Balganesh, T S; Furr, B J A
Selection of appropriate targets for launching antituberculosis drug discovery programmes is challenging. This challenge is magnified by the limited repertoire of 'validated targets' and the paucity of clinically successful drugs. However, continued understanding of the biology of the microbe and its interaction with the host has enabled detailed evaluation of several interesting pathways and novel targets. The value of a target that is suitable for antituberculosis drug discovery needs to be defined not only in the context of its 'essentiality' for survival in vitro but also against a variety of properties relevant to activities in the drug discovery process, e.g.; selectivity, vulnerability, suitability for structural studies, ability to monitor inhibition in whole cells etc. It is also rarely feasible to obtain all the relevant information on the target prior to the launch of a discovery programme. Thus, there is a continuous confidence-building exercise on the validity of a target. Several novel approaches have enabled exploitation of the mycobacterial genome and prioritisation of putative targets; the concept of 'sterilisation' is now being evaluated not only through the availability of structurally diverse probe compounds but also by the ability to characterise metabolic pathways in vivo. The impact of the current knowledge base on the different facets of 'target validation' relevant to antituberculosis drug discovery is discussed in this article with emphasis on developing appropriate matrix systems to prioritise them. The article also discusses the influence of lead generation approaches with specific reference to antibacterial drug discovery.
Scott, Latanya. M.; Lawrence, Harshani. R.; Sebti, Saïd. M.; Lawrence, Nicholas. J.; Wu, Jie.
Protein tyrosine phosphatases (PTPs) are a diverse family of enzymes encoded by 107 genes in the human genome. Together with protein tyrosine kinases (PTKs), PTPs regulate various cellular activities essential for the initiation and maintenance of malignant phenotypes. While PTK inhibitors are now used routinely for cancer treatment, the PTP inhibitor development field is still in the discovery phase. In this article, the suitability of targeting PTPs for novel anticancer drug discovery is discussed. Examples are presented for PTPs that have been targeted for anticancer drug discovery as well as potential new PTP targets for novel anticancer drug discovery. PMID:20337577
Tian, Hai-Feng; Chen, Bing; Wen, Jian-Fan
Giardiasis is a worldwide parasitic disease caused by the protozoan Giardia lamblia in humans and other animals, especially live stocks. Here, we briefly review the current state of therapeutic availability for giardiasis, including chemical drugs and vaccines, and the dilemma in the prevention and treatment of this disease, including the emergence of drug resistance and the shortage of vaccine (especially for humans). Future efforts and progress in controlling giardiasis are expected in three aspects: clarification of the drug resistance mechanisms, development of efficient vaccines, and identification of more targets for new drugs and vaccines.
Frigeri, Antonio; Nicchia, Grazia Paola; Svelto, Maria
The intracellular hydric balance is an essential process of mammalian cells. The water movement across cell membranes is driven by osmotic and hydrostatic forces and the speed of this process is dependent on the presence of specific aquaporin water channels. Since the molecular identification of the first water channel, AQP1, by Peter Agre's group, 13 homologous members have been found in mammals with varying degree of homology. The fundamental importance of these proteins in all living cells is suggested by their genetic conservation in eukaryotic organisms through plants to mammals. A number of recent studies have revealed the importance of mammalian AQPs in both physiology and pathophysiology and have suggested that pharmacological modulation of aquaporins expression and activity may provide new tools for the treatment of variety of human disorders, such as brain edema, glaucoma, tumour growth, congestive heart failure and obesity in which water and small solute transport may be involved. This review will highlight the physiological role and the pathological involvement of AQPs in mammals and the potential use of some recent therapeutic approaches, such as RNAi and immunotherapy, for AQP-related diseases. Furthermore, strategies that can be developed for the discovery of selective AQP-drugs will be introduced and discussed.
The advances of genomics, sequencing, and high throughput technologies have led to the creation of large volumes of diverse datasets for drug discovery. Analyzing these datasets to better understand disease and discover new drugs is becoming more common. Recent open data initiatives in basic and clinical research have dramatically increased the types of data available to the public. The past few years have witnessed successful use of big data in many sectors across the whole drug discovery pipeline. In this review, we will highlight the state of the art in leveraging big data to identify new targets, drug indications, and drug response biomarkers in this era of precision medicine. PMID:26659699
Foulks, Jason M; Parnell, K Mark; Nix, Rebecca N; Chau, Suzanna; Swierczek, Krzysztof; Saunders, Michael; Wright, Kevin; Hendrickson, Thomas F; Ho, Koc-Kan; McCullar, Michael V; Kanner, Steven B
Epigenetic modification of DNA leads to changes in gene expression. DNA methyltransferases (DNMTs) comprise a family of nuclear enzymes that catalyze the methylation of CpG dinucleotides, resulting in an epigenetic methylome distinguished between normal cells and those in disease states such as cancer. Disrupting gene expression patterns through promoter methylation has been implicated in many malignancies and supports DNMTs as attractive therapeutic targets. This review focuses on the rationale of targeting DNMTs in cancer, the historical approach to DNMT inhibition, and current marketed hypomethylating therapeutics azacytidine and decitabine. In addition, we address novel DNMT inhibitory agents emerging in development, including CP-4200 and SGI-110, analogs of azacytidine and decitabine, respectively; the oligonucleotides MG98 and miR29a; and a number of reversible inhibitors, some of which appear to be selective against particular DNMT isoforms. Finally, we discuss future opportunities and challenges for next-generation therapeutics.
Zheng, Chunli; Guo, Zihu; Huang, Chao; Wu, Ziyin; Li, Yan; Chen, Xuetong; Fu, Yingxue; Ru, Jinlong; Ali Shar, Piar; Wang, Yuan; Wang, Yonghua
A system-level identification of drug-target direct interactions is vital to drug repositioning and discovery. However, the biological means on a large scale remains challenging and expensive even nowadays. The available computational models mainly focus on predicting indirect interactions or direct interactions on a small scale. To address these problems, in this work, a novel algorithm termed weighted ensemble similarity (WES) has been developed to identify drug direct targets based on a large-scale of 98,327 drug-target relationships. WES includes: (1) identifying the key ligand structural features that are highly-related to the pharmacological properties in a framework of ensemble; (2) determining a drug’s affiliation of a target by evaluation of the overall similarity (ensemble) rather than a single ligand judgment; and (3) integrating the standardized ensemble similarities (Z score) by Bayesian network and multi-variate kernel approach to make predictions. All these lead WES to predict drug direct targets with external and experimental test accuracies of 70% and 71%, respectively. This shows that the WES method provides a potential in silico model for drug repositioning and discovery. PMID:26155766
Rylova, Gabriela; Ozdian, Tomas; Varanasi, Lakshman; Soural, Miroslav; Hlavac, Jan; Holub, Dusan; Dzubak, Petr; Hajduch, Marian
Target discovery using the molecular approach, as opposed to the more traditional systems approach requires the study of the cellular or biological process underlying a condition or disease. The approaches that are employed by the "bench" scientist may be genetic, genomic or proteomic and each has its rightful place in the drug-target discovery process. Affinity-based proteomic techniques currently used in drug-discovery draw upon several disciplines, synthetic chemistry, cell-biology, biochemistry and mass spectrometry. An important component of such techniques is the probe that is specifically designed to pick out a protein or set of proteins from amongst the varied thousands in a cell lysate. A second component, that is just as important, is liquid-chromatography tandem massspectrometry (LC-MS/MS). LC-MS/MS and the supporting theoretical framework has come of age and is the tool of choice for protein identification and quantification. These proteomic tools are critical to maintaining the drug-candidate supply, in the larger context of drug discovery.
Several diseases are characterized by alterations in the molecular distribution of vascular structures, presenting the opportunity to use monoclonal antibodies for clinical therapies. This pharmaceutical strategy, often referred to as "vascular targeting", has promise in promoting the discovery and development of selective biological drugs to regulate angiogenesis-related diseases such as cancer. Various experimental approaches have been utilized to discover accessible vascular markers of health and disease at the protein level. Our group has developed a new chemical proteomics technology to identify and quantify accessible vascular proteins in normal organs and at disease sites. Our developed methodology relies on the perfusion of animal models with suitable ester derivatives of biotin, which react with the primary amine groups of proteins as soon as the molecules are attached. This presentation reports biomedical applications based on vascular targeting strategies, as well as methodologies that have been used to discover new vascular targets. The identification of antigens located in the stromal tissue of pathological blood vessels may provide attractive targets for the development of antibody drugs. This method will also provide an efficient discovery target that could lead to the development of novel antibody drugs.
Gilbert, Ian H
Target-based approaches for human African trypanosomiasis (HAT) and related parasites can be a valuable route for drug discovery for these diseases. However, care needs to be taken in selection of both the actual drug target and the chemical matter that is developed. In this article, potential criteria to aid target selection are described. Then the physiochemical properties of typical oral drugs are discussed and compared to those of known anti-parasitics.
Płocińska, Renata; Korycka-Machała, Małgorzata; Płociński, Przemysław; Dziadek, Jarosław
Mycobacterium tuberculosis (M. tuberculosis), the causative agent of tuberculosis, is a leading infectious disease organism, causing millions of deaths each year. This serious pathogen has been greatly spread worldwide and recent years have observed an increase in the number of multi-drug resistant and totally drug resistant M. tuberculosis strains (WHO report, 2014). The danger of tuberculosis becoming an incurable disease has emphasized the need for the discovery of a new generation of antimicrobial agents. The development of novel alternative medical strategies, new drugs and the search for optimal drug targets are top priority areas of tuberculosis research. Key characteristics of mycobacteria include: slow growth, the ability to transform into a metabolically silent - latent state, intrinsic drug resistance and the relatively rapid development of acquired drug resistance. These factors make finding an ideal antituberculosis drug enormously challenging, even if it is designed to treat drug sensitive tuberculosis strains. A vast majority of canonical antibiotics including antituberculosis agents target bacterial cell wall biosynthesis or DNA/RNA processing. Novel therapeutic approaches are being tested to target mycobacterial cell division, two-component regulatory factors, lipid synthesis and the transition between the latent and actively growing states. This review discusses the choice of cellular targets for an antituberculosis therapy, describes putative drug targets evaluated in the recent literature and summarizes potential candidates under clinical and pre-clinical development. We focus on the key cellular process of DNA replication, as a prominent target for future antituberculosis therapy. We describe two main pathways: the biosynthesis of nucleic acids precursors - the nucleotides, and the synthesis of DNA molecules. We summarize data regarding replication associated proteins that are critical for nucleotide synthesis, initiation, unwinding and
Sotgia, Federica; Martinez-Outschoorn, Ubaldo E; Lisanti, Michael P
Recent studies in cancer metabolism directly implicate catabolic fibroblasts as a new rich source of i) energy and ii) biomass, for the growth and survival of anabolic cancer cells. Conversely, anabolic cancer cells upregulate oxidative mitochondrial metabolism, to take advantage of the abundant fibroblast fuel supply. This simple model of "metabolic-symbiosis" has now been independently validated in several different types of human cancers, including breast, ovarian, and prostate tumors. Biomarkers of metabolic-symbiosis are excellent predictors of tumor recurrence, metastasis, and drug resistance, as well as poor patient survival. New pre-clinical models of metabolic-symbiosis have been generated and they genetically validate that catabolic fibroblasts promote tumor growth and metastasis. Over 30 different stable lines of catabolic fibroblasts and >10 different lines of anabolic cancer cells have been created and are well-characterized. For example, catabolic fibroblasts harboring ATG16L1 increase tumor cell metastasis by >11.5-fold, despite the fact that genetically identical cancer cells were used. Taken together, these studies provide >40 novel validated targets, for new drug discovery and anti-cancer therapy. Since anabolic cancer cells amplify their capacity for oxidative mitochondrial metabolism, we should consider therapeutically targeting mitochondrial biogenesis and OXPHOS in epithelial cancer cells. As metabolic-symbiosis promotes drug-resistance and may represent the escape mechanism during anti-angiogenic therapy, new drugs targeting metabolic-symbiosis may also be effective in cancer patients with recurrent and advanced metastatic disease.
Sotgia, Federica; Martinez-Outschoorn, Ubaldo E.; Lisanti, Michael P.
Recent studies in cancer metabolism directly implicate catabolic fibroblasts as a new rich source of i) energy and ii) biomass, for the growth and survival of anabolic cancer cells. Conversely, anabolic cancer cells upregulate oxidative mitochondrial metabolism, to take advantage of the abundant fibroblast fuel supply. This simple model of “metabolic-symbiosis” has now been independently validated in several different types of human cancers, including breast, ovarian, and prostate tumors. Biomarkers of metabolic-symbiosis are excellent predictors of tumor recurrence, metastasis, and drug resistance, as well as poor patient survival. New pre-clinical models of metabolic-symbiosis have been generated and they genetically validate that catabolic fibroblasts promote tumor growth and metastasis. Over 30 different stable lines of catabolic fibroblasts and >10 different lines of anabolic cancer cells have been created and are well-characterized. For example, catabolic fibroblasts harboring ATG16L1 increase tumor cell metastasis by >11.5-fold, despite the fact that genetically identical cancer cells were used. Taken together, these studies provide >40 novel validated targets, for new drug discovery and anti-cancer therapy. Since anabolic cancer cells amplify their capacity for oxidative mitochondrial metabolism, we should consider therapeutically targeting mitochondrial biogenesis and OXPHOS in epithelial cancer cells. As metabolic-symbiosis promotes drug-resistance and may represent the escape mechanism during anti-angiogenic therapy, new drugs targeting metabolic-symbiosis may also be effective in cancer patients with recurrent and advanced metastatic disease. PMID:23896568
Shakespeare, William C; Metcalf, Chester A; Wang, Yihan; Sundaramoorthi, Raji; Keenan, Terence; Weigele, Manfred; Bohacek, Regine S; Dalgarno, David C; Sawyer, Tomi K
Bone-targeted Src tyrosine kinase (STK) inhibitors have recently been developed for the treatment of osteoporosis and cancer-related bone diseases. The concept of bone targeting derives from bisphosphonates, and from the evolution of such molecules in terms of therapeutic efficacy for the treatment of bone disorders. Interestingly, some of the earliest bisphosphonates were recognized for their ability to inhibit calcium carbonate precipitation (scaling) by virtue of their affinity to chelate calcium. This chelating property was subsequently exploited in the development of bisphosphonate analogs as inhibitors of the bone-resorbing cells known as osteoclasts, giving rise to breakthrough medicines, such as Fosamax (for the treatment of osteoporosis) and Zometa (for the treatment of osteoporosis and bone metastases). Relative to these milestone achievements, there is a tremendous opportunity to explore beyond the limited chemical space (functional group diversity) of such bisphosphonates to design novel bone-targeting moieties, which may be used to develop other classes of promising small-molecule drugs affecting different biological pathways. Here, we review studies focused on bone-targeted inhibitors of STK, a key enzyme in osteoclast-dependent bone resorption. Two strategies are described relative to bone-targeted STK inhibitor drug discovery: (i) the development of novel Src homology (SH)-2 inhibitors incorporating non-hydrolyzable phosphotyrosine mimics and exhibiting molecular recognition and bone-targeting properties, leading to the in vivo-effective lead compound AP-22408; and (ii) the development of novel ATP-based Src kinase inhibitors incorporating bone-targeting moieties, leading to the in vivo-effective lead compound AP-23236. In summary, AP-22408 and AP-23236, which differ mechanistically by virtue of blocking Src-dependent non-catalytic or catalytic activities in osteoclasts, exemplify ARIAD Pharmaceuticals' structure-based design of novel bone-targeted
Mdluli, Khisimuzi; Kaneko, Takushi; Upton, Anna
The recent accelerated approval for use in extensively drug-resistant and multidrug-resistant-tuberculosis (MDR-TB) of two first-in-class TB drugs, bedaquiline and delamanid, has reinvigorated the TB drug discovery and development field. However, although several promising clinical development programs are ongoing to evaluate new TB drugs and regimens, the number of novel series represented is few. The global early-development pipeline is also woefully thin. To have a chance of achieving the goal of better, shorter, safer TB drug regimens with utility against drug-sensitive and drug-resistant disease, a robust and diverse global TB drug discovery pipeline is key, including innovative approaches that make use of recently acquired knowledge on the biology of TB. Fortunately, drug discovery for TB has resurged in recent years, generating compounds with varying potential for progression into developable leads. In parallel, advances have been made in understanding TB pathogenesis. It is now possible to apply the lessons learned from recent TB hit generation efforts and newly validated TB drug targets to generate the next wave of TB drug leads. Use of currently underexploited sources of chemical matter and lead-optimization strategies may also improve the efficiency of future TB drug discovery. Novel TB drug regimens with shorter treatment durations must target all subpopulations of Mycobacterium tuberculosis existing in an infection, including those responsible for the protracted TB treatment duration. This review summarizes the current TB drug development pipeline and proposes strategies for generating improved hits and leads in the discovery phase that could help achieve this goal.
The aim of this study was to make a scientometric assessment of drug discovery efforts centered on pain-related molecular targets. The following scientometric indices were used: the popularity index, representing the share of articles (or patents) on a specific topic among all articles (or patents) on pain over the same 5-year period; the index of change, representing the change in the number of articles (or patents) on a topic from one 5-year period to the next; the index of expectations, representing the ratio of the number of all types of articles on a topic in the top 20 journals relative to the number of articles in all (>5,000) biomedical journals covered by PubMed over a 5-year period; the total number of articles representing Phase I-III trials of investigational drugs over a 5-year period; and the trial balance index, a ratio of Phase I-II publications to Phase III publications. Articles (PubMed database) and patents (US Patent and Trademark Office database) on 17 topics related to pain mechanisms were assessed during six 5-year periods from 1984 to 2013. During the most recent 5-year period (2009-2013), seven of 17 topics have demonstrated high research activity (purinergic receptors, serotonin, transient receptor potential channels, cytokines, gamma aminobutyric acid, glutamate, and protein kinases). However, even with these seven topics, the index of expectations decreased or did not change compared with the 2004-2008 period. In addition, publications representing Phase I-III trials of investigational drugs (2009-2013) did not indicate great enthusiasm on the part of the pharmaceutical industry regarding drugs specifically designed for treatment of pain. A promising development related to the new tool of molecular targeting, ie, monoclonal antibodies, for pain treatment has not yet resulted in real success. This approach has not yet demonstrated clinical effectiveness (at least with nerve growth factor) much beyond conventional analgesics, when its
The aim of this study was to make a scientometric assessment of drug discovery efforts centered on pain-related molecular targets. The following scientometric indices were used: the popularity index, representing the share of articles (or patents) on a specific topic among all articles (or patents) on pain over the same 5-year period; the index of change, representing the change in the number of articles (or patents) on a topic from one 5-year period to the next; the index of expectations, representing the ratio of the number of all types of articles on a topic in the top 20 journals relative to the number of articles in all (>5,000) biomedical journals covered by PubMed over a 5-year period; the total number of articles representing Phase I–III trials of investigational drugs over a 5-year period; and the trial balance index, a ratio of Phase I–II publications to Phase III publications. Articles (PubMed database) and patents (US Patent and Trademark Office database) on 17 topics related to pain mechanisms were assessed during six 5-year periods from 1984 to 2013. During the most recent 5-year period (2009–2013), seven of 17 topics have demonstrated high research activity (purinergic receptors, serotonin, transient receptor potential channels, cytokines, gamma aminobutyric acid, glutamate, and protein kinases). However, even with these seven topics, the index of expectations decreased or did not change compared with the 2004–2008 period. In addition, publications representing Phase I–III trials of investigational drugs (2009–2013) did not indicate great enthusiasm on the part of the pharmaceutical industry regarding drugs specifically designed for treatment of pain. A promising development related to the new tool of molecular targeting, ie, monoclonal antibodies, for pain treatment has not yet resulted in real success. This approach has not yet demonstrated clinical effectiveness (at least with nerve growth factor) much beyond conventional analgesics
Guo, Dong; Heitman, Laura H; IJzerman, Adriaan P
Traditionally structure-activity/affinity relationships (SAR) have dominated research in medicinal chemistry. However, structure-kinetics relationships (SKR) can be very informative too. In this viewpoint we explore the molecular determinants of binding kinetics and discuss challenges for future binding kinetics studies. A scheme for future kinetics-directed drug design and discovery is also proposed.
Progesterone A-Form as a Target for New Drug Discovery in Human Breast Cancer PRINCIPAL INVESTIGATOR: James Voltz Paloma Giangrande Donald McDonnell, Ph.D...SUBTITLE 5. FUNDING NUMBERS Human Progesterone A-Form as a Target for New Drug DAMD17-98-1-8070 Discovery in Human Breast Cancer 6. AUTHOR(S) James
Taylor, Christina M.; Wang, Qi; Rosa, Bruce A.; Huang, Stanley Ching-Cheng; Powell, Kerrie; Schedl, Tim; Pearce, Edward J.; Abubucker, Sahar; Mitreva, Makedonka
Parasitic roundworm infections plague more than 2 billion people (1/3 of humanity) and cause drastic losses in crops and livestock. New anthelmintic drugs are urgently needed as new drug resistance and environmental concerns arise. A “chokepoint reaction” is defined as a reaction that either consumes a unique substrate or produces a unique product. A chokepoint analysis provides a systematic method of identifying novel potential drug targets. Chokepoint enzymes were identified in the genomes of 10 nematode species, and the intersection and union of all chokepoint enzymes were found. By studying and experimentally testing available compounds known to target proteins orthologous to nematode chokepoint proteins in public databases, this study uncovers features of chokepoints that make them successful drug targets. Chemogenomic screening was performed on drug-like compounds from public drug databases to find existing compounds that target homologs of nematode chokepoints. The compounds were prioritized based on chemical properties frequently found in successful drugs and were experimentally tested using Caenorhabditis elegans. Several drugs that are already known anthelmintic drugs and novel candidate targets were identified. Seven of the compounds were tested in Caenorhabditis elegans and three yielded a detrimental phenotype. One of these three drug-like compounds, Perhexiline, also yielded a deleterious effect in Haemonchus contortus and Onchocerca lienalis, two nematodes with divergent forms of parasitism. Perhexiline, known to affect the fatty acid oxidation pathway in mammals, caused a reduction in oxygen consumption rates in C. elegans and genome-wide gene expression profiles provided an additional confirmation of its mode of action. Computational modeling of Perhexiline and its target provided structural insights regarding its binding mode and specificity. Our lists of prioritized drug targets and drug-like compounds have potential to expedite the discovery
Kathiravan, Muthu K; Khilare, Madhavi M; Nikoomanesh, Kiana; Chothe, Aparna S; Jain, Kishor S
DNA topoisomerases comprise a major aspect of basic cellular biology and are molecular targets for a variety of drugs like antibiotics, antibacterials and anticancer drugs. They act by inhibiting the topoisomerase molecule from relegating DNA strands after cleavage and convert the topoisomerases molecule into a DNA damaging agent. Though drugs of various categories acting through different mechanisms are available for the treatment, there are still problems associated with the currently available drugs. Therefore, Structural biologists, Structural chemists and Medicinal chemists all around the world have been identifying, designing, synthesizing and evaluating a variety of novel bioactive molecules targeting topoisomerase. This review summarizes types of topoisomerase and drug treating each class along with their structural requirement and activity. The emphasis has been laid in particular on the new potential heterocyles and the possible treatments as well as the current ongoing research status in the field of topoisomerase as dual targeting.
Lv, Junfang; Shim, Joong Sup
Despite standard cancer therapies such as chemotherapy and targeted therapy have shown some efficacies, the cancer in many cases eventually relapses and metastasizes upon stopping the treatment. There is a small subpopulation of cancer cells within tumor, with specific characters similar to those found in stem cells. This group of cancer cells is known as tumor-initiating or cancer stem cells (CSCs), which have an ability to self-renew and give rise to cancer cell progeny. CSCs are related with drug resistance, metastasis and relapse of cancer, hence emerging as a crucial drug target for eliminating cancer. Rapid advancement of CSC biology has enabled researchers to isolate and culture CSCs in vitro, making the cells amenable to high-throughput drug screening. Recently, drug repositioning, which utilizes existing drugs to develop potential new indications, has been gaining popularity as an alternative approach for the drug discovery. As existing drugs have favorable bioavailability and safety profiles, drug repositioning is now actively exploited for prompt development of therapeutics for many serious diseases, such as cancer. In this review, we will introduce latest examples of attempted drug repositioning targeting CSCs and discuss potential use of the repositioned drugs for cancer therapy.
De novo experimental drug discovery is an expensive and time-consuming task. It requires the identification of drug-target interactions (DTIs) towards targets of biological interest, either to inhibit or enhance a specific molecular function. Dedicated computational models for protein simulation and DTI prediction are crucial for speed and to reduce the costs associated with DTI identification. In this paper we present a computational pipeline that enables the discovery of putative leads for drug repositioning that can be applied to any microbial proteome, as long as the interactome of interest is at least partially known. Network metrics calculated for the interactome of the bacterial organism of interest were used to identify putative drug-targets. Then, a random forest classification model for DTI prediction was constructed using known DTI data from publicly available databases, resulting in an area under the ROC curve of 0.91 for classification of out-of-sampling data. A drug-target network was created by combining 3,081 unique ligands and the expected ten best drug targets. This network was used to predict new DTIs and to calculate the probability of the positive class, allowing the scoring of the predicted instances. Molecular docking experiments were performed on the best scoring DTI pairs and the results were compared with those of the same ligands with their original targets. The results obtained suggest that the proposed pipeline can be used in the identification of new leads for drug repositioning. The proposed classification model is available at http://bioinformatics.ua.pt/software/dtipred/. PMID:27893735
Bouvard, Claire; Barefield, Colleen; Zhu, Shoutian
Cancer stem cells (CSCs) have been identified in a growing list of malignancies and are believed to be responsible for cancer initiation, metastasis and relapse following certain therapies, even though they may only represent a small fraction of the cells in a given cancer. Like somatic stem cells and embryonic stem cells, CSCs are capable of self-renewal and differentiation into more mature, less tumorigenic cells that make up the bulk populations of cancer cells. Elimination of CSCs promises intriguing therapeutic potential and this concept has been adopted in preclinical drug discovery programs. Herein we will discuss the progress of these efforts, general considerations in practice, major challenges and possible solutions.
Dunlop, John; Brandon, Nicholas J
Current therapeutics for schizophrenia, the typical and atypical antipsychotic class of drugs, derive their therapeutic benefit predominantly by antagonism of the dopamine D2 receptor subtype and have robust clinical benefit on positive symptoms of the disease with limited to no impact on negative symptoms and cognitive impairment. Driven by these therapeutic limitations of current treatments and the recognition that transmitter systems beyond the dopaminergic system in particular glutamatergic transmission contribute to the etiology of schizophrenia significant recent efforts have focused on the discovery and development of novel treatments for schizophrenia with mechanisms of action that are distinct from current drugs. Specifically, compounds selectively targeting the metabotropic glutamate receptor 2/3 subtype, phosphodiesterase subtype 10, glycine transporter subtype 1 and the alpha7 nicotinic acetylcholine receptor have been the subject of intense drug discovery and development efforts. Here we review recent clinical experience with the most advanced drug candidates targeting each of these novel mechanisms and discuss whether these new agents are living up to expectations.
Ebner, David C; Bialek, Peter; El-Kattan, Ayman F; Ambler, Catherine M; Tu, Meihua
The targeting of drugs to skeletal muscle is an emerging area of research. Driven by the need for new therapies to treat a range of muscle-associated diseases, these strategies aim to provide improved drug exposure at the site of action in skeletal muscle with reduced concentration in other tissues where unwanted side effects could occur. By interacting with muscle-specific cell surface recognition elements, both tissue localization and selective uptake into skeletal muscle cells can be achieved. The design of molecules that are substrates for muscle uptake transporters can provide concentration in m uscle tissue. For example, drug conjugates with carnitine can provide improved muscle uptake via OCTN2 transport. Binding to muscle surface recognition elements followed by endocytosis can allow even large molecules such as antibodies to enter muscle cells. Monoclonal antibody 3E10 demonstrated selective uptake into skeletal muscle in vivo. Hybrid adeno-associated viral vectors have recently shown promise for high skeletal muscle selectivity in gene transfer applications. Delivery technology methods, including electroporation of DNA plasmids, have also been investigated for selective muscle uptake. This review discusses challenges and opportunities for skeletal muscle targeting, highlighting specific examples and areas in need of additional research.
Chakraborty, Chiranjib; Doss C, George Priya; Chen, Luonan; Zhu, Hailong
In silico pharmacology is a promising field in the current state-of drug discovery. This area exploits "protein-protein Interaction (PPI) network analysis for drug discovery using the drug "target class". To document the current status, we have discussed in this article how this an integrated system of PPI networks contribute to understand the disease pathways, present state-of-the-art drug target discovery and drug discovery process. This review article enhances our knowledge on conventional drug discovery and current drug discovery using in silico techniques, best "target class", universal architecture of PPI networks, the present scenario of disease pathways and protein-protein interaction networks as well as the method to comprehend the PPI networks. Taken all together, ultimately a snapshot has been discussed to be familiar with how PPI network architecture can used to validate a drug target. At the conclusion, we have illustrated the future directions of PPI in target discovery and drug-design.
Ojima, Iwao; Kumar, Kunal; Awasthi, Divya; Vineberg, Jacob G
Eukaryotic cell division or cytokinesis has been a major target for anticancer drug discovery. After the huge success of paclitaxel and docetaxel, microtubule-stabilizing agents (MSAs) appear to have gained a premier status in the discovery of next-generation anticancer agents. However, the drug resistance caused by MDR, point mutations, and overexpression of tubulin subtypes, etc., is a serious issue associated with these agents. Accordingly, the discovery and development of new-generation MSAs that can obviate various drug resistances has a significant meaning. In sharp contrast, prokaryotic cell division has been largely unexploited for the discovery and development of antibacterial drugs. However, recent studies on the mechanism of bacterial cytokinesis revealed that the most abundant and highly conserved cell division protein, FtsZ, would be an excellent new target for the drug discovery of next-generation antibacterial agents that can circumvent drug-resistances to the commonly used drugs for tuberculosis, MRSA and other infections. This review describes an account of our research on these two fronts in drug discovery, targeting eukaryotic as well as prokaryotic cell division.
Ito, Takumi; Ando, Hideki; Handa, Hiroshi
Half a century ago, the sedative thalidomide caused a serious drug disaster because of its teratogenicity and was withdrawn from the market. However, thalidomide, which has returned to the market, is now used for the treatment of leprosy and multiple myeloma (MM) under strict control. The mechanism of thalidomide action had been a long-standing question. We developed a new affinity bead technology and identified cereblon (CRBN) as a thalidomide-binding protein. We found that CRBN functions as a substrate receptor of an E3 cullin-Ring ligase complex 4 (CRL4) and is a primary target of thalidomide teratogenicity. Recently, new thalidomide derivatives, called immunomodulatory drugs (IMiDs), have been developed by Celgene. Among them, lenalidomide (Len) and pomalidomide (Pom) were shown to exert strong therapeutic effects against MM. It was found that Len and Pom both bind CRBN-CRL4 and recruit neomorphic substrates (Ikaros and Aiolos). More recently it was reported that casein kinase 1a (Ck1a) was identified as a substrate for CRBN-CRL4 in the presence of Len, but not Pom. Ck1a breakdown explains why Len is specifically effective for myelodysplastic syndrome with 5q deletion. It is now proposed that binding of IMiDs to CRBN appears to alter the substrate specificity of CRBN-CRL4. In this review, we introduce recent findings on IMiDs.
Neelapu, Nageswara R R; Srimath-Tirumala-Peddinti, Ravi C P K; Nammi, Deepthi; Pasupuleti, Amita C M
The discovery and exploitation of new drug targets is a key focus for both the pharmaceutical industry and academic research. To provide an insight into trends in the exploitation of new drug targets, we have analysed different methods during the past six decades and advances made in drug target discovery. A special focus remains on different methods used for drug target discovery on infectious diseases such as Tuberculosis, Gastritis, Malaria, Trypanosomiasis and Leishmaniasis. We herewith provide a paradigm that is can be used for drug target discovery in the near future.
Stoilova-McPhie, Svetla; Ali, Syed; Laezza, Fernanda
Protein-protein interactions (PPI) are key molecular elements that provide the basis of signaling in virtually all cellular processes. The precision and specificity of these molecular interactions have ignited a strong interest in pursuing PPI surfaces as new targets for drug discovery, especially against ion channels in the central nervous system (CNS) where selectivity and specificity are vital for developing drugs with limited side effects. Ion channels are large transmembrane domain proteins assembled with multiple regulatory proteins binding to the intracellular portion of channels. These macromolecular complexes are difficult to isolate, purify and reconstitute, posing a significant barrier in targeting these PPI for drug discovery purposes. Here, we will provide a short overview of salient features of PPI and discuss successful studies focusing on protein-channel interactions that could inspire new drug discovery campaigns targeting ion channel complexes. PMID:25485305
Malhotra, Sony; Thomas, Sherine E; Ochoa Montano, Bernardo; Blundell, Tom L
The use of protein crystallography in structure-guided drug discovery allows identification of potential inhibitor-binding sites and optimisation of interactions of hits and lead compounds with a target protein. An early example of this approach was the use of the structure of HIV protease in designing AIDS antivirals. More recently, use of structure-guided design with fragment-based drug discovery, which reduces the size of screening libraries by decreasing complexity, has improved ligand efficiency in drug design. Here, we discuss the use of structure-guided target identification and lead optimisation using fragment-based approaches in the development of new antimicrobials for mycobacterial infections.
Xu, Zhijian; Yang, Zhuo; Liu, Yingtao; Lu, Yunxiang; Chen, Kaixian; Zhu, Weiliang
Halogen bond has attracted a great deal of attention in the past years for hit-to-lead-to-candidate optimization aiming at improving drug-target binding affinity. In general, heavy organohalogens (i.e., organochlorines, organobromines, and organoiodines) are capable of forming halogen bonds while organofluorines are not. In order to explore the possible roles that halogen bonds could play beyond improving binding affinity, we performed a detailed database survey and quantum chemistry calculation with close attention paid to (1) the change of the ratio of heavy organohalogens to organofluorines along the drug discovery and development process and (2) the halogen bonds between organohalogens and nonbiopolymers or nontarget biopolymers. Our database survey revealed that (1) an obviously increasing trend of the ratio of heavy organohalogens to organofluorines was observed along the drug discovery and development process, illustrating that more organofluorines are worn and eliminated than heavy organohalogens during the process, suggesting that heavy halogens with the capability of forming halogen bonds should have priority for lead optimization; and (2) more than 16% of the halogen bonds in PDB are formed between organohalogens and water, and nearly 20% of the halogen bonds are formed with the proteins that are involved in the ADME/T process. Our QM/MM calculations validated the contribution of the halogen bond to the binding between organohalogens and plasma transport proteins. Thus, halogen bonds could play roles not only in improving drug-target binding affinity but also in tuning ADME/T property. Therefore, we suggest that albeit halogenation is a valuable approach for improving ligand bioactivity, more attention should be paid in the future to the application of the halogen bond for ligand ADME/T property optimization.
