteins interacting with more than 3 partners are more likely to be targetable. These quantitative characteristics could serve as criteria to search for promising targetable disease genes.     

Protein biomarkers for in vitro testing of embryotoxicity

There are new challenges for hazard and risk assessment in the chemical industry with regard to REACH legislation in Europe and related activities in the U.S. and Japan, which require the development of novel in vitro models for the molecular characterization of drug- or chemical-related effects replacing conventional animal testing. In the frame of a European FP6 project on reproductive toxicology ( www.reprotect.eu ), we prepared protein samples from mouse embryonic stem cells differentiated into contracting cardiomyocytes according to the validated embryonic stem cell test (EST) protocol, which had been exposed to toxic substances selected by an expert committee from different in vivo categories of embryotoxicity. Lysates were used to carry out the following investigations: (i) identify optimal dose range conditions in the EST that are suitable for (ii) performing a differential quantitative proteomic study of underlying molecular pathways, (iii) define classes of substances with similar proteomic response patterns, (iv) relate these classes to the traditional in vivo categories of embryotoxicity with (v) the final goal to identify novel surrogate protein biomarker candidates for embryo toxicity. We found two distinct classes of toxic substances (Dinoseb, Ochratoxin-A, and Nitrofen vs β-aminoproprionitril, Metoclopramide, Doxylamine succinate, and d-penicillamine) with clear pathway-related differences in their proteomic patterns. Most notably, different responses to cluster 1 and cluster 2 substances were observed for Heat shock protein β-1, Ras-GTPase-activating protein SH3-domain binding protein, Ran binding protein 5, and Calreticulin, Dihydropyrimidinase-like 2 (Ulip2 protein). On the other hand, Heat shock protein 8 and Fscn1 protein were down-regulated by all compounds from both clusters.     

An engineered mouse embryonic stem cell model with survivin as a molecular marker and EGFP as the reporter for high throughput screening of embryotoxic chemicals in vitro

Embryonic stem cell test (EST) is the only generally accepted in vitro method for assessing embryotoxicity without animal sacrifice. However, the implementation and application of EST for regulatory embryotoxicity screening are impeded by its technical complexity, long testing period, and limited endpoint data. In this study, a high throughput embryotoxicity screening based on mouse embryonic stem cells (mESCs) expressing enhanced green fluorescent protein (EGFP) driven by a human survivin promoter and a human cytomegalovirus promoter, respectively, was developed. These EGFP expressing mESCs were cultured in three-dimensional (3D) fibrous scaffolds in microbioreactors on a multiwell plate with EGFP fluorescence signals as cell responses to chemicals monitored noninvasively in a high throughput manner. Nine chemicals with known developmental toxicity were used to validate the survivin-based embryotoxicity assay, which showed that strongly embryotoxic compounds such as 5-fluorouracil, retinoic acid, and methotrexate downregulated survivin expression by more than 50% in 3 days, while weakly embryotoxic compounds such as boric acid, methoxyacetic acid, and tetracyclin showed modest downregulation effect and nonembryotoxic saccharin, penicillin G, and acrylamide had negligible downregulation effect on survivin expression, confirming that survivin can be used as a molecular endpoint for high throughput screening of embryotoxicants. The potential developmental toxicity of three Chinese herbal medicines were also evaluated using this assay, demonstrating its application in in vitro developmental toxicity test for drug safety assessment.     

Increased cathepsin D release by Hyp mouse osteoblast cells

The X-linked hypophosphatemia (XLH), the most common form of hereditary rickets, is caused by loss-of-function mutations of PHEX (phosphate-regulating gene with homology to endopeptidases on the X chromosome) leading to rachitic bone disease and hypophosphatemia. Available evidence today indicates that the bone defect in XLH is caused not only by hypophosphatemia and altered vitamin D metabolism but also by factor(s) locally released by osteoblast cells (ObCs). The identity of these ObC-derived pathogenic factors remains unclear. In our present study, we report our finding of a prominent protein in the culture media derived from ObC of the hypophosphatemic (Hyp) mice, a murine homolog of human XLH, which was identified as the murine procathepsin D (Cat D). By metabolic labeling studies, we further confirmed that Hyp mouse ObCs released greater amount of Cat D into culture media. This increased Cat D release by Hyp mouse ObCs was unlikely to be due to nonspecific cell damage or heterogeneous cell population and was found to be associated with an increased Cat D expression at the protein level, possibly due to a reduced Cat D degradation. However, we were not able to detect a direct effect of PHEX protein on Cat D cleavage. In support of the involvement of Cat D in mediating the inhibitory effect of Hyp mouse ObC-conditioned media on ObC calcification, we found that exposure to Cat D inhibited ObC (45)Ca incorporation and that inhibition of Cat D abolished the inhibitory effect of Hyp mouse-conditioned media on ObC calcification. In conclusion, results from our present study showed that Hyp mouse ObCs release a greater amount of Cat D, which may contribute to the inhibitory effect of Hyp mouse ObC-conditioned media on ObC mineralization.     

