From large networks to small molecules

Synthesis and mechanistic studies of 4-aminoquinoline-Isatin molecular hybrids and Schiff's bases as promising antimicrobial agents

In this investigation, to determine their potential as specific antibacterial agents, Schiff's bases (LT-SB1-23 and SB1-SB12) and novel quinoline-isatin hybrids were subjected to microbiological testing. The in-vitro screening against bacterial strains (Escherichia coli, Enterococcus faecalis, Bacillus subtilis, Staphylococcus aureus, Pseudomonas aeruginosa, and Salmonella typhi) exhibited their antibacterial potential with many of the compounds showing inhibition range of 90-100 % at 200 μg/mL, against most of the tested strains. The MIC values of some of the compounds showed good antibacterial efficacy with values ranging from 32 to 128 μg/mL. Their bacterial growth inhibitory potential was further supported by disk diffusion and growth curve assays. Interestingly, one of the Schiff's bases (LT-SB7) displayed strong synergistic activity against E. coli and S. typhi with 16-64 folds reduction in MIC values. Additionally, it exhibited up to 85 % suppression of biofilm at ½MIC against AA209 environmental bacterial isolate and reduced the development of multidrug-resistant bacterial isolates. Promising compound LT-SB7 underwent 100 ns molecular dynamics simulations with biofilm-causing protein (PDB ID: 7C7U) to assess conformational changes and complex stability. Overall, this study identified compounds as effective antibacterial alternatives for the future.

Model organism life extending therapeutics modulate diverse nodes in the drug-gene-microbe tripartite human longevity interactome

Advances in antiaging drug/lead discovery in animal models constitute a large body of literature on novel senotherapeutics and geroprotectives. However, with little direct evidence or mechanism of action in humans-these drugs are utilized as nutraceuticals or repurposed supplements without proper testing directions, appropriate biomarkers, or consistent in-vivo models. In this study, we take previously identified drug candidates that have significant evidence of prolonging lifespan and promoting healthy aging in model organisms, and simulate them in human metabolic interactome networks. Screening for drug-likeness, toxicity, and KEGG network correlation scores, we generated a library of 285 safe and bioavailable compounds. We interrogated this library to present computational modeling-derived estimations of a tripartite interaction map of animal geroprotective compounds in the human molecular interactome extracted from longevity, senescence, and dietary restriction-associated genes. Our findings reflect previous studies in aging-associated metabolic disorders, and predict 25 best-connected drug interactors including Resveratrol, EGCG, Metformin, Trichostatin A, Caffeic Acid and Quercetin as direct modulators of lifespan and healthspan-associated pathways. We further clustered these compounds and the functionally enriched subnetworks therewith to identify longevity-exclusive, senescence-exclusive, pseudo-omniregulators and omniregulators within the set of interactome hub genes. Additionally, serum markers for drug-interactions, and interactions with potentially geroprotective gut microbial species distinguish the current study and present a holistic depiction of optimum gut microbial alteration by candidate drugs. These findings provide a systems level model of animal life-extending therapeutics in human systems, and act as precursors for expediting the ongoing global effort to find effective antiaging pharmacological interventions.Communicated by Ramaswamy H. Sarma.

Design, Synthesis and Mechanistic Studies of Novel Isatin-Pyrazole Hydrazone Conjugates as Selective and Potent Bacterial MetAP Inhibitors

Methionine aminopeptidases (MetAPs) are attractive drug targets due to their essential role in eukaryotes as well as prokaryotic cells. In this study, biochemical assays were performed on newly synthesized Isatin-pyrazole hydrazones (PS1-14) to identify potent and selective bacterial MetAPs inhibitors. Compound PS9 inhibited prokaryotic MetAPs, i.e., MtMetAP1c, EfMetAP1a and SpMetAP1a with Ki values of 0.31, 6.93 and 0.37 µM, respectively. Interestingly, PS9 inhibited the human analogue HsMetAP1b with Ki (631.7 µM) about ten thousand-fold higher than the bacterial MetAPs. The in vitro screening against Gram-positive (Enterococcus faecalis, Bacillus subtilis and Staphylococcus aureus) and Gram-negative (Pseudomonas aeruginosa, Klebsiella pneumonia and Escherichia coli) bacterial strains also exhibited their antibacterial potential supported by minimum bactericidal concentration (MBC), disk diffusion assay, growth curve and time-kill curve experiments. Additionally, PS6 and PS9 had synergistic effects when combined with ampicillin (AMP) and ciprofloxacin (CIP) against selective bacterial strains. PS9 showed no significant cytotoxic effect on human RBCs, HEK293 cells and Galleria mellonella larvae in vivo. PS9 inhibited the growth of multidrug-resistant environmental isolates as it showed the MIC lower than the standard drugs used against selective bacterial strains. Overall, the study suggested PS9 could be a useful candidate for the development of antibacterial alternatives.

Targeting fungal membrane homeostasis with imidazopyrazoindoles impairs azole resistance and biofilm formation

Fungal infections cause more than 1.5 million deaths annually. With an increase in immune-deficient susceptible populations and the emergence of antifungal drug resistance, there is an urgent need for novel strategies to combat these life-threatening infections. Here, we use a combinatorial screening approach to identify an imidazopyrazoindole, NPD827, that synergizes with fluconazole against azole-sensitive and -resistant isolates of Candida albicans. NPD827 interacts with sterols, resulting in profound effects on fungal membrane homeostasis and induction of membrane-associated stress responses. The compound impairs virulence in a Caenorhabditis elegans model of candidiasis, blocks C. albicans filamentation in vitro, and prevents biofilm formation in a rat model of catheter infection by C. albicans. Collectively, this work identifies an imidazopyrazoindole scaffold with a non-protein-targeted mode of action that re-sensitizes the leading human fungal pathogen, C. albicans, to azole antifungals.

On the Fourier transform of a quantitative trait: Implications for compressive sensing

This paper explores the genotype-phenotype relationship. It outlines conditions under which the dependence of a quantitative trait on the genome might be predictable, based on measurement of a limited subset of genotypes. It uses the theory of real-valued Boolean functions in a systematic way to translate trait data into the Fourier domain. Important trait features, such as the roughness of the trait landscape or the modularity of a trait have a simple Fourier interpretation. Roughness at a gene location corresponds to high sensitivity to mutation, while a modular organization of gene activity reduces such sensitivity. Traits where rugged loci are rare will naturally compress gene data in the Fourier domain, leading to a sparse representation of trait data, concentrated in identifiable, low-level coefficients. This Fourier representation of a trait organizes epistasis in a form which is isometric to the trait data. As Fourier matrices are known to be maximally incoherent with the standard basis, this permits employing compressive sensing techniques to work from data sets that are relatively small-sometimes even of polynomial size-compared to the exponentially large sets of possible genomes. This theory provides a theoretical underpinning for systematic use of Boolean function machinery to dissect the dependency of a trait on the genome and environment.