Vandamme, Drieke; Minke, Benedikt A; Fitzmaurice, William; Kholodenko, Boris N; Kolch, Walter
The pharmaceutical industry is faced with a range of challenges with the ever-escalating costs of drug development and a drying out of drug pipelines. By harnessing advances in -omics technologies and moving away from the standard, reductionist model of drug discovery, there is significant potential to reduce costs and improve efficacy. Embedding systems biology approaches in drug discovery, which seek to investigate underlying molecular mechanisms of potential drug targets in a network context, will reduce attrition rates by earlier target validation and the introduction of novel targets into the currently stagnant market. Systems biology approaches also have the potential to assist in the design of multidrug treatments and repositioning of existing drugs, while stratifying patients to give a greater personalization of medical treatment.
Patel, Hershna; Kukol, Andreas
Sequence variations in the binding sites of influenza A proteins are known to limit the effectiveness of current antiviral drugs. Clinically, this leads to increased rates of virus transmission and pathogenicity. Potential influenza A inhibitors are continually being discovered as a result of high-throughput cell based screening studies, whereas the application of computational tools to aid drug discovery has further increased the number of predicted inhibitors reported. This review brings together the aspects that relate to the identification of influenza A drug target sites and the findings from recent antiviral drug discovery strategies.
The tumor microenvironment, characterized by regions of hypoxia, low nutrition, and acidosis due to incomplete blood vessel networks, has been recognized as a major factor that influences not only the response to conventional anti-cancer therapies but also malignant progression and metastasis. However, exploiting such a cumbersome tumor microenvironment for cancer treatment could provide tumor-specific therapeutic approaches. In particular, hypoxia is now considered a fundamentally important characteristic of the tumor microenvironment in which hypoxia inducible factor (HIF)-1-mediated gene regulation is considered essential for angiogenesis and tumor development. Additional oxygen sensitive signaling pathways including mammalian target of rapamycin (mTOR) signaling and signaling through activation of the unfolded protein response (UPR) also contribute to the adaptation in the tumor microenvironment. This in turn has led to the current extensive interest in the signal molecules related to adaptive responses in the tumor microenvironment as potential molecular targets for cancer therapy against refractory cancer and recurrence in preparation for the aging society. Therefore, we should focus on the drug discovery for targeting the tumor microenvironment to develop tumor-specific cytostatic agents including angiogenesis inhibitors. In this paper, the development of hypoxia-selective prodrugs, HIF-1 inhibitors, and modulators of the tumor microenvironment will be discussed.
Ou-Yang, Si-sheng; Lu, Jun-yan; Kong, Xiang-qian; Liang, Zhong-jie; Luo, Cheng; Jiang, Hualiang
Computational drug discovery is an effective strategy for accelerating and economizing drug discovery and development process. Because of the dramatic increase in the availability of biological macromolecule and small molecule information, the applicability of computational drug discovery has been extended and broadly applied to nearly every stage in the drug discovery and development workflow, including target identification and validation, lead discovery and optimization and preclinical tests. Over the past decades, computational drug discovery methods such as molecular docking, pharmacophore modeling and mapping, de novo design, molecular similarity calculation and sequence-based virtual screening have been greatly improved. In this review, we present an overview of these important computational methods, platforms and successful applications in this field. PMID:22922346
Savino, Rocco; Paduano, Sergio; Preianò, Mariaimmacolata; Terracciano, Rosa
In the modern process of drug discovery, clinical, functional and chemical proteomics can converge and integrate synergies. Functional proteomics explores and elucidates the components of pathways and their interactions which, when deregulated, lead to a disease condition. This knowledge allows the design of strategies to target multiple pathways with combinations of pathway-specific drugs, which might increase chances of success and reduce the occurrence of drug resistance. Chemical proteomics, by analyzing the drug interactome, strongly contributes to accelerate the process of new druggable targets discovery. In the research area of clinical proteomics, proteome and peptidome mass spectrometry-profiling of human bodily fluid (plasma, serum, urine and so on), as well as of tissue and of cells, represents a promising tool for novel biomarker and eventually new druggable targets discovery. In the present review we provide a survey of current strategies of functional, chemical and clinical proteomics. Major issues will be presented for proteomic technologies used for the discovery of biomarkers for early disease diagnosis and identification of new drug targets. PMID:23203042
Bald, Dirk; Villellas, Cristina; Lu, Ping; Koul, Anil
Drug-resistant mycobacterial infections are a serious global health challenge, leading to high mortality and socioeconomic burdens in developing countries worldwide. New innovative approaches, from identification of new targets to discovery of novel chemical scaffolds, are urgently needed. Recently, energy metabolism in mycobacteria, in particular the oxidative phosphorylation pathway, has emerged as an object of intense microbiological investigation and as a novel target pathway in drug discovery. New classes of antibacterials interfering with elements of the oxidative phosphorylation pathway are highly active in combating dormant or latent mycobacterial infections, with a promise of shortening tuberculosis chemotherapy. The regulatory approval of the ATP synthase inhibitor bedaquiline and the discovery of Q203, a candidate drug targeting the cytochrome bc1 complex, have highlighted the central importance of this new target pathway. In this review, we discuss key features and potential applications of inhibiting energy metabolism in our quest for discovering potent novel and sterilizing drug combinations for combating tuberculosis. We believe that the combination of drugs targeting elements of the oxidative phosphorylation pathway can lead to a completely new regimen for drug-susceptible and multidrug-resistant tuberculosis.
Villellas, Cristina; Lu, Ping
ABSTRACT Drug-resistant mycobacterial infections are a serious global health challenge, leading to high mortality and socioeconomic burdens in developing countries worldwide. New innovative approaches, from identification of new targets to discovery of novel chemical scaffolds, are urgently needed. Recently, energy metabolism in mycobacteria, in particular the oxidative phosphorylation pathway, has emerged as an object of intense microbiological investigation and as a novel target pathway in drug discovery. New classes of antibacterials interfering with elements of the oxidative phosphorylation pathway are highly active in combating dormant or latent mycobacterial infections, with a promise of shortening tuberculosis chemotherapy. The regulatory approval of the ATP synthase inhibitor bedaquiline and the discovery of Q203, a candidate drug targeting the cytochrome bc1 complex, have highlighted the central importance of this new target pathway. In this review, we discuss key features and potential applications of inhibiting energy metabolism in our quest for discovering potent novel and sterilizing drug combinations for combating tuberculosis. We believe that the combination of drugs targeting elements of the oxidative phosphorylation pathway can lead to a completely new regimen for drug-susceptible and multidrug-resistant tuberculosis.
Waldmann, Herbert; Valeur, Eric; Guéret, Stéphanie M; Adihou, Hélène; Gopalakrishnan, Ranganath; Lemurell, Malin; Grossmann, Tom N; Plowright, Alleyn T
An ever increasing understanding of biological systems is providing a range of exciting novel biological targets whose modulation may enable novel therapeutic options in many diseases. These targets include protein-protein and protein-nucleic acid interactions, which are, however, often refractory to classical small molecule approaches. Other types of molecules, or modalities, are therefore required to address these targets, which has led several academic research groups and pharmaceutical companies to increasingly use the concept of so-called 'New Modalities'. This review defines for the first time the scope of this term, which includes novel peptidic scaffolds, oligonucleotides, hybrids, molecular conjugates as well as new uses of classical small molecules. We provide herein a journey through the most representative examples of these modalities to target large binding surface areas such as those found in protein-protein interactions and for biological processes at the center of cell regulation.
Huang, Lei; Li, Fuhai; Sheng, Jianting; Xia, Xiaofeng; Ma, Jinwen; Zhan, Ming; Wong, Stephen T.C.
Motivation: Currently there are no curative anticancer drugs, and drug resistance is often acquired after drug treatment. One of the reasons is that cancers are complex diseases, regulated by multiple signaling pathways and cross talks among the pathways. It is expected that drug combinations can reduce drug resistance and improve patients’ outcomes. In clinical practice, the ideal and feasible drug combinations are combinations of existing Food and Drug Administration-approved drugs or bioactive compounds that are already used on patients or have entered clinical trials and passed safety tests. These drug combinations could directly be used on patients with less concern of toxic effects. However, there is so far no effective computational approach to search effective drug combinations from the enormous number of possibilities. Results: In this study, we propose a novel systematic computational tool DrugComboRanker to prioritize synergistic drug combinations and uncover their mechanisms of action. We first build a drug functional network based on their genomic profiles, and partition the network into numerous drug network communities by using a Bayesian non-negative matrix factorization approach. As drugs within overlapping community share common mechanisms of action, we next uncover potential targets of drugs by applying a recommendation system on drug communities. We meanwhile build disease-specific signaling networks based on patients’ genomic profiles and interactome data. We then identify drug combinations by searching drugs whose targets are enriched in the complementary signaling modules of the disease signaling network. The novel method was evaluated on lung adenocarcinoma and endocrine receptor positive breast cancer, and compared with other drug combination approaches. These case studies discovered a set of effective drug combinations top ranked in our prediction list, and mapped the drug targets on the disease signaling network to highlight the
Blundell, Tom L; Sibanda, Bancinyane L; Montalvão, Rinaldo Wander; Brewerton, Suzanne; Chelliah, Vijayalakshmi; Worth, Catherine L; Harmer, Nicholas J; Davies, Owen; Burke, David
Impressive progress in genome sequencing, protein expression and high-throughput crystallography and NMR has radically transformed the opportunities to use protein three-dimensional structures to accelerate drug discovery, but the quantity and complexity of the data have ensured a central place for informatics. Structural biology and bioinformatics have assisted in lead optimization and target identification where they have well established roles; they can now contribute to lead discovery, exploiting high-throughput methods of structure determination that provide powerful approaches to screening of fragment binding. PMID:16524830
Molek, Peter; Strukelj, Borut; Bratkovic, Tomaz
Ligands selected from phage-displayed random peptide libraries tend to be directed to biologically relevant sites on the surface of the target protein. Consequently, peptides derived from library screenings often modulate the target protein's activity in vitro and in vivo and can be used as lead compounds in drug design and as alternatives to antibodies for target validation in both genomics and drug discovery. This review discusses the use of phage display to identify membrane receptor modulators with agonistic or antagonistic activities. Because isolating or producing recombinant membrane proteins for use as target molecules in library screening is often impossible, innovative selection strategies such as panning against whole cells or tissues, recombinant receptor ectodomains, or neutralizing antibodies to endogenous binding partners were devised. Prominent examples from a two-decade history of peptide phage display will be presented, focusing on the design of affinity selection experiments, methods for improving the initial hits, and applications of the identified peptides.
An, Songzhu Michael; Ding, Qiang; Zhang, Jie; Xie, JingYi; Li, LingSong
Signaling pathways transduce extracellular stimuli into cells through molecular cascades to regulate cellular functions. In stem cells, a small number of pathways, notably those of TGF-β/BMP, Hedgehog, Notch, and Wnt, are responsible for the regulation of pluripotency and differentiation. During embryonic development, these pathways govern cell fate specifications as well as the formation of tissues and organs. In adulthood, their normal functions are important for tissue homeostasis and regeneration, whereas aberrations result in diseases, such as cancer and degenerative disorders. In complex biological systems, stem cell signaling pathways work in concert as a network and exhibit crosstalk, such as the negative crosstalk between Wnt and Notch. Over the past decade, genetic and genomic studies have identified a number of potential drug targets that are involved in stem cell signaling pathways. Indeed, discovery of new targets and drugs for these pathways has become one of the most active areas in both the research community and pharmaceutical industry. Remarkable progress has been made and several promising drug candidates have entered into clinical trials. This review focuses on recent advances in the discovery of novel drugs which target the Notch and Wnt pathways.
Hallenbeck, Kenneth K; Turner, David M; Renslo, Adam R; Arkin, Michelle R
The targeting of non-catalytic cysteine residues with small molecules is drawing increased attention from drug discovery scientists and chemical biologists. From a biological perspective, genomic and proteomic studies have revealed the presence of cysteine mutations in several oncogenic proteins, suggesting both a functional role for these residues and also a strategy for targeting them in an 'allele specific' manner. For the medicinal chemist, the structure-guided design of cysteine- reactive molecules is an appealing strategy to realize improved selectivity and pharmacodynamic properties in drug leads. Finally, for chemical biologists, the modification of cysteine residues provides a unique means to probe protein structure and allosteric regulation. Here, we review three applications of cysteinemodifying small molecules: 1) the optimization of existing drug leads, 2) the discovery of new lead compounds, and 3) the use of cysteine-reactive molecules as probes of protein dynamics. In each case, structure-guided design plays a key role in determining which cysteine residue(s) to target and in designing compounds with the proper geometry to enable both covalent interaction with the targeted cysteine and productive non-covalent interactions with nearby protein residues.
Hallenbeck, Kenneth K.; Turner, David M.; Renslo, Adam R.; Arkin, Michelle R.
The targeting of non-catalytic cysteine residues with small molecules is drawing increased attention from drug discovery scientists and chemical biologists. From a biological perspective, genomic and proteomic studies have revealed the presence of cysteine mutations in several oncogenic proteins, suggesting both a functional role for these residues and also a strategy for targeting them in an ‘allele specific’ manner. For the medicinal chemist, the structure-guided design of cysteine-reactive molecules is an appealing strategy to realize improved selectivity and pharmacodynamic properties in drug leads. Finally, for chemical biologists, the modification of cysteine residues provides a unique means to probe protein structure and allosteric regulation. Here, we review three applications of cysteine-modifying small molecules: 1) the optimization of existing drug leads, 2) the discovery of new lead compounds, and 3) the use of cysteine-reactive molecules as probes of protein dynamics. In each case, structure-guided design plays a key role in determining which cysteine residue(s) to target and in designing compounds with the proper geometry to enable both covalent interaction with the targeted cysteine and productive non-covalent interactions with nearby protein residues. PMID:27449257
Lappano, Rosamaria; Maggiolini, Marcello
G protein-coupled receptors (GPCRs) belong to a superfamily of cell surface signalling proteins that have a pivotal role in many physiological functions and in multiple diseases, including the development of cancer and cancer metastasis. Current drugs that target GPCRs - many of which have excellent therapeutic benefits - are directed towards only a few GPCR members. Therefore, huge efforts are currently underway to develop new GPCR-based drugs, particularly for cancer. We review recent findings that present unexpected opportunities to interfere with major tumorigenic signals by manipulating GPCR-mediated pathways. We also discuss current data regarding novel GPCR targets that may provide promising opportunities for drug discovery in cancer prevention and treatment.
Harvey, Alan L
Components from venoms have stimulated many drug discovery projects, with some notable successes. These are briefly reviewed, from captopril to ziconotide. However, there have been many more disappointments on the road from toxin discovery to approval of a new medicine. Drug discovery and development is an inherently risky business, and the main causes of failure during development programmes are outlined in order to highlight steps that might be taken to increase the chances of success with toxin-based drug discovery. These include having a clear focus on unmet therapeutic needs, concentrating on targets that are well-validated in terms of their relevance to the disease in question, making use of phenotypic screening rather than molecular-based assays, and working with development partners with the resources required for the long and expensive development process.
San Lucas, F Anthony; Fowler, Jerry; Chang, Kyle; Kopetz, Scott; Vilar, Eduardo; Scheet, Paul
Large-scale cancer datasets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a powerful computational approach for candidate drug identification, but due to the complexity of TCGA and technology differences between CMap and TCGA experiments, such analyses are challenging to conduct and reproduce. We present Cancer in silico Drug Discovery (CiDD; scheet.org/software), a computational drug discovery platform that addresses these challenges. CiDD integrates data from TCGA, CMap, and Cancer Cell Line Encyclopedia (CCLE) to perform computational drug discovery experiments, generating hypotheses for the following three general problems: (i) determining whether specific clinical phenotypes or molecular characteristics are associated with unique gene expression signatures; (ii) finding candidate drugs to repress these expression signatures; and (iii) identifying cell lines that resemble the tumors being studied for subsequent in vitro experiments. The primary input to CiDD is a clinical or molecular characteristic. The output is a biologically annotated list of candidate drugs and a list of cell lines for in vitro experimentation. We applied CiDD to identify candidate drugs to treat colorectal cancers harboring mutations in BRAF. CiDD identified EGFR and proteasome inhibitors, while proposing five cell lines for in vitro testing. CiDD facilitates phenotype-driven, systematic drug discovery based on clinical and molecular data from TCGA.
The identification of sites on receptors topographically distinct from the orthosteric sites, so-called allosteric sites, has heralded novel approaches and modes of pharmacology for target modulation. Over the past 20 years, our understanding of allosteric modulation has grown significantly, and numerous advantages, as well as caveats (e.g., flat structure–activity relationships, species differences, “molecular switches”), have been identified. For multiple receptors and proteins, numerous examples have been described where unprecedented levels of selectivity are achieved along with improved physiochemical properties. While not a panacea, these novel approaches represent exciting opportunities for tool compound development to probe the pharmacology and therapeutic potential of discrete molecular targets, as well as new medicines. In this Perspective, in commemoration of the 2013 Philip S. Portoghese Medicinal Chemistry Lectureship (LindsleyC. W.Adventures in allosteric drug discovery. Presented at the 246th National Meeting of the American Chemical Society, Indianapolis, IN, September 10, 2013; The 2013 Portoghese Lectureship), several vignettes of drug discovery campaigns targeting novel allosteric mechanisms will be recounted, along with lessons learned and guidelines that have emerged for successful lead optimization. PMID:25180768
Lindsley, Craig W
The identification of sites on receptors topographically distinct from the orthosteric sites, so-called allosteric sites, has heralded novel approaches and modes of pharmacology for target modulation. Over the past 20 years, our understanding of allosteric modulation has grown significantly, and numerous advantages, as well as caveats (e.g., flat structure-activity relationships, species differences, "molecular switches"), have been identified. For multiple receptors and proteins, numerous examples have been described where unprecedented levels of selectivity are achieved along with improved physiochemical properties. While not a panacea, these novel approaches represent exciting opportunities for tool compound development to probe the pharmacology and therapeutic potential of discrete molecular targets, as well as new medicines. In this Perspective, in commemoration of the 2013 Philip S. Portoghese Medicinal Chemistry Lectureship ( Lindsley , C. W. Adventures in allosteric drug discovery . Presented at the 246th National Meeting of the American Chemical Society, Indianapolis, IN, September 10, 2013 ; The 2013 Portoghese Lectureship ), several vignettes of drug discovery campaigns targeting novel allosteric mechanisms will be recounted, along with lessons learned and guidelines that have emerged for successful lead optimization.
Moynie, Lucille; Schnell, Robert; McMahon, Stephen A.; Sandalova, Tatyana; Boulkerou, Wassila Abdelli; Schmidberger, Jason W.; Alphey, Magnus; Cukier, Cyprian; Duthie, Fraser; Kopec, Jolanta; Liu, Huanting; Jacewicz, Agata; Hunter, William N.; Naismith, James H.; Schneider, Gunter
Bacterial infections are increasingly difficult to treat owing to the spread of antibiotic resistance. A major concern is Gram-negative bacteria, for which the discovery of new antimicrobial drugs has been particularly scarce. In an effort to accelerate early steps in drug discovery, the EU-funded AEROPATH project aims to identify novel targets in the opportunistic pathogen Pseudomonas aeruginosa by applying a multidisciplinary approach encompassing target validation, structural characterization, assay development and hit identification from small-molecule libraries. Here, the strategies used for target selection are described and progress in protein production and structure analysis is reported. Of the 102 selected targets, 84 could be produced in soluble form and the de novo structures of 39 proteins have been determined. The crystal structures of eight of these targets, ranging from hypothetical unknown proteins to metabolic enzymes from different functional classes (PA1645, PA1648, PA2169, PA3770, PA4098, PA4485, PA4992 and PA5259), are reported here. The structural information is expected to provide a firm basis for the improvement of hit compounds identified from fragment-based and high-throughput screening campaigns. PMID:23295481
Moynie, Lucille; Schnell, Robert; McMahon, Stephen A; Sandalova, Tatyana; Boulkerou, Wassila Abdelli; Schmidberger, Jason W; Alphey, Magnus; Cukier, Cyprian; Duthie, Fraser; Kopec, Jolanta; Liu, Huanting; Jacewicz, Agata; Hunter, William N; Naismith, James H; Schneider, Gunter
Bacterial infections are increasingly difficult to treat owing to the spread of antibiotic resistance. A major concern is Gram-negative bacteria, for which the discovery of new antimicrobial drugs has been particularly scarce. In an effort to accelerate early steps in drug discovery, the EU-funded AEROPATH project aims to identify novel targets in the opportunistic pathogen Pseudomonas aeruginosa by applying a multidisciplinary approach encompassing target validation, structural characterization, assay development and hit identification from small-molecule libraries. Here, the strategies used for target selection are described and progress in protein production and structure analysis is reported. Of the 102 selected targets, 84 could be produced in soluble form and the de novo structures of 39 proteins have been determined. The crystal structures of eight of these targets, ranging from hypothetical unknown proteins to metabolic enzymes from different functional classes (PA1645, PA1648, PA2169, PA3770, PA4098, PA4485, PA4992 and PA5259), are reported here. The structural information is expected to provide a firm basis for the improvement of hit compounds identified from fragment-based and high-throughput screening campaigns.
Davies, Shelley L; Moral, Maria Angels; Bozzo, Jordi
Chronicles in Drug Discovery features special interest reports on advances in drug discovery. This month we highlight agents that target and deplete immunosuppressive regulatory T cells, which are produced by tumor cells to hinder innate immunity against, or chemotherapies targeting, tumor-associated antigens. Antiviral treatments for respiratory syncytial virus, a severe and prevalent infection in children, are limited due to their side effect profiles and cost. New strategies currently under clinical development include monoclonal antibodies, siRNAs, vaccines and oral small molecule inhibitors. Recent therapeutic lines for Huntington's disease include gene therapies that target the mutated human huntingtin gene or deliver neuroprotective growth factors and cellular transplantation in apoptotic regions of the brain. Finally, we highlight the antiinflammatory and antinociceptive properties of new compounds targeting the somatostatin receptor subtype sst4, which warrant further study for their potential application as clinical analgesics.
Kumari, Shraddha; Kumar, Awanish; Samant, Mukesh; Singh, Neeloo; Dube, Anuradha
Among the three clinical forms (cutaneous, mucosal and visceral) of leishmaniasis visceral (VL) one is the most devastating type caused by the invasion of the reticuloendothelial system of human by Leishmania donovani, L. infantum and L. chagasi. India and Sudan account for about half the world's burden of VL. Current control strategy is based on chemotherapy, which is difficult to administer, expensive and becoming ineffective due to the emergence of drug resistance. An understanding of resistance mechanism(s) operating in clinical isolates might provide additional leads for the development of new drugs. Further, due to the lack of fully effective treatment the search for novel immune targets is also needed. So far, no vaccine exists for VL despite indications of naturally developing immunity. Therefore, an urgent need for new and effective leishmanicidal agents and for this identification of novel drug and vaccine targets is imperative. The availability of the complete genome sequence of Leishmania has revolutionised many areas of leishmanial research and facilitated functional genomic studies as well as provided a wide range of novel targets for drug designing. Most notably, proteomics and transcriptomics have become important tools in gaining increased understanding of the biology of Leishmania to be explored on a global scale, thus accelerating the pace of discovery of vaccine/drug targets. In addition, these approaches provide the information regarding genes and proteins that are expressed and under which conditions. This review provides a comprehensive view about those proteins/genes identified using proteomics and transcriptomic tools for the development of vaccine/drug against VL.
Pierce, Christopher G.; Lopez-Ribot, Jose L.
Introduction Targeting pathogenetic mechanisms rather than essential processes represents a very attractive alternative for the development of new antibiotics. This may be particularly important in the case of antimycotics, due to the urgent need for novel antifungal drugs and the paucity of selective fungal targets. The opportunistic pathogenic fungus Candida albicans is the main etiological agent of candidiasis, the most common human fungal infection. These infections carry unacceptably high mortality rates, a clear reflection of the many shortcomings of current antifungal therapy, including the limited armamentarium of antifungal agents, their toxicity, and the emergence of resistance. Moreover the antifungal pipeline is mostly dry. Areas covered This review covers some of the most recent progress towards understanding C. albicans pathogenetic processes and how to harness this information for the development of anti-virulence agents. The two principal areas covered are filamentation and biofilm formation, as C. albicans pathogenicity is intimately linked to its ability to undergo morphogenetic conversions between yeast and filamentous morphologies and to its ability to form biofilms. Expert opinion We argue that filamentation and biofilm formation represent high value targets, yet clinically unexploited, for the development of novel anti-virulence approaches against candidiasis. Although this has proved a difficult task despite increasing understanding at the molecular level of C. albicans virulence, we highlight new opportunities and prospects for antifungal drug development targeting these two important biological processes. PMID:23738751
Deigan, Katherine E; Ferré-D'Amaré, Adrian R
Riboswitches are messenger RNA (mRNA) domains that regulate gene function in response to the intracellular concentration of a variety of metabolites and second messengers. They control essential genes in many pathogenic bacteria, thus representing an inviting new class of biomolecular target for the development of antibiotics and chemical-biological tools. In this Account, we briefly review the discovery of riboswitches in the first years of the 21st century and their ensuing characterization over the past decade. We then discuss the progress achieved so far in using riboswitches as a focus for drug discovery, considering both the value of past serendipity and the particular challenges that confront current researchers. Five mechanisms of gene regulation have been determined for riboswitches. Most bacterial riboswitches modulate either transcription termination or translation initiation in response to ligand binding. All known examples of eukaryotic riboswitches, and some bacterial riboswitches, control gene expression by alternative splicing. The glmS riboswitch, which is widespread in Gram-positive bacteria, is a catalytic RNA activated by ligand binding: its self-cleavage destabilizes the mRNA of which it is part. Finally, one example of a trans-acting riboswitch is known. Three-dimensional structures have been determined for representatives of 13 structurally distinct riboswitch classes, providing atomic-level insight into their mechanisms of ligand recognition. While cellular and viral RNAs have attracted widespread interest as potential drug targets, riboswitches show special promise due to the diversity of small-molecule recognition strategies that are on display in their ligand-binding pockets. Moreover, riboswitches have evolved to recognize small-molecule ligands, which is unique among known structured RNA domains. Structural and biochemical advances in the study of riboswitches provide an impetus for the development of methods for the discovery of novel
Khurdayan, V; Bozzo, J; Sorbera, L
Chronicles in Drug Discovery is a series of brief reports on timely topics in the field of drug R&D. This month's chronicles contain the following reports: Targeting DNA repair enzymes instead of viral proteins provides a great advantage in preventing the emergence of resistant mutants. A striking increase in therapeutic approaches for the treatment of IBD has been fueled by an improved understanding of the mechanisms that underlie its pathophysiology. Peptide deformylase inhibitors are under active investigation for bacterial infections and cancer treatment. Dopamine D3 receptors present an attractive target for alcoholism therapy since they are involved in the mechanisms of alcohol dependency and abuse.
Andreol, Federico; Barbosa, Arménio Jorge Moura; Daniele Parenti, Marco; Rio, Alberto Del
Research on cancer epigenetics has flourished in the last decade. Nevertheless growing evidence point on the importance to understand the mechanisms by which epigenetic changes regulate the genesis and progression of cancer growth. Several epigenetic targets have been discovered and are currently under validation for new anticancer therapies. Drug discovery approaches aiming to target these epigenetic enzymes with small-molecules inhibitors have produced the first pre-clinical and clinical outcomes and many other compounds are now entering the pipeline as new candidate epidrugs. The most studied targets can be ascribed to histone deacetylases and DNA methyltransferases, although several other classes of enzymes are able to operate post-translational modifications to histone tails are also likely to represent new frontiers for therapeutic interventions. By acknowledging that the field of cancer epigenetics is evolving with an impressive rate of new findings, with this review we aim to provide a current overview of pre-clinical applications of small-molecules for cancer pathologies, combining them with the current knowledge of epigenetic targets in terms of available structural data and drug design perspectives. PMID:23016851
Wang, Zhiyu; Wang, Neng; Chen, Jianping; Shen, Jiangang
Molecular-targeted therapy has been developed for cancer chemoprevention and treatment. Cancer cells have different metabolic properties from normal cells. Normal cells mostly rely upon the process of mitochondrial oxidative phosphorylation to produce energy whereas cancer cells have developed an altered metabolism that allows them to sustain higher proliferation rates. Cancer cells could predominantly produce energy by glycolysis even in the presence of oxygen. This alternative metabolic characteristic is known as the “Warburg Effect.” Although the exact mechanisms underlying the Warburg effect are unclear, recent progress indicates that glycolytic pathway of cancer cells could be a critical target for drug discovery. With a long history in cancer treatment, traditional Chinese medicine (TCM) is recognized as a valuable source for seeking bioactive anticancer compounds. A great progress has been made to identify active compounds from herbal medicine targeting on glycolysis for cancer treatment. Herein, we provide an overall picture of the current understanding of the molecular targets in the cancer glycolytic pathway and reviewed active compounds from Chinese herbal medicine with the potentials to inhibit the metabolic targets for cancer treatment. Combination of TCM with conventional therapies will provide an attractive strategy for improving clinical outcome in cancer treatment. PMID:22844340
Harati, Sahar; Cooper, Lee A D; Moran, Josue D; Giuste, Felipe O; Du, Yuhong; Ivanov, Andrei A; Johns, Margaret A; Khuri, Fadlo R; Fu, Haian; Moreno, Carlos S
Protein-protein interactions (PPIs) mediate the transmission and regulation of oncogenic signals that are essential to cellular proliferation and survival, and thus represent potential targets for anti-cancer therapeutic discovery. Despite their significance, there is no method to experimentally disrupt and interrogate the essentiality of individual endogenous PPIs. The ability to computationally predict or infer PPI essentiality would help prioritize PPIs for drug discovery and help advance understanding of cancer biology. Here we introduce a computational method (MEDICI) to predict PPI essentiality by combining gene knockdown studies with network models of protein interaction pathways in an analytic framework. Our method uses network topology to model how gene silencing can disrupt PPIs, relating the unknown essentialities of individual PPIs to experimentally observed protein essentialities. This model is then deconvolved to recover the unknown essentialities of individual PPIs. We demonstrate the validity of our approach via prediction of sensitivities to compounds based on PPI essentiality and differences in essentiality based on genetic mutations. We further show that lung cancer patients have improved overall survival when specific PPIs are no longer present, suggesting that these PPIs may be potentially new targets for therapeutic development. Software is freely available at https://github.com/cooperlab/MEDICI. Datasets are available at https://ctd2.nci.nih.gov/dataPortal.
Moran, Josue D.; Giuste, Felipe O.; Du, Yuhong; Ivanov, Andrei A.; Johns, Margaret A.; Khuri, Fadlo R.; Fu, Haian
Protein-protein interactions (PPIs) mediate the transmission and regulation of oncogenic signals that are essential to cellular proliferation and survival, and thus represent potential targets for anti-cancer therapeutic discovery. Despite their significance, there is no method to experimentally disrupt and interrogate the essentiality of individual endogenous PPIs. The ability to computationally predict or infer PPI essentiality would help prioritize PPIs for drug discovery and help advance understanding of cancer biology. Here we introduce a computational method (MEDICI) to predict PPI essentiality by combining gene knockdown studies with network models of protein interaction pathways in an analytic framework. Our method uses network topology to model how gene silencing can disrupt PPIs, relating the unknown essentialities of individual PPIs to experimentally observed protein essentialities. This model is then deconvolved to recover the unknown essentialities of individual PPIs. We demonstrate the validity of our approach via prediction of sensitivities to compounds based on PPI essentiality and differences in essentiality based on genetic mutations. We further show that lung cancer patients have improved overall survival when specific PPIs are no longer present, suggesting that these PPIs may be potentially new targets for therapeutic development. Software is freely available at https://github.com/cooperlab/MEDICI. Datasets are available at https://ctd2.nci.nih.gov/dataPortal. PMID:28118365
Fostel, J M; Montgomery, D A; Shen, L L
Candida albicans is an opportunistic pathogen responsible for life-threatening infections in persons with impaired immune systems. Topoisomerase I is a potential target for novel antifungal agents; however, in order for this enzyme to be a therapeutically useful target, it needs to be demonstrated that the fungal and human topoisomerases differ sufficiently as to allow the fungal topoisomerase to be selectively targeted. To address this question, we isolated the topoisomerase I from C. albicans and compared its biochemical properties with those of the mammalian enzyme. Similar to other eukaryotic type I topoisomerases, the C. albicans type I topoisomerase has an apparent molecular mass of 102 kDa and covalently links to the 3' end of DNA, as shown after the reaction is interrupted by sodium dodecyl sulfate. Topoisomerase poisons such as camptothecin act by stabilizing the cleavage complex formed by the topoisomerase I and DNA. We observed that the C. albicans and mammalian type I topoisomerases differ in that the C. albicans cleavage complex is approximately 10-fold less sensitive to camptothecin than the mammalian cleavage complex is. In addition, we found that the antifungal agent eupolauridine can stabilize the cleavage complex formed by both the C. albicans and human topoisomerases and that the response of the C. albicans topoisomerase I to this drug is greater than that of the human enzyme. Thus, the topoisomerase I from C. albicans is sufficiently distinct from the human enzyme as to allow differential chemical targeting and will therefore make a good target for antifungal drug discovery. Images PMID:1332588
Song, Chenchen; Knöpfel, Thomas
Optogenetics - the use of light and genetics to manipulate and monitor the activities of defined cell populations - has already had a transformative impact on basic neuroscience research. Now, the conceptual and methodological advances associated with optogenetic approaches are providing fresh momentum to neuroscience drug discovery, particularly in areas that are stalled on the concept of 'fixing the brain chemistry'. Optogenetics is beginning to translate and transit into drug discovery in several key domains, including target discovery, high-throughput screening and novel therapeutic approaches to disease states. Here, we discuss the exciting potential of optogenetic technologies to transform neuroscience drug discovery.
Protein-protein interactions (PPIs) mediate the transmission and regulation of oncogenic signals that are essential to cellular proliferation and survival, and thus represent potential targets for anti-cancer therapeutic discovery. Despite their significance, there is no method to experimentally disrupt and interrogate the essentiality of individual endogenous PPIs. The ability to computationally predict or infer PPI essentiality would help prioritize PPIs for drug discovery and help advance understanding of cancer biology.
