Shedding light on the puzzle of drug-membrane interactions: Experimental techniques and molecular dynamics simulations

Lipid membranes work as barriers, which leads to inevitable drug-membrane interactions in vivo. These interactions affect the pharmacokinetic properties of drugs, such as their diffusion, transport, distribution, and accumulation inside the membrane. Furthermore, these interactions also affect their pharmacodynamic properties with respect to both therapeutic and toxic effects. Experimental membrane models have been used to perform in vitro assessment of the effects of drugs on the biophysical properties of membranes by employing different experimental techniques. In in silico studies, molecular dynamics simulations have been used to provide new insights at an atomistic level, which enables the study of properties that are difficult or even impossible to measure experimentally. Each model and technique has its advantages and disadvantages. Hence, combining different models and techniques is necessary for a more reliable study. In this review, the theoretical backgrounds of these (in vitro and in silico) approaches are presented, followed by a discussion of the pharmacokinetic and pharmacodynamic properties of drugs that are related to their interactions with membranes. All approaches are discussed in parallel to present for a better connection between experimental and simulation studies. Finally, an overview of the molecular dynamics simulation studies used for drug-membrane interactions is provided.     

Liquid chromatography-inductively coupled plasma-based metallomic approaches to probe health-relevant interactions between xenobiotics and mammalian organisms

In mammals, the transport of essential elements from the gastrointestinal tract to organs is orchestrated by biochemical mechanisms which have evolved over millions of years. The subsequent organ-based assembly of sufficient amounts of metalloproteins is a prerequisite to maintain mammalian health and well-being. The chronic exposure of various human populations to environmentally abundant toxic metals/metalloid compounds and/or the deliberate administration of medicinal drugs, however, can adversely affect these processes which may eventually result in disease. A better understanding of the perturbation of these processes has the potential to advance human health, but their visualization poses a major problem. Nonetheless, liquid chromatography-inductively coupled plasma-based 'metallomics' methods, however, can provide much needed insight. Size-exclusion chromatography-inductively coupled plasma atomic emission spectrometry, for example, can be used to visualize changes that toxic metals/medicinal drugs exert at the metalloprotein level when they are added to plasma in vitro. In addition, size-exclusion chromatography-inductively coupled plasma mass spectrometry can be employed to analyze organs from toxic metal/medicinal drug-exposed organisms for metalloproteins to gain insight into the biochemical changes that are associated with their acute or chronic toxicity. The execution of such studies-from the selection of an appropriate model organism to the generation of accurate analytical data-is littered with potential pitfalls that may result in artifacts. Drawing on recent lessons that were learned by two research groups, this tutorial review is intended to provide relevant information with regard to the experimental design and the practical application of these aforementioned metallomics tools in applied health research.     

Thermodynamics of drug-DNA interactions

Many anticancer, antibiotic, and antiviral drugs exert their primary biological effects by reversibly interacting with nucleic acids. Therefore, these biomolecules represent a major target in drug development strategies designed to produce next generation therapeutics for diseases such as cancer. In order to improve the clinical efficacy of existing drugs and also to design new ones it is necessary to understand the molecular basis of drug-DNA interactions in structural, thermodynamic, and kinetic detail. The past decade has witnessed an increase in the number of rigorous biophysical studies of drug-DNA systems and considerable knowledge has been gained in the energetics of these binding reactions. This is, in part, due to the increased availability of high-sensitivity calorimetric techniques, which have allowed the thermodynamics of drug-DNA interactions to be probed directly and accurately. The focus of this article is to review thermodynamic approaches to examining drug-DNA recognition. Specifically, an overview of a recently developed method of analysis that dissects the binding free energy of these reactions into five component terms is presented. The results of applying this analysis to the DNA binding interactions of both minor groove drugs and intercalators are discussed. The solvent water plays a key role in nucleic acid structure and consequently in the binding of ligands to these biomolecules. Any rational approach to DNA-targeted drug design requires an understanding of how water participates in recognition and binding events. Recent studies examining hydration changes that accompany DNA binding by intercalators will be reviewed. Finally some aspects of cooperativity in drug-DNA interactions are described and the importance of considering cooperative effects when examining these reactions is highlighted.     