Development of Oxadiazole-Sulfonamide-Based Compounds as Potential Antibacterial Agents

In this work, substituted 1,2,4-oxadiazoles (OX1-OX27) were screened against five bacterial strains, identified to be OX7 and OX11 as growth inhibitors with minimum inhibitory concentration (MIC) values of 31.25 and 15.75 μg/mL, respectively. The growth inhibitory property of OX7 and OX11 was further validated by disk diffusion, growth curve, and time kill curve assays. Both disrupted biofilm formation with 92-100% reduction examined by the XTT assay were further visualized by scanning electron microscopy analysis. These compounds in combination with ciprofloxacin also exhibit synergy against Escherichia coli cells. With insignificant cytotoxic behavior on HEK293 cells, human red blood cells, and Galleria mellonella larvae, OX11 was tested against 28 multidrug resistant environmental isolates of bacteria and showed inhibition of Kluyvera georgiana and Citrobacter werkmanii strains with 32 and 16 μg/mL MIC values, respectively. The synergistic behavior of OX11 with ampicillin showed many fold reductions in MIC values against K. georgiana and Klebsiella pneumoniae multidrug resistant strains. Further, transmission electron microscopy analysis of OX11-treated E. coli cells showed a significantly damaged cell wall, which resulted in the loss of integrity and cytosolic oozing. OX11 showed significant changes in the secondary structure of human serum albumin (HSA) in the presence of OX11, enhancing HSA stability. Overall, the study provided a suitable core for further synthetic alterations and development as an antibacterial agent.

Functionalized graphene oxide as a vehicle for targeted drug delivery and bioimaging applications

Graphene oxide (GO) has attracted tremendous attention as a most promising nanomaterial among the carbon family since it emerged as a polynomial functional tool with rational applications in diverse fields such as biomedical engineering, electrocatalysis, biosensing, energy conversion, and storage devices. Despite having certain limitations due to its irreversible aggregation performance owing largely to the strong van der Waals interactions, efforts have been made to smartly engineer its surface chemistry for realistic multimodal applications. The use of such GO-based engineered devices has increased rapidly in the last few years, principally due to its excellent properties, such as huge surface area, honeycomb-like structure allowing vacant interstitial space to accommodate compounds, sp2 hybridized carbon, improved biocompatibility and cell surface penetration due to electronic interactions. Amongst multifaceted GO dynamics, in this review, attempts are made to discuss the advanced applications of GO or graphene-based materials (GBNs) in the biomedical field involving drug or therapeutic gene delivery, dual drug or drug-gene combination targeting, special delivery of drug cocktails to the brain, stimuli-responsive release of molecular payloads, and Janus-structured smart applications for polar-nonpolar combination drug loading followed by targeting together with smart bioimaging approaches. In addition, the advantages of duel-drug delivery systems are discussed in detail. We also discuss various electronic mechanisms, and detailed surface engineering to meet microcosmic criteria for its utilization, various novel implementations of engineered GO as mentioned above, together with discussions of its inevitable toxicity or disadvantages. We hope that the target audience, belonging to biomedical engineering, pharmaceutical or material science fields, may acquire relevant information from this review which may help them design future studies in this field.

Towards the routine use of in silico screenings for drug discovery using metabolic modelling

Currently, the development of new effective drugs for cancer therapy is not only hindered by development costs, drug efficacy, and drug safety but also by the rapid occurrence of drug resistance in cancer. Hence, new tools are needed to study the underlying mechanisms in cancer. Here, we discuss the current use of metabolic modelling approaches to identify cancer-specific metabolism and find possible new drug targets and drugs for repurposing. Furthermore, we list valuable resources that are needed for the reconstruction of cancer-specific models by integrating various available datasets with genome-scale metabolic reconstructions using model-building algorithms. We also discuss how new drug targets can be determined by using gene essentiality analysis, an in silico method to predict essential genes in a given condition such as cancer and how synthetic lethality studies could greatly benefit cancer patients by suggesting drug combinations with reduced side effects.

Combined Cutaneous Therapy Using Biocompatible Metal-Organic Frameworks

Combined therapies emerge as an interesting tool to overcome limitations of traditional pharmacological treatments (efficiency, side effects). Among other materials, metal-organic frameworks (MOFs) offer versatilities for the accommodation of multiple and complementary active pharmaceutical ingredients (APIs): accessible large porosity, availability of functionalization sites, and biocompatibility. Here, we propose topical patches based on water-stable and biosafe Fe carboxylate MOFs (MIL-100 and MIL-127), the biopolymer polyvinyl alcohol (PVA) and two co-encapsulated drugs used in skin disorders (azelaic acid (AzA) as antibiotic, and nicotinamide (Nic) as anti-inflammatory), in order to develop an advanced cutaneous combined therapy. Exceptional MOF drug contents were reached (total amount 77.4 and 48.1 wt.% for MIL-100 and MIL-127, respectively), while an almost complete release of both drugs was achieved after 24 h, adapted to cutaneous delivery. The prepared cutaneous PVA-MOF formulations are safe and maintain the high drug-loading capacity (total drug content of 38.8 and 24.2 wt.% for MIL-100 and MIL-127, respectively), while allowing a controlled delivery of their cargoes, permeating through the skin to the active target sites. The total amount of drug retained or diffused through the skin is within the range (Nic), or even better (AzA) than commercial formulations. The presented results make these drug combined formulations promising candidates for new cutaneous devices for skin treatment.