Liu, Ke; Liu, Yanli; Lau, Johnathan L; Min, Jinrong
Chromatin structure is dynamically modulated by various chromatin modifications, such as histone/DNA methylation and demethylation. We have reviewed histone methyltransferases and methyllysine binders in terms of small molecule screening and drug discovery in the first part of this review series. In this part, we will summarize recent progress in chemical probe and drug discovery of histone demethylases and DNA methyltransferases. Histone demethylation and DNA methylation have attracted a lot of attention regarding their biology and disease implications. Correspondingly, many small molecule compounds have been designed to modulate the activity of histone demethylases and DNA methyltransferases, and some of them have been developed into therapeutic drugs or put into clinical trials.
Felciano, Ramon M; Bavari, Sina; Richards, Daniel R; Billaud, Jean-Noel; Warren, Travis; Panchal, Rekha; Krämer, Andreas
Knowledge of immune system and host-pathogen pathways can inform development of targeted therapies and molecular diagnostics based on a mechanistic understanding of disease pathogenesis and the host response. We investigated the feasibility of rapid target discovery for novel broad-spectrum molecular therapeutics through comprehensive systems biology modeling and analysis of pathogen and host-response pathways and mechanisms. We developed a system to identify and prioritize candidate host targets based on strength of mechanistic evidence characterizing the role of the target in pathogenesis and tractability desiderata that include optimal delivery of new indications through potential repurposing of existing compounds or therapeutics. Empirical validation of predicted targets in cellular and mouse model systems documented an effective target prediction rate of 34%, suggesting that such computational discovery approaches should be part of target discovery efforts in operational clinical or biodefense research initiatives. We describe our target discovery methodology, technical implementation, and experimental results. Our work demonstrates the potential for in silico pathway models to enable rapid, systematic identification and prioritization of novel targets against existing or emerging biological threats, thus accelerating drug discovery and medical countermeasures research.
Wang, Zhenya; Chen, Xinli; Wu, Chunli; Xu, Haiwei; Liu, Hongmin
Hepatitis C virus (HCV) infection is a major worldwide epidemic disease. It is estimated that more than 170 million individuals are infected with HCV and with three to four million new cases each year. Many new direct-acting antiviral (DAA) agents that specifically target HCV NS3 protease or NS5B polymerase inhibitors are therefore in development, with a significant effect for the patient and for the market recently. The non-structural 4B (NS4B) protein, is among the least characterized of the HCV proteins. A variety of functions have been recognized for NS4B, such as the ability to induce the membranous web replication platform, RNA binding and NTPase activity. In order to maximize antiviral efficacy and prevent the emergence of resistance, novel NS4B inhibitors have been subjected to pharmacological studies. In this review, we discussed current understanding of the structure and function of NS4B, and novel drug discoveries targeting NS4B as anti-hepatitis C virus such as sulfonamide, piperidine, carboxamide, piperazinone and quinoline derivatives within the last three years.
Shen, L L; Baranowski, J; Fostel, J; Montgomery, D A; Lartey, P A
DNA topoisomerases, a class of enzymes that change the topological structure of DNA, have been shown to be the target of many therapeutic agents, including antibacterial agents (quinolones) and anticancer agents. These drugs inhibit the enzyme in a unique way so that the enzyme is converted into a cellular poison. Candida albicans and Aspergillus niger are two major opportunistic fungal pathogens. Our results show that these fungi have high levels of both type I and type II topoisomerases (with a minimum of 5 x 10(5) ATP-independent relaxation units and 2 x 10(5) P-4 unknotting units per liter of wild-type C. albicans). The ATP-dependent type II topoisomerase (termed C. albicans topoisomerase II) was purified by approximately 2,000-fold from C. albicans cells by using a simple isolation scheme that consists of three column procedures: hydroxylapatite, phosphocellulose, and heparin-agarose chromatographies. The responses of the Candida and the calf thymus topoisomerase II to some known topoisomerase II inhibitors were measured. Etoposide and 4'-(9-acridinylamino)methanesulfon-m-anisidide, compounds known to inhibit catalysis and to enhance DNA breakage by mammalian topoisomerase II, and A-80198, an etoposide derivative, enhanced cleavage by both enzymes at similar concentrations of these compounds, with the response of the calf thymus topoisomerase II from slightly to fourfold higher in magnitude than the response of the Candida enzyme in the same concentration range. In contrast, A-75272 (a cytotoxic tricyclic quinolone) shows a slightly stronger DNA cleavage enhancement effect with the Candida enzyme than with the mammalian counterpart. The abundance of the enzyme in cells and the different drug responses of the host enzyme and the fungal enzyme suggest that the fungal topoisomerase may serve as a target for the discovery of effective and safe antifungal agents.
Lee, Wen Hwa
There is a scarcity of novel treatments to address many unmet medical needs. Industry and academia are finally coming to terms with the fact that the prevalent models and incentives for innovation in early stage drug discovery are failing to promote progress quickly enough. Here we will examine how an open model of precompetitive public–private research partnership is enabling efficient derisking and acceleration in the early stages of drug discovery, whilst also widening the range of communities participating in the process, such as patient and disease foundations. PMID:26042736
de Mooij-van Malsen, Annetrude J G; Pjetri, Eneda; Kas, Martien J
Animal studies play a central role in the identification and testing of novel drugs for CNS disorders. In his longstanding career, Berend Olivier has significantly contributed to CNS drug discovery by applying and supporting novel views and methodologies in the fields of behavioral neuroscience, pharmacology, and (epi-) genetics. Here we review and put forward some of these integrated approaches that have led to a productive collaboration and new insights into the genetic and epigenetic regulation of neurobehavioural traits related to psychiatric disorders.
Hunter, William N
Two, simple, C5 compounds, dimethylally diphosphate and isopentenyl diphosphate, are the universal precursors of isoprenoids, a large family of natural products involved in numerous important biological processes. Two distinct biosynthetic pathways have evolved to supply these precursors. Humans use the mevalonate route whilst many species of bacteria including important pathogens, plant chloroplasts and apicomplexan parasites exploit the non-mevalonate pathway. The absence from humans, combined with genetic and chemical validation suggests that the non-mevalonate pathway holds the potential to support new drug discovery programmes targeting Gram-negative bacteria and the apicomplexan parasites responsible for causing serious human diseases, and also infections of veterinary importance. The non-mevalonate pathway relies on eight enzyme-catalyzed stages exploiting a range of cofactors and metal ions. A wealth of structural and mechanistic data, mainly derived from studies of bacterial enzymes, now exists for most components of the pathway and these will be described. Particular attention will be paid to how these data inform on the apicomplexan orthologues concentrating on the enzymes from Plasmodium spp. these cause malaria, one the most important parasitic diseases in the world today.
Lipinski, Christopher A
The rule of five (Ro5), based on physicochemical profiles of phase II drugs, is consistent with structural limitations in protein targets and the drug target ligands. Three of four parameters in Ro5 are fundamental to the structure of both target and drug binding sites. The chemical structure of the drug ligand depends on the ligand chemistry and design philosophy. Two extremes of chemical structure and design philosophy exist; ligands constructed in the medicinal chemistry synthesis laboratory without input from natural selection and natural product (NP) metabolites biosynthesized based on evolutionary selection. Exceptions to Ro5 are found mostly among NPs. Chemistry chameleon-like behavior of some NPs due to intra-molecular hydrogen bonding as exemplified by cyclosporine A is a strong contributor to NP Ro5 outliers. The fragment derived, drug Navitoclax is an example of the extensive expertise, resources, time and key decisions required for the rare discovery of a non-NP Ro5 outlier.
Smith, Andrew M.; Ammar, Ron; Nislow, Corey; Giaever, Guri
Over the past decade, the development and application of chemical genomic assays using the model organism Saccharomyces cerevisiae has provided powerful methods to identify the mechanism of action of known drugs and novel small molecules in vivo. These assays identify drug target candidates, genes involved in buffering drug target pathways and also help to define the general cellular response to small molecules. In this review, we examine current yeast chemical genomic assays and summarize the potential applications of each approach. PMID:20546776
Chichester, Christine; Digles, Daniela; Siebes, Ronald; Loizou, Antonis; Groth, Paul; Harland, Lee
Modern data-driven drug discovery requires integrated resources to support decision-making and enable new discoveries. The Open PHACTS Discovery Platform (http://dev.openphacts.org) was built to address this requirement by focusing on drug discovery questions that are of high priority to the pharmaceutical industry. Although complex, most of these frequently asked questions (FAQs) revolve around the combination of data concerning compounds, targets, pathways and diseases. Computational drug discovery using workflow tools and the integrated resources of Open PHACTS can deliver answers to most of these questions. Here, we report on a selection of workflows used for solving these use cases and discuss some of the research challenges. The workflows are accessible online from myExperiment (http://www.myexperiment.org) and are available for reuse by the scientific community.
Recent years have seen a significant improvement in available treatment options for leishmaniasis. Two new drugs, miltefosine and paromomycin, have been registered for the treatment of visceral leishmaniasis (VL) in India since 2002. Combination therapy is now explored in clinical trials as a new treatment approach for VL to reduce the length of treatment and potentially prevent selection of resistant parasites. However there is still a need for new drugs due to safety, resistance, stability and cost issues with existing therapies. The search for topical treatments for cutaneous leishmaniasis (CL) is ongoing. This review gives a brief overview of recent developments and approaches in anti-leishmanial drug discovery and development. PMID:21629509
Sheng, Jia; Gan, Jianhua; Huang, Zhen
Nucleic acids are the molecular targets of many clinical anticancer drugs. However, compared with proteins, nucleic acids have traditionally attracted much less attention as drug targets in structure-based drug design, partially because limited structural information of nucleic acids complexed with potential drugs is available. Over the past several years, enormous progresses in nucleic acid crystallization, heavy-atom derivatization, phasing, and structural biology have been made. Many complicated nucleic acid structures have been determined, providing new insights into the molecular functions and interactions of nucleic acids, especially DNAs complexed with small molecule ligands. Thus, opportunities have been created to further discover nucleic acid-targeting drugs for disease treatments. This review focuses on the structure studies of DNAs complexed with small molecule ligands for discovering lead compounds, drug candidates, and/or therapeutics.
Sheng, Jia; Gan, Jianhua; Huang, Zhen
Nucleic acids are the molecular targets of many clinical anticancer drugs. However, compared with proteins, nucleic acids have traditionally attracted much less attention as drug targets in structure-based drug design, partially because limited structural information of nucleic acids complexed with potential drugs is available. Over the past several years, enormous progresses in nucleic acid crystallization, heavy-atom derivatization, phasing, and structural biology have been made. Many complicated nucleic acid structures have been determined, providing new insights into the molecular functions and interactions of nucleic acids, especially DNAs complexed with small molecule ligands. Thus, opportunities have been created to further discover nucleic acid-targeting drugs for disease treatments. This review focuses on the structure studies of DNAs complexed with small molecule ligands for discovering lead compounds, drug candidates, and/or therapeutics. PMID:23633219
Li, Xiuyun; Hou, Yinglong; Yue, Longtao; Liu, Shuyuan; Du, Juan; Sun, Shujuan
Fungal infections, especially infections caused by Candida albicans, remain a challenging problem in clinical settings. Despite the development of more-effective antifungal drugs, their application is limited for various reasons. Thus, alternative treatments with drugs aimed at novel targets in C. albicans are needed. Knowledge of growth and virulence in fungal cells is essential not only to understand their pathogenic mechanisms but also to identify potential antifungal targets. This article reviews the current knowledge of the mechanisms of growth and virulence in C. albicans and examines potential targets for the development of new antifungal drugs.
Plasmodium . There are four species of Plasmodium that may cause malaria in humans: P. falciparum , P. malariae, P. ovale, and P. vivax. P...gold standard for drug discovery is the in vitro screen for efficacy against Plasmodium falciparum (fig. 1, yellow box). This assay acts as a... falciparum is the most dangerous, as it can cause severe anemia, kidney failure, and brain damage; it is often fatal, especially among children. In P. vivax
Abdolmalekia, Azizeh; Ghasemi, Jahan B
Finding high quality beginning compounds is a critical job at the start of the lead generation stage for multi-target drug discovery (MTDD). Designing hybrid compounds as a selective multi-target chemical entity is a challenge, opportunity, and new idea to better act against specific multiple targets. One hybrid molecule is formed by two (or more) pharmacophore group's participation. So, these new compounds often exhibit two or more activities going about as multi-target drugs (mt-drugs) and may have superior safety or efficacy. Application of integrating a range of information and sophisticated new in silico, bioinformatics, structural biology, pharmacogenomics methods may be useful to discover/design, and synthesis of the new hybrid molecules. In this regard, many rational and screening approaches have followed by medicinal chemists for the lead generation in MTDD. Here, we review some popular lead generation approaches that have been used for designing multiple ligands (DMLs). This paper focuses on dual- acting chemical entities that incorporate a part of two drugs or bioactive compounds to compose hybrid molecules. Also, it presents some of key concepts and limitations/strengths of lead generation methods by comparing combination framework method with screening approaches. Besides, a number of examples to represent applications of hybrid molecules in the drug discovery are included.
Reguera, Rosa M.; Calvo-Álvarez, Estefanía; Álvarez-Velilla, Raquel; Balaña-Fouce, Rafael
Drug discovery programs sponsored by public or private initiatives pursue the same ambitious goal: a crushing defeat of major Neglected Tropical Diseases (NTDs) during this decade. Both target-based and target-free screenings have pros and cons when it comes to finding potential small-molecule leads among chemical libraries consisting of myriads of compounds. Within the target-based strategy, crystals of pathogen recombinant-proteins are being used to obtain three-dimensional (3D) structures in silico for the discovery of structure-based inhibitors. On the other hand, genetically modified parasites expressing easily detectable reporters are in the pipeline of target-free (phenotypic) screenings. Furthermore, lead compounds can be scaled up to in vivo preclinical trials using rodent models of infection monitoring parasite loads by means of cutting-edge bioimaging devices. As such, those preferred are fluorescent and bioluminescent readouts due to their reproducibility and rapidity, which reduces the number of animals used in the trials and allows for an earlier stage detection of the infective process as compared with classical methods. In this review, we focus on the current differences between target-based and phenotypic screenings in Leishmania, as an approach that leads to the discovery of new potential drugs against leishmaniasis. PMID:25516847
Geromichalos, George D; Alifieris, Constantinos E; Geromichalou, Elena G; Trafalis, Dimitrios T
Conventional drug design embraces the "one gene, one drug, one disease" philosophy. Nowadays, new generation of anti- cancer drugs, able to inhibit more than one pathway, is believed to play a major role in contemporary anticancer drug research. In this way, polypharmacology, focusing on multi-target drugs, has emerged as a new paradigm in drug discovery. A number of recent successful drugs have in part or in whole emerged from a structure-based research approach. Many advances including crystallography and informatics are behind these successes. Increasing insight into the genetics and molecular biology of cancer has resulted in the identification of an increasing number of potential molecular targets, for anticancer drug discovery and development. These targets can be approached through exploitation of emerging structural biology, "rational" drug design, screening of chemical libraries, or a combination of these methods. The result is the rapid discovery of new anticancer drugs. In this article we discuss the application of molecular modeling, molecular docking and virtual high-throughput screening to multi-targeted anticancer drug discovery. Efforts have been made to employ in silico methods for facilitating the search and design of selective multi-target agents. These computer aided molecular design methods have shown promising potential in facilitating drug discovery directed at selective multiple targets and is expected to contribute to intelligent lead anticancer drugs.
Hughes, JP; Rees, S; Kalindjian, SB; Philpott, KL
Developing a new drug from original idea to the launch of a finished product is a complex process which can take 12–15 years and cost in excess of $1 billion. The idea for a target can come from a variety of sources including academic and clinical research and from the commercial sector. It may take many years to build up a body of supporting evidence before selecting a target for a costly drug discovery programme. Once a target has been chosen, the pharmaceutical industry and more recently some academic centres have streamlined a number of early processes to identify molecules which possess suitable characteristics to make acceptable drugs. This review will look at key preclinical stages of the drug discovery process, from initial target identification and validation, through assay development, high throughput screening, hit identification, lead optimization and finally the selection of a candidate molecule for clinical development. PMID:21091654
Hughes, J P; Rees, S; Kalindjian, S B; Philpott, K L
Developing a new drug from original idea to the launch of a finished product is a complex process which can take 12-15 years and cost in excess of $1 billion. The idea for a target can come from a variety of sources including academic and clinical research and from the commercial sector. It may take many years to build up a body of supporting evidence before selecting a target for a costly drug discovery programme. Once a target has been chosen, the pharmaceutical industry and more recently some academic centres have streamlined a number of early processes to identify molecules which possess suitable characteristics to make acceptable drugs. This review will look at key preclinical stages of the drug discovery process, from initial target identification and validation, through assay development, high throughput screening, hit identification, lead optimization and finally the selection of a candidate molecule for clinical development.
Alagappan, Muthuraman; Jiang, Dadi; Denko, Nicholas; Koong, Albert C
In silico drug discovery refers to a combination of computational techniques that augment our ability to discover drug compounds from compound libraries. Many such techniques exist, including virtual high-throughput screening (vHTS), high-throughput screening (HTS), and mechanisms for data storage and querying. However, presently these tools are often used independent of one another. In this chapter, we describe a new multimodal in silico technique for the hit identification and lead generation phases of traditional drug discovery. Our technique leverages the benefits of three independent methods-virtual high-throughput screening, high-throughput screening, and structural fingerprint analysis-by using a fourth technique called topological data analysis (TDA). We describe how a compound library can be independently tested with vHTS, HTS, and fingerprint analysis, and how the results can be transformed into a topological data analysis network to identify compounds from a diverse group of structural families. This process of using TDA or similar clustering methods to identify drug leads is advantageous because it provides a mechanism for choosing structurally diverse compounds while maintaining the unique advantages of already established techniques such as vHTS and HTS.
Ekins, S; Mestres, J; Testa, B
Computational (in silico) methods have been developed and widely applied to pharmacology hypothesis development and testing. These in silico methods include databases, quantitative structure-activity relationships, similarity searching, pharmacophores, homology models and other molecular modeling, machine learning, data mining, network analysis tools and data analysis tools that use a computer. Such methods have seen frequent use in the discovery and optimization of novel molecules with affinity to a target, the clarification of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The first part of this review discussed the methods that have been used for virtual ligand and target-based screening and profiling to predict biological activity. The aim of this second part of the review is to illustrate some of the varied applications of in silico methods for pharmacology in terms of the targets addressed. We will also discuss some of the advantages and disadvantages of in silico methods with respect to in vitro and in vivo methods for pharmacology research. Our conclusion is that the in silico pharmacology paradigm is ongoing and presents a rich array of opportunities that will assist in expediating the discovery of new targets, and ultimately lead to compounds with predicted biological activity for these novel targets. PMID:17549046
Shi, Junwei; Wang, Eric; Milazzo, Joseph P; Wang, Zihua; Kinney, Justin B; Vakoc, Christopher R
CRISPR-Cas9 genome editing technology holds great promise for discovering therapeutic targets in cancer and other diseases. Current screening strategies target CRISPR-Cas9-induced mutations to the 5' exons of candidate genes, but this approach often produces in-frame variants that retain functionality, which can obscure even strong genetic dependencies. Here we overcome this limitation by targeting CRISPR-Cas9 mutagenesis to exons encoding functional protein domains. This generates a higher proportion of null mutations and substantially increases the potency of negative selection. We also show that the magnitude of negative selection can be used to infer the functional importance of individual protein domains of interest. A screen of 192 chromatin regulatory domains in murine acute myeloid leukemia cells identifies six known drug targets and 19 additional dependencies. A broader application of this approach may allow comprehensive identification of protein domains that sustain cancer cells and are suitable for drug targeting.
El-Sherbeni, Ahmed A; El-Kadi, Ayman O S
Cytochrome P450 (P450) enzymes are ancient electron-transfer-chain system of remarkable biological importance. Microsomal P450 enzymes are the P450 attached to endoplasmic reticulum, which, in humans, are critical for body's defenses against xenobiotics by mediating their metabolism, and cell signaling by mediating arachidonic acid (AA) transformation to several potent bioactive molecules. Only recently, modulating P450-mediated AA metabolism has risen as a promising new drug target. This review presents the therapeutic potential of finding effective, selective and safe treatments targeting P450-mediated AA metabolism, and the several approaches that have been used to find these treatments; among which, our focus was on modulators of P450 activities. We detailed the efforts done to develop new molecular entities designed to modulate P450, and the more recent efforts tried to employ our previous knowledge on drug metabolism to repurpose old drugs with the capacity to alter P450-mediated drug metabolism to target AA metabolism. Because of the long recognition of P450 role in xenobiotic metabolism, several clinically approved agents were identified to alter P450 activity. Repurposing old drugs as P450 modulators can facilitate bringing treatments targeting P450-mediated AA metabolism to clinical trials. However, the capacity of the modulation of P450-derived AA metabolites of clinically approved drugs has to be systematically investigated and validated for their new use in humans.
Bullard, Kristen M; DeLisle, Robert Kirk; Keenan, Susan M
Malaria, the disease caused by infection with protozoan parasites from the genus Plasmodium, claims the lives of nearly 1 million people annually. Developing nations, particularly in the African Region, bear the brunt of this malaria burden. Alarmingly, the most dangerous etiologic agent of malaria, Plasmodium falciparum, is becoming increasingly resistant to current first-line antimalarials. In light of the widespread devastation caused by malaria, the emergence of drug-resistant P. falciparum strains, and the projected decrease in funding for malaria eradication that may occur over the next decade, the identification of promising new targets for antimalarial drug design is imperative. P. falciparum kinases have been proposed as ideal drug targets for antimalarial drug design because they mediate critical cellular processes within the parasite and are, in many cases, structurally and mechanistically divergent when compared with kinases from humans. Identifying a molecule capable of inhibiting the activity of a target enzyme is generally an arduous and expensive process that can be greatly aided by utilizing in silico drug design techniques. Such methods have been extensively applied to human kinases, but as yet have not been fully exploited for the exploration and characterization of antimalarial kinase targets. This review focuses on in silico methods that have been used for the evaluation of potential antimalarials and the Plasmodium kinases that could be explored using these techniques.
Liu, Qing; Wang, Ming-wei
Post-translational epigenetic modification of histones is controlled by a number of histone-modifying enzymes. Such modification regulates the accessibility of DNA and the subsequent expression or silencing of a gene. Human histone methyltransferases (HMTs)constitute a large family that includes histone lysine methyltransferases (HKMTs) and histone/protein arginine methyltransferases (PRMTs). There is increasing evidence showing a correlation between HKMTs and cancer pathogenesis. Here, we present an overview of representative HKMTs, including their biological and biochemical properties as well as the profiles of small molecule inhibitors for a comprehensive understanding of HKMTs in drug discovery. PMID:27397541
Jiang, Guoqian; Wang, Chen; Zhu, Qian; Chute, Christopher G.
Knowledge-driven text mining is becoming an important research area for identifying pharmacogenomics target genes. However, few of such studies have been focused on the pharmacogenomics targets of adverse drug events (ADEs). The objective of the present study is to build a framework of knowledge integration and discovery that aims to support pharmacogenomics target predication of ADEs. We integrate a semantically annotated literature corpus Semantic MEDLINE with a semantically coded ADE knowledgebase known as ADEpedia using a semantic web based framework. We developed a knowledge discovery approach combining a network analysis of a protein-protein interaction (PPI) network and a gene functional classification approach. We performed a case study of drug-induced long QT syndrome for demonstrating the usefulness of the framework in predicting potential pharmacogenomics targets of ADEs. PMID:24303306
Wynn, Jessica E.
Human immunodeficiency virus type 1 (HIV-1) is an RNA virus that is prone to high rates of mutation. While the disease is managed with current antiretroviral therapies, drugs with a new mode of action are needed. A strategy towards this goal is aimed at targeting the native three-dimensional fold of conserved RNA structures. This perspective highlights medium-sized peptides and peptidomimetics used to target two conserved RNA structures of HIV-1. In particular, branched peptides have the capacity to bind in a multivalent fashion, utilizing a large surface area to achieve the necessary affinity and selectivity toward the target RNA. PMID:25958855
Dahlin, Jayme L; Inglese, James; Walters, Michael A
The number of academic drug discovery centres has grown considerably in recent years, providing new opportunities to couple the curiosity-driven research culture in academia with rigorous preclinical drug discovery practices used in industry. To fully realize the potential of these opportunities, it is important that academic researchers understand the risks inherent in preclinical drug discovery, and that translational research programmes are effectively organized and supported at an institutional level. In this article, we discuss strategies to mitigate risks in several key aspects of preclinical drug discovery at academic drug discovery centres, including organization, target selection, assay design, medicinal chemistry and preclinical pharmacology.
Ortiz, Diana; Forquer, Isaac; Boitz, Jan; Soysa, Radika; Elya, Carolyn; Fulwiler, Audrey; Nilsen, Aaron; Polley, Tamsen; Riscoe, Michael K; Ullman, Buddy; Landfear, Scott M
Endochin-like quinolones (ELQs) are potent and specific inhibitors of cytochrome bc1 from Plasmodium falciparum and Toxoplasma gondii and show promise for novel antiparasitic drug development. To determine whether the mitochondrial electron transport chain of Leishmania parasites could be targeted similarly for drug development, we investigated the activity of 134 structurally diverse ELQs. A cohort of ELQs was selectively toxic to amastigotes of Leishmania mexicana and L. donovani, with 50% inhibitory concentrations (IC50s) in the low micromolar range, but the structurally similar hydroxynaphthoquinone buparvaquone was by far the most potent inhibitor of electron transport, ATP production, and intracellular amastigote growth. Cytochrome bc1 is thus a promising target for novel antileishmanial drugs, and further improvements on the buparvaquone scaffold are warranted for development of enhanced therapeutics.
Ortiz, Diana; Forquer, Isaac; Boitz, Jan; Soysa, Radika; Elya, Carolyn; Fulwiler, Audrey; Nilsen, Aaron; Polley, Tamsen; Riscoe, Michael K.; Ullman, Buddy
Endochin-like quinolones (ELQs) are potent and specific inhibitors of cytochrome bc1 from Plasmodium falciparum and Toxoplasma gondii and show promise for novel antiparasitic drug development. To determine whether the mitochondrial electron transport chain of Leishmania parasites could be targeted similarly for drug development, we investigated the activity of 134 structurally diverse ELQs. A cohort of ELQs was selectively toxic to amastigotes of Leishmania mexicana and L. donovani, with 50% inhibitory concentrations (IC50s) in the low micromolar range, but the structurally similar hydroxynaphthoquinone buparvaquone was by far the most potent inhibitor of electron transport, ATP production, and intracellular amastigote growth. Cytochrome bc1 is thus a promising target for novel antileishmanial drugs, and further improvements on the buparvaquone scaffold are warranted for development of enhanced therapeutics. PMID:27297476
Eder, Jörg; Herrling, Paul L
Drugs discovered by the pharmaceutical industry over the past 100 years have dramatically changed the practice of medicine and impacted on many aspects of our culture. For many years, drug discovery was a target- and mechanism-agnostic approach that was based on ethnobotanical knowledge often fueled by serendipity. With the advent of modern molecular biology methods and based on knowledge of the human genome, drug discovery has now largely changed into a hypothesis-driven target-based approach, a development which was paralleled by significant environmental changes in the pharmaceutical industry. Laboratories became increasingly computerized and automated, and geographically dispersed research sites are now more and more clustered into large centers to capture technological and biological synergies. Today, academia, the regulatory agencies, and the pharmaceutical industry all contribute to drug discovery, and, in order to translate the basic science into new medical treatments for unmet medical needs, pharmaceutical companies have to have a critical mass of excellent scientists working in many therapeutic fields, disciplines, and technologies. The imperative for the pharmaceutical industry to discover breakthrough medicines is matched by the increasing numbers of first-in-class drugs approved in recent years and reflects the impact of modern drug discovery approaches, technologies, and genomics.
Despite striking advances in the biomedical sciences, the flow of new drugs has slowed to a trickle, impairing therapeutic advances as well as the commercial success of drug companies. Reduced productivity in the drug industry is caused mainly by corporate policies that discourage innovation. This is compounded by various consequences of mega-mergers, the obsession for blockbuster drugs, the shift of control of research from scientists to marketers, the need for fast sales growth, and the discontinuation of development compounds for nontechnical reasons. Lessons from the past indicate that these problems can be overcome, and herein, new and improved directions for drug discovery are suggested. PMID:17080187
Sharma, Charu; Sadek, Bassem; Goyal, Sameer N.; Sinha, Satyesh; Ojha, Shreesh
The cannabinoid molecules are derived from Cannabis sativa plant which acts on the cannabinoid receptors types 1 and 2 (CB1 and CB2) which have been explored as potential therapeutic targets for drug discovery and development. Currently, there are numerous cannabinoid based synthetic drugs used in clinical practice like the popular ones such as nabilone, dronabinol, and Δ9-tetrahydrocannabinol mediates its action through CB1/CB2 receptors. However, these synthetic based Cannabis derived compounds are known to exert adverse psychiatric effect and have also been exploited for drug abuse. This encourages us to find out an alternative and safe drug with the least psychiatric adverse effects. In recent years, many phytocannabinoids have been isolated from plants other than Cannabis. Several studies have shown that these phytocannabinoids show affinity, potency, selectivity, and efficacy towards cannabinoid receptors and inhibit endocannabinoid metabolizing enzymes, thus reducing hyperactivity of endocannabinoid systems. Also, these naturally derived molecules possess the least adverse effects opposed to the synthetically derived cannabinoids. Therefore, the plant based cannabinoid molecules proved to be promising and emerging therapeutic alternative. The present review provides an overview of therapeutic potential of ligands and plants modulating cannabinoid receptors that may be of interest to pharmaceutical industry in search of new and safer drug discovery and development for future therapeutics. PMID:26664449
Cox, Adrienne D; Der, Channing J; Philips, Mark R
RAS proteins require membrane association for their biologic activity, making this association a logical target for anti-RAS therapeutics. Lipid modification of RAS proteins by a farnesyl isoprenoid is an obligate step in that association, and is an enzymatic process. Accordingly, farnesyltransferase inhibitors (FTI) were developed as potential anti-RAS drugs. The lack of efficacy of FTIs as anticancer drugs was widely seen as indicating that blocking RAS membrane association was a flawed approach to cancer treatment. However, a deeper understanding of RAS modification and trafficking has revealed that this was an erroneous conclusion. In the presence of FTIs, KRAS and NRAS, which are the RAS isoforms most frequently mutated in cancer, become substrates for alternative modification, can still associate with membranes, and can still function. Thus, FTIs failed not because blocking RAS membrane association is an ineffective approach, but because FTIs failed to accomplish that task. Recent findings regarding RAS isoform trafficking and the regulation of RAS subcellular localization have rekindled interest in efforts to target these processes. In particular, improved understanding of the palmitoylation/depalmitoylation cycle that regulates RAS interaction with the plasma membrane, endomembranes, and cytosol, and of the potential importance of RAS chaperones, have led to new approaches. Efforts to validate and target other enzymatically regulated posttranslational modifications are also ongoing. In this review, we revisit lessons learned, describe the current state of the art, and highlight challenging but promising directions to achieve the goal of disrupting RAS membrane association and subcellular localization for anti-RAS drug development. Clin Cancer Res; 21(8); 1819-27. ©2015 AACR. See all articles in this CCR Focus section, "Targeting RAS-Driven Cancers."
Trindade, Marla; van Zyl, Leonardo Joaquim; Navarro-Fernández, José; Abd Elrazak, Ahmed
Microbial natural products exhibit immense structural diversity and complexity and have captured the attention of researchers for several decades. They have been explored for a wide spectrum of applications, most noteworthy being their prominent role in medicine, and their versatility expands to application as drugs for many diseases. Accessing unexplored environments harboring unique microorganisms is expected to yield novel bioactive metabolites with distinguishing functionalities, which can be supplied to the starved pharmaceutical market. For this purpose the oceans have turned out to be an attractive and productive field. Owing to the enormous biodiversity of marine microorganisms, as well as the growing evidence that many metabolites previously isolated from marine invertebrates and algae are actually produced by their associated bacteria, the interest in marine microorganisms has intensified. Since the majority of the microorganisms are uncultured, metagenomic tools are required to exploit the untapped biochemistry. However, after years of employing metagenomics for marine drug discovery, new drugs are vastly under-represented. While a plethora of natural product biosynthetic genes and clusters are reported, only a minor number of potential therapeutic compounds have resulted through functional metagenomic screening. This review explores specific obstacles that have led to the low success rate. In addition to the typical problems encountered with traditional functional metagenomic-based screens for novel biocatalysts, there are enormous limitations which are particular to drug-like metabolites. We also present how targeted and function-guided strategies, employing modern, and multi-disciplinary approaches have yielded some of the most exciting discoveries attributed to uncultured marine bacteria. These discoveries set the stage for progressing the production of drug candidates from uncultured bacteria for pre-clinical and clinical development. PMID:26379658
Sugimoto, Keiki; Hayakawa, Fumihiko; Shimada, Satoko; Morishita, Takanobu; Shimada, Kazuyuki; Katakai, Tomoya; Tomita, Akihiro; Kiyoi, Hitoshi; Naoe, Tomoki
Cell lines have been used for drug discovery as useful models of cancers; however, they do not recapitulate cancers faithfully, especially in the points of rapid growth rate and microenvironment independency. Consequently, the majority of conventional anti-cancer drugs are less sensitive to slow growing cells and do not target microenvironmental support, although most primary cancer cells grow slower than cell lines and depend on microenvironmental support. Here, we developed a novel high throughput drug screening system using patient-derived xenograft (PDX) cells of lymphoma that maintained primary cancer cell phenotype more than cell lines. The library containing 2613 known pharmacologically active substance and off-patent drugs were screened by this system. We could find many compounds showing higher cytotoxicity than conventional anti-tumor drugs. Especially, pyruvinium pamoate showed the highest activity and its strong anti-tumor effect was confirmed also in vivo. We extensively investigated its mechanism of action and found that it inhibited glutathione supply from stromal cells to lymphoma cells, implying the importance of the stromal protection from oxidative stress for lymphoma cell survival and a new therapeutic strategy for lymphoma. Our system introduces a primary cancer cell phenotype into cell-based phenotype screening and sheds new light on anti-cancer drug development. PMID:26278963
Sugimoto, Keiki; Hayakawa, Fumihiko; Shimada, Satoko; Morishita, Takanobu; Shimada, Kazuyuki; Katakai, Tomoya; Tomita, Akihiro; Kiyoi, Hitoshi; Naoe, Tomoki
Cell lines have been used for drug discovery as useful models of cancers; however, they do not recapitulate cancers faithfully, especially in the points of rapid growth rate and microenvironment independency. Consequently, the majority of conventional anti-cancer drugs are less sensitive to slow growing cells and do not target microenvironmental support, although most primary cancer cells grow slower than cell lines and depend on microenvironmental support. Here, we developed a novel high throughput drug screening system using patient-derived xenograft (PDX) cells of lymphoma that maintained primary cancer cell phenotype more than cell lines. The library containing 2613 known pharmacologically active substance and off-patent drugs were screened by this system. We could find many compounds showing higher cytotoxicity than conventional anti-tumor drugs. Especially, pyruvinium pamoate showed the highest activity and its strong anti-tumor effect was confirmed also in vivo. We extensively investigated its mechanism of action and found that it inhibited glutathione supply from stromal cells to lymphoma cells, implying the importance of the stromal protection from oxidative stress for lymphoma cell survival and a new therapeutic strategy for lymphoma. Our system introduces a primary cancer cell phenotype into cell-based phenotype screening and sheds new light on anti-cancer drug development.