Analysis of virus-infected cells by flow cytometry

Flow cytometry has been used to study virus-cell interactions for many years. This article critically reviews a number of reports on the use of flow cytometry for the detection of virus-infected cells directly in clinical samples and in virus-infected cultured cells. Examples are presented of the use of flow cytometry to screen antiviral drugs against human immunodeficiency virus (HIV), human cytomegalovirus, and herpes simplex viruses (HSV) and to perform drug susceptibility testing for these viruses. The use of reporter genes such as green fluorescent protein incorporated into HIV or HSV or into cells for the detection of the presence of virus, for drug susceptibility assay, and for viral pathogenesis is also covered. Finally, studies on the use of flow cytometry for studying the effect of virus infection on apoptosis and the cell cycle are summarized. It is hoped that this article will give the reader some understanding of the great potential of this technology for studying virus cell interactions.     

双分子荧光互补技术在动物病毒中的研究进展

病毒侵染宿主的过程存在着一系列相互作用,了解病毒与宿主之间的蛋白质相互作用对于深入研究病毒具有重要意义。在众多研究蛋白质相互作用的方法中,双分子荧光互补技术（bimolecular fluorescence complementation,BiFC）因其能在活细胞中可视化相互作用而被广泛应用。介绍了双分子荧光技术的原理、发展和优势,总结了双分子荧光技术在动物病毒以及抗病毒药物研究中的应用,并进一步阐述了新型双分子荧光系统的原理,以期为研究动物病毒致病机制和抗病毒药物研发提供新的思路。     

High-performance affinity chromatography: a powerful tool for studying serum protein binding

High-performance affinity chromatography (HPAC) is a method in which a biologically-related ligand is used as a stationary phase in an HPLC system. This approach is a powerful means for selectively isolating or quantitating agents in complex samples, but it can also be employed to study the interactions of biological systems. In recent years there have been numerous reports in which HPAC has been used to examine the interactions of drugs, hormones and other substances with serum proteins. This review discusses how HPAC has been used in such work. Particular attention is given to the techniques of zonal elution and frontal analysis. Various applications are provided for these techniques, along with a list of factors that need to be considered in their optimization and use. New approaches based on band-broadening studies and rapid immunoextraction are also discussed.     

Exploiting azide–alkyne click chemistry in the synthesis,tracking and targeting of platinum anticancer complexes

Click chemistry is fundamentally important to medicinal chemistry and chemical biology. It represents a powerful and versatile tool, which can be exploited to develop novel Pt-based anticancer drugs and to better understand the biological effects of Pt-based anticancer drugs at a cellular level. Innovative azide–alkyne cycloaddition–based approaches are being used to functionalise Pt-based complexes with biomolecules to enhance tumour targeting. Valuable information in relation to the mechanisms of action and resistance of Pt-based drugs is also being revealed through click-based detection, isolation and tracking of Pt drug surrogates in biological and cellular environments. Although less well-explored, inorganic Pt-click reactions enable synthesis of novel (potentially multimetallic) Pt complexes and provide plausible routes to introduce functional groups and monitoring Pt-azido drug localisation.     

Serotonin receptor changes after chronic antidepressant treatments: ligand binding, electrophysiological, and behavioral studies

Early biochemical research on antidepressant treatments provided evidence that the treatments alter catecholaminergic and serotonergic activity. The mechanisms of action proposed by the resulting biogenic amine hypotheses of affective disorders, however, are not consistent with the delayed onset of therapeutic effects of antidepressant treatments nor with the acute effects of more recently developed antidepressant drugs. Recent investigation of chronic antidepressant treatments using ligand binding, electrophysiological, and behavioral techniques have attempted to identify subgroups of receptors that might be affected uniquely and specifically by chronic antidepressant treatments. Such receptor changes have been suggested to form a basis for the mechanism of action of antidepressants. At the present time, however, the data produced by ligand binding experiments and electrophysiological experiments investigating serotonergic functioning do not fit together. In addition, interpretational problems and internal contradictions exist within each of the three bodies of data when straightforward hypotheses regarding a serotonergic role in antidepressant treatment are formulated. In order to clarify the serotonergic role in antidepressant drug and ECS effects the functional significance of observed changes in putative serotonergic receptors must be discovered. Unfortunately, putative receptors identified by ligand binding cannot be directly compared to those identified by electrophysiological techniques, because these two methods require the disassembly of the organism in mutually incompatible ways. In order to prove that either or both techniques do in fact identify functional serotonin receptors, investigators need to proceed both more microscopically and also more globally. Further anatomical and physiological studies are necessary to locate putative receptors and to demonstrate their place in existing serotonergic networks. Further behavioral studies must be done to relate alterations in receptor characteristics to the functioning of the intact organism.     