The purinergic P2X7 receptor as a potential drug target to combat neuroinflammation in neurodegenerative diseases

Neurodegenerative diseases (NDDs) represent a huge social burden, particularly in Alzheimer's disease (AD) in which all proposed treatments investigated in murine models have failed during clinical trials (CTs). Thus, novel therapeutic strategies remain crucial. Neuroinflammation is a common pathogenic feature of NDDs. As purinergic P2X7 receptors (P2X7Rs) are gatekeepers of inflammation, they could be developed as drug targets for NDDs. Herein, we review this challenging hypothesis and comment on the numerous studies that have investigated P2X7Rs, emphasizing their molecular structure and functions, as well as their role in inflammation. Then, we elaborate on research undertaken in the field of medicinal chemistry to determine potential P2X7R antagonists. Subsequently, we review the state of neuroinflammation and P2X7R expression in the brain, in animal models and patients suffering from AD, Parkinson's disease, amyotrophic lateral sclerosis, Huntington's disease, multiple sclerosis, and retinal degeneration. Next, we summarize the in vivo studies testing the hypothesis that by mitigating neuroinflammation, P2X7R blockers afford neuroprotection, increasing neuroplasticity and neuronal repair in animal models of NDDs. Finally, we reviewed previous and ongoing CTs investigating compounds directed toward targets associated with NDDs; we propose that CTs with P2X7R antagonists should be initiated. Despite the high expectations for putative P2X7Rs antagonists in various central nervous system diseases, the field is moving forward at a relatively slow pace, presumably due to the complexity of P2X7Rs. A better pharmacological approach to combat NDDs would be a dual strategy, combining P2X7R antagonism with drugs targeting a selective pathway in a given NDD.

Drug combinations: a strategy to extend the life of antibiotics in the 21st century

Antimicrobial resistance threatens a resurgence of life-threatening bacterial infections and the potential demise of many aspects of modern medicine. Despite intensive drug discovery efforts, no new classes of antibiotics have been developed into new medicines for decades, in large part owing to the stringent chemical, biological and pharmacological requisites for effective antibiotic drugs. Combinations of antibiotics and of antibiotics with non-antibiotic activity-enhancing compounds offer a productive strategy to address the widespread emergence of antibiotic-resistant strains. In this Review, we outline a theoretical and practical framework for the development of effective antibiotic combinations.

Use of genetic and chemical synthetic lethality as probes of complexity in bacterial cell systems

Different conditions and genomic contexts are known to have an impact on gene essentiality and interactions. Synthetic lethal interactions occur when a combination of perturbations, either genetic or chemical, result in a more profound fitness defect than expected based on the effect of each perturbation alone. Synthetic lethality in bacterial systems has long been studied; however, during the past decade, the emerging fields of genomics and chemical genomics have led to an increase in the scale and throughput of these studies. Here, we review the concepts of genomics and chemical genomics in the context of synthetic lethality and their revolutionary roles in uncovering novel biology such as the characterization of genes of unknown function and in antibacterial drug discovery. We provide an overview of the methodologies, examples and challenges of both genetic and chemical synthetic lethal screening platforms. Finally, we discuss how to apply genetic and chemical synthetic lethal approaches to rationalize the synergies of drugs, screen for new and improved antibacterial therapies and predict drug mechanism of action.

Enhanced cytotoxicity by a benzothiazole-containing cisplatin derivative in breast cancer cells

A synergic acting cisplatin derivative, made via conjugating CJM126 with cisplatin, was synthesized and delivered using liposomes to inhibit tumor cells.

Systematic chemical-genetic and chemical-chemical interaction datasets for prediction of compound synergism

The network structure of biological systems suggests that effective therapeutic intervention may require combinations of agents that act synergistically. However, a dearth of systematic chemical combination datasets have limited the development of predictive algorithms for chemical synergism. Here, we report two large datasets of linked chemical-genetic and chemical-chemical interactions in the budding yeast Saccharomyces cerevisiae. We screened 5,518 unique compounds against 242 diverse yeast gene deletion strains to generate an extended chemical-genetic matrix (CGM) of 492,126 chemical-gene interaction measurements. This CGM dataset contained 1,434 genotype-specific inhibitors, termed cryptagens. We selected 128 structurally diverse cryptagens and tested all pairwise combinations to generate a benchmark dataset of 8,128 pairwise chemical-chemical interaction tests for synergy prediction, termed the cryptagen matrix (CM). An accompanying database resource called ChemGRID was developed to enable analysis, visualisation and downloads of all data. The CGM and CM datasets will facilitate the benchmarking of computational approaches for synergy prediction, as well as chemical structure-activity relationship models for anti-fungal drug discovery.

In vitro antimicrobial activities of animal-used quinoxaline 1,4-di-N-oxides against mycobacteria, mycoplasma and fungi

Background

The quinoxaline 1,4-di-N-oxides (QdNOs) were known as potent antibacterial agents. For the purpose of evaluating the bioactivity of existing animal-used QdNOs drugs against representative pathogenic microorganism, the representative drugs of quinoxalines including cyadox, mequindox, quinocetone and their metabolites were submitted to the in vitro evaluation for antituberculosis, antimycoplasma, antifungal and antiviral activities.

Results

In antituberculosis assays, the prototype compounds were active (MIC = 4 ~ 8 μg/mL) against Mycobacterium tuberculosis H37Rv and M. bovis. Combined antimicrobial susceptibility test indicated that cyadox, mequindox and quinocetone combined with rifampicin had additive effect against M. tuberculosis complex with Fractional Inhibitory Concentration Index (FIC) of 0.75. Results of antifungal assays showed that quinocetone was active against Microsporum canis with MIC of 8 μg/mL. Antimycoplasma screening showed a generally good activity of quinocetone against Mycoplasma gallisepticum and Mycoplasma hyopneumoniae, with MIC between 8 and 16 μg/mL. As shown from the combined antimicrobial susceptibility test, cyadox, mequindox and quinocetone combined with tetracycline had additive effect against Mycoplasma gallisepticum with FIC of 0.75. These compounds were also submitted to antiviral assay against infectious bursal disease virus, porcine reproductive and respiratory syndrome virus, porcine parvovirus and classical swine fever virus. The results obtained showed that these QdNOs and their metabolites have no inhibitory activity against these viruses in vitro.

Conclusions

QdNOs exhibit antimicrobial activities against mycobacteria, mycoplasma and fungi. This study gives new insight in further application of QdNOs and offers a way to promote the healthcare of animal husbandry.

Electronic supplementary material

The online version of this article (doi:10.1186/s12917-016-0812-7) contains supplementary material, which is available to authorized users.