Geromichalos, George D; Alifieris, Constantinos E; Geromichalou, Elena G; Trafalis, Dimitrios T
Conventional drug design embraces the "one gene, one drug, one disease" philosophy. Nowadays, new generation of anticancer drugs, able to inhibit more than one pathway, is believed to play a major role in contemporary anticancer drug research. In this way, polypharmacology, focusing on multi-target drugs, has emerged as a new paradigm in drug discovery. A number of recent successful drugs have in part or in whole emerged from a structure-based research approach. Many advances including crystallography and informatics are behind these successes. In this part II we will review the role and methodology of ligand-, structure- and fragment-based computer-aided drug design computer aided drug desing (CADD), virtual high throughput screening (vHTS), de novo drug design, fragment-based design and structure-based molecular docking, homology modeling, combinatorial chemistry and library design, pharmacophore model chemistry and informatics in modern drug discovery.
Winter, Anja; Higueruelo, Alicia P; Marsh, May; Sigurdardottir, Anna; Pitt, Will R; Blundell, Tom L
Drug discovery has classically targeted the active sites of enzymes or ligand-binding sites of receptors and ion channels. In an attempt to improve selectivity of drug candidates, modulation of protein-protein interfaces (PPIs) of multiprotein complexes that mediate conformation or colocation of components of cell-regulatory pathways has become a focus of interest. However, PPIs in multiprotein systems continue to pose significant challenges, as they are generally large, flat and poor in distinguishing features, making the design of small molecule antagonists a difficult task. Nevertheless, encouragement has come from the recognition that a few amino acids - so-called hotspots - may contribute the majority of interaction-free energy. The challenges posed by protein-protein interactions have led to a wellspring of creative approaches, including proteomimetics, stapled α-helical peptides and a plethora of antibody inspired molecular designs. Here, we review a more generic approach: fragment-based drug discovery. Fragments allow novel areas of chemical space to be explored more efficiently, but the initial hits have low affinity. This means that they will not normally disrupt PPIs, unless they are tethered, an approach that has been pioneered by Wells and co-workers. An alternative fragment-based approach is to stabilise the uncomplexed components of the multiprotein system in solution and employ conventional fragment-based screening. Here, we describe the current knowledge of the structures and properties of protein-protein interactions and the small molecules that can modulate them. We then describe the use of sensitive biophysical methods - nuclear magnetic resonance, X-ray crystallography, surface plasmon resonance, differential scanning fluorimetry or isothermal calorimetry - to screen and validate fragment binding. Fragment hits can subsequently be evolved into larger molecules with higher affinity and potency. These may provide new leads for drug candidates
Apelin is a recently isolated peptide that appears to act as an endogenous ligand for the previously orphaned G-protein-coupled receptor APJ. A number of studies have reported cardiovascular actions of apelin, including changes in the blood pressure and potent inotropic actions. Furthermore, perturbations of both apelin and APJ within the myocardial tissue and circulating levels of the peptide have been reported in a number of cardiovascular disease states. Taken together, these studies suggest a role for apelin in the pressure/volume homeostasis and in the pathophysiology of cardiovascular diseases. However, findings in the literature to date are, at times, disparate. This review highlights key areas where further work is required to clarify the role of apelin/APJ in both normal physiology and pathophysiology. Nonetheless, preliminary evidence suggests that the manipulation of this receptor/ligand peptide system may be a target for drug development, thereby offering a therapeutic benefit in cardiovascular diseases.
Olson, Keith M.; Lei, Wei; Keresztes, Attila; LaVigne, Justin; Streicher, John M.
Opioid drugs like morphine and fentanyl are the gold standard for treating moderate to severe acute and chronic pain. However, opioid drug use can be limited by serious side effects, including constipation, tolerance, respiratory suppression, and addiction. For more than 100 years, we have tried to develop opioids that decrease or eliminate these liabilities, with little success. Recent advances in understanding opioid receptor signal transduction have suggested new possibilities to activate the opioid receptors to cause analgesia, while reducing or eliminating unwanted side effects. These new approaches include designing functionally selective ligands, which activate desired signaling cascades while avoiding signaling cascades that are thought to provoke side effects. It may also be possible to directly modulate downstream signaling through the use of selective activators and inhibitors. Separate from downstream signal transduction, it has also been found that when the opioid system is stimulated, various negative feedback systems are upregulated to compensate, which can drive side effects. This has led to the development of multi-functional molecules that simultaneously activate the opioid receptor while blocking various negative feedback receptor systems including cholecystokinin and neurokinin-1. Other novel approaches include targeting heterodimers of the opioid and other receptor systems which may drive side effects, and making endogenous opioid peptides druggable, which may also reduce opioid mediated side effects. Taken together, these advances in our molecular understanding provide a path forward to break the barrier in producing an opioid with reduced or eliminated side effects, especially addiction, which may provide relief for millions of patients. PMID:28356897
Dlamini, Zodwa; Hull, Rodney
HIV-1 is able to express multiple protein types and isoforms from a single 9 kb mRNA transcript. These proteins are also expressed at particular stages of viral development, and this is achieved through the control of alternative splicing and the export of these transcripts from the nucleus. The nuclear export is controlled by the HIV protein Rev being required to transport incompletely spliced and partially spliced mRNA from the nucleus where they are normally retained. This implies a close relationship between the control of alternate splicing and the nuclear export of mRNA in the control of HIV-1 viral proliferation. This review discusses both the processes. The specificity and regulation of splicing in HIV-1 is controlled by the use of specific splice sites as well as exonic splicing enhancer and exonic splicing silencer sequences. The use of these silencer and enhancer sequences is dependent on the serine arginine family of proteins as well as the heterogeneous nuclear ribonucleoprotein family of proteins that bind to these sequences and increase or decrease splicing. Since alternative splicing is such a critical factor in viral development, it presents itself as a promising drug target. This review aims to discuss the inhibition of splicing, which would stall viral development, as an anti-HIV therapeutic strategy. In this review, the most recent knowledge of splicing in human immunodeficiency viral development and the latest therapeutic strategies targeting human immunodeficiency viral splicing are discussed.
Dlamini, Zodwa; Hull, Rodney
HIV-1 is able to express multiple protein types and isoforms from a single 9 kb mRNA transcript. These proteins are also expressed at particular stages of viral development, and this is achieved through the control of alternative splicing and the export of these transcripts from the nucleus. The nuclear export is controlled by the HIV protein Rev being required to transport incompletely spliced and partially spliced mRNA from the nucleus where they are normally retained. This implies a close relationship between the control of alternate splicing and the nuclear export of mRNA in the control of HIV-1 viral proliferation. This review discusses both the processes. The specificity and regulation of splicing in HIV-1 is controlled by the use of specific splice sites as well as exonic splicing enhancer and exonic splicing silencer sequences. The use of these silencer and enhancer sequences is dependent on the serine arginine family of proteins as well as the heterogeneous nuclear ribonucleoprotein family of proteins that bind to these sequences and increase or decrease splicing. Since alternative splicing is such a critical factor in viral development, it presents itself as a promising drug target. This review aims to discuss the inhibition of splicing, which would stall viral development, as an anti-HIV therapeutic strategy. In this review, the most recent knowledge of splicing in human immunodeficiency viral development and the latest therapeutic strategies targeting human immunodeficiency viral splicing are discussed. PMID:28331370
Randhawa, Vinay; Bagler, Ganesh
Network-biology inspired modeling of interactome data and computational chemistry have the potential to revolutionize drug discovery by complementing conventional methods. We consider asthma, a complex disease characterized by intricate molecular mechanisms, for our study. We aim to integrate prediction of potent drug targets using graph-theoretical methods and subsequent identification of small molecules capable of modulating activity of the best target. In this work, we construct the protein interactome underlying this disease: Asthma Protein Interactome (API). Using a strategy based on network analysis of the interactome, we identify a set of potential drug targets for asthma. Topologically and dynamically, v-src sarcoma (Schmidt-Ruppin A-2) viral oncogene homolog (SRC) emerges as the most central target in API. SRC is known to play an important role in promoting airway smooth muscle cell growth and facilitating migration in airway remodeling. From interactome analysis, and with the reported role in respiratory mechanisms, SRC emerges as a promising drug target for asthma. Further, we proceed to identify leads for SRC from a public database of small molecules. We predict two potential leads for SRC using ligand-based virtual screening methodology.
Guo, Jing; Liu, Hui; Zheng, Jie
Synthetic lethality (SL) is a type of genetic interaction between two genes such that simultaneous perturbations of the two genes result in cell death or a dramatic decrease of cell viability, while a perturbation of either gene alone is not lethal. SL reflects the biologically endogenous difference between cancer cells and normal cells, and thus the inhibition of SL partners of genes with cancer-specific mutations could selectively kill cancer cells but spare normal cells. Therefore, SL is emerging as a promising anticancer strategy that could potentially overcome the drawbacks of traditional chemotherapies by reducing severe side effects. Researchers have developed experimental technologies and computational prediction methods to identify SL gene pairs on human and a few model species. However, there has not been a comprehensive database dedicated to collecting SL pairs and related knowledge. In this paper, we propose a comprehensive database, SynLethDB (http://histone.sce.ntu.edu.sg/SynLethDB/), which contains SL pairs collected from biochemical assays, other related databases, computational predictions and text mining results on human and four model species, i.e. mouse, fruit fly, worm and yeast. For each SL pair, a confidence score was calculated by integrating individual scores derived from different evidence sources. We also developed a statistical analysis module to estimate the druggability and sensitivity of cancer cells upon drug treatments targeting human SL partners, based on large-scale genomic data, gene expression profiles and drug sensitivity profiles on more than 1000 cancer cell lines. To help users access and mine the wealth of the data, we developed other practical functionalities, such as search and filtering, orthology search, gene set enrichment analysis. Furthermore, a user-friendly web interface has been implemented to facilitate data analysis and interpretation. With the integrated data sets and analytics functionalities, SynLethDB would
Parsons, Joshua B; Rock, Charles O
The emergence of resistance against most current drugs emphasizes the need to develop new approaches to control bacterial pathogens, particularly Staphylococcus aureus. Bacterial fatty acid synthesis is one such target that is being actively pursued by several research groups to develop anti-Staphylococcal agents. Recently, the wisdom of this approach has been challenged based on the ability of a Gram-positive bacterium to incorporate extracellular fatty acids and thus circumvent the inhibition of de novo fatty acid synthesis. The generality of this conclusion has been challenged, and there is enough diversity in the enzymes and regulation of fatty acid synthesis in bacteria to conclude that there is not a single organism that can be considered typical and representative of bacteria as a whole. We are left without a clear resolution to this ongoing debate and await new basic research to define the pathways for fatty acid uptake and that determine the biochemical and genetic mechanisms for the regulation of fatty acid synthesis in Gram-positive bacteria. These crucial experiments will determine whether diversity in the control of this important pathway accounts for the apparently different responses of Gram-positive bacteria to the inhibition of de novo fatty acid synthesis in presence of extracellular fatty acid supplements.
Sliwoski, Gregory; Kothiwale, Sandeepkumar; Meiler, Jens
Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature. PMID:24381236
ABSTRACT Fungal diseases represent a major burden to health care globally. As with other pathogenic microbes, there is a limited number of agents suitable for use in treating fungal diseases, and resistance to these agents can develop rapidly. Cryptococcus neoformans is a basidiomycete fungus that causes cryptococcosis worldwide in both immunocompromised and healthy individuals. As a basidiomycete, it diverged from other common pathogenic or model ascomycete fungi more than 500 million years ago. Here, we report C. neoformans genes that are essential for viability as identified through forward and reverse genetic approaches, using an engineered diploid strain and genetic segregation after meiosis. The forward genetic approach generated random insertional mutants in the diploid strain, the induction of meiosis and sporulation, and selection for haploid cells with counterselection of the insertion event. More than 2,500 mutants were analyzed, and transfer DNA (T-DNA) insertions in several genes required for viability were identified. The genes include those encoding the thioredoxin reductase (Trr1), a ribosome assembly factor (Rsa4), an mRNA-capping component (Cet1), and others. For targeted gene replacement, the C. neoformans homologs of 35 genes required for viability in ascomycete fungi were disrupted, meiosis and sporulation were induced, and haploid progeny were evaluated for their ability to grow on selective media. Twenty-one (60%) were found to be required for viability in C. neoformans. These genes are involved in mitochondrial translation, ergosterol biosynthesis, and RNA-related functions. The heterozygous diploid mutants were evaluated for haploinsufficiency on a number of perturbing agents and drugs, revealing phenotypes due to the loss of one copy of an essential gene in C. neoformans. This study expands the knowledge of the essential genes in fungi using a basidiomycete as a model organism. Genes that have no mammalian homologs and are essential
Bulatov, Emil; Ciulli, Alessio
In the last decade, the ubiquitin–proteasome system has emerged as a valid target for the development of novel therapeutics. E3 ubiquitin ligases are particularly attractive targets because they confer substrate specificity on the ubiquitin system. CRLs [Cullin–RING (really interesting new gene) E3 ubiquitin ligases] draw particular attention, being the largest family of E3s. The CRLs assemble into functional multisubunit complexes using a repertoire of substrate receptors, adaptors, Cullin scaffolds and RING-box proteins. Drug discovery targeting CRLs is growing in importance due to mounting evidence pointing to significant roles of these enzymes in diverse biological processes and human diseases, including cancer, where CRLs and their substrates often function as tumour suppressors or oncogenes. In the present review, we provide an account of the assembly and structure of CRL complexes, and outline the current state of the field in terms of available knowledge of small-molecule inhibitors and modulators of CRL activity. A comprehensive overview of the reported crystal structures of CRL subunits, components and full-size complexes, alone or with bound small molecules and substrate peptides, is included. This information is providing increasing opportunities to aid the rational structure-based design of chemical probes and potential small-molecule therapeutics targeting CRLs. PMID:25886174
Al-Ali, Hassan; Lemmon, Vance P; Bixby, John L
The inability of central nervous system (CNS) neurons to regenerate damaged axons and dendrites following traumatic brain injury (TBI) creates a substantial obstacle for functional recovery. Apoptotic cell death, deposition of scar tissue, and growth-repressive molecules produced by glia further complicate the problem and make it challenging for re-growing axons to extend across injury sites. To date, there are no approved drugs for the treatment of TBI, accentuating the need for relevant leads. Cell-based and organotypic bioassays can better mimic outcomes within the native CNS microenvironment than target-based screening methods and thus should speed the discovery of therapeutic agents that induce axon or dendrite regeneration. Additionally, when used to screen focused chemical libraries such as small-molecule protein kinase inhibitors, these assays can help elucidate molecular mechanisms involved in neurite outgrowth and regeneration as well as identify novel drug targets. Here, we describe a phenotypic cellular (high content) screening assay that utilizes brain-derived primary neurons for screening small-molecule chemical libraries.
block the HC channel. memantine NH2 amantadine H2N quinacrine NH O N lidocaine NH O N QX-222 S N Cl chlorpromazine N NCl O HN N Our objective was to...which include drugs currently used in humans (Fig. 1)1: amantadine , an anti-influenza drug that blocks the channels formed by the influenza virus
The popularization of genomic high-throughput technologies is causing a revolution in biomedical research and, particularly, is transforming the field of drug discovery. Systems biology offers a framework to understand the extensive human genetic heterogeneity revealed by genomic sequencing in the context of the network of functional, regulatory and physical protein-drug interactions. Thus, approaches to find biomarkers and therapeutic targets will have to take into account the complex system nature of the relationships of the proteins with the disease. Pharmaceutical companies will have to reorient their drug discovery strategies considering the human genetic heterogeneity. Consequently, modeling and computational data analysis will have an increasingly important role in drug discovery.
Zheng, Wei; Thorne, Natasha; McKew, John C.
The significant reduction in the number of newly approved drugs in past decade has been partially attributed to failures in discovery and validation of new targets. Evaluation of recently approved new drugs has revealed that the number of approved drugs discovered through phenotypic screens, an original drug screening paradigm, has exceeded those discovered through the molecular target-based approach. Phenotypic screening is thus gaining new momentum in drug discovery with the hope that this approach may revitalize drug discovery and improve the success rate of drug approval through the discovery of viable lead compounds and identification of novel drug targets. PMID:23850704
Curtin, Joshua C; Lorenzi, Matthew V
Cancer stem cells (CSCs) represent a unique subset of cells within a tumor that possess self-renewal capacity and pluripotency, and can drive tumor initiation and maintenance. First identified in hematological malignancies, CSCs are now thought to play an important role in a wide variety of solid tumors such as NSCLC, breast and colorectal cancer. The role of CSCs in driving tumor formation illustrates the dysregulation of differentiation in tumorigenesis. The Wnt, Notch and Hedgehog (HH) pathways are developmental pathways that are commonly activated in many types of cancer. While substantial progress has been made in developing therapeutics targeting Notch and HH, the Wnt pathway has remained an elusive therapeutic target. This review will focus on the clinical relevance of the Wnt pathway in CSCs and tumor cell biology, as well as points of therapeutic intervention and recent advances in targeting Wnt/β-catenin signaling.
Lv, Jing; Wang, Jieqiong; Chang, Siyu; Liu, Mingyao; Pang, Xiufeng
RAS oncogene mutations are frequently detected in human cancers. Among RAS-mediated tumorigenesis, KRAS-driven cancers are the most frequently diagnosed and resistant to current therapies. Despite more than three decades of intensive efforts, there are still no specific therapies for mutant RAS proteins. While trying to block those well-established downstream pathways, such as the RAF-MAPK pathway and the PI3K-AKT pathway, attentions have been paid to potential effects of RAS on metabolic pathways and the feasibility for targeting these pathways. Recent studies have proved that RAS not only promotes aerobic glycolysis and glutamine metabolism reprograming to provide energy, but it also facilitates branched metabolism pathways, autophagy, and macropinocytosis. These alterations generate building blocks for tumor growth and strengthen antioxidant defense in tumor cells. All of these metabolic changes meet different demands of RAS-driven cancers, making them distinct from normal cells. Indeed, some achievements have been made to inhibit tumor growth through targeting specific metabolism rewiring in preclinical models. Although there is still a long way to elucidate the landscape of altered metabolism, we believe that specific metabolic enzymes or pathways could be therapeutically targeted for selective inhibition of RAS-driven cancers.
Shrestha, Liza; Bolaender, Alexander; Patel, Hardik J.; Taldone, Tony
Heat shock proteins (HSPs) present as a double edged sword. While they play an important role in maintaining protein homeostasis in a normal cell, cancer cells have evolved to co-opt HSP function to promote their own survival. As a result, HSPs such as HSP90 have attracted a great deal of interest as a potential anticancer target. These efforts have resulted in over 20 distinct compounds entering clinical evaluation for the treatment of cancer. However, despite the potent anticancer activity demonstrated in preclinical models, to date no HSP90 inhibitor has obtained regulatory approval. In this review we discuss the unique challenges faced in targeting HSPs that have likely contributed to their lack of progress in the clinic and suggest ways to overcome these so that the enormous potential of these compounds to benefit patients can finally be realized. We also provide a guideline for the future development of HSP-targeted agents based on the many lessons learned during the last two decades in developing HSP90 inhibitors. PMID:27072696
The RAS Drug Discovery group aims to develop assays that will reveal aspects of RAS biology upon which cancer cells depend. Successful assay formats are made available for high-throughput screening programs to yield potentially effective drug compounds.
Aug 01) 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS Discovery of New Drugs that Target Peroxisomal DAMD17-00-1-0686 Proliferator-Activated Receptor...of breast tumor cells and can be used to develop new drugs to treat breast cancer. The specific aims of this proposal are: 1. Evaluate in vitro...Ft. Detrick, MD 21702-5012. AUTHORITY USAMRMC ltr, 28 Aug 2002 THIS PAGE IS UNCLASSIFIED AD Award Number: DAMD17-00-1-0686 TITLE: Discovery of New
Tiefenbrunn, Theresa; Forli, Stefano; Happer, Meaghan; Gonzalez, Ana; Tsai, Yingssu; Soltis, Michael; Elder, John H; Olson, Arthur J; Stout, Charles D
A library of 68 brominated fragments was screened against a new crystal form of inhibited HIV-1 protease in order to probe surface sites in soaking experiments. Often, fragments are weak binders with partial occupancy, resulting in weak, difficult-to-fit electron density. The use of a brominated fragment library addresses this challenge, as bromine can be located unequivocally via anomalous scattering. Data collection was carried out in an automated fashion using AutoDrug at SSRL. Novel hits were identified in the known surface sites: 3-bromo-2,6-dimethoxybenzoic acid (Br6) in the flap site and 1-bromo-2-naphthoic acid (Br27) in the exosite, expanding the chemistry of known fragments for development of higher affinity potential allosteric inhibitors. At the same time, mapping the binding sites of a number of weaker binding Br-fragments provides further insight into the nature of these surface pockets.
Tiefenbrunn, Theresa; Forli, Stefano; Happer, Meaghan; Gonzalez, Ana; Tsai, Yingssu; Soltis, Michael; Elder, John H.; Olson, Arthur J.; Stout, C. David
A library of 68 brominated fragments was screened against a new crystal form of inhibited HIV-1 protease in order to probe surface sites in soaking experiments. Often fragments are weak binders with partial occupancy, resulting in weak, difficult-to-fit electron density. The use of a brominated fragment library addresses this challenge, as bromine can be located unequivocally via anomalous scattering. Data collection was carried out in an automated fashion using AutoDrug at SSRL. Novel hits were identified in the known surface sites: 3-bromo-2,6-dimethoxybenzoic acid (Br6) in the flap site, and 1-bromo-2-naphthoic acid (Br27) in the exosite, expanding the chemistry of known fragments for development of higher affinity potential allosteric inhibitors. At the same time, mapping the binding sites of a number of weaker binding Br-fragments provides further insight into the nature of these surface pockets. PMID:23998903
YAN, KUO; GAO, LI-NA; CUI, YUAN-LU; ZHANG, YI; ZHOU, XIN
During development of disease, complex intracellular signaling pathways regulate an intricate series of events, including resistance to external toxins, the secretion of cytokines and the production of pathological phenomena. Adenosine 3′,5′-cyclic monophosphate (cAMP) is a nucleotide that acts as a key second messenger in numerous signal transduction pathways. cAMP regulates various cellular functions, including cell growth and differentiation, gene transcription and protein expression. This review aimed to provide an understanding of the effects of the cAMP signaling pathway and the associated factors on disease occurrence and development by examining the information from a new perspective. These novel insights aimed to promote the development of novel therapeutic approaches and aid in the development of new drugs. PMID:27035868
Moorthy, N S Hari Narayana; Poongavanam, Vasanthanathan; Pratheepa, V
Influenza virus is an important RNA virus causing pandemics (Spanish Flu (1918), Asian Flu (1957), Hong Kong Flu (1968) and Swine Flu (2009)) over the last decades. Due to the spontaneous mutations of these viral proteins, currently available antiviral and anti-influenza drugs quickly develop resistance. To account this, only limited antiinfluenza drugs have been approved for the therapeutic use. These include amantadine and rimantadine (M2 proton channel blockers), zanamivir, oseltamivir and peramivir (neuraminidase inhibitors), favipravir (polymerase inhibitor) and laninamivir. This review provides an outline on the strategies to develop novel, potent chemotherapeutic agents against M2 proton channel. Primarily, the M2 proton channel blockers elicit pharmacological activity through destabilizing the helices by blocking the proton transport across the transmembrane. The biologically important compounds discovered using the scaffolds such as bisnoradmantane, noradamantane, triazine, spiroadamantane, isoxazole, amino alcohol, azaspiro, spirene, pinanamine, etc are reported to exhibit anti-influenza activity against wild or mutant type (S31N and V27A) of M2 proton channel protein. The reported studies explained that the adamantane based compounds (amantadine and rimantadine) strongly interact with His37 (through hydrogen bonding) and Ala30, Ile33 and Gly34 residues (hydrophobic interactions). The adamantane and the non-adamantane scaffolds fit perfectly in the active site pocket present in the wild type and the charged amino groups (ammonium) create positive electrostatic potential, which blocks the transport of protons across the pore. In the mutated proteins, larger or smaller binding pocket are created by small or large mutant residues, which do not allow the molecules fit in the active site. This causes the channel to be unblocked and the protons are allowed to transfer inside the pore. The structural analysis of the M2 proton channel blockers illustrated that
Srinivas, Nuggehally R; Mullangi, Ramesh
Bioanalysis is an important aspect of drug discovery process regardless of the chosen therapeutic area. There is a general misconception that bioanalysis is seldom important during the drug discovery process because there is no scrutiny of the data from a regulatory perspective. However, bioanalytical data gathered during the discovery stage enable several key decision(s) inclusive of termination of the program and/or creating adequate differentiation from the lead competitive molecules. The review covers various stage gate screens and experimental designs where bioanalytical data are extensively used for making an informed decision during the process of drug discovery.
Galan, M Carmen; Benito-Alifonso, David; Watt, Gregory M
The multitude of roles that carbohydrates and their glyco-conjugates play in biological processes has stimulated great interest in determining the nature of their interactions in both normal and diseased states. Manipulating such interactions will provide leads for drug discovery. Of the major classes of biomolecule, carbohydrates are the most structurally diverse. This hetereogeneity makes isolation of pure samples, and in sufficient amounts, from biological sources extremely difficult. Chemical synthesis offers the advantage of producing pure and structurally defined oligosaccharides for biological investigations. Although the complex nature of carbohydrates means that this is challenging, recent advances in the field have facilitated access to these molecules. The synthesis and isolation of oligosaccharides combined with progress in glycoarray technology have aided the identification of new carbohydrate-binding drug targets. This review aims to provide an overview of the latest advancements in carbohydrate chemistry and the role of these complex molecules in drug discovery, focusing particularly on synthetic methodologies, glycosaminoglycans, glycoprotein synthesis and vaccine development over the last few years.
Guido, Rafael V C; Oliva, Glaucius; Andricopulo, Adriano D
The identification of promising hits and the generation of high quality leads are crucial steps in the early stages of drug discovery projects. The definition and assessment of both chemical and biological space have revitalized the screening process model and emphasized the importance of exploring the intrinsic complementary nature of classical and modern methods in drug research. In this context, the widespread use of combinatorial chemistry and sophisticated screening methods for the discovery of lead compounds has created a large demand for small organic molecules that act on specific drug targets. Modern drug discovery involves the employment of a wide variety of technologies and expertise in multidisciplinary research teams. The synergistic effects between experimental and computational approaches on the selection and optimization of bioactive compounds emphasize the importance of the integration of advanced technologies in drug discovery programs. These technologies (VS, HTS, SBDD, LBDD, QSAR, and so on) are complementary in the sense that they have mutual goals, thereby the combination of both empirical and in silico efforts is feasible at many different levels of lead optimization and new chemical entity (NCE) discovery. This paper provides a brief perspective on the evolution and use of key drug design technologies, highlighting opportunities and challenges.
Chen, Haijun; Wu, Jianlei; Gao, Yu; Chen, Haiying; Zhou, Jia
As commented by the Nobelist James Black that "The most fruitful basis of the discovery of a new drug is to start with an old drug", drug repurposing represents an attractive drug discovery strategy. Despite the success of several repurposed drugs on the market, the ultimate therapeutic potential of a large number of non-cancer drugs is hindered during their repositioning due to various issues including the limited efficacy and intellectual property. With the increasing knowledge about the pharmacological properties and newly identified targets, the scaffolds of the old drugs emerge as a great treasure-trove towards new cancer drug discovery. In this review, we summarize the recent advances in the development of novel small molecules for cancer therapy by scaffold repurposing with highlighted examples. The relevant strategies, advantages, challenges and future research directions associated with this approach are also discussed.
Slusher, Barbara S.; Conn, P. Jeffrey; Frye, Stephen; Glicksman, Marcie; Arkin, Michelle
The newly formed Academic Drug Discovery Consortium (ADDC) aims to support the growing numbers of university centres engaged in drug discovery that have emerged in response to recent changes in the drug discovery ecosystem. PMID:24172316
Gawehn, Erik; Hiss, Jan A; Schneider, Gisbert
Artificial neural networks had their first heyday in molecular informatics and drug discovery approximately two decades ago. Currently, we are witnessing renewed interest in adapting advanced neural network architectures for pharmaceutical research by borrowing from the field of "deep learning". Compared with some of the other life sciences, their application in drug discovery is still limited. Here, we provide an overview of this emerging field of molecular informatics, present the basic concepts of prominent deep learning methods and offer motivation to explore these techniques for their usefulness in computer-assisted drug discovery and design. We specifically emphasize deep neural networks, restricted Boltzmann machine networks and convolutional networks.
Mehraei, Mani; Bashirov, Rza; Tüzmen, Şükrü
Recent molecular studies provide important clues into treatment of [Formula: see text]-thalassemia, sickle-cell anaemia and other [Formula: see text]-globin disorders revealing that increased production of fetal hemoglobin, that is normally suppressed in adulthood, can ameliorate the severity of these diseases. In this paper, we present a novel approach for drug prediction for [Formula: see text]-globin disorders. Our approach is centered upon quantitative modeling of interactions in human fetal-to-adult hemoglobin switch network using hybrid functional Petri nets. In accordance with the reverse pharmacology approach, we pose a hypothesis regarding modulation of specific protein targets that induce [Formula: see text]-globin and consequently fetal hemoglobin. Comparison of simulation results for the proposed strategy with the ones obtained for already existing drugs shows that our strategy is the optimal as it leads to highest level of [Formula: see text]-globin induction and thereby has potential beneficial therapeutic effects on [Formula: see text]-globin disorders. Simulation results enable verification of model coherence demonstrating that it is consistent with qPCR data available for known strategies and/or drugs.
Calderone, Richard; Sun, Nuo; Gay-Andrieu, Francoise; Groutas, William; Weerawarna, Pathum; Prasad, Sridhar; Alex, Deepu; Li, Dongmei
New data suggest that the global incidence of several types of fungal diseases have traditionally been under-documented. Of these, mortality caused by invasive fungal infections remains disturbingly high, equal to or exceeding deaths caused by drug-resistant tuberculosis and malaria. It is clear that basic research on new antifungal drugs, vaccines and diagnostic tools is needed. In this review, we focus upon antifungal drug discovery including in vitro assays, compound libraries and approaches to target identification. Genome mining has made it possible to identify fungal-specific targets; however, new compounds to these targets are apparently not in the antimicrobial pipeline. We suggest that ‘repurposing’ compounds (off patent) might be a more immediate starting point. Furthermore, we examine the dogma on antifungal discovery and suggest that a major thrust in technologies such as structural biology, homology modeling and virtual imaging is needed to drive discovery. PMID:25046525
Hu, Wenhui; Ralay Ranaivo, Hantamalala; Craft, Jeffrey M; Van Eldik, Linda J; Watterson, D Martin
The neuroinflammation cycle has been proposed as a potential therapeutic target in the development of new approaches to altering Alzheimer's disease (AD) progression. However, the efficacy and toxicological profile of compounds that focus only on classical NSAID targets have been disappointing to date. Therefore, we recently initiated an unbiased, integrative chemical biology approach that used a hierarchal set of cell-based screens, followed by efficacy analysis in a new AD-relevant animal model that more closely resembles human pathology endpoints in terms of neuroinflammation and neuronal loss. The prior investigations provided a proof of concept that targeting the neuroinflammation cycle may be a viable drug discovery approach for AD. However, recent informatics analyses of the high attrition rate in drug development have identified the need for starting drug development with lead compounds that are well below cut off values in computed molecular properties in order to facilitate late stage medicinal chemistry refinement to improve in vivo functions. We describe here how we are leveraging our novel, unbiased, integrative chemical biology approach for the rapid discovery of potential lead compounds for AD drug discovery. Specifically, we show that orally bioavailable compounds with the desired physical properties and in vivo functions can be identified in focused synthetic libraries composed of chemical diversifications of the inactive but privileged pyridazine molecular fragment.
Peltier, John M.; Askovic, Srdjan; Becklin, Robert R.; Chepanoske, Cindy Lou; Ho, Yew-Seng J.; Kery, Vladimir; Lai, Shuping; Mujtaba, Tahmina; Pyne, Mike; Robbins, Paul B.; Rechenberg, Moritz Von; Richardson, Bonnie; Savage, Justin; Sheffield, Peter; Thompson, Sam; Weir, Lawrence; Widjaja, Kartika; Xu, Nafei; Zhen, Yuejun; Boniface, J. Jay
Proteomics-based technologies have the potential to accelerate the development of drugs, but such technologies must be well integrated in order to have a positive impact. We describe, herein, a multi-step process for the discovery of protein-protein interactions. It is shown that process stages are interdependent and can influence, either positively or negatively, subsequent steps. Optimization of each step, in the context of the full process, is essential for the overall success of the experiment.
Durieu, Emilie; Prina, Eric; Leclercq, Olivier; Oumata, Nassima; Gaboriaud-Kolar, Nicolas; Vougogiannopoulou, Konstantina; Aulner, Nathalie; Defontaine, Audrey; No, Joo Hwan; Ruchaud, Sandrine; Skaltsounis, Alexios-Leandros; Galons, Hervé; Späth, Gerald F.; Meijer, Laurent
Existing therapies for leishmaniases present significant limitations, such as toxic side effects, and are rendered inefficient by parasite resistance. It is of utmost importance to develop novel drugs targeting Leishmania that take these two limitations into consideration. We thus chose a target-based approach using an exoprotein kinase, Leishmania casein kinase 1.2 (LmCK1.2) that was recently shown to be essential for intracellular parasite survival and infectivity. We developed a four-step pipeline to identify novel selective antileishmanial compounds. In step 1, we screened 5,018 compounds from kinase-biased libraries with Leishmania and mammalian CK1 in order to identify hit compounds and assess their specificity. For step 2, we selected 88 compounds among those with the lowest 50% inhibitory concentration to test their biological activity on host-free parasites using a resazurin reduction assay and on intramacrophagic amastigotes using a high content phenotypic assay. Only 75 compounds showed antileishmanial activity and were retained for step 3 to evaluate their toxicity against mouse macrophages and human cell lines. The four compounds that displayed a selectivity index above 10 were then assessed for their affinity to LmCK1.2 using a target deconvolution strategy in step 4. Finally, we retained two compounds, PP2 and compound 42, for which LmCK1.2 seems to be the primary target. Using this four-step pipeline, we identify from several thousand molecules, two lead compounds with a selective antileishmanial activity. PMID:26902771
A common view within the pharmaceutical industry is that there is a problem with drug discovery and we should do something about it. There is much sympathy for this from academics, regulators and politicians. In this article I propose that lessons learnt from evolution help identify those factors that favour successful drug discovery. This personal view is influenced by a decade spent reviewing drug development programmes submitted for European regulatory approval. During the prolonged gestation of a new medicine few candidate molecules survive. This process of elimination of many variants and the survival of so few has much in common with evolution, an analogy that encourages discussion of the forces that favour, and those that hinder, successful drug discovery. Imagining a world without vaccines, anaesthetics, contraception and anti-infectives reveals how medicines revolutionized humanity. How to manipulate conditions that favour such discoveries is worth consideration. PMID:21395642
Leelananda, Sumudu P
The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein–ligand docking, pharmacophore modeling and QSAR techniques are reviewed. PMID:28144341
Leelananda, Sumudu P; Lindert, Steffen
The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein-ligand docking, pharmacophore modeling and QSAR techniques are reviewed.