Insights into the selective inhibition of Candida albicans secreted aspartyl protease: a docking analysis study

Severe fungal infections have taken precedence over other bacterial infections. Of the several fungal species, Candida albicans and others belonging to the genus Candida are responsible for several clinically important fungal infections. Emerging cases of drug resistance to the currently available drugs has limited the spectrum of currently available antifungal agents. Thus, it is imperative that new biochemical targets are identified so that better effective and selective agents can be developed. Many enzymes contribute towards the complex disease process of fungal infections; the secreted aspartyl protease (SAP), expressed both in vitro and during infection, has been implicated as one of the major virulence factors of C. albicans. Three-dimensional crystal structures of C. albicans SAP and closely related clinical isolate designated as SAP2X complexed with the same potent inhibitor A-70450 have been reported. Several analogues of A-70450 with potent C. albicans SAP2X inhibitory activity are also known. However, the structural effects of the binding of these compounds with the enzyme active site are not completely understood. Our efforts in this direction involve the docking analysis of C. albicans SAP2X inhibitors complexed with SAP2X enzyme, which is reported in this work. Docking analysis was performed on a set of molecules with differing selectivities and inhibitory potencies towards C. albicans, renin and cathepsin D. The structural effects of ligand binding were analyzed on the basis of hydrophobic and hydrogen bond interactions, binding energy analysis, interaction energies, rms deviations, etc. in the resulting energy-minimized structures of the receptor-ligand complexes. Structural analysis of the resulting models indicates that hydrophobic and hydrogen bonding interactions together with binding and interaction energies are responsible for selective inhibition of C. albicans SAP2X. Hydrophobic and hydrogen bonding interactions in the various subsites of the enzyme, contributing to both increase as well as decrease in selectivity of the molecules have been detailed. Hydrogen bonding interaction plays an important role for amino acid residues such as Gly-85, Asp-86, Asp-32, Asp-218, Tyr-225, Ala-133, and so on. Significant hydrophobic interactions with the S3, S2 and S2' subsites contribute to selectivity of the compounds. These molecular modeling analyses should, in our view, contribute for further development of selective C. albicans secreted aspartyl protease inhibitors.     

Anti-inflammatory and immunosuppressive drugs and reproduction

Rheumatic diseases in women of childbearing years may necessitate drug treatment during a pregnancy, to control maternal disease activity and to ensure a successful pregnancy outcome. This survey is based on a consensus workshop of international experts discussing effects of anti-inflammatory, immunosuppressive and biological drugs during pregnancy and lactation. In addition, effects of these drugs on male and female fertility and possible long-term effects on infants exposed to drugs antenatally are discussed where data were available. Recommendations for drug treatment during pregnancy and lactation are given.     

DRUGS IN PREGNANCY—Their Effects on the Fetus and Newborn

In considering drug therapy for pregnant women, it must be borne in mind that almost all chemical compounds in use as therapeutic agents pass from the maternal to the fetal circulation through the placenta. These drugs can produce a wide range of harmful effects on the fetus and neonatal infant. The effects of some substances for which we have data reflecting a deleterious effect are listed.It is suggested that in the future more caution be exercised in using drugs during pregnancy and that in histories, both obstetrical and pediatric, any therapy given to the mother during gestation be recorded in detail.     

Analysis of FDA Approved Anticancer Drugs Reveals the Future of Cancer Therapy

This review discusses 26 new anticancer drugs approved by the FDA in the past decade. Based on their targets, these anticancer agents can be divided into three groups. First group contains cancer-selective or semi-selective drugs that are effective in rare kinase-addictive cancers. For other malignancies, semi-selective drugs have to be judiciously combined with non-selective agents. The second group includes analogs of classic cytotoxic agents such as DNA alkylating agents, nucleoside analogs, and anti-microtubule agents. As expected, they have a marginal advantage over the existing cytotoxic drugs, nevertheless are more effective (in common cancers) than semi-selective agents. The third is a diverse group of tissue-selective agents that essentially attack the normal tissues of tumor origin and thus, exploit the tissue-specific similarities between normal and cancer cells. Our analysis predicts that monotherapy with semi-selective agents will be limited to rare cancers. In most cancers however, two anticancer strategies may be most fruitful: (a) combinations of cytotoxic drugs with semi-selective agents aimed at matching targets and (b) tissue-selective therapy aimed at normal and tumor cells of the same tissues.     