DNA Damage Repair and the Emerging Role of Poly(ADP-ribose) Polymerase Inhibition in Cancer Therapeutics

PURPOSE

As a result of improved understanding of DNA repair mechanisms, poly(ADP-ribose) polymerase inhibitors (PARPi) are increasingly recognized to play an important therapeutic role in the treatment of cancer. The aim of this article is to provide a review of PARPi function in DNA damage repair and synthetic lethality and to demonstrate how these mechanisms can be exploited to provide new PARPi-based therapies to patients with solid tumors.

METHODS

Literature from a range of sources, including PubMed and MEDLINE, were searched to identify recent reports regarding DNA damage repair and PARPi.

FINDINGS

DNA damage repair is central to cellular viability. The family of poly(ADP-ribose) polymerase proteins play multiple intracellular roles in DNA repair, but function primarily in the resolution of repair of single-strand DNA breaks. Insights through the discovery of germline BRCA1/2 mutations led to the understanding of synthetic lethality and the potential therapeutic role of PARPi in the treatment of cancer. Further understanding of DNA damage repair and the concept of BRCA-like tumors have catalyzed PARPi clinical investigation in multiple oncologic settings.

IMPLICATIONS

PARPi hold great promise in the treatment of solid tumors, both as monotherapy and in combination with other cancer therapeutics. Multiple PARPi clinical trials are currently underway. Further understanding of aberrant DNA repair mechanisms in the germline and in the tumor genome will allow clinicians and researchers to apply PARPi most strategically in the era of personalized medicine.

Therapeutic potential and critical analysis of trastuzumab and bevacizumab in combination with different chemotherapeutic agents against metastatic breast/colorectal cancer affecting various endpoints

Researchers are working day and night across the globe to eradicate or at least lessen the menace of cancer faced by the mankind. The two very frequently occurring cancers faced by the human beings are metastatic breast cancer and metastatic colorectal cancer. The various chemotherapeutic agents like anthracycline, cyclophosphamide, paclitaxel, irinotecan, fluorouracil and leucovorin etc., have been used impressively for long. But the obstinate character of metastatic breast cancer and metastatic colorectal cancer needs more to tackle the threat. So, the scientists found the use of monoclonal antibodies trastuzumab (Herceptin(®)) and bevacizumab (Avastin(®)) for the same. The current study critically investigates the therapeutic potential of trastuzumab and bevacizumab in combination with various chemotherapeutic agents against metastatic breast cancer and metastatic colorectal cancer. To the best of our knowledge, this is the very first critical analysis showing percent wise increase in various positive endpoints like median time to disease progression, median survival, and progression free survival etc. for the treatment of metastatic breast/colorectal cancer using trastuzumab and bevacizumab in combination with different chemotherapeutic agents and provides the rational for the success and failure of the selected monoclonal antibodies.

Combinatorial strategies for combating invasive fungal infections

Invasive fungal infections are an important cause of human mortality and morbidity, particularly for immunocompromised populations. However, there remains a paucity of antifungal drug treatments available to combat these fungal pathogens. Further, antifungal compounds are plagued with problems such as host toxicity, fungistatic activity, and the emergence of drug resistance in pathogen populations. A promising therapeutic strategy to increase drug effectiveness and mitigate the emergence of drug resistance is through the use of combination drug therapy. In this review we describe the current arsenal of antifungals in medicine and elaborate on the benefits of combination therapy to expand our current antifungal drug repertoire. We examine those antifungal combinations that have shown potential against fungal pathogens and discuss strategies being employed to discover novel combination therapeutics, in particular combining antifungal agents with non-antifungal bioactive compounds. The findings summarized in this review highlight the promise of combinatorial strategies in combatting invasive mycoses.

Prediction of Synergism from Chemical-Genetic Interactions by Machine Learning

The structure of genetic interaction networks predicts that, analogous to synthetic lethal interactions between non-essential genes, combinations of compounds with latent activities may exhibit potent synergism. To test this hypothesis, we generated a chemical-genetic matrix of 195 diverse yeast deletion strains treated with 4,915 compounds. This approach uncovered 1,221 genotype-specific inhibitors, which we termed cryptagens. Synergism between 8,128 structurally disparate cryptagen pairs was assessed experimentally and used to benchmark predictive algorithms. A model based on the chemical-genetic matrix and the genetic interaction network failed to accurately predict synergism. However, a combined random forest and Naive Bayesian learner that associated chemical structural features with genotype-specific growth inhibition had strong predictive power. This approach identified previously unknown compound combinations that exhibited species-selective toxicity toward human fungal pathogens. This work demonstrates that machine learning methods trained on unbiased chemical-genetic interaction data may be widely applicable for the discovery of synergistic combinations in different species.

An Antifungal Combination Matrix Identifies a Rich Pool of Adjuvant Molecules that Enhance Drug Activity against Diverse Fungal Pathogens

There is an urgent need to identify new treatments for fungal infections. By combining sub-lethal concentrations of the known antifungals fluconazole, caspofungin, amphotericin B, terbinafine, benomyl, and cyprodinil with ∼3,600 compounds in diverse fungal species, we generated a deep reservoir of chemical-chemical interactions termed the Antifungal Combinations Matrix (ACM). Follow-up susceptibility testing against a fluconazole-resistant isolate of C. albicans unveiled ACM combinations capable of potentiating fluconazole in this clinical strain. We used chemical genetics to elucidate the mode of action of the antimycobacterial drug clofazimine, a compound with unreported antifungal activity that synergized with several antifungals. Clofazimine induces a cell membrane stress for which the Pkc1 signaling pathway is required for tolerance. Additional tests against additional fungal pathogens, including Aspergillus fumigatus, highlighted that clofazimine exhibits efficacy as a combination agent against multiple fungi. Thus, the ACM is a rich reservoir of chemical combinations with therapeutic potential against diverse fungal pathogens.

A self-assembled nanoparticle platform based on poly(ethylene glycol)–diosgenin conjugates for co-delivery of anticancer drugs

We developed a nanoparticle platform based on poly(ethylene glycol)–diosgenin (mPEG–DGN) conjugates for co-delivery of anticancer drug HCPT.