Costa, Ricardo; Shah, Ami N; Santa-Maria, Cesar A; Cruz, Marcelo R; Mahalingam, Devalingam; Carneiro, Benedito A; Chae, Young Kwang; Cristofanilli, Massimo; Gradishar, William J; Giles, Francis J
Triple negative breast cancer (TNBC) accounts for 10-20% of cases in breast cancer. Despite recent advances in the treatment of hormonal receptor+ and HER2+ breast cancers, there are no targeted therapies available for TNBC. Evidence supports that most patients with TNBC express the transmembrane Epidermal Growth Factor Receptor (EGFR). However, early phase clinical trials failed to demonstrate significant activity of EGFR-targeted monoclonal antibodies and/or tyrosine kinase inhibitors. Here, we review the recent discoveries related to the underlying biology of the EGFR pathway in TNBC, clinical progress to date and suggest rational future approaches for investigational therapies in TNBC.
Prasad, Sahdeo; Gupta, Subash C; Aggarwal, Bharat B
Novel drug development leading to final approval by the US FDA can cost as much as two billion dollars. Why the cost of novel drug discovery is so expensive is unclear, but high failure rates at the preclinical and clinical stages are major reasons. Although therapies targeting a given cell signaling pathway or a protein have become prominent in drug discovery, such treatments have done little in preventing or treating any disease alone because most chronic diseases have been found to be multigenic. A review of the discovery of numerous drugs currently being used for various diseases including cancer, diabetes, cardiovascular, pulmonary, and autoimmune diseases indicates that serendipity has played a major role in the discovery. In this review we provide evidence that rational drug discovery and targeted therapies have minimal roles in drug discovery, and that serendipity and coincidence have played and continue to play major roles. The primary focus in this review is on cancer-related drug discovery.
Brötz-Oesterhelt, Heike; Sass, Peter
During the last decade the field of antibacterial drug discovery has changed in many aspects including bacterial organisms of primary interest, discovery strategies applied and pharmaceutical companies involved. Target-based high-throughput screening had been disappointingly unsuccessful for antibiotic research. Understanding of this lack of success has increased substantially and the lessons learned refer to characteristics of targets, screening libraries and screening strategies. The 'genomics' approach was replaced by a diverse array of discovery strategies, for example, searching for new natural product leads among previously abandoned compounds or new microbial sources, screening for synthetic inhibitors by targeted approaches including structure-based design and analyses of focused libraries and designing resistance-breaking properties into antibiotics of established classes. Furthermore, alternative treatment options are being pursued including anti-virulence strategies and immunotherapeutic approaches. This article summarizes the lessons learned from the genomics era and describes discovery strategies resulting from that knowledge.
Zhou, Wei; Wang, Yonghua; Lu, Aiping; Zhang, Ge
Drug discovery is a risky, costly and time-consuming process depending on multidisciplinary methods to create safe and effective medicines. Although considerable progress has been made by high-throughput screening methods in drug design, the cost of developing contemporary approved drugs did not match that in the past decade. The major reason is the late-stage clinical failures in Phases II and III because of the complicated interactions between drug-specific, human body and environmental aspects affecting the safety and efficacy of a drug. There is a growing hope that systems-level consideration may provide a new perspective to overcome such current difficulties of drug discovery and development. The systems pharmacology method emerged as a holistic approach and has attracted more and more attention recently. The applications of systems pharmacology not only provide the pharmacodynamic evaluation and target identification of drug molecules, but also give a systems-level of understanding the interaction mechanism between drugs and complex disease. Therefore, the present review is an attempt to introduce how holistic systems pharmacology that integrated in silico ADME/T (i.e., absorption, distribution, metabolism, excretion and toxicity), target fishing and network pharmacology facilitates the discovery of small molecular drugs at the system level. PMID:26901192
Zhou, Wei; Wang, Yonghua; Lu, Aiping; Zhang, Ge
Drug discovery is a risky, costly and time-consuming process depending on multidisciplinary methods to create safe and effective medicines. Although considerable progress has been made by high-throughput screening methods in drug design, the cost of developing contemporary approved drugs did not match that in the past decade. The major reason is the late-stage clinical failures in Phases II and III because of the complicated interactions between drug-specific, human body and environmental aspects affecting the safety and efficacy of a drug. There is a growing hope that systems-level consideration may provide a new perspective to overcome such current difficulties of drug discovery and development. The systems pharmacology method emerged as a holistic approach and has attracted more and more attention recently. The applications of systems pharmacology not only provide the pharmacodynamic evaluation and target identification of drug molecules, but also give a systems-level of understanding the interaction mechanism between drugs and complex disease. Therefore, the present review is an attempt to introduce how holistic systems pharmacology that integrated in silico ADME/T (i.e., absorption, distribution, metabolism, excretion and toxicity), target fishing and network pharmacology facilitates the discovery of small molecular drugs at the system level.
Wilkinson, Trevor C I; Gardener, Matthew J; Williams, Wendy A
Ion channels play critical roles in physiology and disease by modulation of cellular functions such as electrical excitability, secretion, cell migration, and gene transcription. Ion channels represent an important target class for drug discovery that has been largely addressed, to date, using small-molecule approaches. A significant opportunity exists to target these channels with antibodies and alternative formats of biologics. Antibodies display high specificity and affinity for their target antigen, and they have the potential to target ion channels very selectively. Nevertheless, isolating antibodies to this target class is challenging due to the difficulties in expression and purification of ion channels in a format suitable for antibody drug discovery in addition to the complexity of screening for function. In this article, we will review the current state of ion channel biologics discovery and the progress that has been made. We will also highlight the challenges in isolating functional antibodies to these targets and how these challenges may be addressed. Finally, we also illustrate successful approaches to isolating functional monoclonal antibodies targeting ion channels by way of a number of case studies drawn from recent publications.
Moroni, Elisabetta; Paladino, Antonella; Colombo, Giorgio
Proteins are not static objects. To carry out their functions in the cells and participate in biochemical interaction networks, proteins have to explore different conformational substates, which favor the adaptation to different partners and ultimately allow them to respond to changes in the environment. In this paper we discuss the implications of including the atomistic description of protein dynamics and flexibility in the context of drug discovery and design. The underlying idea is that a better understanding of the atomistic details of molecular recognition phenomena and conformational cross-talk between a ligand and a receptor can in fact translate in unexplored opportunities for the discovery of new drug like molecules. We will illustrate and discuss dynamics-based pharmacophores, the discovery of cryptic binding sites, the characterization and exploitation of allosteric regulation mechanisms and the definition of potential protein-protein interaction sites as potential sources of new bases for the rational design of small molecules endowed with specific biological functions. Overall, the inclusion of protein flexibility in the drug discovery process is starting to attract attention not only in the academic but also in the industrial community. This is supported by experimental tests that prove the actual feasibility of considering the explicit dynamics of drug-protein interactions at all relevant levels of resolution and the use of multiple receptor conformations in drug discovery, as affordable complements (if not an alternative) to classical High Throughput Screening (HTS) efforts based on static structures.
Scotti, Luciana; Scotti, Marcus Tullius
Secondary metabolites are plant products that occur usually in differentiated cells, generally not being necessary for the cells themselves, but likely useful for the plant as a whole. Neurodegeneration can be found in many different levels in the neurons, it always begins at the molecular level and progresses toward the systemic levels. Usually, alterations are observed such as decreasing cholinergic impulse, toxicity related to reactive oxygen species (ROS, inflammatory "amyloid plaque" related processes, catecholamine disequilibrium, etc. Computer aided drug design (CADD has become relevant in the drug discovery process; technological advances in the areas of molecular structure characterization, computational science, and molecular biology have contributed to the planning of new drugs against neurodegenerative diseases. This review discusses scientific CADD studies of the secondary metabolites. Flavonoids, alkaloids, and xanthone compounds have been studied by various researchers (as inhibitory ligands in molecular docking; mainly with three enzymes: acetylcholinesterase (AChE; EC 220.127.116.11, butyrylcholinesterase (BChE; EC 18.104.22.168, and monoamine oxidase (MAO; EC 22.214.171.124. In addition, we have applied ligand-based-virtual screening (using Random Forest, associated with structure-based- virtual screening (docking of a small dataset of 469 alkaloids of the Apocynaceae family from an in-house data bank to select structures with potential inhibitory activity against human AChE. This computer-aided drug design study selected certain alkaloids that might be useful in further studies for the treatment of neurological disorders such as Alzheimer's and Parkinson's disease.
Haseltine, W A
Genomics, the systematic study of all the genes of an organism, offers a new and much-needed source of systematic productivity for the pharmaceutical industry. The isolation of the majority of human genes in their most useful form is leading to the creation of new drugs based on human proteins, antibodies, peptides, and genes. Human Genome Sciences, Inc, was the first company to use the systematic, genomics approach to discovering drugs, and we have placed 4 of these in clinical trials. Two are described: repifermin (keratinocyte growth factor-2, KGF-2) for wound healing and treatment of mucositis caused by cancer therapy, and B lymphocyte stimulator (BLyS) for stimulation of the immune system. An anti-BLyS antibody drug is in advanced preclinical development for treatment of autoimmune diseases.
Khurdayan, V K; Bozzo, J; Prous, J R
New brief reports this month include: Strategies for Duchenne Muscular Dystrophy: Various approaches are being explored to abate the dystrophic process including cellular therapies (transplanting stem cells or myogenic precursors into muscles), molecular approaches (delivering a functional or correcting the mutant dystrophin gene), such as MyoDys, Biostrophin(R) and antisense technology, and pharmacotherapeutics, which include calcium channel blockers, calpain inhibitors, phosphodiesterase inhibitors and monoclonal antibodies; Immunotherapy for Multiple Myeloma: Increasing numbers of antibodies and immunoconjugates with anticancer drugs are entering clinical development; Acute respiratory distress syndrome is among the most frequent reasons for intensive care. Current medications include antibiotics, diuretics, drugs to counteract low blood pressure caused by shock, anxiolytics and antiinflammatories, while there are eight potential drugs in active development; Pulmonary Hypertension: Drugs intervening at four signaling pathways (endothelin, prostacyclin, nitric oxide and platelet-derived growth factor), which are implicated in pulmonary hypertension, include readily available bosentan, sildenafil citrate and sitaxsentan sodium and investigational aviptadil and TBC-3711, among others.
Khurdayan, V; Cullell-Young, M
New brief reports this month describe five timely topics: IDO inhibitors have demonstrated antitumor properties by increasing immune response to tumors and improving chemotherapy effectiveness. One of the current therapeutic efforts for Alzheimer's disease is directed towards blocking the gamma-secretase activity, thus reducing amyloid-beta production. Patients with premature ovarian failure (POF), at present mainly treated with hormone replacement therapy, are belated for novel treatment options. Selective ERbeta agonists are anticipated to emerge as therapeutics for the treatment of various diseases including inflammatory bowel syndrome, endometriosis, dementia and cognitive disorders. Phospholipase A2 inhibitors specific for enzyme isoforms are actively studied as potential antiallergic/antiasthmatic drugs, antiarthritic agents and therapeutics for atherosclerosis.
Mears, Emily Rose; Modabber, Farrokh; Don, Robert; Johnson, George E.
The current in vivo models for the utility and discovery of new potential anti-leishmanial drugs targeting Cutaneous Leishmaniasis (CL) differ vastly in their immunological responses to the disease and clinical presentation of symptoms. Animal models that show similarities to the human form of CL after infection with Leishmania should be more representative as to the effect of the parasite within a human. Thus, these models are used to evaluate the efficacy of new anti-leishmanial compounds before human clinical trials. Current animal models aim to investigate (i) host–parasite interactions, (ii) pathogenesis, (iii) biochemical changes/pathways, (iv) in vivo maintenance of parasites, and (v) clinical evaluation of drug candidates. This review focuses on the trends of infection observed between Leishmania parasites, the predictability of different strains, and the determination of parasite load. These factors were used to investigate the overall effectiveness of the current animal models. The main aim was to assess the efficacy and limitations of the various CL models and their potential for drug discovery and evaluation. In conclusion, we found that the following models are the most suitable for the assessment of anti-leishmanial drugs: L. major–C57BL/6 mice (or–vervet monkey, or–rhesus monkeys), L. tropica–CsS-16 mice, L. amazonensis–CBA mice, L. braziliensis–golden hamster (or–rhesus monkey). We also provide in-depth guidance for which models are not suitable for these investigations. PMID:26334763
There is currently a crisis in drug discovery for neuropsychiatric disorders, with a profound, yet unexpected drought in new drug development across the spectrum. In this commentary, the sources of this dilemma and potential avenues to redress the issue are explored. These include a critical review of diagnostic issues and of selection of participants for clinical trials, and the mechanisms for identifying new drugs and new drug targets. Historically, the vast majority of agents have been discovered serendipitously or have been modifications of existing agents. Serendipitous discoveries, based on astute clinical observation or data mining, remain a valid option, as is illustrated by the suggestion in the paper by Wahlqvist and colleagues that treatment with sulfonylurea and metformin reduces the risk of affective disorder. However, the identification of agents targeting disorder-related biomarkers is currently proving particularly fruitful. There is considerable hope for genetics as a purist, pathophysiologically valid pathway to drug discovery; however, it is unclear whether the science is ready to meet this promise. Fruitful paradigms will require a break from the orthodoxy, and creativity and risk may well be the fingerprints of success.See related article http://www.biomedcentral.com/1741-7015/10/150.
There is currently a crisis in drug discovery for neuropsychiatric disorders, with a profound, yet unexpected drought in new drug development across the spectrum. In this commentary, the sources of this dilemma and potential avenues to redress the issue are explored. These include a critical review of diagnostic issues and of selection of participants for clinical trials, and the mechanisms for identifying new drugs and new drug targets. Historically, the vast majority of agents have been discovered serendipitously or have been modifications of existing agents. Serendipitous discoveries, based on astute clinical observation or data mining, remain a valid option, as is illustrated by the suggestion in the paper by Wahlqvist and colleagues that treatment with sulfonylurea and metformin reduces the risk of affective disorder. However, the identification of agents targeting disorder-related biomarkers is currently proving particularly fruitful. There is considerable hope for genetics as a purist, pathophysiologically valid pathway to drug discovery; however, it is unclear whether the science is ready to meet this promise. Fruitful paradigms will require a break from the orthodoxy, and creativity and risk may well be the fingerprints of success. See related article http://www.biomedcentral.com/1741-7015/10/150 PMID:23194414
Edwards, Bruce S.; Sklar, Larry A.
Summary Modern flow cytometers can make optical measurements of 10 or more parameters per cell at tens-of-thousands of cells per second and over five orders of magnitude dynamic range. Although flow cytometry is used in most drug discovery stages, “sip-and-spit” sampling technology has restricted it to low sample throughput applications. The advent of HyperCyt sampling technology has recently made possible primary screening applications in which tens-of-thousands of compounds are analyzed per day. Target-multiplexing methodologies in combination with extended multi-parameter analyses enable profiling of lead candidates early in the discovery process, when the greatest numbers of candidates are available for evaluation. The ability to sample small volumes with negligible waste reduces reagent costs, compound usage and consumption of cells. Improved compound library formatting strategies can further extend primary screening opportunities when samples are scarce. Dozens of targets have been screened in 384- and 1536-well assay formats, predominantly in academic screening lab settings. In concert with commercial platform evolution and trending drug discovery strategies, HyperCyt-based systems are now finding their way into mainstream screening labs. Recent advances in flow-based imaging, mass spectrometry and parallel sample processing promise dramatically expanded single cell profiling capabilities to bolster systems level approaches to drug discovery. PMID:25805180
Gómez-Outes, Antonio; Suárez-Gea, Ma Luisa; Calvo-Rojas, Gonzalo; Lecumberri, Ramón; Rocha, Eduardo; Pozo-Hernández, Carmen; Terleira-Fernández, Ana Isabel; Vargas-Castrillón, Emilio
The history of the traditional anticoagulants is marked by both perseverance and serendipity. The anticoagulant effect of heparin was discovered by McLean in 1915, while he was searching for a procoagulant in dog liver. Link identified dicumarol from spoiled sweet clover hay in 1939 as the causal agent of the sweet clover disease, a hemorrhagic disorder in cattle. Hirudin extracts from the medicinal leech were first used for parenteral anticoagulation in the clinic in 1909, but their use was limited due to adverse effects and difficulties in achieving highly purified extracts. Heparins and coumarins (i.e.: warfarin, phenprocoumon, acenocoumarol) have been the mainstay of anticoagulant therapy for more than 60 years. Over the past decades, the drug discovery paradigm has shifted toward rational design following a target-based approach, in which specific proteins, or "targets", are chosen on current understandings of pathophysiology, small molecules that inhibit the target's activity may be identified by high-throughput screening and, in selected cases, these new molecules can be developed further as drugs. Despite the application of rational design, serendipity has still played a significant role in some of the new discoveries. This review will focus on the discovery of the main anticoagulant drugs in current clinical use, like unfractionated heparin, low-molecular-weight heparins, fondaparinux, coumarins (i.e.: warfarin, acenocoumarol, phenprocoumon), parenteral direct thrombin inhibitors (DTIs) (i.e.: argatroban, recombinant hirudins, bivalirudin), oral DTIs (i.e.: dabigatran) and oral direct factor Xa inhibitors (i.e.: rivaroxaban, apixaban).
Jacobson, Kenneth A.
G protein-coupled receptors (GPCRs) remain a major domain of pharmaceutical discovery. The discovery of GPCR lead compounds and their optimization are now structure-based, thanks to advances in X-ray crystallography, molecular modeling, protein engineering and biophysical techniques. In silico screening provides useful hit molecules. New pharmacological approaches to tuning the pleotropic action of GPCRs include: allosteric modulators, biased ligands, GPCR heterodimer-targeted compounds, manipulation of polypharmacology, receptor antibodies and tailoring of drug molecules to fit GPCR pharmacogenomics. Measurements of kinetics and drug efficacy are factors influencing clinical success. With the exception of inhibitors of GPCR kinases, targeting of intracellular GPCR signaling or receptor cycling for therapeutic purposes remains a futuristic concept. New assay approaches are more efficient and multidimensional: cell-based, label-free, fluorescence-based assays, and biosensors. Tailoring GPCR drugs to a patient’s genetic background is now being considered. Chemoinformatic tools can predict ADME-tox properties. New imaging technology visualizes drug action in vivo. Thus, there is reason to be optimistic that new technology for GPCR ligand discovery will help improve the current narrowing of the pharmaceutical pipeline. PMID:26265138
Hao, Haiping; Zheng, Xiao; Wang, Guangji
Natural medicines (NMs) are indispensable sources for the development of modern drugs. However, the targets for most natural compounds are unknown and the current pharmacokinetic evaluation systems developed for target-defined drugs may not be directly applicable to NM-based drug discovery, which is a major hindrance in bringing natural compounds to the clinic. Here, we propose the concept of 'reverse pharmacokinetics' and discuss how a 'reverse pharmacokinetics' perspective could help clarify key questions in modern drug discovery from NMs with validated clinical benefits, thereby strengthening the translational potential. Reverse pharmacokinetics can provide physiologically relevant clues to the target identification and mechanistic study of NMs, which may also innovate drug discovery for complex diseases. We anticipate that an evolving deep understanding of the novel mode of action of natural compounds with a reverse pharmacokinetic insight may improve discovery of both single ingredient and multiple-component modern drugs from NMs.
Hargrave-Thomas, Emily; Yu, Bo; Reynisson, Jóhannes
It was found that the discovery of 5.8% (84/1437) of all drugs on the market involved serendipity. Of these drugs, 31 (2.2%) were discovered following an incident in the laboratory and 53 (3.7%) were discovered in a clinical setting. In addition, 263 (18.3%) of the pharmaceuticals in clinical use today are chemical derivatives of the drugs discovered with the aid of serendipity. Therefore, in total, 24.1% (347/1437) of marketed drugs can be directly traced to serendipitous events confirming the importance of this elusive phenomenon. In the case of anticancer drugs, 35.2% (31/88) can be attributed to a serendipitous event, which is somewhat larger than for all drugs. The therapeutic field that has benefited the most from serendipity are central nervous system active drugs reflecting the difficulty in designing compounds to pass the blood-brain-barrier and the lack of laboratory-based assays for many of the diseases of the mind. PMID:22247822
Hargrave-Thomas, Emily; Yu, Bo; Reynisson, Jóhannes
It was found that the discovery of 5.8% (84/1437) of all drugs on the market involved serendipity. Of these drugs, 31 (2.2%) were discovered following an incident in the laboratory and 53 (3.7%) were discovered in a clinical setting. In addition, 263 (18.3%) of the pharmaceuticals in clinical use today are chemical derivatives of the drugs discovered with the aid of serendipity. Therefore, in total, 24.1% (347/1437) of marketed drugs can be directly traced to serendipitous events confirming the importance of this elusive phenomenon. In the case of anticancer drugs, 35.2% (31/88) can be attributed to a serendipitous event, which is somewhat larger than for all drugs. The therapeutic field that has benefited the most from serendipity are central nervous system active drugs reflecting the difficulty in designing compounds to pass the blood-brain-barrier and the lack of laboratory-based assays for many of the diseases of the mind.
Verkman, Alan S.; Galietta, Luis J. V.
Chloride channels represent a relatively under-explored target class for drug discovery as elucidation of their identity and physiological roles has lagged behind that of many other drug targets. Chloride channels are involved in a wide range of biological functions, including epithelial fluid secretion, cell-volume regulation, neuroexcitation, smooth-muscle contraction and acidification of intracellular organelles. Mutations in several chloride channels cause human diseases, including cystic fibrosis, macular degeneration, myotonia, kidney stones, renal salt wasting and hyperekplexia. Chloride-channel modulators have potential applications in the treatment of some of these disorders, as well as in secretory diarrhoeas, polycystic kidney disease, osteoporosis and hypertension. Modulators of GABAA (γ-aminobutyric acid A) receptor chloride channels are in clinical use and several small-molecule chloride-channel modulators are in preclinical development and clinical trials. Here, we discuss the broad opportunities that remain in chloride-channel-based drug discovery. PMID:19153558
Mancini, Francesca; De Simone, Angela; Andrisano, Vincenza
β-Secretase 1 (BACE1) is the enzyme involved in the abnormal production of the amyloidogenic peptide Aβ42, one of the major causes of histological hallmarks of Alzheimer's disease. Thus, BACE1 represents a key target protein in the development of new potential drugs for the non-symptomatic treatment of Alzheimer's disease. Since the discovery of BACE1 one decade ago, both in the pharmaceutical industry and in academia there has been an intense search for novel inhibitors to be developed as new effective drugs. There is a great deal of interest in the discovery of selective non-peptide BACE1 inhibitors with a new chemical skeleton, suited for central nervous system penetration and endowed with more appropriate pharmacokinetic properties. Therefore, the selection of appropriate methods for screening and characterization of BACE1 inhibitors is crucial. This review focuses on the description of the in vitro methods to test BACE1 activity and inhibition, with particular emphasis on fluorescence resonance energy transfer (FRET) methods, aiming at critically highlighting advantages and drawbacks. An overview of BACE1 inhibitors is given, underlying the variability of the FRET methods reported in the literature, and the structure evolution of inhibitors active in cellular cultures and in vivo, from peptide to small synthetic and natural structures.
Lisanti, Michael P; Martinez-Outschoorn, Ubaldo E; Sotgia, Federica
Metabolic coupling, between mitochondria in cancer cells and catabolism in stromal fibroblasts, promotes tumor growth, recurrence, metastasis, and predicts anticancer drug resistance. Catabolic fibroblasts donate the necessary fuels (such as L-lactate, ketones, glutamine, other amino acids, and fatty acids) to anabolic cancer cells, to metabolize via their TCA cycle and oxidative phosphorylation (OXPHOS). This provides a simple mechanism by which metabolic energy and biomass are transferred from the host microenvironment to cancer cells. Recently, we showed that catabolic metabolism and "glycolytic reprogramming" in the tumor microenvironment are orchestrated by oncogene activation and inflammation, which originates in epithelial cancer cells. Oncogenes drive the onset of the cancer-associated fibroblast phenotype in adjacent normal fibroblasts via paracrine oxidative stress. This oncogene-induced transition to malignancy is "mirrored" by a loss of caveolin-1 (Cav-1) and an increase in MCT4 in adjacent stromal fibroblasts, functionally reflecting catabolic metabolism in the tumor microenvironment. Virtually identical findings were obtained using BRCA1-deficient breast and ovarian cancer cells. Thus, oncogene activation (RAS, NFkB, TGF-β) and/or tumor suppressor loss (BRCA1) have similar functional effects on adjacent stromal fibroblasts, initiating "metabolic symbiosis" and the cancer-associated fibroblast phenotype. New therapeutic strategies that metabolically uncouple oxidative cancer cells from their glycolytic stroma or modulate oxidative stress could be used to target this lethal subtype of cancers. Targeting "fibroblast addiction" in primary and metastatic tumor cells may expose a critical Achilles' heel, leading to disease regression in both sporadic and familial cancers.
Hua, Yun Hao; Wu, Chih Yuan; Sargsyan, Karen; Lim, Carmay
Many enzymes use nicotinamide adenine dinucleotide or nicotinamide adenine dinucleotide phosphate (NAD(P)) as essential coenzymes. These enzymes often do not share significant sequence identity and cannot be easily detected by sequence homology. Previously, we determined all distinct locally conserved pyrophosphate-binding structures (3d motifs) from NAD(P)-bound protein structures, from which 1d sequence motifs were derived. Here, we aim to establish the precision of these 3d and 1d motifs to annotate NAD(P)-binding proteins. We show that the pyrophosphate-binding 3d motifs are characteristic of NAD(P)-binding proteins, as they are rarely found in nonNAD(P)-binding proteins. Furthermore, several 1d motifs could distinguish between proteins that bind only NAD and those that bind only NADP. They could also distinguish between NAD(P)-binding proteins from nonNAD(P)-binding ones. Interestingly, one of the pyrophosphate-binding 3d and corresponding 1d motifs was found only in enoyl-acyl carrier protein reductases, which are enzymes essential for bacterial fatty acid biosynthesis. This unique 3d motif serves as an attractive novel drug target, as it is conserved across many bacterial species and is not found in human proteins.
Chien, Andrew; Foster, Ian; Goddette, Dean
Grid technologies enable flexible coupling and sharing of computers, instruments and storage. Grids can provide technical solutions to the volume of data and computational demands associated with drug discovery by delivering larger computing capability (flexible resource sharing), providing coordinated access to large data resources and enabling novel online exploration (coupling computing, data and instruments online). Here, we illustrate this potential by describing two applications: the use of desktop PC grid technologies for virtual screening, and distributed X-ray structure reconstruction and online visualization.
Trosset, Jean-Yves; Carbonell, Pablo
Synthetic biology (SB) is an emerging discipline, which is slowly reorienting the field of drug discovery. For thousands of years, living organisms such as plants were the major source of human medicines. The difficulty in resynthesizing natural products, however, often turned pharmaceutical industries away from this rich source for human medicine. More recently, progress on transformation through genetic manipulation of biosynthetic units in microorganisms has opened the possibility of in-depth exploration of the large chemical space of natural products derivatives. Success of SB in drug synthesis culminated with the bioproduction of artemisinin by microorganisms, a tour de force in protein and metabolic engineering. Today, synthetic cells are not only used as biofactories but also used as cell-based screening platforms for both target-based and phenotypic-based approaches. Engineered genetic circuits in synthetic cells are also used to decipher disease mechanisms or drug mechanism of actions and to study cell-cell communication within bacteria consortia. This review presents latest developments of SB in the field of drug discovery, including some challenging issues such as drug resistance and drug toxicity.
Dudley, Joel T; Schadt, Eric; Sirota, Marina; Butte, Atul J; Ashley, Euan
Despite great strides in revealing and understanding the physiological and molecular bases of cardiovascular disease, efforts to translate this understanding into needed therapeutic interventions continue to lag far behind the initial discoveries. Although pharmaceutical companies continue to increase investments into research and development, the number of drugs gaining federal approval is in decline. Many factors underlie these trends, and a vast number of technological and scientific innovations are being sought through efforts to reinvigorate drug discovery pipelines. Recent advances in molecular profiling technologies and development of sophisticated computational approaches for analyzing these data are providing new, systems-oriented approaches towards drug discovery. Unlike the traditional approach to drug discovery which is typified by a one-drug-one-target mindset, systems-oriented approaches to drug discovery leverage the parallelism and high-dimensionality of the molecular data to construct more comprehensive molecular models that aim to model broader bimolecular systems. These models offer a means to explore complex molecular states (e.g., disease) where thousands to millions of molecular entities comprising multiple molecular data types (e.g., proteomics and gene expression) can be evaluated simultaneously as components of a cohesive biomolecular system. In this paper, we discuss emerging approaches towards systems-oriented drug discovery and contrast these efforts with the traditional, unidimensional approach to drug discovery. We also highlight several applications of these system-oriented approaches across various aspects of drug discovery, including target discovery, drug repositioning and drug toxicity. When available, specific applications to cardiovascular drug discovery are highlighted and discussed.
Gerwick, William H.; Fenner, Amanda M.
The marine environment has been a source of more than 20,000 inspirational natural products discovered over the past 50 years. From these efforts, 9 approved drugs and 12 current clinical trial agents have been discovered, either as natural products or molecules inspired from the natural product structure. To a significant degree, these have come from collections of marine invertebrates largely obtained from shallow water tropical ecosystems. However, there is a growing recognition that marine invertebrates are oftentimes populated with enormous quantities of ‘associated’ or symbiotic microorganisms, and that microorganisms are the true metabolic sources of these most valuable of marine natural products. Also, because of the inherently multidisciplinary nature of this field, a high degree of innovation is characteristic of marine natural product drug discovery efforts. PMID:23274881
Jacobson, Kenneth A
G protein-coupled receptors (GPCRs) remain a major domain of pharmaceutical discovery. The identification of GPCR lead compounds and their optimization are now structure-based, thanks to advances in X-ray crystallography, molecular modeling, protein engineering and biophysical techniques. In silico screening provides useful hit molecules. New pharmacological approaches to tuning the pleotropic action of GPCRs include: allosteric modulators, biased ligands, GPCR heterodimer-targeted compounds, manipulation of polypharmacology, receptor antibodies and tailoring of drug molecules to fit GPCR pharmacogenomics. Measurements of kinetics and drug efficacy are factors influencing clinical success. With the exception of inhibitors of GPCR kinases, targeting of intracellular GPCR signaling or receptor cycling for therapeutic purposes remains a futuristic concept. New assay approaches are more efficient and multidimensional: cell-based, label-free, fluorescence-based assays, and biosensors. Tailoring GPCR drugs to a patient's genetic background is now being considered. Chemoinformatic tools can predict ADME-tox properties. New imaging technology visualizes drug action in vivo. Thus, there is reason to be optimistic that new technology for GPCR ligand discovery will help reverse the current narrowing of the pharmaceutical pipeline.
Marsden, Catherine J; Eckersley, Sonia; Hebditch, Max; Kvist, Alexander J; Milner, Roy; Mitchell, Danielle; Warwicker, Juli; Marley, Anna E
Antibodies are powerful research tools that can be used in many areas of biology to probe, measure, and perturb various biological structures. Successful drug discovery is dependent on the correct identification of a target implicated in disease, coupled with the successful selection, optimization, and development of a candidate drug. Because of their specific binding characteristics, with regard to specificity, affinity, and avidity, coupled with their amenability to protein engineering, antibodies have become a key tool in drug discovery, enabling the quantification, localization, and modulation of proteins of interest. This review summarizes the application of antibodies and other protein affinity reagents as specific research tools within the drug discovery process.
Background Genome wide association studies (GWAS) have revealed a large number of links between genome variation and complex disease. Among other benefits, it is expected that these insights will lead to new therapeutic strategies, particularly the identification of new drug targets. In this paper, we evaluate the power of GWAS studies to find drug targets by examining how many existing drug targets have been directly 'rediscovered' by this technique, and the extent to which GWAS results may be leveraged by network information to discover known and new drug targets. Results We find that only a very small fraction of drug targets are directly detected in the relevant GWAS studies. We investigate two possible explanations for this observation. First, we find evidence of negative selection acting on drug target genes as a consequence of strong coupling with the disease phenotype, so reducing the incidence of SNPs linked to the disease. Second, we find that GWAS genes are substantially longer on average than drug targets and than all genes, suggesting there is a length related bias in GWAS results. In spite of the low direct relationship between drug targets and GWAS reported genes, we found these two sets of genes are closely coupled in the human protein network. As a consequence, machine-learning methods are able to recover known drug targets based on network context and the set of GWAS reported genes for the same disease. We show the approach is potentially useful for identifying drug repurposing opportunities. Conclusions Although GWA studies do not directly identify most existing drug targets, there are several reasons to expect that new targets will nevertheless be discovered using these data. Initial results on drug repurposing studies using network analysis are encouraging and suggest directions for future development. PMID:25057111
Bates, Susan E; Amiri-Kordestani, Laleh; Giaccone, Giuseppe
A British humorist said, "There is much to be said for failure. It is much more interesting than success." This CCR Focus section is aimed at identifying lessons to be learned from difficulties encountered in recent years during development of anticancer agents. Clearly, we have not found a silver bullet tyrosine kinase inhibitor against solid tumors comparable with imatinib in chronic myelogenous leukemia. Although vemurafenib for B-Raf-mutated melanoma and crizotinib for non-small cell lung cancers with echinoderm microtubule-associated protein-like 4 (EML4)-anaplastic lymphoma kinase (ALK) rearrangements were developed rapidly and offer hope for individualized targeted therapies, the development of agents targeting a number of other pathways has been slower and less successful. These agents include drugs for blocking the insulin-like growth factor I/insulin receptor pathways, mitotic kinase inhibitors, and Hsp90 antagonists. Several potentially useful, if not groundbreaking, agents have had setbacks in clinical development, including trastuzumab emtansine, gemtuzumab ozogamicin, and satraplatin. From experience, we have learned the following: (i) not every altered protein or pathway is a valid anticancer target; (ii) drugs must effectively engage the target; (iii) the biology of the systems we use must be very well understood; and (iv) clinical trials must be designed to assess whether the drug reached and impaired the target. It is also important that we improve the drug development enterprise to enhance enrollment, streamline clinical trials, reduce financial risk, and encourage the development of agents for niche indications. Such enormous challenges are offset by potentially tremendous gains in our understanding and treatment of cancer.