Classifying Drugs by their Arrhythmogenic Risk Using Machine Learning

All medications have adverse effects. Among the most serious of these are cardiac arrhythmias. Current paradigms for drug safety evaluation are costly, lengthy, conservative, and impede efficient drug development. Here, we combine multiscale experiment and simulation, high-performance computing, and machine learning to create a risk estimator to stratify new and existing drugs according to their proarrhythmic potential. We capitalize on recent developments in machine learning and integrate information across 10 orders of magnitude in space and time to provide a holistic picture of the effects of drugs, either individually or in combination with other drugs. We show, both experimentally and computationally, that drug-induced arrhythmias are dominated by the interplay between two currents with opposing effects: the rapid delayed rectifier potassium current and the L-type calcium current. Using Gaussian process classification, we create a classifier that stratifies drugs into safe and arrhythmic domains for any combinations of these two currents. We demonstrate that our classifier correctly identifies the risk categories of 22 common drugs exclusively on the basis of their concentrations at 50% current block. Our new risk assessment tool explains under which conditions blocking the L-type calcium current can delay or even entirely suppress arrhythmogenic events. Using machine learning in drug safety evaluation can provide a more accurate and comprehensive mechanistic assessment of the proarrhythmic potential of new drugs. Our study paves the way toward establishing science-based criteria to accelerate drug development, design safer drugs, and reduce heart rhythm disorders.     

Phase 0 clinical trials in cancer drug development: from FDA guidance to clinical practice

The Food and Drug Administration (FDA) recently introduced the Exploratory Investigational New Drug Guidance to expedite the clinical evaluation of new therapeutic and imaging agents. Early clinical studies performed under the auspices of this guidance, so-called "Phase 0" trials, have been initiated at the National Cancer Institute to integrate qualified pharmacodynamic biomarker assays into first-in-human cancer clinical trials of molecularly targeted agents. The goal of this integration is to perform molecular proof-of-concept investigations at the earliest stage of cancer drug development. Phase 0 trials do not offer any possibility of patient benefit; instead, intensive, real-time pharmacodynamic and pharmacokinetic analyses of patient tumor samples and/or surrogate tissues are performed to inform subsequent trials. Phase 0 studies do not replace formal Phase I drug safety testing and require a substantial investment of resources in assay development early on; however, they offer the promise of more rational selection of agents for further, large-scale development as well as the molecular identification of potential therapeutic failures early in the development process.     

Lead genetic studies in Dictyostelium discoideum and translational studies in human cells demonstrate that sphingolipids are key regulators of sensitivity to cisplatin and other anticancer drugs

A Dictyostelium discoideum mutant with a disruption in the sphingosine-1-phosphate (S-1-P) lyase gene was obtained in an unbiased genetic analysis, using random insertional mutagenesis, for mutants with increased resistance to the widely used cancer chemotherapeutic drug cisplatin. This finding opened the way to extensive studies in both D. discoideum and human cells on the role and mechanism of action of the bioactive sphingolipids S-1-P and ceramide in regulating the response to chemotherapeutic drugs. These studies showed that the levels of activities of the sphingolipid metabolizing enzymes S-1-P lyase, sphingosine kinase and ceramide synthase, affect whether a cell dies or lives in the presence of specific drugs. The demonstration that multiple enzymes of this biochemical pathway were involved in regulating drug sensitivity provided new opportunities to test whether pharmacological intervention might increase sensitivity. Thus it is of considerable clinical significance that pharmacological inhibition of sphingosine kinase synergistically sensitizes cells to cisplatin, both in D. discoideum and human cells. Linkage to the p38 MAP kinase and protein kinase C (PKC) signaling pathways has been demonstrated. This work demonstrates the utility of D. discoideum as a lead genetic system to interrogate molecular mechanisms controlling the sensitivity of tumor cells to chemotherapeutic agents and for determining novel ways of increasing efficacy. The D. discoideum system could be easily adapted to a high throughput screen for novel chemotherapeutic agents.