Rapid conversion of Pseudomonas aeruginosa to a spherical cell morphotype facilitates tolerance to carbapenems and penicillins but increases susceptibility to antimicrobial peptides

The Gram-negative human pathogen Pseudomonas aeruginosa tolerates high concentrations of β-lactam antibiotics. Despite inhibiting the growth of the organism, these cell wall-targeting drugs exhibit remarkably little bactericidal activity. However, the mechanisms underlying β-lactam tolerance are currently unclear. Here, we show that P. aeruginosa undergoes a rapid en masse transition from normal rod-shaped cells to viable cell wall-defective spherical cells when treated with β-lactams from the widely used carbapenem and penicillin classes. When the antibiotic is removed, the entire population of spherical cells quickly converts back to the normal bacillary form. Our results demonstrate that these rapid population-wide cell morphotype transitions function as a strategy to survive antibiotic exposure. Taking advantage of these findings, we have developed a novel approach to efficiently kill P. aeruginosa by using carbapenem treatment to induce en masse transition to the spherical cell morphotype and then exploiting the relative fragility and sensitivity of these cells to killing by antimicrobial peptides (AMPs) that are relatively inactive against P. aeruginosa bacillary cells. This approach could broaden the repertoire of antimicrobial compounds used to treat P. aeruginosa and serve as a basis for developing new therapeutic agents to combat bacterial infections.

Combinatorial bio-conjugation of gemcitabine and curcumin enables dual drug delivery with synergistic anticancer efficacy and reduced toxicity

Enhanced efficacy and reduced cytotoxicity of novel bio-conjugate of gemcitabine and curcumin.

Synergistic Synthetic Biology: Units in Concert

Synthetic biology aims at translating the methods and strategies from engineering into biology in order to streamline the design and construction of biological devices through standardized parts. Modular synthetic biology devices are designed by means of an adequate elimination of cross-talk that makes circuits orthogonal and specific. To that end, synthetic constructs need to be adequately optimized through in silico modeling by choosing the right complement of genetic parts and by experimental tuning through directed evolution and craftsmanship. In this review, we consider an additional and complementary tool available to the synthetic biologist for innovative design and successful construction of desired circuit functionalities: biological synergies. Synergy is a prevalent emergent property in biological systems that arises from the concerted action of multiple factors producing an amplification or cancelation effect compared with individual actions alone. Synergies appear in domains as diverse as those involved in chemical and protein activity, polypharmacology, and metabolic pathway complementarity. In conventional synthetic biology designs, synergistic cross-talk between parts and modules is generally attenuated in order to verify their orthogonality. Synergistic interactions, however, can induce emergent behavior that might prove useful for synthetic biology applications, like in functional circuit design, multi-drug treatment, or in sensing and delivery devices. Synergistic design principles are therefore complementary to those coming from orthogonal design and may provide added value to synthetic biology applications. The appropriate modeling, characterization, and design of synergies between biological parts and units will allow the discovery of yet unforeseeable, novel synthetic biology applications.

Computational structural analysis of protein interactions and networks

Protein interactions have been at the focus of computational biology in recent years. In particular, interest has come from two different communities--structural and systems biology. Here, we will discuss key systems and structural biology methods that have been used for analysis and prediction of protein-protein interactions and the insight these approaches have provided on the nature and organization of protein-protein interactions inside cells.

Evolutionary and Biochemical Aspects of Chemical Stress Resistance in Saccharomyces cerevisiae

Large-scale chemical genetics screens (chemogenomics) in yeast have been widely used to find drug targets, understand the mechanism-of-action of compounds, and unravel the biochemistry of drug resistance. Chemogenomics is based on the comparison of growth of gene deletants in the presence and absence of a chemical substance. Such studies showed that more than 90% of the yeast genes are required for growth in the presence of at least one chemical. Analysis of these data, using computational approaches, has revealed non-trivial features of the natural chemical tolerance systems. As a result two non-overlapping sets of genes are seen to respectively impart robustness and evolvability in the context of natural chemical resistance. The former is composed of multidrug-resistance genes, whereas the latter comprises genes sharing chemical genetic profiles with many others. Recent publications showing the potential applications chemogenomics in studying the pharmacological basis of various drugs are discussed, as well as the expansion of chemogenomics to other organisms. Finally, integration of chemogenomics with sensitive sequence analysis and ubiquitination/phosphorylation data led to the discovery of a new conserved domain and important post-translational modification pathways involved in stress resistance.

Enhanced anti-tumor efficacy by co-delivery of doxorubicin and paclitaxel with amphiphilic methoxy PEG-PLGA copolymer nanoparticles

The use of single chemotherapeutic drug has shown some limitations in anti-tumor treatment, such as development of drug resistance, high toxicity and limited regime of clinical uses. The combination of two or more therapeutic drugs is feasible means to overcome the limitations. Co-delivery strategy has been proposed to minimize the amount of each drug and to achieve the synergistic effect for cancer therapies. Attempts have been made to deliver chemotherapeutic drugs simultaneously using drug carriers, such as micelles, liposomes, and inorganic nanoparticles (NPs). Here we reported core-shell NPs that were doubly emulsified from an amphiphilic copolymer methoxy poly(ethylene glycol)-poly(lactide-co-glycolide) (mPEG-PLGA). These NPs offered advantages over other nanocarriers, as they were easy to fabricate by improved double emulsion method, biocompatible, and showed high loading efficacy. More importantly, these NPs could co-deliver hydrophilic doxorubicin (DOX) and hydrophobic paclitaxel (TAX). The drug-loaded NPs possessed a better polydispersity, indicating that they are more readily subject to controlled size distribution. Studies on drug release and cellular uptake of the co-delivery system demonstrated that both drugs were effectively taken up by the cells and released simultaneously. Furthermore, the co-delivery nanocarrier suppressed tumor cells growth more efficiently than the delivery of either DOX or TAX at the same concentrations, indicating a synergistic effect. Moreover, the NPs loading drugs with a DOX/TAX concentration ratio of 2:1 showed the highest anti-tumor activity to three different types of tumor cells. This nanocarrier might have important potential in clinical implications for co-delivery of multiple anti-tumor drugs with different properties.