Blair, Wade; Cox, Christopher
Continued discovery and development of new antiviral medications are paramount for global human health, particularly as new pathogens emerge and old ones evolve to evade current therapeutic agents. Great success has been achieved in developing effective therapies to suppress human immunodeficiency virus (HIV) and hepatitis B virus (HBV); however, the therapies are not curative and therefore current efforts in HIV and HBV drug discovery are directed toward longer-acting therapies and/or developing new mechanisms of action that could potentially lead to cure, or eradication, of the virus. Recently, exciting early clinical data have been reported for novel antivirals targeting respiratory syncytial virus (RSV) and influenza (flu). Preclinical data suggest that these new approaches may be effective in treating high-risk patients afflicted with serious RSV or flu infections. In this review, we highlight new directions in antiviral approaches for HIV, HBV, and acute respiratory virus infections. PMID:26962437
Lodén, Henrik; Shariatgorji, Mohammadreza; Nilsson, Anna; Andrén, Per E
A vital process in drug discovery and development is to assess the absorption, distribution, metabolism, excretion and toxicology of potentially therapeutic compounds in the body. The potential utility of MS imaging has been demonstrated in many studies focusing on molecules including peptides, proteins and lipids. However, MS imaging also permits the direct analysis of drugs and drug metabolites in tissue samples without requiring the use of target-specific labels or reagents. Here, a brief technical description of the technique is presented along with examples of its usefulness at different stages of the drug discovery and development process including absorption, distribution, metabolism, excretion and toxicology, and blood-brain barrier drug penetration investigations.
Jones, Lyn H; Bunnage, Mark E
The allure of phenotypic screening, combined with the industry preference for target-based approaches, has prompted the development of innovative chemical biology technologies that facilitate the identification of new therapeutic targets for accelerated drug discovery. A chemogenomic library is a collection of selective small-molecule pharmacological agents, and a hit from such a set in a phenotypic screen suggests that the annotated target or targets of that pharmacological agent may be involved in perturbing the observable phenotype. In this Review, we describe opportunities for chemogenomic screening to considerably expedite the conversion of phenotypic screening projects into target-based drug discovery approaches. Other applications are explored, including drug repositioning, predictive toxicology and the discovery of novel pharmacological modalities.
Heller, Anne; Brockhoff, Gero; Goepferich, Achim
Mitochondria are of an increasing interest in pharmaceutical and medical research since it has been reported that dysfunction of these organelles contributes to several diseases with a great diversity of clinical appearance. By the fact that mitochondria are located inside the cell and, in turn, origins of mitochondrial diseases or targets of drugs are located inside mitochondria, a drug molecule has to cross several barriers. This is a severe drawback for the selective accumulation of drug molecules in mitochondria. Therefore, targeting strategies such as direct drug modification or encapsulation into nanocarriers have to be applied to achieve an accumulation of drug molecules in these organelles. In this review, it will be demonstrated how properties and dysfunctions of mitochondria are generating a need for the development of mitochondria specific therapies. Furthermore, intracellular targets of mitochondrial diseases, strategies to utilize mitochondrial specificities and targeting approaches will be discussed. Finally, techniques to investigate mitochondrial characteristics and functionality are reviewed.
Toxicogenomics, drug discovery, and pathologist.
The field of toxicogenomics, which currently focuses on the application of large-scale differential gene expression (DGE) data to toxicology, is starting to influence drug discovery and development in the pharmaceutical indu...
The progress made in genome research raises the question whether the new knowledge bases that have emerged may also lead to better antidepressants. The past has seen many remarkable improvements over traditional drugs, but not a real breakthrough. More recently hypothesis-driven research in depression has focussed upon stress-hormone regulation as a possible target, but validation of new drugs is not yet in sight. In parallel, we see an upsurge of systematic unbiased research in a biotechnology-driven drug discovery effort. This research can only lead to results if clinical research adapts to these new demands by phenotyping depressed patients not only according to psychopathological characteristics but also by utilising functional (e.g. neuroendocrine, neuropsychological, neurophysiological, neuroimaging and clinical drug response) data that are to be correlated with data from genotyping. To achieve the goal of genotype/phenotype-based differential therapy, large-scale efforts with regards to both patient samples and genotyping capacities are needed. In the long term, increasingly detailed patient information, if translated into specific pharmacological treatments, will lead to customized drugs and thus to a partial fragmentation of the antidepressant market. Concurrently, the improved genotyping/phenotyping efforts will also lead to more widely applicable drugs that promise to avoid side effects and refractoriness and also to hasten the time to onset of action. Once these goals are achieved notorious undertreatment of depression may come to an end.
Jubb, Adrian M; Koeppen, Hartmut; Reis-Filho, Jorge S
The rapid pace of drug discovery and drug development in oncology, immunology and ophthalmology brings new challenges; the efficient and effective development of new targeted drugs will require more detailed molecular classifications of histologically homogeneous diseases that show heterogeneous clinical outcomes. To this end, single companion diagnostics for specific drugs will be replaced by multiplex diagnostics for entire therapeutic areas, preserving tissue and enabling rapid molecular taxonomy. The field will move away from the development of new molecular entities as single agents, to which resistance is common. Instead, a detailed understanding of the pathological mechanisms of resistance, in patients and in preclinical models, will be key to the validation of scientifically rational and clinically effective drug combinations. To remain at the heart of disease diagnosis and appropriate management, pathologists must evolve into translational biologists and biomarker scientists. Herein, we provide examples of where this metamorphosis has already taken place, in lung cancer and melanoma, where the transformation has yet to begin, in the use of immunotherapies for ophthalmology and oncology, and where there is fertile soil for a revolution in treatment, in efforts to classify glioblastoma and personalize treatment. The challenges of disease heterogeneity, the regulatory environment and adequate tissue are ever present, but these too are being overcome in dedicated academic centres. In summary, the tools necessary to overcome the 'whens' and 'ifs' of the molecular revolution are in the hands of pathologists today; it is a matter of standardization, training and leadership to bring these into routine practice and translate science into patient benefit. This Annual Review Issue of the Journal of Pathology highlights the central role for pathology in modern drug discovery and development.
Neglected tropical diseases (NTDs) are an extremely important issue facing global health care. To improve "access to health" where people are unable to access adequate medical care due to poverty and weak healthcare systems, we have established two consortiums: the NTD drug discovery research consortium, and the pediatric praziquantel consortium. The NTD drug discovery research consortium, which involves six institutions from industry, government, and academia, as well as an international non-profit organization, is committed to developing anti-protozoan active compounds for three NTDs (Leishmaniasis, Chagas disease, and African sleeping sickness). Each participating institute will contribute their efforts to accomplish the following: selection of drug targets based on information technology, and drug discovery by three different approaches (in silico drug discovery, "fragment evolution" which is a unique drug designing method of Astellas Pharma, and phenotypic screening with Astellas' compound library). The consortium has established a brand new database (Integrated Neglected Tropical Disease Database; iNTRODB), and has selected target proteins for the in silico and fragment evolution drug discovery approaches. Thus far, we have identified a number of promising compounds that inhibit the target protein, and we are currently trying to improve the anti-protozoan activity of these compounds. The pediatric praziquantel consortium was founded in July 2012 to develop and register a new praziquantel pediatric formulation for the treatment of schistosomiasis. Astellas Pharma has been a core member in this consortium since its establishment, and has provided expertise and technology in the area of pediatric formulation development and clinical development.
Kumar, Ashutosh; Zhang, Kam Y J
Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery.
Small molecule drug discovery critically depends on the availability of meaningful in vitro assays to guide medicinal chemistry programs that are aimed at optimizing drug potency and selectivity. As it becomes increasingly evident, most disease relevant drug targets do not act as a single protein. In the body, they are instead generally found in complex with protein cofactors that are highly relevant for their correct function and regulation. This review highlights selected examples of the increasing trend to use biologically relevant protein complexes for rational drug discovery to reduce costly late phase attritions due to lack of efficacy or toxicity.
Williams, Antony J; Harland, Lee; Groth, Paul; Pettifer, Stephen; Chichester, Christine; Willighagen, Egon L; Evelo, Chris T; Blomberg, Niklas; Ecker, Gerhard; Goble, Carole; Mons, Barend
Open PHACTS is a public-private partnership between academia, publishers, small and medium sized enterprises and pharmaceutical companies. The goal of the project is to deliver and sustain an 'open pharmacological space' using and enhancing state-of-the-art semantic web standards and technologies. It is focused on practical and robust applications to solve specific questions in drug discovery research. OPS is intended to facilitate improvements in drug discovery in academia and industry and to support open innovation and in-house non-public drug discovery research. This paper lays out the challenges and how the Open PHACTS project is hoping to address these challenges technically and socially.
Zheng, Heping; Hou, Jing; Zimmerman, Matthew D; Wlodawer, Alexander; Minor, Wladek
Introduction X-ray crystallography plays an important role in structure-based drug design (SBDD), and accurate analysis of crystal structures of target macromolecules and macromolecule–ligand complexes is critical at all stages. However, whereas there has been significant progress in improving methods of structural biology, particularly in X-ray crystallography, corresponding progress in the development of computational methods (such as in silico high-throughput screening) is still on the horizon. Crystal structures can be overinterpreted and thus bias hypotheses and follow-up experiments. As in any experimental science, the models of macromolecular structures derived from X-ray diffraction data have their limitations, which need to be critically evaluated and well understood for structure-based drug discovery. Areas covered This review describes how the validity, accuracy and precision of a protein or nucleic acid structure determined by X-ray crystallography can be evaluated from three different perspectives: i) the nature of the diffraction experiment; ii) the interpretation of an electron density map; and iii) the interpretation of the structural model in terms of function and mechanism. The strategies to optimally exploit a macromolecular structure are also discussed in the context of ‘Big Data’ analysis, biochemical experimental design and structure-based drug discovery. Expert opinion Although X-ray crystallography is one of the most detailed ‘microscopes’ available today for examining macromolecular structures, the authors would like to re-emphasize that such structures are only simplified models of the target macromolecules. The authors also wish to reinforce the idea that a structure should not be thought of as a set of precise coordinates but rather as a framework for generating hypotheses to be explored. Numerous biochemical and biophysical experiments, including new diffraction experiments, can and should be performed to verify or falsify
Levin, Victor A.; Tonge, Peter J.; Gallo, James M.; Birtwistle, Marc R.; Dar, Arvin C.; Iavarone, Antonio; Paddison, Patrick J.; Heffron, Timothy P.; Elmquist, William F.; Lachowicz, Jean E.; Johnson, Ted W.; White, Forest M.; Sul, Joohee; Smith, Quentin R.; Shen, Wang; Sarkaria, Jann N.; Samala, Ramakrishna; Wen, Patrick Y.; Berry, Donald A.; Petter, Russell C.
Following the first CNS Anticancer Drug Discovery and Development Conference, the speakers from the first 4 sessions and organizers of the conference created this White Paper hoping to stimulate more and better CNS anticancer drug discovery and development. The first part of the White Paper reviews, comments, and, in some cases, expands on the 4 session areas critical to new drug development: pharmacological challenges, recent drug approaches, drug targets and discovery, and clinical paths. Following this concise review of the science and clinical aspects of new CNS anticancer drug discovery and development, we discuss, under the rubric “Accelerating Drug Discovery and Development for Brain Tumors,” further reasons why the pharmaceutical industry and academia have failed to develop new anticancer drugs for CNS malignancies and what it will take to change the current status quo and develop the drugs so desperately needed by our patients with malignant CNS tumors. While this White Paper is not a formal roadmap to that end, it should be an educational guide to clinicians and scientists to help move a stagnant field forward. PMID:26403167
Levin, Victor A; Tonge, Peter J; Gallo, James M; Birtwistle, Marc R; Dar, Arvin C; Iavarone, Antonio; Paddison, Patrick J; Heffron, Timothy P; Elmquist, William F; Lachowicz, Jean E; Johnson, Ted W; White, Forest M; Sul, Joohee; Smith, Quentin R; Shen, Wang; Sarkaria, Jann N; Samala, Ramakrishna; Wen, Patrick Y; Berry, Donald A; Petter, Russell C
Following the first CNS Anticancer Drug Discovery and Development Conference, the speakers from the first 4 sessions and organizers of the conference created this White Paper hoping to stimulate more and better CNS anticancer drug discovery and development. The first part of the White Paper reviews, comments, and, in some cases, expands on the 4 session areas critical to new drug development: pharmacological challenges, recent drug approaches, drug targets and discovery, and clinical paths. Following this concise review of the science and clinical aspects of new CNS anticancer drug discovery and development, we discuss, under the rubric "Accelerating Drug Discovery and Development for Brain Tumors," further reasons why the pharmaceutical industry and academia have failed to develop new anticancer drugs for CNS malignancies and what it will take to change the current status quo and develop the drugs so desperately needed by our patients with malignant CNS tumors. While this White Paper is not a formal roadmap to that end, it should be an educational guide to clinicians and scientists to help move a stagnant field forward.
Zuniga, Edison S; Early, Julie; Parish, Tanya
There is an urgent need for new and better drugs to treat tuberculosis due to lengthy and complex treatment regimens and a rising problem of drug resistance. Drug discovery efforts have increased over the past few years, with a larger focus on modern high-throughput screening technologies. A combination of target-based approaches, with the traditional empirical means of drug identification, has been complemented by the use of target-based phenotypic screens only recently made possibly with newer genetic tools. Using these approaches, a number of promising compound series have been discovered. However, significant problems remain in developing these into drugs. This review highlights recent advances in TB drug discovery, including an overview of screening campaigns, lessons learned and future directions. PMID:25689534
The molecular structures of drug target proteins and receptors form the basis for 'rational' or structure guided drug design. The majority of target structures are experimentally determined by protein X-ray crystallography, which as evolved into a highly automated, high throughput drug discovery and screening tool. Process automation has accelerated tasks from parallel protein expression, fully automated crystallization, and rapid data collection to highly efficient structure determination methods. A thoroughly designed automation technology platform supported by a powerful informatics infrastructure forms the basis for optimal workflow implementation and the data mining and analysis tools to generate new leads from experimental protein drug target structures.
Background Drug discovery is a complex and unpredictable endeavor with a high failure rate. Current trends in the pharmaceutical industry have exasperated these challenges and are contributing to the dramatic decline in productivity observed over the last decade. The industrialization of science by forcing the drug discovery process to adhere to assembly-line protocols is imposing unnecessary restrictions, such as short project time-lines. Recent advances in nuclear magnetic resonance are responding to these self-imposed limitations and are providing opportunities to increase the success rate of drug discovery. Objective/Method A review of recent advancements in NMR technology that have the potential of significantly impacting and benefiting the drug discovery process will be presented. These include fast NMR data collection protocols and high-throughput protein structure determination, rapid protein-ligand co-structure determination, lead discovery using fragment-based NMR affinity screens, NMR metabolomics to monitor in vivo efficacy and toxicity for lead compounds, and the identification of new therapeutic targets through the functional annotation of proteins by FAST-NMR. Conclusion NMR is a critical component of the drug discovery process, where the versatility of the technique enables it to continually expand and evolve its role. NMR is expected to maintain this growth over the next decade with advancements in automation, speed of structure calculation, in-cell imaging techniques, and the expansion of NMR amenable targets. PMID:20333269
Rodrigues, Tiago; Reker, Daniel; Welin, Martin; Caldera, Michael; Brunner, Cyrill; Gabernet, Gisela; Schneider, Petra; Walse, Björn; Schneider, Gisbert
Automated molecular de novo design led to the discovery of an innovative inhibitor of death-associated protein kinase 3 (DAPK3). An unprecedented crystal structure of the inactive DAPK3 homodimer shows the fragment-like hit bound to the ATP pocket. Target prediction software based on machine learning models correctly identified additional macromolecular targets of the computationally designed compound and the structurally related marketed drug azosemide. The study validates computational de novo design as a prime method for generating chemical probes and starting points for drug discovery.
... Matters NIH Research Matters January 13, 2014 Arthritis Genetics Analysis Aids Drug Discovery An international research team ... may play a role in triggering the disease. Genetic factors are also thought to play a role. ...
Mullane, Kevin; Winquist, Raymond J; Williams, Michael
The translational sciences represent the core element in enabling and utilizing the output from the biomedical sciences and to improving drug discovery metrics by reducing the attrition rate as compounds move from preclinical research to clinical proof of concept. Key to understanding the basis of disease causality and to developing therapeutics is an ability to accurately diagnose the disease and to identify and develop safe and effective therapeutics for its treatment. The former requires validated biomarkers and the latter, qualified targets. Progress has been hampered by semantic issues, specifically those that define the end product, and by scientific issues that include data reliability, an overt reductionistic cultural focus and a lack of hierarchically integrated data gathering and systematic analysis. A necessary framework for these activities is represented by the discipline of pharmacology, efforts and training in which require recognition and revitalization.
The Society for Medicines Research (SMR) held a one-day meeting on case histories in drug discovery on December 4, 2003, at the National Heart and Lung Institute in London. These meetings have been organized by the SMR biannually for many years, and this latest meeting proved extremely popular, attracting a capacity audience of more than 130 registrants. The purpose of these meetings is educational; they allow those interested in drug discovery to hear key learnings from recent successful drug discovery programs. There was no overall linking theme between the talks, other than each success story has led to the introduction of a new and improved product of therapeutic use. The drug discovery stories covered in the meeting were extremely varied and, put together, they emphasized that each successful story is unique and special. This meeting is also special for the SMR because it presents the "SMR Award for Drug Discovery" in recognition of outstanding achievement and contribution in the area. It should be remembered that drug discovery is an extremely risky business and an extremely costly and complicated process in which the success rate is, at best, low.
Pandey, Saurabh; Pandey, Preeti; Tiwari, Gaurav; Tiwari, Ruchi
Recent years have witnessed the introduction of several high-quality review articles into the literature covering various scientific and technical aspects of bioanalysis. Now it is widely accepted that bioanalysis is an integral part of the pharmacokinetic/pharmacodynamic characterization of a novel chemical entity from the time of its discovery and during various stages of drug development, leading to its market authorization. In this compilation, the important bioanalytical parameters and its application to drug discovery and development approaches are discussed, which will help in the development of safe and more efficacious drugs with reduced development time and cost. It is intended to give some general thoughts in this area which will form basis of a general framework as to how one would approach bioanalysis from inception (i.e., discovery of a lead molecule) and progressing through various stages of drug development. PMID:23781412
BIT's Seventh Annual International Drug Discovery Science and Technology Congress, held in Shanghai, included topics covering new therapeutic and technological developments in the field of drug discovery. This conference report highlights selected presentations on open-access approaches to R&D, novel and multifactorial targets, and technologies that assist drug discovery. Investigational drugs discussed include the anticancer agents astuprotimut-r (GlaxoSmithKline plc) and AS-1411 (Antisoma plc).
Current industry perspective of how discovery is conducted seems to be fragmented and does not have a unified overall outlook of how discovery challenges are being addressed. Consequently, well-defined processes and drug-likeness criteria are being viewed as "broken" and will not maintain future R&D productivity. In this commentary, an analysis of existing practices for defining successful development candidates resulted in a 5 "must do" list to help advance Drug Discovery as presented from a Pharmaceutics perspective. The 5 "must do" list includes: what an ideal discovery team model should look like, what criteria should be considered for the desired development candidate profile, what the building blocks of the development candidate should look like, and how to assess the development risks of the candidate.
In recent years, there has been unprecedented growth in compound activity data in the public domain. These compound data provide an indispensable resource for drug discovery in academic environments as well as in the pharmaceutical industry. To handle large volumes of heterogeneous and complex compound data and extract discovery-relevant knowledge from these data, advanced computational mining approaches are required. Herein, major public compound data repositories are introduced, data confidence criteria reviewed, and selected data mining approaches discussed.
Méndez-Lucio, Oscar; Medina-Franco, José L
Molecular complexity is becoming a crucial concept in drug discovery. It has been associated with target selectivity, success in progressing into clinical development and compound safety, among other factors. Multiple metrics have been developed to quantify molecular complexity and explore complexity-property relationships. However, there is no general agreement regarding how to measure this molecular feature. Herein, we have surveyed the many roles of molecular complexity in drug discovery discussing in a critical manner different quantification methods. Through the analysis of various reference compound databases, common pitfalls and workarounds of the quantification of molecular complexity are discussed.
Itoh, Yukihiro; Suzuki, Takayoshi
The first step in "drug" discovery is to find compounds binding to a potential drug target. In modern medicinal chemistry, the screening of a chemical library, structure-based drug design, and ligand-based drug design, or a combination of these methods, are generally used for identifying the desired compounds. However, they do not necessarily lead to success and there is no infallible method for drug discovery. Therefore, it is important to explore medicinal chemistry based on not only the conventional methods but also new ideas. So far, we have found various compounds as drug candidates. In these studies, some strategies based on organic chemistry have allowed us to find drug candidates, through 1) construction of a focused library using organic reactions and 2) rational design of enzyme inhibitors based on chemical reactions catalyzed by the target enzyme. Medicinal chemistry based on organic chemical reactions could be expected to supplement the conventional methods. In this review, we present drug discovery with the help of organic chemistry showing examples of our explorative studies on histone deacetylase inhibitors and lysine-specific demethylase 1 inhibitors.
Bauer, Renato A
Drugs that covalently bond to their biological targets have a long history in drug discovery. A look at drug approvals in recent years suggests that covalent drugs will continue to make impacts on human health for years to come. Although fraught with concerns about toxicity, the high potencies and prolonged effects achievable with covalent drugs may result in less-frequent drug dosing and in wide therapeutic margins for patients. Covalent inhibition can also dissociate drug pharmacodynamics (PD) from pharmacokinetics (PK), which can result in desired drug efficacy for inhibitors that have short systemic exposure. Evidence suggests that there is a reduced risk for the development of resistance against covalent drugs, which is a major challenge in areas such as oncology and infectious disease.
Hoelder, Swen; Clarke, Paul A; Workman, Paul
The discovery and development of small molecule cancer drugs has been revolutionised over the last decade. Most notably, we have moved from a one-size-fits-all approach that emphasized cytotoxic chemotherapy to a personalised medicine strategy that focuses on the discovery and development of molecularly targeted drugs that exploit the particular genetic addictions, dependencies and vulnerabilities of cancer cells. These exploitable characteristics are increasingly being revealed by our expanding understanding of the abnormal biology and genetics of cancer cells, accelerated by cancer genome sequencing and other high-throughput genome-wide campaigns, including functional screens using RNA interference. In this review we provide an overview of contemporary approaches to the discovery of small molecule cancer drugs, highlighting successes, current challenges and future opportunities. We focus in particular on four key steps: Target validation and selection; chemical hit and lead generation; lead optimization to identify a clinical drug candidate; and finally hypothesis-driven, biomarker-led clinical trials. Although all of these steps are critical, we view target validation and selection and the conduct of biology-directed clinical trials as especially important areas upon which to focus to speed progress from gene to drug and to reduce the unacceptably high attrition rate during clinical development. Other challenges include expanding the envelope of druggability for less tractable targets, understanding and overcoming drug resistance, and designing intelligent and effective drug combinations. We discuss not only scientific and technical challenges, but also the assessment and mitigation of risks as well as organizational, cultural and funding problems for cancer drug discovery and development, together with solutions to overcome the 'Valley of Death' between basic research and approved medicines. We envisage a future in which addressing these challenges will enhance
McCammon, J. Andrew
This lecture will provide a general introduction to some of the ways that modern computational physics is contributing to the discovery of new pharmaceuticals, with special emphasis on drugs for infectious diseases. The basic sciences and computing technologies involved have advanced to the point that physics-based simulations of drug targets are now yielding truly valuable suggestions for new compounds. Supported in part by NSF, NIH, HHMI, CTBP, NBCR, and SDSC.
Hoelder, Swen; Clarke, Paul A.; Workman, Paul
The discovery and development of small molecule cancer drugs has been revolutionised over the last decade. Most notably, we have moved from a one-size-fits-all approach that emphasized cytotoxic chemotherapy to a personalised medicine strategy that focuses on the discovery and development of molecularly targeted drugs that exploit the particular genetic addictions, dependencies and vulnerabilities of cancer cells. These exploitable characteristics are increasingly being revealed by our expanding understanding of the abnormal biology and genetics of cancer cells, accelerated by cancer genome sequencing and other high-throughput genome-wide campaigns, including functional screens using RNA interference. In this review we provide an overview of contemporary approaches to the discovery of small molecule cancer drugs, highlighting successes, current challenges and future opportunities. We focus in particular on four key steps: Target validation and selection; chemical hit and lead generation; lead optimization to identify a clinical drug candidate; and finally hypothesis-driven, biomarker-led clinical trials. Although all of these steps are critical, we view target validation and selection and the conduct of biology-directed clinical trials as especially important areas upon which to focus to speed progress from gene to drug and to reduce the unacceptably high attrition rate during clinical development. Other challenges include expanding the envelope of druggability for less tractable targets, understanding and overcoming drug resistance, and designing intelligent and effective drug combinations. We discuss not only scientific and technical challenges, but also the assessment and mitigation of risks as well as organizational, cultural and funding problems for cancer drug discovery and development, together with solutions to overcome the ‘Valley of Death’ between basic research and approved medicines. We envisage a future in which addressing these challenges will
Yap, Timothy A; Smith, Alan D; Ferraldeschi, Roberta; Al-Lazikani, Bissan; Workman, Paul; de Bono, Johann S
Castration-resistant prostate cancer (CRPC) is associated with a poor prognosis and poses considerable therapeutic challenges. Recent genetic and technological advances have provided insights into prostate cancer biology and have enabled the identification of novel drug targets and potent molecularly targeted therapeutics for this disease. In this article, we review recent advances in prostate cancer target identification for drug discovery and discuss their promise and associated challenges. We review the evolving therapeutic landscape of CRPC and discuss issues associated with precision medicine as well as challenges encountered with immunotherapy for this disease. Finally, we envision the future management of CRPC, highlighting the use of circulating biomarkers and modern clinical trial designs.
Huang, Wei-Hsuan; Tseng, Chao-Neng; Tang, Jen-Yang; Yang, Cheng-Hong; Liang, Shih-Shin; Chang, Hsueh-Wei
RNA editing is vital to provide the RNA and protein complexity to regulate the gene expression. Correct RNA editing maintains the cell function and organism development. Imbalance of the RNA editing machinery may lead to diseases and cancers. Recently, RNA editing has been recognized as a target for drug discovery although few studies targeting RNA editing for disease and cancer therapy were reported in the field of natural products. Therefore, RNA editing may be a potential target for therapeutic natural products. In this review, we provide a literature overview of the biological functions of RNA editing on gene expression, diseases, cancers, and drugs. The bioinformatics resources of RNA editing were also summarized.
Jordan, Allan M; Waddell, Ian D; Ogilvie, Donald J
The contraction in research within pharma has seen a renaissance in drug discovery within the academic setting. Often, groups grow organically from academic research laboratories, exploiting a particular area of novel biology or new technology. However, increasingly, new groups driven by industrial staff are emerging with demonstrable expertise in the delivery of medicines. As part of a strategic review by Cancer Research UK (CR-UK), the drug discovery team at the Manchester Institute was established to translate novel research from the Manchester cancer research community into drug discovery programmes. From a standing start, we have taken innovative approaches to solve key issues faced by similar groups, such as hit finding and target identification. Herein, we share our lessons learnt and successful strategies.
Zheng, Mingyue; Liu, Xian; Xu, Yuan; Li, Honglin; Luo, Cheng; Jiang, Hualiang
In the past decades, China's computational drug design and discovery research has experienced fast development through various novel methodologies. Application of these methods spans a wide range, from drug target identification to hit discovery and lead optimization. In this review, we firstly provide an overview of China's status in this field and briefly analyze the possible reasons for this rapid advancement. The methodology development is then outlined. For each selected method, a short background precedes an assessment of the method with respect to the needs of drug discovery, and, in particular, work from China is highlighted. Furthermore, several successful applications of these methods are illustrated. Finally, we conclude with a discussion of current major challenges and future directions of the field.
Renaud, Jean-Paul; Chung, Chun-Wa; Danielson, U Helena; Egner, Ursula; Hennig, Michael; Hubbard, Roderick E; Nar, Herbert
Over the past 25 years, biophysical technologies such as X-ray crystallography, nuclear magnetic resonance spectroscopy, surface plasmon resonance spectroscopy and isothermal titration calorimetry have become key components of drug discovery platforms in many pharmaceutical companies and academic laboratories. There have been great improvements in the speed, sensitivity and range of possible measurements, providing high-resolution mechanistic, kinetic, thermodynamic and structural information on compound-target interactions. This Review provides a framework to understand this evolution by describing the key biophysical methods, the information they can provide and the ways in which they can be applied at different stages of the drug discovery process. We also discuss the challenges for current technologies and future opportunities to use biophysical methods to solve drug discovery problems.
Macalino, Stephani Joy Y; Gosu, Vijayakumar; Hong, Sunhye; Choi, Sun
Drug discovery utilizes chemical biology and computational drug design approaches for the efficient identification and optimization of lead compounds. Chemical biology is mostly involved in the elucidation of the biological function of a target and the mechanism of action of a chemical modulator. On the other hand, computer-aided drug design makes use of the structural knowledge of either the target (structure-based) or known ligands with bioactivity (ligand-based) to facilitate the determination of promising candidate drugs. Various virtual screening techniques are now being used by both pharmaceutical companies and academic research groups to reduce the cost and time required for the discovery of a potent drug. Despite the rapid advances in these methods, continuous improvements are critical for future drug discovery tools. Advantages presented by structure-based and ligand-based drug design suggest that their complementary use, as well as their integration with experimental routines, has a powerful impact on rational drug design. In this article, we give an overview of the current computational drug design and their application in integrated rational drug development to aid in the progress of drug discovery research.
Svennebring, Andreas M; Wikberg, Jarl Es
Three dedicated approaches to the calculation of the risk-adjusted net present value (rNPV) in drug discovery projects under different assumptions are suggested. The probability of finding a candidate drug suitable for clinical development and the time to the initiation of the clinical development is assumed to be flexible in contrast to the previously used models. The rNPV of the post-discovery cash flows is calculated as the probability weighted average of the rNPV at each potential time of initiation of clinical development. Practical considerations how to set probability rates, in particular during the initiation and termination of a project is discussed.
Lin, Guimiao; Yin, Feng; Yong, Ken-Tye
The rapid development of drug discovery today is inseparable from the interaction of advanced particle technologies and new drug synthesis protocols. Quantum dots (QDs) are regarded as a unique class of fluorescent labels, with unique optical properties such as high brightness and long-term colloidal and optical stability; these are suitable for optical imaging, drug delivery and optical tracking, fluorescence immunoassay and other medicinal applications. More importantly, QD possesses a rich surface chemistry property that is useful for incorporating various drug molecules, targeting ligands, and additional contrast agents (e.g., MRI, PET, etc.) onto the nanoparticle surface for achieving targeted and traceable drug delivery therapy at both cellular and systemic levels. In recent times, the advancement of QD technology has promoted the use of functionalized nanocrystals for in vivo applications. Such research is paving the way for drug discovery using various bioconjugated QD formulations. In this editorial, the authors highlight the current research progress and future applications of QDs in drug discovery.
Eng-Chong, Tan; Yean-Kee, Lee; Chin-Fei, Chee; Choon-Han, Heh; Sher-Ming, Wong; Li-Ping, Christina Thio; Gen-Teck, Foo; Khalid, Norzulaani; Abd Rahman, Noorsaadah; Karsani, Saiful Anuar; Othman, Shatrah; Othman, Rozana; Yusof, Rohana
Boesenbergia rotunda is a herb from the Boesenbergia genera under the Zingiberaceae family. B. rotunda is widely found in Asian countries where it is commonly used as a food ingredient and in ethnomedicinal preparations. The popularity of its ethnomedicinal usage has drawn the attention of scientists worldwide to further investigate its medicinal properties. Advancement in drug design and discovery research has led to the development of synthetic drugs from B. rotunda metabolites via bioinformatics and medicinal chemistry studies. Furthermore, with the advent of genomics, transcriptomics, proteomics, and metabolomics, new insights on the biosynthetic pathways of B. rotunda metabolites can be elucidated, enabling researchers to predict the potential bioactive compounds responsible for the medicinal properties of the plant. The vast biological activities exhibited by the compounds obtained from B. rotunda warrant further investigation through studies such as drug discovery, polypharmacology, and drug delivery using nanotechnology. PMID:23243448
The increased use of drugs (and the concurrent increased risks of drug-induced illness) require definition of relevant research areas and strategy. For established marketed drugs, research needs depend on the magnitudes of risk of an illness from a drug and the base-line risk. With the drug risk high and the base-line risk low, the problem surfaces in premarketing studies or through the epidemic that develops after marketing. If the drug adds slightly to a high base-line risk, the effect is undetectable. When both risks are low, adverse effects can be discovered by chance, but systematic case-referent studies can speed discovery. If both risks are high, clinical trials and nonexperimental studies may be used. With both risks intermediate, systematic evaluations, especially case-referent studies are needed. Newly marketed drugs should be routinely evaluated through compulsory registration and follow-up study of the earliest users.