miREnvironment database: providing a bridge for microRNAs, environmental factors and phenotypes

The interaction between genetic factors and environmental factors has critical roles in determining the phenotype of an organism. In recent years, a number of studies have reported that the dysfunctions on microRNA (miRNAs), environmental factors and their interactions have strong effects on phenotypes and even may result in abnormal phenotypes and diseases, whereas there has been no a database linking miRNAs, environmental factors and phenotypes. Such a resource platform is believed to be of great value in the understanding of miRNAs, environmental factors, especially drugs and diseases. In this study, we constructed the miREnvironment database, which contains a comprehensive collection and curation of experimentally supported interactions among miRNAs, environmental factors and phenotypes. The names of miRNAs, phenotypes, environmental factors, conditions of environmental factors, samples, species, evidence and references were further annotated. miREnvironment represents a biomedical resource for researches on miRNAs, environmental factors and diseases. AVAILABILITY: http://cmbi.bjmu.edu.cn/miren. CONTACT: cuiqinghua@hsc.pku.edu.cn.     

Organisms as Functional Machines: A Connectivity Explanation

Living organisms exist as a complex set of levels of organizationarranged in a pattern of strong ordering with none of theselevels being more important than others for a full understandingof life. Central to biological strong ordering is the organismallevel. Individual organisms are of special interest to biologistsbecause they are relevant to all biological processes regardlessof the operational level of the process. This is especiallytrue for investigations of the morphological-physiological propertiesof organisms. For such studies, living organisms must be consideredas complex machines with all of the sophisticated integrationand multifarious interactions of component parts typical ofcomplex systems. Understanding of the properties of any individualfeature in an organism depends as much, or possibly even more,on an appreciation of its connections and interactions withother features of that organism than on an understanding ofits intrinsic attributes. Learning the connectivity skills,including the modes of thinking, needed to comprehend the integrationof diverse components of any complex system requires a differenttraining than that needed to determine the detailed attributesof individual parts; both are necessary, however, to achieveproper advances in biological knowledge. Case studies of severalvertebrate features will be used to illustrate types of interactionswhich exist between structural/functional attributes, and howtheir recognition can lead to new and interesting questions.This "feeling for the organism" may be the major factor separatingthose biologists who are able to make important discoveriesfrom those who will only provide the subsequent, less excitingdetails of normal science.     

Novel antimicrobial peptides that exhibit activity against select agents and other drug resistant bacteria

One of the greatest challenges facing modern medicine is the evolution of drug resistant strains of bacteria. In addition to traditional methods of exposure to traditional bacterial organisms there is a growing concerned of the use of bacteria as bio-terrorism agents. To counter the evolution of drug resistant and potential bio-terrorism bacterial agents new antibiotic drugs must be developed. One potential source of new therapeutic agents that act via a novel mechanism of action are natural and synthetic antimicrobial peptides (AMPs). In our laboratories we have developed a series of AMPs incorporating the un-natural amino acids Tic-Oic to impart organism selectivity and potency while increasing metabolic stability. Herein the in vitro activity of these peptides, including ten new compounds, against eight potential bio-terrorism bacterial agents and three other bacterial strains is presented and discussed. These peptides exhibit a wide range of organism potency and selectivity. Calcein fluorescence leakage and circular dichroism studies were conducted to confirm that these peptides interact with zwitterionic and anionic liposomes.     