Recent advances in the multitarget-directed ligands approach for the treatment of Alzheimer's disease

With 27 million cases worldwide documented in 2006, Alzheimer's disease (AD) constitutes an overwhelming health, social, economic, and political problem to nations. Unless a new medicine capable to delay disease progression is found, the number of cases will reach 107 million in 2050. So far, the therapeutic paradigm one-compound-one-target has failed. This could be due to the multiple pathogenic mechanisms involved in AD including amyloid β (Aβ) aggregation to form plaques, τ hyperphosphorylation to disrupt microtubule to form neurofibrillary tangles, calcium imbalance, enhanced oxidative stress, impaired mitochondrial function, apoptotic neuronal death, and deterioration of synaptic transmission, particularly at cholinergic neurons. Approximately 100 compounds are presently been investigated directed to single targets, namely inhibitors of β and γ secretase, vaccines or antibodies that clear Aβ, metal chelators to inhibit Aβ aggregation, blockers of glycogen synthase kinase 3β, enhancers of mitochondrial function, antioxidants, modulators of calcium-permeable channels such as voltage-dependent calcium channels, N-methyl-D-aspartate receptors for glutamate, or enhancers of cholinergic neurotransmission such as inhibitors of acetylcholinesterase or butyrylcholinesterase. In view of this complex pathogenic mechanisms, and the successful treatment of chronic diseases such as HIV or cancer, with multiple drugs having complementary mechanisms of action, the concern is growing that AD could better be treated with a single compound targeting two or more of the pathogenic mechanisms leading to neuronal death. This review summarizes the current therapeutic strategies based on the paradigm one-compound-various targets to treat AD. A treatment that delays disease onset and/or progression by 5 years could halve the number of people requiring institutionalization and/or dying from AD. 

Cross-species discovery of syncretic drug combinations that potentiate the antifungal fluconazole

The authors screen for compounds that show synergistic antifungal activity when combined with the widely-used fungistatic drug fluconazole. Chemogenomic profiling explains the mode of action of synergistic drugs and allows the prediction of additional drug synergies.

The authors screen for compounds that show synergistic antifungal activity when combined with the widely-used fungistatic drug fluconazole. Chemogenomic profiling explains the mode of action of synergistic drugs and allows the prediction of additional drug synergies.

Chemical screens with a library enriched for known drugs identified a diverse set of 148 compounds that potentiated the action of the antifungal drug fluconazole against the fungal pathogens Cryptococcus neoformans, Cryptococcus gattii and Candida albicans, and the model yeast Saccharomyces cerevisiae, often in a species-specific manner.

Chemogenomic profiles of six confirmed hits in S. cerevisiae revealed different modes of action and enabled the prediction of additional synergistic combinations; three-way synergistic interactions exhibited even stronger synergies at low doses of fluconazole.

The synergistic combination of fluconazole and the antidepressant sertraline was active against fluconazole-resistant clinical fungal isolates and in an in vivo model of Cryptococcal infection.

Rising fungal infection rates, especially among immune-suppressed individuals, represent a serious clinical challenge (Gullo, 2009). Cancer, organ transplant and HIV patients, for example, often succumb to opportunistic fungal pathogens. The limited repertoire of approved antifungal agents and emerging drug resistance in the clinic further complicate the effective treatment of systemic fungal infections. At the molecular level, the paucity of fungal-specific essential targets arises from the conserved nature of cellular functions from yeast to humans, as well as from the fact that many essential yeast genes can confer viability at a fraction of wild-type dosage (Yan et al, 2009). Although only ∼1100 of the ∼6000 genes in yeast are essential, almost all genes become essential in specific genetic backgrounds in which another non-essential gene has been deleted or otherwise attenuated, an effect termed synthetic lethality (Tong et al, 2001). Genome-scale surveys suggest that over 200 000 binary synthetic lethal gene combinations dominate the yeast genetic landscape (Costanzo et al, 2010). The genetic buffering phenomenon is also manifest as a plethora of differential chemical–genetic interactions in the presence of sublethal doses of bioactive compounds (Hillenmeyer et al, 2008). These observations frame the difficulty of interdicting network functions in eukaryotic pathogens with single agent therapeutics. At the same time, however, this genetic network organization suggests that judicious combinations of small molecule inhibitors of both essential and non-essential targets may elicit additive or synergistic effects on cell growth (Sharom et al, 2004; Lehar et al, 2008). Unbiased screens for drugs that synergistically enhance a specific bioactive effect, but which are not themselves individually active—termed a syncretic combination—are one means to substantially elaborate chemical space (Keith et al, 2005). Indeed, compounds that enhance the activity of known agents in model yeast and cancer cell line systems have been identified both by focused small molecule library screens and by computational methods (Borisy et al, 2003; Lehar et al, 2007; Nelander et al, 2008; Jansen et al, 2009; Zinner et al, 2009).

To extend the stratagem of chemical synthetic lethality to clinically relevant fungal pathogens, we screened a bioactive library of known drugs for synergistic enhancers of the widely used fungistatic drug fluconazole against the clinically relevant pathogens C. albicans, C. neoformans and C. gattii, as well as the genetically tractable budding yeast S. cerevisiae. Fluconazole is an azole drug that inhibits lanosterol 14α-demethylase, the gene product of ERG11, an essential cytochrome P450 enzyme in the ergosterol biosynthetic pathway (Groll et al, 1998). We identified 148 drugs that potentiate the antifungal action of fluconazole against the four species. These syncretic compounds had not been previously recognized in the clinic as antifungal agents, and many acted in a species-specific manner, often in a potent fungicidal manner.

To understand the mechanisms of synergism, we interrogated six syncretic drugs—trifluoperazine, tamoxifen, clomiphene, sertraline, suloctidil and L-cycloserine—in genome-wide chemogenomic profiles of the S. cerevisiae deletion strain collection (Giaever et al, 1999). These profiles revealed that membrane, vesicle trafficking and lipid biosynthesis pathways are targeted by five of the synergizers, whereas the sphingolipid biosynthesis pathway is targeted by L-cycloserine. Cell biological assays confirmed the predicted membrane disruption effects of the former group of compounds, which may perturb ergosterol metabolism, impair fluconazole export by drug efflux pumps and/or affect active import of fluconazole (Kuo et al, 2010; Mansfield et al, 2010). Based on the integration of chemical–genetic and genetic interaction space, a signature set of deletion strains that are sensitive to the membrane active synergizers correctly predicted additional drug synergies with fluconazole. Similarly, the L-cycloserine chemogenomic profile correctly predicted a synergistic interaction between fluconazole and myriocin, another inhibitor of sphingolipid biosynthesis. The structure of genetic networks suggests that it should be possible to devise higher order drug combinations with even greater selectivity and potency (Sharom et al, 2004). In an initial test of this concept, we found that the combination of a non-synergistic pair drawn from the membrane active and sphingolipid target classes exhibited potent three-way synergism with a low dose of fluconazole. Finally, the combination of sertraline and fluconazole was active in a G. mellonella model of Cryptococcal infection, and was also efficacious against fluconazole-resistant clinical isolates of C. albicans and C. glabrata.