Grabowski, Marek; Chruszcz, Maksymilian; Zimmerman, Matthew D.; Kirillova, Olga; Minor, Wladek
While three dimensional structures have long been used to search for new drug targets, only a fraction of new drugs coming to the market has been developed with the use of a structure-based drug discovery approach. However, the recent years have brought not only an avalanche of new macromolecular structures, but also significant advances in the protein structure determination methodology only now making their way into structure-based drug discovery. In this paper, we review recent developments resulting from the Structural Genomics (SG) programs, focusing on the methods and results most likely to improve our understanding of the molecular foundation of human diseases. SG programs have been around for almost a decade, and in that time, have contributed a significant part of the structural coverage of both the genomes of pathogens causing infectious diseases and structurally uncharacterized biological processes in general. Perhaps most importantly, SG programs have developed new methodology at all steps of the structure determination process, not only to determine new structures highly efficiently, but also to screen protein/ligand interactions. We describe the methodologies, experience and technologies developed by SG, which range from improvements to cloning protocols to improved procedures for crystallographic structure solution that may be applied in “traditional” structural biology laboratories particularly those performing drug discovery. We also discuss the conditions that must be met to convert the present high-throughput structure determination pipeline into a high-output structure-based drug discovery system. PMID:19594422
Grabowski, M.; Chruszcz, M; Zimmerman, M; Kirillova, O; Minor, W
While three dimensional structures have long been used to search for new drug targets, only a fraction of new drugs coming to the market has been developed with the use of a structure-based drug discovery approach. However, the recent years have brought not only an avalanche of new macromolecular structures, but also significant advances in the protein structure determination methodology only now making their way into structure-based drug discovery. In this paper, we review recent developments resulting from the Structural Genomics (SG) programs, focusing on the methods and results most likely to improve our understanding of the molecular foundation of human diseases. SG programs have been around for almost a decade, and in that time, have contributed a significant part of the structural coverage of both the genomes of pathogens causing infectious diseases and structurally uncharacterized biological processes in general. Perhaps most importantly, SG programs have developed new methodology at all steps of the structure determination process, not only to determine new structures highly efficiently, but also to screen protein/ligand interactions. We describe the methodologies, experience and technologies developed by SG, which range from improvements to cloning protocols to improved procedures for crystallographic structure solution that may be applied in 'traditional' structural biology laboratories particularly those performing drug discovery. We also discuss the conditions that must be met to convert the present high-throughput structure determination pipeline into a high-output structure-based drug discovery system.
Liu, Fa; Mayer, John P
The discovery of novel therapeutics to combat human disease has traditionally been among the most important goals of research chemists. After a century of innovation, state-of-the-art chemical protein synthesis is now capable of efficiently assembling proteins of up to several hundred residues in length from individual amino acids. By virtue of its unique ability to incorporate non-native structural elements, chemical protein synthesis has been seminal in the recent development of several novel drug discovery technologies. In this chapter, we review the key advances in peptide and protein chemistry which have enabled our current synthetic capabilities. We also discuss the synthesis of D-proteins and their applications in mirror image phage-display and racemic protein crystallography, the synthesis of enzymes for structure-based drug discovery, and the direct synthesis of homogenous protein pharmaceuticals.
Wolf, Antje; Shahid, Mohammad; Kasam, Vinod; Ziegler, Wolfgang; Hofmann-Apitius, Martin
The first step in finding a "drug" is screening chemical compound databases against a protein target. In silico approaches like virtual screening by molecular docking are well established in modern drug discovery. As molecular databases of compounds and target structures are becoming larger and more and more computational screening approaches are available, there is an increased need in compute power and more complex workflows. In this regard, computational Grids are predestined and offer seamless compute and storage capacity. In recent projects related to pharmaceutical research, the high computational and data storage demands of large-scale in silico drug discovery approaches have been addressed by using Grid computing infrastructures, in both; pharmaceutical industry as well as academic research. Grid infrastructures are part of the so-called eScience paradigm, where a digital infrastructure supports collaborative processes by providing relevant resources and tools for data- and compute-intensive applications. Substantial computing resources, large data collections and services for data analysis are shared on the Grid infrastructure and can be mobilized on demand. This review gives an overview on the use of Grid computing for in silico drug discovery and tries to provide a vision of future development of more complex and integrated workflows on Grids, spanning from target identification and target validation via protein-structure and ligand dependent screenings to advanced mining of large scale in silico experiments.
Yerien, Damian E; Bonesi, Sergio; Postigo, Al
Fluorination reactions of medicinal and biologically-active compounds will be discussed. Late stage fluorination strategies of medicinal targets have recently attracted considerable attention on account of the influence that a fluorine atom can impart to targets of medicinal importance, such as modulation of lipophilicity, electronegativity, basicity and bioavailability, the latter as a consequence of membrane permeability. Therefore, the recourse to late-stage fluorine substitution on compounds with already known and relevant biological activity can provide the pharmaceutical industry with new leads with improved medicinal properties. The fluorination strategies will take into account different fluorinating reagents, either of nucleophilic or electrophilic, and of radical nature. Diverse families of organic compounds such as (hetero)aromatic rings, and aliphatic substrates (sp(3), sp(2), and sp carbon atoms) will be studied in late-stage fluorination reaction strategies.
Ekins, Sean; Mietchen, Daniel; Coffee, Megan; Stratton, Thomas P; Freundlich, Joel S; Freitas-Junior, Lucio; Muratov, Eugene; Siqueira-Neto, Jair; Williams, Antony J; Andrade, Carolina
The Zika virus (ZIKV) outbreak in the Americas has caused global concern that we may be on the brink of a healthcare crisis. The lack of research on ZIKV in the over 60 years that we have known about it has left us with little in the way of starting points for drug discovery. Our response can build on previous efforts with virus outbreaks and lean heavily on work done on other flaviviruses such as dengue virus. We provide some suggestions of what might be possible and propose an open drug discovery effort that mobilizes global science efforts and provides leadership, which thus far has been lacking. We also provide a listing of potential resources and molecules that could be prioritized for testing as in vitro assays for ZIKV are developed. We propose also that in order to incentivize drug discovery, a neglected disease priority review voucher should be available to those who successfully develop an FDA approved treatment. Learning from the response to the ZIKV, the approaches to drug discovery used and the success and failures will be critical for future infectious disease outbreaks. PMID:27134728
Lesterhuis, W Joost; Bosco, Anthony; Lake, Richard A
The pathobiology-based approach to research and development has been the dominant paradigm for successful drug discovery over the last decades. We propose that the molecular and cellular events that govern a resolving, rather than an evolving, disease may reveal new druggable pathways.
Lowe, Derek B.
The generation of chemical libraries for screening is a key part of the drug discovery process. Now, two studies describe attempts to combine features of natural product biosynthesis into the creation of libraries with the aim of mimicking nature's success at the production of bioactive molecules.
Rogawski, M A
Levetiracetam, the α-ethyl analogue of the nootropic piracetam, is a widely used antiepileptic drug (AED) that provides protection against partial seizures and is also effective in the treatment of primary generalized seizure syndromes including juvenile myoclonic epilepsy. Levetiracetam was discovered in 1992 through screening in audiogenic seizure susceptible mice and, 3 years later, was reported to exhibit saturable, stereospecific binding in brain to a ∼90 kDa protein, later identified as the ubiquitous synaptic vesicle glycoprotein SV2A. A large-scale screening effort to optimize binding affinity identified the 4-n-propyl analogue, brivaracetam, as having greater potency and a broadened spectrum of activity in animal seizure models. Recent phase II clinical trials demonstrating that brivaracetam is efficacious and well tolerated in the treatment of partial onset seizures have validated the strategy of the discovery programme. Brivaracetam is among the first clinically effective AEDs to be discovered by optimization of pharmacodynamic activity at a molecular target. PMID:18552880
Schwartz, Phillip A; Murray, Brion W
Protein kinases are fascinating biological catalysts with a rapidly expanding knowledge base, a growing appreciation in cell regulatory control, and an ascendant role in successful therapeutic intervention. To better understand protein kinases, the molecular underpinnings of phosphoryl group transfer, protein phosphorylation, and inhibitor interactions are examined. This analysis begins with a survey of phosphate group and phosphoprotein properties which provide context to the evolutionary selection of phosphorylation as a central mechanism for biological regulation of most cellular processes. Next, the kinetic and catalytic mechanisms of protein kinases are examined with respect to model aqueous systems to define the elements of catalysis. A brief structural biology overview further delves into the molecular basis of catalysis and regulation of catalytic activity. Concomitant with a prominent role in normal physiology, protein kinases have important roles in the disease state. To facilitate effective kinase drug discovery, classic and emerging approaches for characterizing kinase inhibitors are evaluated including biochemical assay design, inhibitor mechanism of action analysis, and proper kinetic treatment of irreversible inhibitors. As the resulting protein kinase inhibitors can modulate intended and unintended targets, profiling methods are discussed which can illuminate a more complete range of an inhibitor's biological activities to enable more meaningful cellular studies and more effective clinical studies. Taken as a whole, a wealth of protein kinase biochemistry knowledge is available, yet it is clear that a substantial extent of our understanding in this field remains to be discovered which should yield many new opportunities for therapeutic intervention.
Among the fields of expertise required to develop drugs successfully, biochemistry holds a key position in drug discovery at the interface between chemistry, structural biology and cell biology. However, taking the example of protein kinases, it appears that biochemical assays are mostly used in the pharmaceutical industry to measure compound potency and/or selectivity. This limited use of biochemistry is surprising, given that detailed biochemical analyses are commonly used in academia to unravel molecular recognition processes. In this article, I show that biochemistry can provide invaluable information on the dynamics and energetics of compound-target interactions that cannot be obtained on the basis of potency measurements and structural data. Therefore, an extensive use of biochemistry in drug discovery could facilitate the identification and/or development of new drugs.
Richon, Victoria M
Over the past decade, the number of new therapies developed for the treatment of rare diseases continues to increase. The most rapid growth has been in the development of new drugs for oncology indications. One focus in drug discovery for oncology indications is the development of targeted therapies for select patient subgroups characterized by genetic alterations. The identification of these patient subgroups has increased in the past decade and has resulted in a corresponding increase in the development of new drugs for genetically defined patient subgroups. As an example of the development of new therapeutics for rare indications, I describe here the drug discovery efforts leading to the development of DOT1L inhibitors for the treatment of MLL-rearranged leukemia.
Tell, Volkmar; Holzer, Max; Herrmann, Lydia; Mahmoud, Kazem Ahmed; Schächtele, Christoph; Totzke, Frank; Hilgeroth, Andreas
Alzheimer disease (AD) turned out to be a multifactorial process leading to neuronal decay. So far merely single target structures which attribute to the AD progression have been considered to develop specific drugs. However, such drug developments have been disappointing in clinical stages. Multitargeting of more than one target structure determines recent studies of developing novel lead compounds. Protein kinases have been identified to contribute to the neuronal decay with CDK1, GSK-3β and CDK5/p25 being involved in a pathological tau protein hyperphosphorylation. We discovered novel lead structures of the dihydroxy-1-aza-9-oxafluorene type with nanomolar activities against CDK1, GSK-3β and CDK5/p25. Structure-activity relationships (SAR) of the protein kinase inhibition are discussed within our first compound series. One nanomolar active compound profiled as selective protein kinase inhibitor. Bioanalysis of a harmless cellular toxicity and of the inhibition of tau protein phosphorylation qualifies the compound for further studies.
The CTD2 Center at Emory University has developed a computational methodology to combine high-throughput knockdown data with known protein network topologies to infer the importance of protein-protein interactions (PPIs) for the survival of cancer cells. Applying these data to the Achilles shRNA results, the CCLE cell line characterizations, and known and newly identified PPIs provides novel insights for potential new drug targets for cancer therapies and identifies important PPI hubs.
Kassner, Paul D
High throughput technologies have the potential to affect all aspects of drug discovery. Considerable attention is paid to high throughput screening (HTS) for small molecule lead compounds. The identification of the targets that enter those HTS campaigns had been driven by basic research until the advent of genomics level data acquisition such as sequencing and gene expression microarrays. Large-scale profiling approaches (e.g., microarrays, protein analysis by mass spectrometry, and metabolite profiling) can yield vast quantities of data and important information. However, these approaches usually require painstaking in silico analysis and low-throughput basic wet-lab research to identify the function of a gene and validate the gene product as a potential therapeutic drug target. Functional genomic screening offers the promise of direct identification of genes involved in phenotypes of interest. In this review, RNA interference (RNAi) mediated loss-of-function screens will be discussed and as well as their utility in target identification. Some of the genes identified in these screens should produce similar phenotypes if their gene products are antagonized with drugs. With a carefully chosen phenotype, an understanding of the biology of RNAi and appreciation of the limitations of RNAi screening, there is great potential for the discovery of new drug targets.
Drinkwater, Nyssa; McGowan, Sheena
Despite a century of control and eradication campaigns, malaria remains one of the world's most devastating diseases. Our once-powerful therapeutic weapons are losing the war against the Plasmodium parasite, whose ability to rapidly develop and spread drug resistance hamper past and present malaria-control efforts. Finding new and effective treatments for malaria is now a top global health priority, fuelling an increase in funding and promoting open-source collaborations between researchers and pharmaceutical consortia around the world. The result of this is rapid advances in drug discovery approaches and technologies, with three major methods for antimalarial drug development emerging: (i) chemistry-based, (ii) target-based, and (iii) cell-based. Common to all three of these approaches is the unique ability of structural biology to inform and accelerate drug development. Where possible, SBDD (structure-based drug discovery) is a foundation for antimalarial drug development programmes, and has been invaluable to the development of a number of current pre-clinical and clinical candidates. However, as we expand our understanding of the malarial life cycle and mechanisms of resistance development, SBDD as a field must continue to evolve in order to develop compounds that adhere to the ideal characteristics for novel antimalarial therapeutics and to avoid high attrition rates pre- and post-clinic. In the present review, we aim to examine the contribution that SBDD has made to current antimalarial drug development efforts, covering hit discovery to lead optimization and prevention of parasite resistance. Finally, the potential for structural biology, particularly high-throughput structural genomics programmes, to identify future targets for drug discovery are discussed.
Kolb, V M
Selected works are discussed which clearly demonstrate that mimicking various aspects of the process by which natural products evolved is becoming a powerful tool in contemporary drug discovery. Natural products are an established and rich source of drugs. The term "natural product" is often used synonymously with "secondary metabolite." Knowledge of genetics and molecular evolution helps us understand how biosynthesis of many classes of secondary metabolites evolved. One proposed hypothesis is termed "inventive evolution." It invokes duplication of genes, and mutation of the gene copies, among other genetic events. The modified duplicate genes, per se or in conjunction with other genetic events, may give rise to new enzymes, which, in turn, may generate new products, some of which may be selected for. Steps of the inventive evolution can be mimicked in several ways for purpose of drug discovery. For example, libraries of chemical compounds of any imaginable structure may be produced by combinatorial synthesis. Out of these libraries new active compounds can be selected. In another example, genetic system can be manipulated to produce modified natural products ("unnatural natural products"), from which new drugs can be selected. In some instances, similar natural products turn up in species that are not direct descendants of each other. This is presumably due to a horizontal gene transfer. The mechanism of this inter-species gene transfer can be mimicked in therapeutic gene delivery. Mimicking specifics or principles of chemical evolution including experimental and test-tube evolution also provides leads for new drug discovery.
Hyun, Bo-ra; Jung, Hwiesung; Jang, Woo-Hyuk; Jung, Suk Hoon; Han, Dong-Soo
Drug discovery is a long process in which only a few successful new therapeutic discoveries are made and identification of drug target candidate proteins requires considerable time and efforts. However, the accumulation of information on drugs has made it possible to devise new computational methods for classifying drug target candidates. In this paper, we devise a Drug Target Protein (DT-P) classification method by the summation of weighted features which is extracted from known DT-P. The method is validated using Bayesian decision theory and SVM, and it was revealed to achieve high specificity of 89.5% with 88% accuracy.
Myung, Kyung; Klittich, Carla J R
Twelve drugs from four chemical classes are currently available for treatment of systemic fungal infections in humans. By contrast, more than 100 structurally distinct compounds from over 30 chemical classes have been developed as agricultural fungicides, and these fungicides target many modes of action not represented among human antifungal drugs. In this article we introduce the diverse aspects of agricultural fungicides and compare them with human antifungal drugs. We propose that the information gained from the development of agricultural fungicides can be applied to the discovery of new mechanisms of action and new antifungal agents for the management of human fungal infections.
Zhang, Ming-Qiang; Wilkinson, Barrie
Although a very useful guideline for orally bioavailable small-molecule drug design, the 'rule-of-five' (also known as 'Lipinski's rule of drug-likeness') has to some extent been overemphasized. Firstly, only 51% of all FDA-approved small-molecule drugs are both used orally and comply with the 'rule-of-five'. This does not even include the increasing number of biologicals of which several have reached 'blockbuster' status. Secondly, it does not cover natural product and semisynthetic natural product drugs, which constitute over one-third of all marketed small-molecule drugs. A more balanced and programmatic approach to drug discovery should be more productive than to rely on an overemphasis of 'rule-of-five' compliance. Rather it should consider proactively the development of parenteral drugs in parallel to oral drugs and to consider the development of therapeutic antibodies in parallel to small-molecule drugs. These are particularly relevant for efforts against 'first-in-class' and/or particularly challenging targets such as proteases and those involving protein-protein interactions. In addition, more effort should be invested in natural product research. Emerging novel technologies such as synthetic biology (genetic engineering of living organisms to produce small-molecule therapeutics) may address several challenging issues of natural product-based drug discovery including synthetic feasibility and ligand efficiency.
Brown, Eric D; Wright, Gerard D
The looming antibiotic-resistance crisis has penetrated the consciousness of clinicians, researchers, policymakers, politicians and the public at large. The evolution and widespread distribution of antibiotic-resistance elements in bacterial pathogens has made diseases that were once easily treatable deadly again. Unfortunately, accompanying the rise in global resistance is a failure in antibacterial drug discovery. Lessons from the history of antibiotic discovery and fresh understanding of antibiotic action and the cell biology of microorganisms have the potential to deliver twenty-first century medicines that are able to control infection in the resistance era.
Decher, Niels; Netter, Michael F; Streit, Anne K
Virtually all organisms use RNA editing as a powerful post-transcriptional mechanism to recode genomic information and to increase functional protein diversity. The enzymatic editing of pre-mRNA by ADARs and CDARs is known to change the functional properties of neuronal receptors and ion channels regulating cellular excitability. However, RNA editing is also an important mechanism for genes expressed outside the brain. The fact that RNA editing breaks the 'one gene encodes one protein' hypothesis is daunting for scientists and a probable drawback for drug development, as scientists might search for drugs targeting the 'wrong' protein. This possible difficulty for drug discovery and development became more evident from recent publications, describing that RNA editing events have profound impact on the pharmacology of some common drug targets. These recent studies highlight that RNA editing can cause massive discrepancies between the in vitro and in vivo pharmacology. Here, we review the putative impact of RNA editing on drug discovery, as RNA editing has to be considered before using high-throughput screens, rational drug design or choosing the right model organism for target validation.
Quan, Yuan; Xiong, Le; Chen, Jing; Zhang, Hong-Yu
Mycobacterium tuberculosis (Mtb), the pathogen of tuberculosis (TB), is one of the most infectious bacteria in the world. The traditional strategy to combat TB involves targeting the pathogen directly; however, the rapid evolution of drug resistance lessens the efficiency of this anti-TB method. Therefore, in recent years, some researchers have turned to an alternative anti-TB strategy, which hinders Mtb infection through targeting host genes. In this work, using a theoretical genetic analysis, we identified 170 Mtb infection-associated genes from human genetic variations related to Mtb infection. Then, the agents targeting these genes were identified to have high potential as anti-TB drugs. In particular, the agents that can target multiple Mtb infection-associated genes are more druggable than the single-target counterparts. These potential anti-TB agents were further screened by gene expression data derived from connectivity map. As a result, some agents were revealed to have high interest for experimental evaluation. This study not only has important implications for anti-TB drug discovery, but also provides inspirations for streamlining the pipeline of modern drug discovery.
Garg, Vibhav; Arora, Suchir; Gupta, Chitra
Continued advancements in the area of technology have helped high throughput screening (HTS) evolve from a linear to parallel approach by performing system level screening. Advanced experimental methods used for HTS at various steps of drug discovery (i.e. target identification, target validation, lead identification and lead validation) can generate data of the order of terabytes. As a consequence, there is pressing need to store, manage, mine and analyze this data to identify informational tags. This need is again posing challenges to computer scientists to offer the matching hardware and software infrastructure, while managing the varying degree of desired computational power. Therefore, the potential of "On-Demand Hardware" and "Software as a Service (SAAS)" delivery mechanisms cannot be denied. This on-demand computing, largely referred to as Cloud Computing, is now transforming the drug discovery research. Also, integration of Cloud computing with parallel computing is certainly expanding its footprint in the life sciences community. The speed, efficiency and cost effectiveness have made cloud computing a 'good to have tool' for researchers, providing them significant flexibility, allowing them to focus on the 'what' of science and not the 'how'. Once reached to its maturity, Discovery-Cloud would fit best to manage drug discovery and clinical development data, generated using advanced HTS techniques, hence supporting the vision of personalized medicine.
Brown, David G; Shotton, Elizabeth J
Structure-based drug design has become a key tool for the development of novel drugs. The process involves elucidating the three-dimensional structure of the potential drug molecule bound to the target protein that has been identified as playing a key role in the disease state. Using this three-dimensional information facilitates the process of making improvements to the potential drug molecule by highlighting existing and possible new interactions within the binding site. This knowledge is used to inform increases in potency and selectivity of the molecules as well as to help improve other drug-like properties. The speed and numbers of samples that can be studied, combined with the improved resolution of the structures that can be obtained using synchrotron radiation, have had a significant impact on the utilization of crystallography in the drug discovery process.
Schiess, Ralph; Wollscheid, Bernd; Aebersold, Ruedi
The high complexity and large dynamic range of blood plasma proteins currently prohibit the sensitive and high-throughput profiling of disease and control plasma proteome sample sets large enough to reliably detect disease indicating differences. To circumvent these technological limitations we describe here a new two-stage strategy for the mass spectrometry (MS) assisted discovery, verification and validation of disease biomarkers. In an initial discovery phase N-linked glycoproteins with distinguishable expression patterns in primary normal and diseased tissue are detected and identified. In the second step the proteins identified in the initial phase are subjected to targeted MS analysis in plasma samples, using the highly sensitive and specific selected reaction monitoring (SRM) technology. Since glycosylated proteins, such as those secreted or shed from the cell surface are likely to reside and persist in blood, the two-stage strategy is focused on the quantification of tissue derived glycoproteins in plasma. The focus on the N-glycoproteome not only reduces the complexity of the analytes, but also targets an information-rich subproteome which is relevant for remote sensing of diseases in the plasma. The N-glycoprotein based biomarker discovery and validation workflow reviewed here allows for the robust identification of protein candidate panels that can finally be selectively monitored in the blood plasma at high sensitivity in a reliable, non-invasive and quantitative fashion.
Introduction There is an immediate need for functional and molecular studies to decipher differences between disease and “normal” settings to identify large quantities of validated targets with the highest therapeutic utilities. Furthermore, drug mechanism of action and biomarkers to predict drug efficacy and safety need to be identified for effective design of clinical trials, decreasing attrition rates, regulatory agency approval process and drug repositioning. By expanding the power of genetics and pharmacogenetics studies, next generation nucleic acid sequencing technologies have started to play an important role in all stages of drug discovery. Areas covered This article reviews the first and second generation sequencing technologies (SGSTs) and challenges they pose to biomedicine. The article then focuses on the emerging third generation sequencing technologies (TGSTs), their technological foundations and potential contributions to drug discovery. Expert Opinion Despite the scientific and commercial success of SGSTs, the goal of rapid, comprehensive and unbiased sequencing of nucleic acids has not been achieved. TGSTs promise to increase sequencing throughput and read lengths, decrease costs, run times and error rates, eliminate biases inherent in SGSTs, and offer capabilities beyond nucleic acid sequencing. Such changes will have positive impact in all sequencing applications to drug discovery. PMID:22468954
Weaver, Ian N; Weaver, Donald F
Drug design and discovery is an innovation process that translates the outcomes of fundamental biomedical research into therapeutics that are ultimately made available to people with medical disorders in many countries throughout the world. To identify which nations succeed, exceed, or fail at the drug design/discovery endeavor--more specifically, which countries, within the context of their national size and wealth, are "pulling their weight" when it comes to developing medications targeting the myriad of diseases that afflict humankind--we compiled and analyzed a comprehensive survey of all new drugs (small molecular entities and biologics) approved annually throughout the world over the 20-year period from 1991 to 2010. Based upon this analysis, we have devised prediction algorithms to ascertain which countries are successful (or not) in contributing to the worldwide need for effective new therapeutics.
Cromie, Karen D; Van Heeke, Gino; Boutton, Carlo
Nanobodies are therapeutic proteins derived from the variable domain (VHH) of naturally occurring heavy-chain antibodies. These VHH domains are the smallest functional fragments derived from a naturally occurring immunoglobulin. Nanobodies can be easily produced in prokaryotic or eukaryotic host organisms and their unique biophysical characteristics render these molecules ideal candidates for drug development. They are also emerging as an interesting new class of potential therapeutics for targets such as GPCRs, which have historically been challenging for small molecule drug discovery and even more difficult for biologics discovery. The ability to easily combine Nanobodies with different binding sites and different modes of action can be used to generate highly selective and highly potent drug candidates with very attractive pharmacological profiles. In addition, Nanobodies have been used as crystallization chaperones to enable or facilitate the structural determination of an active GPCR conformation.
Skora, Lukasz; Jahnke, Wolfgang
Drug discovery is a complex process, and a variety of technologies contribute to its success. Biophysical methods have gained widespread attention within the last decade, and in particular NMR spectroscopy as the most versatile biophysical method has seen numerous applications and significant impact to drug discovery. Here we summarize the potential of NMR to support drug discovery, and highlight a number of recent applications.
Lai, Ashton C; Crews, Craig M
Small-molecule drug discovery has traditionally focused on occupancy of a binding site that directly affects protein function, and this approach typically precludes targeting proteins that lack such amenable sites. Furthermore, high systemic drug exposures may be needed to maintain sufficient target inhibition in vivo, increasing the risk of undesirable off-target effects. Induced protein degradation is an alternative approach that is event-driven: upon drug binding, the target protein is tagged for elimination. Emerging technologies based on proteolysis-targeting chimaeras (PROTACs) that exploit cellular quality control machinery to selectively degrade target proteins are attracting considerable attention in the pharmaceutical industry owing to the advantages they could offer over traditional small-molecule strategies. These advantages include the potential to reduce systemic drug exposure, the ability to counteract increased target protein expression that often accompanies inhibition of protein function and the potential ability to target proteins that are not currently therapeutically tractable, such as transcription factors, scaffolding and regulatory proteins.
Volker, Craig; Brown, James R
Genomic research is playing a critical role in the discovery of new anti-microbial drugs. The rapid increase in bacterial and eukaryotic genome sequences allows for new and innovative ways for obtaining antimicrobial protein targets. Here, we describe a two level strategy for target identification and validation using computers (in silico). First, large scale comparative analyses of genome sequences were used to identify highly conserved genes which might be essential for in vitro and/or in vivo survival of bacterial pathogens. Lab-based experiments provided confirmation or validation of the hypothesis of in silico essentiality for over 350 individual genes. Over 200 validated, broad spectrum; yet highly specific gene targets, were identified in community infection pathogens. The second part of the target discovery strategy is an in-depth evolutionary, structural and cellular analysis of key drug targets. As an example, phylogenetic and structural analyses suggest that sequence and binding-pocket conservation in FabH (beta-ketoacyl-ACP synthase III) would allow for the development of small molecule inhibitors not only effective against a broad species spectrum of community bacterial pathogens but also as potential new therapies for tuberculosis and malaria.
Ortega, Santiago Schiaffino; Cara, Luisa Carlota López; Salvador, María Kimatrai
The process of bringing new and innovative drugs, from conception and synthesis through to approval on the market can take the pharmaceutical industry 8-15 years and cost approximately $1.8 billion. Two key technologies are improving the hit-to-drug timeline: high-throughput screening (HTS) and rational drug design. In the latter case, starting from some known ligand-based or target-based information, a lead structure will be rationally designed to be tested in vitro or in vivo. Computational methods are part of many drug discovery programs, including the assessment of ADME (absorption-distribution-metabolism-excretion) and toxicity (ADMET) properties of compounds at the early stages of discovery/development with impressive results. The aim of this paper is to review, in a simple way, some of the most popular strategies used by modelers and some successful applications on computational chemistry to raise awareness of its importance and potential for an actual multidisciplinary drug discovery process.
Batra, Ankita S; Greenwood, Wendy
Despite remarkable advances in our understanding of the drivers of human malignancies, new targeted therapies often fail to show sufficient efficacy in clinical trials. Indeed, the cost of bringing a new agent to market has risen substantially in the last several decades, in part fuelled by extensive reliance on preclinical models that fail to accurately reflect tumour heterogeneity. To halt unsustainable rates of attrition in the drug discovery process, we must develop a new generation of preclinical models capable of reflecting the heterogeneity of varying degrees of complexity found in human cancers. Patient-derived tumour xenograft (PDTX) models prevail as arguably the most powerful in this regard because they capture cancer’s heterogeneous nature. Herein, we review current breast cancer models and their use in the drug discovery process, before discussing best practices for developing a highly annotated cohort of PDTX models. We describe the importance of extensive multidimensional molecular and functional characterisation of models and combination drug–drug screens to identify complex biomarkers of drug resistance and response. We reflect on our own experiences and propose the use of a cost-effective intermediate pharmacogenomic platform (the PDTX-PDTC platform) for breast cancer drug and biomarker discovery. We discuss the limitations and unanswered questions of PDTX models; yet, still strongly envision that their use in basic and translational research will dramatically change our understanding of breast cancer biology and how to more effectively treat it. PMID:27702751
Andrade, E.L.; Bento, A.F.; Cavalli, J.; Oliveira, S.K.; Freitas, C.S.; Marcon, R.; Schwanke, R.C.; Siqueira, J.M.; Calixto, J.B.
This review presents a historical overview of drug discovery and the non-clinical stages of the drug development process, from initial target identification and validation, through in silico assays and high throughput screening (HTS), identification of leader molecules and their optimization, the selection of a candidate substance for clinical development, and the use of animal models during the early studies of proof-of-concept (or principle). This report also discusses the relevance of validated and predictive animal models selection, as well as the correct use of animal tests concerning the experimental design, execution and interpretation, which affect the reproducibility, quality and reliability of non-clinical studies necessary to translate to and support clinical studies. Collectively, improving these aspects will certainly contribute to the robustness of both scientific publications and the translation of new substances to clinical development. PMID:27783811
Andrade, E L; Bento, A F; Cavalli, J; Oliveira, S K; Freitas, C S; Marcon, R; Schwanke, R C; Siqueira, J M; Calixto, J B
This review presents a historical overview of drug discovery and the non-clinical stages of the drug development process, from initial target identification and validation, through in silico assays and high throughput screening (HTS), identification of leader molecules and their optimization, the selection of a candidate substance for clinical development, and the use of animal models during the early studies of proof-of-concept (or principle). This report also discusses the relevance of validated and predictive animal models selection, as well as the correct use of animal tests concerning the experimental design, execution and interpretation, which affect the reproducibility, quality and reliability of non-clinical studies necessary to translate to and support clinical studies. Collectively, improving these aspects will certainly contribute to the robustness of both scientific publications and the translation of new substances to clinical development.
drug design and development. The biological focus of our research addresses estrogen biosynthesis and on estrogen- induced gene expression in hormone-dependent breast cancer. Identification of critical small molecule-protein and protein-protein interactions during gene expression and signal transduction in the areas of steroidogenesis and estrogen-induced responses will result in new molecular targets for drug discovery and design for the treatment of hormone-dependent breast cancer. The Sabbatical Training Grant provided an enhancement of our research endeavors by
The application of structural genomics methods and approaches to proteins from organisms causing infectious diseases is making available the three dimensional structures of many proteins that are potential drug targets and laying the groundwork for structure aided drug discovery efforts. There are a number of structural genomics projects with a focus on pathogens that have been initiated worldwide. The Center for Structural Genomics of Infectious Diseases (CSGID) was recently established to apply state-of-the-art high throughput structural biology technologies to the characterization of proteins from the National Institute for Allergy and Infectious Diseases (NIAID) category A-C pathogens and organisms causing emerging, or re-emerging infectious diseases. The target selection process emphasizes potential biomedical benefits. Selected proteins include known drug targets and their homologs, essential enzymes, virulence factors and vaccine candidates. The Center also provides a structure determination service for the infectious disease scientific community. The ultimate goal is to generate a library of structures that are available to the scientific community and can serve as a starting point for further research and structure aided drug discovery for infectious diseases. To achieve this goal, the CSGID will determine protein crystal structures of 400 proteins and protein-ligand complexes using proven, rapid, highly integrated, and cost-effective methods for such determination, primarily by X-ray crystallography. High throughput crystallographic structure determination is greatly aided by frequent, convenient access to high-performance beamlines at third-generation synchrotron X-ray sources.
LaPlante, Steven R; Edwards, Paul J; Fader, Lee D; Jakalian, Araz; Hucke, Oliver
An often overlooked source of chirality is atropisomerism, which results from slow rotation along a bond axis due to steric hindrance and/or electronic factors. If undetected or not managed properly, this time-dependent chirality has the potential to lead to serious consequences, because atropisomers can be present as distinct enantiomers or diastereoisomers with their attendant different properties. Herein we introduce a strategy to reveal and classify compounds that have atropisomeric chirality. Energy barriers to axial rotation were calculated using quantum mechanics, from which predicted high barriers could be experimentally validated. A calculated rotational energy barrier of 20 kcal mol(-1) was established as a suitable threshold to distinguish between atropisomers and non-atropisomers with a prediction accuracy of 86%. This methodology was applied to subsets of drug databases in the course of which atropisomeric drugs were identified. In addition, some drugs were exposed that were not yet known to have this chiral attribute. The most valuable utility of this tool will be to predict atropisomerism along the drug discovery pathway. When used in concert with our compound classification scheme, decisions can be made during early discovery stages such as "hit-to-lead" and "lead optimization," to foresee and validate the presence of atropisomers and to exercise options of removing, further stabilizing, or rendering the chiral axis of interest more freely rotatable via SAR design, thereby decreasing this potential liability within a compound series. The strategy can also improve drug development plans, such as determining whether a drug or series should be developed as a racemic mixture or as an isolated single compound. Moreover, the work described herein can be extended to other chemical fields that require the assessment of potential chiral axes.
Felder, Christian C
The Strategic Research Institute provided a well-organised 2-day summit that offered presentations and posters on new assay technology, structure-based small-molecule discovery and examples of clinical candidates targeted to G-protein-coupled receptor (GPCR) targets. A wide variety of topics were presented providing recent advances in GPCR target selection, bioassay-enabling technology and medicinal chemistry targeted to GPCR-relevant chemical libraries. GPCRs continue to be an attractive platform for drug discovery.