A luminal breast cancer genome atlas: progress and barriers

The challenge of developing an atlas that catalogs all the functionally important genomic changes associated with the development of luminal-type breast cancer is discussed in this article. The development of genome-wide techniques such as expression profiling, array-based comparative genomic hybridization and unbiased sequencing have put a cancer genome atlas within reach. However these techniques have revealed that the somatic DNA alterations associated with the development of a common solid tumor such as breast cancer are extremely complex. For example, large scale tumor DNA resequencing projects, focused on a small number of cell lines and the analysis of many genes, suggest that as many as 100 somatic mutations may have accumulated by the time a diagnosis is made. Similarly, array comparative hybridization experiments have uncovered multiple gene amplification and deletion events. Dealing with this complexity requires access to tumor and matched normal DNA from a large number of cases, with sufficient material to complete a spectrum of analytical techniques. Second, an acceptable approach to patient consent or sample de-identification must be in place if DNA sequencing traces are to be entered into public databases. Third, samples must be linked to detailed information on disease outcomes in order to identify lesions associated with aggressive clinical behavior. We conclude that samples from neoadjuvant endocrine therapy clinical protocols offer the best sample sets to initiate a luminal breast cancer genome atlas because these studies are amongst the few in which investigators have obtained high quality frozen tumor samples associated with both short term information on the estrogen dependence of individual ER+ tumors, as well as conventional data on long-term cancer survival.     

Molecular interactions between Plasmodium and its insect vectors

Our understanding of the intricate interactions between the malarial parasite and the mosquito vector is complicated both by the number and diversity of parasite and vector species, and by the experimental inaccessibility of phenomena under investigation. Steady developments in techniques to study the parasite in the mosquito have recently been augmented by methods to culture in their entirety the sporogonic stages of some parasite species. These, together with the new saturation technologies, and genetic transformation of both parasite and vector will permit penetrating studies into an exciting and largely unknown area of parasite-host interactions, an understanding of which must result in the development of new intervention strategies. This microreview highlights key areas of current basic molecular interest, and identifies numerous lacunae in our knowledge that must be filled if we are to make rational decisions for future control strategies. It will conclude by trying to explain why in the opinion of this reviewer understanding malaria-mosquito interactions may be critical to our future attempts to limit a disease of growing global importance.     

H. influenzae Consortium: integrative study of H. influenzae-human interactions

Developments in high-throughput analysis tools coupled with integrative computational techniques have enabled biological studies to reach new levels. The ability to correlate large volumes of diverse data types into cohesive models of organism function has spawned a new systematic approach to biological investigation. The creation of a new consortium has been proposed to investigate a single organism utilizing these comprehensive approaches. The Haemophilus influenzae Consortium (HIC) would be comprised of five laboratories, each providing separate and complementary areas of expertise in the study of Haemophilus influenzae (HI). The 5-year study proposes to develop coherent models of HI, both as a stand-alone organism, and more importantly, as a human pathogen. Studies in growth condition specificity followed by genomic, metabolic, and proteomic experimentation will be combined and integrated through computational and experimental analyses to form dynamic and predictive models of HI and its responses. Data from the HIC will allow greater understanding of cellular behavior, pathogen-host interactions, bacterial infection, and provide future scientific endeavors with a template for studies of other pathogens.     

Mathematical and computational approaches can complement experimental studies of host–pathogen interactions

In addition to traditional and novel experimental approaches to study host–pathogen interactions, mathematical and computer modelling have recently been applied to address open questions in this area. These modelling tools not only offer an additional avenue for exploring disease dynamics at multiple biological scales, but also complement and extend knowledge gained via experimental tools. In this review, we outline four examples where modelling has complemented current experimental techniques in a way that can or has already pushed our knowledge of host–pathogen dynamics forward. Two of the modelling approaches presented go hand in hand with articles in this issue exploring fluorescence resonance energy transfer and two-photon intravital microscopy. Two others explore virtual or ' in silico ' deletion and depletion as well as a new method to understand and guide studies in genetic epidemiology. In each of these examples, the complementary nature of modelling and experiment is discussed. We further note that multi-scale modelling may allow us to integrate information across length (molecular, cellular, tissue, organism, population) and time (e.g. seconds to lifetimes). In sum, when combined, these compatible approaches offer new opportunities for understanding host–pathogen interactions.