Collectively, these results demonstrate that the combinatorial redeployment of known drugs defines a powerful antifungal strategy and establish a number of potential lead combinations for future clinical assessment.

Resistance to widely used fungistatic drugs, particularly to the ergosterol biosynthesis inhibitor fluconazole, threatens millions of immunocompromised patients susceptible to invasive fungal infections. The dense network structure of synthetic lethal genetic interactions in yeast suggests that combinatorial network inhibition may afford increased drug efficacy and specificity. We carried out systematic screens with a bioactive library enriched for off-patent drugs to identify compounds that potentiate fluconazole action in pathogenic Candida and Cryptococcus strains and the model yeast Saccharomyces. Many compounds exhibited species- or genus-specific synergism, and often improved fluconazole from fungistatic to fungicidal activity. Mode of action studies revealed two classes of synergistic compound, which either perturbed membrane permeability or inhibited sphingolipid biosynthesis. Synergistic drug interactions were rationalized by global genetic interaction networks and, notably, higher order drug combinations further potentiated the activity of fluconazole. Synergistic combinations were active against fluconazole-resistant clinical isolates and an in vivo model of Cryptococcus infection. The systematic repurposing of approved drugs against a spectrum of pathogens thus identifies network vulnerabilities that may be exploited to increase the activity and repertoire of antifungal agents.

Combinations of antibiotics and nonantibiotic drugs enhance antimicrobial efficacy

Combinations of antibiotics are commonly used in medicine to broaden antimicrobial spectrum and generate synergistic effects. Alternatively, combination of nonantibiotic drugs with antibiotics offers an opportunity to sample a previously untapped expanse of bioactive chemical space. We screened a collection of drugs to identify compounds that augment the activity of the antibiotic minocycline. Unexpected synergistic drug combinations exhibited in vitro and in vivo activity against bacterial pathogens, including multidrug-resistant isolates.

Systems biology approaches and tools for analysis of interactomes and multi-target drugs

Systems biology is essentially a proteomic and epigenetic exercise because the relatively condensed information of genomes unfolds on the level of proteins. The flexibility of cellular architectures is not only mediated by a dazzling number of proteinaceous species but moreover by the kinetics of their molecular changes: The time scales of posttranslational modifications range from milliseconds to years. The genetic framework of an organism only provides the blue print of protein embodiments which are constantly shaped by external input. Indeed, posttranslational modifications of proteins represent the scope and velocity of these inputs and fulfil the requirements of integration of external spatiotemporal signal transduction inside an organism. The optimization of biochemical networks for this type of information processing and storage results in chemically extremely fine tuned molecular entities. The huge dynamic range of concentrations, the chemical diversity and the necessity of synchronisation of complex protein expression patterns pose the major challenge of systemic analysis of biological models. One further message is that many of the key reactions in living systems are essentially based on interactions of moderate affinities and moderate selectivities. This principle is responsible for the enormous flexibility and redundancy of cellular circuitries. In complex disorders such as cancer or neurodegenerative diseases, which initially appear to be rooted in relatively subtle dysfunctions of multimodal physiologic pathways, drug discovery programs based on the concept of high affinity/high specificity compounds ("one-target, one-disease"), which has been dominating the pharmaceutical industry for a long time, increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade, and the treatment of "complex diseases" remains a most pressing medical need. Currently, a change of paradigm can be observed with regard to a new interest in agents that modulate multiple targets simultaneously, essentially "dirty drugs." Targeting cellular function as a system rather than on the level of the single target, significantly increases the size of the drugable proteome and is expected to introduce novel classes of multi-target drugs with fewer adverse effects and toxicity. Multiple target approaches have recently been used to design medications against atherosclerosis, cancer, depression, psychosis and neurodegenerative diseases. A focussed approach towards "systemic" drugs will certainly require the development of novel computational and mathematical concepts for appropriate modelling of complex data. But the key is the extraction of relevant molecular information from biological systems by implementing rigid statistical procedures to differential proteomic analytics.

Towards a unifying, systems biology understanding of large-scale cellular death and destruction caused by poorly liganded iron: Parkinson's, Huntington's, Alzheimer's, prions, bactericides, chemical toxicology and others as examples

Exposure to a variety of toxins and/or infectious agents leads to disease, degeneration and death, often characterised by circumstances in which cells or tissues do not merely die and cease to function but may be more or less entirely obliterated. It is then legitimate to ask the question as to whether, despite the many kinds of agent involved, there may be at least some unifying mechanisms of such cell death and destruction. I summarise the evidence that in a great many cases, one underlying mechanism, providing major stresses of this type, entails continuing and autocatalytic production (based on positive feedback mechanisms) of hydroxyl radicals via Fenton chemistry involving poorly liganded iron, leading to cell death via apoptosis (probably including via pathways induced by changes in the NF-κB system). While every pathway is in some sense connected to every other one, I highlight the literature evidence suggesting that the degenerative effects of many diseases and toxicological insults converge on iron dysregulation. This highlights specifically the role of iron metabolism, and the detailed speciation of iron, in chemical and other toxicology, and has significant implications for the use of iron chelating substances (probably in partnership with appropriate anti-oxidants) as nutritional or therapeutic agents in inhibiting both the progression of these mainly degenerative diseases and the sequelae of both chronic and acute toxin exposure. The complexity of biochemical networks, especially those involving autocatalytic behaviour and positive feedbacks, means that multiple interventions (e.g. of iron chelators plus antioxidants) are likely to prove most effective. A variety of systems biology approaches, that I summarise, can predict both the mechanisms involved in these cell death pathways and the optimal sites of action for nutritional or pharmacological interventions.

Synthetic lethality: a framework for the development of wiser cancer therapeutics

The challenge in medical oncology has always been to identify compounds that will kill, or at least tame, cancer cells while leaving normal cells unscathed. Most chemotherapeutic agents in use today were selected primarily for their ability to kill rapidly dividing cancer cells grown in cell culture and in mice, with their selectivity determined empirically during subsequent animal and human testing. Unfortunately, most of the drugs developed in this way have relatively low therapeutic indices (low toxic dose relative to the therapeutic dose). Recent advances in genomics are leading to a more complete picture of the range of mutations, both driver and passenger, present in human cancers. Synthetic lethality provides a conceptual framework for using this information to arrive at drugs that will preferentially kill cancer cells relative to normal cells. It also provides a possible way to tackle 'undruggable' targets. Two genes are synthetically lethal if mutation of either gene alone is compatible with viability but simultaneous mutation of both genes leads to death. If one is a cancer-relevant gene, the task is to discover its synthetic lethal interactors, because targeting these would theoretically kill cancer cells mutant in the cancer-relevant gene while sparing cells with a normal copy of that gene. All cancer drugs in use today, including conventional cytotoxic agents and newer 'targeted' agents, target molecules that are present in both normal cells and cancer cells. Their therapeutic indices almost certainly relate to synthetic lethal interactions, even if those interactions are often poorly understood. Recent technical advances enable unbiased screens for synthetic lethal interactors to be undertaken in human cancer cells. These approaches will hopefully facilitate the discovery of safer, more efficacious anticancer drugs that exploit vulnerabilities that are unique to cancer cells by virtue of the mutations they have accrued during tumor progression.

Synergistic drug combinations tend to improve therapeutically relevant selectivity

Drug combinations are a promising strategy to overcome the compensatory mechanisms and unwanted off-target effects that limit the utility of many potential drugs. However, enthusiasm for this approach is tempered by concerns that the therapeutic synergy of a combination will be accompanied by synergistic side effects. Using large scale simulations of bacterial metabolism and 94,110 multi-dose experiments relevant to diverse diseases, we provide evidence that synergistic drug combinations are generally more specific to particular cellular contexts than are single agent activities. We highlight six combinations whose selective synergy depends on multitarget drug activity. For one anti-inflammatory example, we show how such selectivity is achieved through differential expression of the drugs' targets in cell types associated with therapeutic, but not toxic, effects and validate its therapeutic relevance in a rat model of asthma. The context specificity of synergistic combinations creates many opportunities for therapeutically relevant selectivity and enables improved control of complex biological systems.

Finding multiple target optimal intervention in disease-related molecular network

Drugs against multiple targets may overcome the many limitations of single targets and achieve a more effective and safer control of the disease. Numerous high-throughput experiments have been performed in this emerging field. However, systematic identification of multiple drug targets and their best intervention requires knowledge of the underlying disease network and calls for innovative computational methods that exploit the network structure and dynamics. Here, we develop a robust computational algorithm for finding multiple target optimal intervention (MTOI) solutions in a disease network. MTOI identifies potential drug targets and suggests optimal combinations of the target intervention that best restore the network to a normal state, which can be customer designed. We applied MTOI to an inflammation-related network. The well-known side effects of the traditional non-steriodal anti-inflammatory drugs and the recently recalled Vioxx were correctly accounted for in our network model. A number of promising MTOI solutions were found to be both effective and safer.

Combination chemical genetics

Predicting the behavior of living organisms is an enormous challenge given their vast complexity. Efforts to model biological systems require large datasets generated by physical binding experiments and perturbation studies. Genetic perturbations have proven important and are greatly facilitated by the advent of comprehensive mutant libraries in model organisms. Small-molecule chemical perturbagens provide a complementary approach, especially for systems that lack mutant libraries, and can easily probe the function of essential genes. Though single chemical or genetic perturbations provide crucial information associating individual components (for example, genes, proteins or small molecules) with pathways or phenotypes, functional relationships between pathways and modules of components are most effectively obtained from combined perturbation experiments. Here we review the current state of and discuss some future directions for 'combination chemical genetics', the systematic application of multiple chemical or mixed chemical and genetic perturbations, both to gain insight into biological systems and to facilitate medical discoveries.

Kinase requirements in human cells: III. Altered kinase requirements in VHL-/- cancer cells detected in a pilot synthetic lethal screen

Clear cell renal carcinomas are the most common form of kidney cancer and frequently are linked to biallelic inactivation of the von Hippel-Lindau (VHL) tumor suppressor gene. The VHL gene product, pVHL, has multiple functions including directing the polyubiquitylation of the HIF transcription factor. We screened 100 shRNA vectors, directed against 88 kinases, for their ability to inhibit the viability of VHL-/- renal carcinoma cells preferentially compared with isogenic cells in which pVHL function was restored. shRNAs for "hits" identified in the primary screen were interrogated in secondary screens that included shRNA titration studies. Multiple shRNAs against CDK6, MET, and MAP2K1 (also known as MEK1) preferentially inhibited the viability of 786-O and RCC4 VHL-/- cells compared with their wild-type pVHL-reconstituted counterparts. The sensitivity of pVHL-proficient cells to these shRNAs was not restored upon HIF activation, suggesting that loss of an hypoxia-inducible factor (HIF)-independent pVHL function formed the basis for selectivity. A small-molecule Cdk4/6 inhibitor displayed enhanced activity against VHL-/- renal carcinoma cells, suggesting that in some cases hits from shRNA screens such as described here might translate into therapeutic targets.

High-order combination effects and biological robustness

Biological systems are robust, in that they can maintain stable phenotypes under varying conditions or attacks. Biological systems are also complex, being organized into many functional modules that communicate through interlocking pathways and feedback mechanisms. In these systems, robustness and complexity are linked because both qualities arise from the same underlying mechanisms. When perturbed by multiple attacks, such complex systems become fragile in both theoretical and experimental studies, and this fragility depends on the number of agents applied. We explore how this relationship can be used to study the functional robustness of a biological system using systematic high-order combination experiments. This presents a promising approach toward many biomedical and bioengineering challenges. For example, high-order experiments could determine the point of fragility for pathogenic bacteria and might help identify optimal treatments against multi-drug resistance. Such studies would also reinforce the growing appreciation that biological systems are best manipulated not by targeting a single protein, but by modulating the set of many nodes that can selectively control a system's functional state.

Chemogenomics and biotechnology

A robust knowledge of the interactions between small molecules and specific proteins aids the development of new biotechnological tools and the identification of new drug targets, and can lead to specific biological insights. Such knowledge can be obtained through chemogenomic screens. In these screens, each small molecule from a chemical library is applied to each cell type from a library of cells, and the resulting phenotypes are recorded. Chemogenomic screens have recently become very common and will continue to generate large amounts of data. The interpretation of this data will occupy biologists and chemists alike for some time to come. This review discusses methods for the acquisition and interpretation of chemogenomic data, in addition to possible applications of chemogenomics in biotechnology.