Wang, Huanchen; Godage, Himali Y; Riley, Andrew M; Weaver, Jeremy D; Shears, Stephen B; Potter, Barry V L
Diphosphoinositol pentakisphosphate kinase 2 (PPIP5K2) is one of the mammalian PPIP5K isoforms responsible for synthesis of diphosphoinositol polyphosphates (inositol pyrophosphates; PP-InsPs), regulatory molecules that function at the interface of cell signaling and organismic homeostasis. The development of drugs that inhibit PPIP5K2 could have both experimental and therapeutic applications. Here, we describe a synthetic strategy for producing naturally occurring 5-PP-InsP4, as well as several inositol polyphosphate analogs, and we study their interactions with PPIP5K2 using biochemical and structural approaches. These experiments uncover an additional ligand-binding site on the surface of PPIP5K2, adjacent to the catalytic pocket. This site facilitates substrate capture from the bulk phase, prior to transfer into the catalytic pocket. In addition to demonstrating a "catch-and-pass" reaction mechanism in a small molecule kinase, we demonstrate that binding of our analogs to the substrate capture site inhibits PPIP5K2. This work suggests that the substrate-binding site offers new opportunities for targeted drug design.
Herold, J. Martin; Ingerman, Lindsey A; Gao, Cen; Frye, Stephen V
The recognition of methyl-lysine and -arginine residues on both histone and other proteins by specific “reader” elements is important for chromatin regulation, gene expression, and control of cell-cycle progression. Recently the crucial role of these reader proteins in cancer development and dedifferentiation has emerged, owing to the increased interest among the scientific community. The methyl-lysine and -arginine readers are a large and very diverse set of effector proteins and targeting them with small molecule probes in drug discovery will inevitably require a detailed understanding of their structural biology and mechanism of binding. In the following review, the critical elements of methyl-lysine and -arginine recognition will be summarized with respect to each protein family and initial results in assay development, probe design, and drug discovery will be highlighted. PMID:22145013
Chang, Cheng; Ekins, Sean; Bahadduri, Praveen; Swaan, Peter W.
The ability to identify ligands for drug transporters is an important step in drug discovery and development. It can both improve accurate profiling of lead pharmacokinetic properties and assist in the discovery of new chemical entities targeting transporters. In silico approaches, especially pharmacophore-based database screening methods have great potential in improving the throughput of current transporter ligand identification assays, leading to a higher hit rate by focusing in vitro testing to the most promising hits. In this review, the potential of different in silico methods in transporter ligand identification studies are compared and summarized with an emphasis on pharmacophore modeling. Various implementations of pharmacophore model generation, database compilation and flexible screening algorithms are also introduced. Recent successful utilization of database searching with pharmacophores to identify novel ligands for the pharmaceutically significant transporters hPepT1, P-gp, BCRP, MRP1 and DAT are reviewed and challenges encountered with current approaches are discussed. PMID:17097188
Sacan, Ahmet; Ekins, Sean; Kortagere, Sandhya
Drug discovery in the late twentieth and early twenty-first century has witnessed a myriad of changes that were adopted to predict whether a compound is likely to be successful, or conversely enable identification of molecules with liabilities as early as possible. These changes include integration of in silico strategies for lead design and optimization that perform complementary roles to that of the traditional in vitro and in vivo approaches. The in silico models are facilitated by the availability of large datasets associated with high-throughput screening, bioinformatics algorithms to mine and annotate the data from a target perspective, and chemoinformatics methods to integrate chemistry methods into lead design process. This chapter highlights the applications of some of these methods and their limitations. We hope this serves as an introduction to in silico drug discovery.
Blair, Wade; Perros, Manos
The 5th Antiviral Drug Discovery and Development Summit provided an up-to-date snapshot of the ongoing developments in the area. The topics covered ranged from updates on recently launched drugs (Kaletra), Fuzeon) and new investigational inhibitors (T-1249, Reverset, UK-427857, L-870810, PA-457, remofovir, VX-950), to the discovery of new antiviral targets and advances in technologies that may provide the substrate for the next generation of therapeutics. It is apparent from the range of presentations that much of today's efforts are focused on developing new classes of HIV inhibitors (gp41, integrase), while there is also considerable progress in hepatitis C, where a number of inhibitors have or should reach proof-of-concept studies in the coming months. Here we provide the highlights of this meeting, with particular emphasis on the new developments in HIV and hepatitis C virus.
Blat, Yuval; Blat, Shachar
Duchenne muscular dystrophy (DMD) is a genetic, lethal, muscle disorder caused by the loss of the muscle protein, dystrophin, leading to progressive loss of muscle fibers and muscle weakness. Drug discovery efforts targeting DMD have used two main approaches: (1) the restoration of dystrophin expression or the expression of a compensatory protein, and (2) the mitigation of downstream pathological mechanisms, including dysregulated calcium homeostasis, oxidative stress, inflammation, fibrosis, and muscle ischemia. The aim of this review is to introduce the disease, its pathophysiology, and the available research tools to a drug discovery audience. This review will also detail the most promising therapies that are currently being tested in clinical trials or in advanced preclinical models.
Bortolato, Andrea; Doré, Andrew S; Hollenstein, Kaspar; Tehan, Benjamin G; Mason, Jonathan S; Marshall, Fiona H
Class B GPCRs of the secretin family are important drug targets in many human diseases including diabetes, neurodegeneration, cardiovascular disease and psychiatric disorders. X-ray crystal structures for the glucagon receptor and corticotropin-releasing factor receptor 1 have now been published. In this review, we analyse the new structures and how they compare with each other and with Class A and F receptors. We also consider the differences in druggability and possible similarity in the activation mechanisms. Finally, we discuss the potential for the design of small-molecule modulators for these important targets in drug discovery. This new structural insight allows, for the first time, structure-based drug design methods to be applied to Class B GPCRs. PMID:24628305
We report the discovery of a series of new drug leads that have potent activity against Mycobacterium tuberculosis as well as against other bacteria, fungi, and a malaria parasite. The compounds are analogues of the new tuberculosis (TB) drug SQ109 (1), which has been reported to act by inhibiting a transporter called MmpL3, involved in cell wall biosynthesis. We show that 1 and the new compounds also target enzymes involved in menaquinone biosynthesis and electron transport, inhibiting respiration and ATP biosynthesis, and are uncouplers, collapsing the pH gradient and membrane potential used to power transporters. The result of such multitarget inhibition is potent inhibition of TB cell growth, as well as very low rates of spontaneous drug resistance. Several targets are absent in humans but are present in other bacteria, as well as in malaria parasites, whose growth is also inhibited. PMID:24568559
Mercola, Mark; Colas, Alexandre; Willems, Erik
The unexpected discovery that somatic cells can be reprogrammed to a pluripotent state yielding induced pluripotent stem cells (iPSCs) has made it possible to produce cardiovascular cells exhibiting inherited traits and disorders. Use of these cells in high throughput analyses should broaden our insight into fundamental disease mechanisms and provide many benefits for patients, including new therapeutics and individually tailored therapies. Here we review recent progress in generating iPSC-based models of cardiovascular disease and their multiple applications in drug development. PMID:23371902
Nagle, Dale G.; Zhou, Yu-Dong; Mora, Flor D.; Mohammed, Kaleem A.; Kim, Yong-Pil
Antitumor drug discovery programs aim to identify chemical entities for use in the treatment of cancer. Many strategies have been used to achieve this objective. Natural products have always played a major role in anticancer medicine and the unique metabolites produced by marine organisms have increasingly become major players in antitumor drug discovery. Rapid advances have occurred in the understanding of tumor biology and molecular medicine. New insights into mechanisms responsible for neoplastic disease are significantly changing the general philosophical approach towards cancer treatment. Recently identified molecular targets have created exciting new means for disrupting tumor-specific cell signaling, cell division, energy metabolism, gene expression, drug resistance, and blood supply. Such tumor-specific treatments could someday decrease our reliance on traditional cytotoxicity-based chemotherapy and provide new less toxic treatment options with significantly fewer side effects. Novel molecular targets and state-of-the-art molecular mechanism-based screening methods have revitalized antitumor research and these changes are becoming an ever-increasing component of modern antitumor marine natural products research. This review describes marine natural products identified using tumor-specific mechanism-based assays for regulators of angiogenesis, apoptosis, cell cycle, macromolecule synthesis, mitochondrial respiration, mitosis, multidrug efflux, and signal transduction. Special emphasis is placed on natural products directly discovered using molecular mechanism-based screening. PMID:15279579
Montazerhodjat, Vahid; Frishkopf, John J; Lo, Andrew W
We extend the megafund concept for funding drug discovery to enable dynamic leverage in which the portfolio of candidate therapeutic assets is predominantly financed initially by equity, and debt is introduced gradually as assets mature and begin generating cash flows. Leverage is adjusted so as to maintain an approximately constant level of default risk throughout the life of the fund. Numerical simulations show that applying dynamic leverage to a small portfolio of orphan drug candidates can boost the return on equity almost twofold compared with securitization with a static capital structure. Dynamic leverage can also add significant value to comparable all-equity-financed portfolios, enhancing the return on equity without jeopardizing debt performance or increasing risk to equity investors.
Lim, William K
G protein-coupled receptors (GPCRs) are the largest class of cell surface receptors in humans. They convey extracellular signals into the cell interior by activating intracellular processes such as heterotrimeric G protein-dependent signaling pathways. They are widely distributed in the nervous system, and mediate key physiological processes including cognition, mood, appetite, pain and synaptic transmission. With at least 30% of marketed drugs being GPCR modulators, they are a major therapeutic target in the pharmaceutical industry's drug discovery programs. This review will survey recently patented ligands for GPCRs implicated in CNS disorders, in particular the metabotropic glutamate, adenosine and cannabinoid receptors. Metabotropic glutamate receptors regulate signaling by glutamate, the major excitatory brain neurotransmitter, while adenosine is a ubiquitous neuromodulater mediating diverse physiological effects. Recent patents for ligands of these receptors include mGluR5 antagonists and adenosine A(1) receptor agonists. Cannabinoid receptors remain one of the most important GPCR drug discovery target due to the intense interest in CB(1) receptor antagonists for treating obesity and metabolic syndrome. Such small molecule ligands are the outcome of the continuing focus of many pharmaceutical companies to identify novel GPCR agonist, antagonist or allosteric modulators useful for CNS disorders, for which more effective drugs are eagerly awaited.
Wu, Hongjin; Wang, Charles; Wu, Shixiu
Next-generation sequencing (NGS), particularly single-cell sequencing, has revolutionized the scale and scope of genomic and biomedical research. Recent technological advances in NGS and single-cell studies have made the deep whole-genome (DNA-seq), whole epigenome and whole-transcriptome sequencing (RNA-seq) at single-cell level feasible. NGS at the single-cell level expands our view of genome, epigenome and transcriptome and allows the genome, epigenome and transcriptome of any organism to be explored without a priori assumptions and with unprecedented throughput. And it does so with single-nucleotide resolution. NGS is also a very powerful tool for drug discovery and drug development. In this review, we describe the current state of single-cell sequencing techniques, which can provide a new, more powerful and precise approach for analyzing effects of drugs on treated cells and tissues. Our review discusses single-cell whole genome/exome sequencing (scWGS/scWES), single-cell transcriptome sequencing (scRNA-seq), single-cell bisulfite sequencing (scBS), and multiple omics of single-cell sequencing. We also highlight the advantages and challenges of each of these approaches. Finally, we describe, elaborate and speculate the potential applications of single-cell sequencing for drug discovery and drug development.
Siegel, Marshall M
Electrospray ionization (ESI) and matrix-assisted laser desorption/ionization (MALDI) mass spectrometric methods useful for early discovery drug screening are reviewed. All methods described involve studies of non-covalent complexes between biopolymer receptors and small molecule ligands formed in the condensed phase. The complexes can be sprayed intact directly into the gas phase by ESI-MS using gentle experimental conditions. Gas phase screening applications are illustrated for drug ligand candidates non-covalently interacting with peptides, proteins, RNA, and DNA. In the condensed phase, the complexes can be also isolated, denatured and analyzed by ESI-MS to identify the small molecule ligands. Condensed phase drug screening examples are illustrated for the ESI-MS ancillary techniques of affinity chromatography, ultrafiltration, ultracentrifugation, gel permeation chromatography (GPC), reverse phase-high performance liquid chromatography (RP-HPLC) and capillary electrophoretic methods. Solid phase drug screening using MALDI-MS is illustrated for small molecule ligands bound to MALDI affinity probe tips and to beads. Since ESI and MALDI principally produce molecular ions, high throughput screening is achieved by analyzing mass indexed mixtures.
Park, Soo-Jin; Im, Dong-Soon
Initial discovery on sphingosine 1-phosphate (S1P) as an intracellular second messenger was faced unexpectedly with roles of S1P as a first messenger, which subsequently resulted in cloning of its G protein-coupled receptors, S1P1–5. The molecular identification of S1P receptors opened up a new avenue for pathophysiological research on this lipid mediator. Cellular and molecular in vitro studies and in vivo studies on gene deficient mice have elucidated cellular signaling pathways and the pathophysiological meanings of S1P receptors. Another unexpected finding that fingolimod (FTY720) modulates S1P receptors accelerated drug discovery in this field. Fingolimod was approved as a first-in-class, orally active drug for relapsing multiple sclerosis in 2010, and its applications in other disease conditions are currently under clinical trials. In addition, more selective S1P receptor modulators with better pharmacokinetic profiles and fewer side effects are under development. Some of them are being clinically tested in the contexts of multiple sclerosis and other autoimmune and inflammatory disorders, such as, psoriasis, Crohn’s disease, ulcerative colitis, polymyositis, dermatomyositis, liver failure, renal failure, acute stroke, and transplant rejection. In this review, the authors discuss the state of the art regarding the status of drug discovery efforts targeting S1P receptors and place emphasis on potential clinical applications. PMID:28035084
Ortí, Leticia; Carbajo, Rodrigo J.; Pieper, Ursula; Eswar, Narayanan; Maurer, Stephen M.; Rai, Arti K.; Taylor, Ginger; Todd, Matthew H.; Pineda-Lucena, Antonio; Sali, Andrej; Marti-Renom, Marc A.
Background Conventional patent-based drug development incentives work badly for the developing world, where commercial markets are usually small to non-existent. For this reason, the past decade has seen extensive experimentation with alternative R&D institutions ranging from private–public partnerships to development prizes. Despite extensive discussion, however, one of the most promising avenues—open source drug discovery—has remained elusive. We argue that the stumbling block has been the absence of a critical mass of preexisting work that volunteers can improve through a series of granular contributions. Historically, open source software collaborations have almost never succeeded without such “kernels”. Methodology/Principal Findings Here, we use a computational pipeline for: (i) comparative structure modeling of target proteins, (ii) predicting the localization of ligand binding sites on their surfaces, and (iii) assessing the similarity of the predicted ligands to known drugs. Our kernel currently contains 143 and 297 protein targets from ten pathogen genomes that are predicted to bind a known drug or a molecule similar to a known drug, respectively. The kernel provides a source of potential drug targets and drug candidates around which an online open source community can nucleate. Using NMR spectroscopy, we have experimentally tested our predictions for two of these targets, confirming one and invalidating the other. Conclusions/Significance The TDI kernel, which is being offered under the Creative Commons attribution share-alike license for free and unrestricted use, can be accessed on the World Wide Web at http://www.tropicaldisease.org. We hope that the kernel will facilitate collaborative efforts towards the discovery of new drugs against parasites that cause tropical diseases. PMID:19381286
Zdrazil, Barbara; Chichester, Christine; Zander Balderud, Linda; Engkvist, Ola; Gaulton, Anna; Overington, John P
Transport proteins represent an eminent class of drug targets and ADMET (absorption, distribution, metabolism, excretion, toxicity) associated genes. There exists a large number of distinct activity assays for transport proteins, depending on not only the measurement needed (e.g. transport activity, strength of ligand–protein interaction), but also due to heterogeneous assay setups used by different research groups. Efforts to systematically organize this (divergent) bioassay data have large potential impact in Public-Private partnership and conventional commercial drug discovery. In this short review, we highlight some of the frequently used high-throughput assays for transport proteins, and we discuss emerging assay ontologies and their application to this field. Focusing on human P-glycoprotein (Multidrug resistance protein 1; gene name: ABCB1, MDR1), we exemplify how annotation of bioassay data per target class could improve and add to existing ontologies, and we propose to include an additional layer of metadata supporting data fusion across different bioassays.
Skinner, Gary M; Visscher, Koen
Single-molecule techniques offer a number of key benefits over conventional in vitro assay methods for drug screening, as they use less material and unlock the ability to observe transient states. By observing such states, it should be possible to screen for chemical compounds that isolate these steps. The benefit of this is twofold: (a) inhibitors can be found that target key phases in biochemical processes, e.g., transcription initiation; and (b) the total number of drug targets increases as many biochemical processes consist of many transient steps, e.g., transcription promoter binding, initiation, elongation, and termination. Although single-molecule methods offer exciting opportunities for new ways of discovering drugs, there are a number of obstacles to their adoption for drug screening. The main hurdle is to develop robust apparatus that will allow many thousands of individual single molecule experiments to be performed in parallel. By using recently developed integrated microfluidics technology, this hurdle may be overcome. Here, a number of potential single-molecule approaches to drug screening are presented along with a discussion of the benefits and technical obstacles that must be overcome.
Liang, X-J; Aszalos, A
Transport molecules can significantly affect the pharmacodynamics and pharmacokinetics of drugs. An important transport molecule, the 170 kDa P-glycoprotein (Pgp), is constitutively expressed at several organ sites in the human body. Pgp is expressed at the blood-brain barrier, in the kidneys, liver, intestines and in certain T cells. Other transporters such as the multidrug resistance protein 1 (MRP1) and MRP2 also contribute to drug distribution in the human body, although to a lesser extent than Pgp. These three transporters, and especially Pgp, are often targets of drugs. Pgp can be an intentional or unintentional target. It is directly targeted when one wants to block its function by a modifier drug so that another drug, also a substrate of Pgp, can penetrate the cell membrane, which would otherwise be impermeable. Unintentional targeting occurs when several drugs are administered to a patient and as a consequence, the physiological function of Pgp is blocked at different organ sites. Like Pgp, MRP1 also has the capacity to mediate transport of many drugs and other compounds. MRP1 has a protective role in preventing accumulation of toxic compounds and drugs in epithelial tissue covering the choroid plexus/cerebrospinal fluid compartment, oral epithelium, sertoli cells, intesticular tubules and urinary collecting duct cells. MRP2 primarily transports weakly basic drugs and bilirubin from the liver to bile. Most compounds that efficiently block Pgp have only low affinity for MRP1 and MRP2. There are only a few effective and specific MRP inhibitors available. Drug targeting of these transporters may play a role in cancer chemotherapy and in the pharmacokinetics of substrate drugs.
Doweyko, Arthur M; Doweyko, Lidia M
Humankind has been in the business of discovering drugs for thousands of years. At present, small-molecule drug design is based on specific macromolecular receptors as targets for inhibition or modulation. To this end, a number of clever approaches have evolved over time: computer-aided techniques including structure-activity relationships and synthesis, high-throughput screening, quantitative structure-activity relationships, hypotheses derived from ligand- and/or structure-based information and focused library approaches. In recent years, several alternative strategies have appeared in the form of the emerging paradigms of polypharmacology, systems biology and personalized medicine. These innovations point to key challenges and breakthroughs likely to affect the future of small-molecule drug discovery.
Hulkower, Keren I; Herber, Renee L
Cell migration and invasion are processes that offer rich targets for intervention in key physiologic and pathologic phenomena such as wound healing and cancer metastasis. With the advent of high-throughput and high content imaging systems, there has been a movement towards the use of physiologically relevant cell-based assays earlier in the testing paradigm. This allows more effective identification of lead compounds and recognition of undesirable effects sooner in the drug discovery screening process. This article will review the effective use of several principle formats for studying cell motility: scratch assays, transmembrane assays, microfluidic devices and cell exclusion zone assays.
Tsvetanova, Billyana; Peng, Lansha; Liang, Xiquan; Li, Ke; Hammond, Linda; Peterson, Todd C; Katzen, Federico
Recombinant DNA technologies have had a fundamental impact on drug discovery. The continuous emergence of unique gene assembly techniques resulted in the generation of a variety of therapeutic reagents such as vaccines, cancer treatment molecules and regenerative medicine precursors. With the advent of synthetic biology there is a growing need for precise and concerted assembly of multiple DNA fragments of various sizes, including chromosomes. In this article, we summarize the highlights of the recombinant DNA technology since its inception in the early 1970s, emphasizing on the most recent advances, and underscoring their principles, advantages and shortcomings. Current and prior cloning trends are discussed in the context of sequence requirements and scars left behind. Our opinion is that despite the remarkable progress that has enabled the generation and manipulation of very large DNA sequences, a better understanding of the cell's natural circuits is needed in order to fully exploit the current state-of-the-art gene assembly technologies.
Leal, Miguel C; Calado, Ricardo; Sheridan, Christopher; Alimonti, Andrea; Osinga, Ronald
Marine natural products (NP) are unanimously acknowledged as the 'blue gold' in the urgent quest for new pharmaceuticals. Although corals are among the marine organisms with the greatest diversity of secondary metabolites, growing evidence suggest that their symbiotic bacteria produce most of these bioactive metabolites. The ex hospite culture of coral symbiotic microbiota is extremely challenging and only limited examples of successful culture exist today. By contrast, in toto aquaculture of corals is a commonly applied technology to produce corals for aquaria. Here, we suggest that coral aquaculture could as well be a viable and economically feasible option to produce the biomass required to execute the first steps of the NP-based drug discovery pipeline.
Singeç, Ilyas; Simeonov, Anton
Pluripotent stem cell research has made extraordinary progress over the last decade. The robustness of nuclear reprogramming of somatic cells into induced pluripotent stem cells (iPSCs) has created entirely novel opportunities for drug discovery and personalized regenerative medicine. Patient- and disease-specific iPSCs can be expanded indefinitely and differentiated into relevant cell types of different organ systems. As the utilization of iPSCs is becoming a key enabling technology across various scientific disciplines, there are still important challenges that need to be addressed. Here we review the current state and reflect on the issues that the stem cell and translational communities are facing in bringing iPSCs closer to clinical application. PMID:27774310
Poeta, Maurizio Del
This Special Issue is designed to highlight the latest research and development on new antifungal compounds with mechanisms of action different from the ones of polyenes, azoles, and echinocandins. The papers presented here highlight new pathways and targets that could be exploited for the future development of new antifungal agents to be used alone or in combination with existing antifungals. A computational model for better predicting antifungal drug resistance is also presented. PMID:28058254
Griebel, Guy; Holmes, Andrew
Anxiety disorders are the most prevalent group of psychiatric diseases, and have high personal and societal costs. The search for novel pharmacological treatments for these conditions is driven by the growing medical need to improve on the effectiveness and the side effect profile of existing drugs. A huge volume of data has been generated by anxiolytic drug discovery studies, which has led to the progression of numerous new molecules into clinical trials. However, the clinical outcome of these efforts has been disappointing, as promising results with novel agents in rodent studies have very rarely translated into effectiveness in humans. Here, we analyse the major trends from preclinical studies over the past 50 years conducted in the search for new drugs beyond those that target the prototypical anxiety-associated GABA (γ-aminobutyric acid)–benzodiazepine system, which have focused most intensively on the serotonin, neuropeptide, glutamate and endocannabinoid systems. We highlight various key issues that may have hampered progress in the field, and offer recommendations for how anxiolytic drug discovery can be more effective in the future. PMID:23989795
Recently, ab initio quantum mechanical calculations have been applied to large molecules, including biomolecular systems. The fragment molecular orbital (FMO) method is one of the most efficient approaches for the quantum mechanical investigation of such molecules. In the FMO method, dividing a target molecule into small fragments reduces computational effort. The clear definition of inter-fragment interaction energy (IFIE) as an expression of total energy is another valuable feature of the FMO method because it provides the ability to analyze interactions in biomolecules. Thus, the FMO method is expected to be useful for drug discovery. This study demonstrates applications of the FMO method related to drug discovery. First, IFIE, according to FMO calculations, was used in the optimization of drug candidates for the development of anti-prion compounds. The second example involved interaction analysis of the human immunodeficiency virus type 1 (HIV-1) protease and a drug compound that used a novel analytical method for dispersion interaction, i.e., fragment interaction analysis based on LMP2 (FILM).
Litterman, Nadia K; Rhee, Michele; Swinney, David C; Ekins, Sean
Rare disease research has reached a tipping point, with the confluence of scientific and technologic developments that if appropriately harnessed, could lead to key breakthroughs and treatments for this set of devastating disorders. Industry-wide trends have revealed that the traditional drug discovery research and development (R&D) model is no longer viable, and drug companies are evolving their approach. Rather than only pursue blockbuster therapeutics for heterogeneous, common diseases, drug companies have increasingly begun to shift their focus to rare diseases. In academia, advances in genetics analyses and disease mechanisms have allowed scientific understanding to mature, but the lack of funding and translational capability severely limits the rare disease research that leads to clinical trials. Simultaneously, there is a movement towards increased research collaboration, more data sharing, and heightened engagement and active involvement by patients, advocates, and foundations. The growth in networks and social networking tools presents an opportunity to help reach other patients but also find researchers and build collaborations. The growth of collaborative software that can enable researchers to share their data could also enable rare disease patients and foundations to manage their portfolio of funded projects for developing new therapeutics and suggest drug repurposing opportunities. Still there are many thousands of diseases without treatments and with only fragmented research efforts. We will describe some recent progress in several rare diseases used as examples and propose how collaborations could be facilitated. We propose that the development of a center of excellence that integrates and shares informatics resources for rare diseases sponsored by all of the stakeholders would help foster these initiatives.
Litterman, Nadia K.; Rhee, Michele; Swinney, David C.; Ekins, Sean
Rare disease research has reached a tipping point, with the confluence of scientific and technologic developments that if appropriately harnessed, could lead to key breakthroughs and treatments for this set of devastating disorders. Industry-wide trends have revealed that the traditional drug discovery research and development (R&D) model is no longer viable, and drug companies are evolving their approach. Rather than only pursue blockbuster therapeutics for heterogeneous, common diseases, drug companies have increasingly begun to shift their focus to rare diseases. In academia, advances in genetics analyses and disease mechanisms have allowed scientific understanding to mature, but the lack of funding and translational capability severely limits the rare disease research that leads to clinical trials. Simultaneously, there is a movement towards increased research collaboration, more data sharing, and heightened engagement and active involvement by patients, advocates, and foundations. The growth in networks and social networking tools presents an opportunity to help reach other patients but also find researchers and build collaborations. The growth of collaborative software that can enable researchers to share their data could also enable rare disease patients and foundations to manage their portfolio of funded projects for developing new therapeutics and suggest drug repurposing opportunities. Still there are many thousands of diseases without treatments and with only fragmented research efforts. We will describe some recent progress in several rare diseases used as examples and propose how collaborations could be facilitated. We propose that the development of a center of excellence that integrates and shares informatics resources for rare diseases sponsored by all of the stakeholders would help foster these initiatives. PMID:25685324
Campbell, Robert M; Tummino, Peter J
Over the past several years, there has been rapidly expanding evidence of epigenetic dysregulation in cancer, in which histone and DNA modification play a critical role in tumor growth and survival. These findings have gained the attention of the drug discovery and development community, and offer the potential for a second generation of cancer epigenetic agents for patients following the approved "first generation" of DNA methylation (e.g., Dacogen, Vidaza) and broad-spectrum HDAC inhibitors (e.g., Vorinostat, Romidepsin). This Review provides an analysis of prospects for discovery and development of novel cancer agents that target epigenetic proteins. We will examine key examples of epigenetic dysregulation in tumors as well as challenges to epigenetic drug discovery with emerging biology and novel classes of drug targets. We will also highlight recent successes in cancer epigenetics drug discovery and consider important factors for clinical success in this burgeoning area.
Croston, Glenn E
The availability of genomic information significantly increases the number of potential targets available for drug discovery, although the function of many targets and their relationship to disease is unknown. In a chemical genomic research approach, ultra-high throughput screening (uHTS) of genomic targets takes place early in the drug discovery process, before target validation. Target-selective modulators then provide drug leads and pharmacological research tools to validate target function. Effective implementation of a chemical genomic strategy requires assays that can perform uHTS for large numbers of genomic targets. Cell-based functional assays are capable of the uHTS throughput required for chemical genomic research, and their functional nature provides distinct advantages over ligand-binding assays in the identification of target-selective modulators.
Yu, Chun Yan; Yang, Hong; Zhou, Jin; Xue, Wei Wei; Tan, Jun; Zhu, Feng
The human kinome is one of the most productive classes of drug target, and there is emerging necessity for treating complex diseases by means of polypharmacology (multi-target drugs and combination products). However, the advantages of the multi-target drugs and the combination products are still under debate. A comparative analysis between FDA approved multi-target drugs and combination products, targeting the human kinome, was conducted by mapping targets onto the phylogenetic tree of the human kinome. The approach of network medicine illustrating the drug-target interactions was applied to identify popular targets of multi-target drugs and combination products. As identified, the multi-target drugs tended to inhibit target pairs in the human kinome, especially the receptor tyrosine kinase family, while the combination products were able to against targets of distant homology relationship. This finding asked for choosing the combination products as a better solution for designing drugs aiming at targets of distant homology relationship. Moreover, sub-networks of drug-target interactions in specific disease were generated, and mechanisms shared by multi-target drugs and combination products were identified. In conclusion, this study performed an analysis between approved multi-target drugs and combination products against the human kinome, which could assist the discovery of next generation polypharmacology. PMID:27828998
Orhan, Ilkay Erdogan
Pharmacognosy deals with the natural drugs obtained from organisms such as most plants, microbes, and animals. Up to date, many important drugs including morphine, atropine, galanthamine, etc. have originated from natural sources which continue to be good model molecules in drug discovery. Traditional medicine is also a part of pharmacognosy and most of the third world countries still depend on the use of herbal medicines. Consequently, pharmacognosy always keeps its popularity in pharmaceutical sciences and plays a critical role in drug discovery.
Roy, Anuradha; McDonald, Peter R.; Sittampalam, Sitta; Chaguturu, Rathnam
High throughput screening (HTS) facilitates screening large numbers of compounds against a biochemical target of interest using validated biological or biophysical assays. In recent years, a significant number of drugs in clinical trails originated from HTS campaigns, validating HTS as a bona fide mechanism for hit finding. In the current drug discovery landscape, the pharmaceutical industry is embracing open innovation strategies with academia to maximize their research capabilities and to feed their drug discovery pipeline. The goals of academic research have therefore expanded from target identification and validation to probe discovery, chemical genomics, and compound library screening. This trend is reflected in the emergence of HTS centers in the public domain over the past decade, ranging in size from modestly equipped academic screening centers to well endowed Molecular Libraries Probe Centers Network (MLPCN) centers funded by the NIH Roadmap initiative. These centers facilitate a comprehensive approach to probe discovery in academia and utilize both classical and cutting-edge assay technologies for executing primary and secondary screening campaigns. The various facets of academic HTS centers as well as their implications on technology transfer and drug discovery are discussed, and a roadmap for successful drug discovery in the public domain is presented. New lead discovery against therapeutic targets, especially those involving the rare and neglected diseases, is indeed a Mount Everestonian size task, and requires diligent implementation of pharmaceutical industry’s best practices for a successful outcome. PMID:20809896
Roy, Anuradha; McDonald, Peter R; Sittampalam, Sitta; Chaguturu, Rathnam
High throughput screening (HTS) facilitates screening large numbers of compounds against a biochemical target of interest using validated biological or biophysical assays. In recent years, a significant number of drugs in clinical trails originated from HTS campaigns, validating HTS as a bona fide mechanism for hit finding. In the current drug discovery landscape, the pharmaceutical industry is embracing open innovation strategies with academia to maximize their research capabilities and to feed their drug discovery pipeline. The goals of academic research have therefore expanded from target identification and validation to probe discovery, chemical genomics, and compound library screening. This trend is reflected in the emergence of HTS centers in the public domain over the past decade, ranging in size from modestly equipped academic screening centers to well endowed Molecular Libraries Probe Centers Network (MLPCN) centers funded by the NIH Roadmap initiative. These centers facilitate a comprehensive approach to probe discovery in academia and utilize both classical and cutting-edge assay technologies for executing primary and secondary screening campaigns. The various facets of academic HTS centers as well as their implications on technology transfer and drug discovery are discussed, and a roadmap for successful drug discovery in the public domain is presented. New lead discovery against therapeutic targets, especially those involving the rare and neglected diseases, is indeed a Mount Everestonian size task, and requires diligent implementation of pharmaceutical industry's best practices for a successful outcome.
Bertucci, Carlo; Pistolozzi, Marco; De Simone, Angela
Chirality plays a fundamental role in determining the pharmacodynamic and pharmacokinetic properties of drugs, and contributes significantly to our understanding of the mechanisms that lie behind biorecognition phenomena. Circular dichroism spectroscopy is the technique of choice for determining the stereochemistry of chiral drugs and proteins, and for monitoring and characterizing molecular recognition phenomena in solution. The role of chirality in our understanding of recognition phenomena at the molecular level is discussed here via several selected systems of interest in the drug discovery and development area. The examples were selected in order to underline the utility of circular dichroism in emerging studies of protein-protein interactions in biological context. In particular, the following aspects are discussed here: the relationship between stereochemistry and pharmacological activity--stereochemical characterization of new leads and drugs; stereoselective binding of leads and drugs to target proteins--the binding of drugs to serum albumins; conformational transitions of peptides and proteins of physiological relevance, and the stereochemical characterization of therapeutic peptides.
Jiménez-Díaz, María Belén; Viera, Sara; Fernández-Alvaro, Elena; Angulo-Barturen, Iñigo
The emergence of resistance to artemisinins and the renewed efforts to eradicate malaria demand the urgent development of new drugs. In this endeavour, the evaluation of efficacy in animal models is often a go/no go decision assay in drug discovery. This important role relies on the capability of animal models to assess the disposition, toxicology and efficacy of drugs in a single test. Although the relative merits of each efficacy model of malaria as human surrogate have been extensively discussed, there are no critical analyses on the use of such models in current drug discovery. In this article, we intend to analyse how efficacy models are used to discover new antimalarial drugs. Our analysis indicates that testing drug efficacy is often the last assay in each discovery stage and the experimental designs utilized are not optimized to expedite decision-making and inform clinical development. In light of this analysis, we propose new ways to accelerate drug discovery using efficacy models.
Smith, Thomas J.
Green tea is made from unfermented dried leaves from Camellia sinensis and has been consumed by humans for thousands of years. For nearly as long, it has been used as a folk remedy for a wide array of diseases. More recently, a large number of in-vitro and in-vivo scientific studies have supported this ancient contention that the polyphenols from green tea can provide a number of health benefits. Since these compounds are clearly safe for human consumption and ubiquitous in the food supply, they are highly attractive as lead compounds for drug discovery programs. However, as drugs, they are far from optimum. They are relatively unstable, poorly absorbed, and readily undergo a number of metabolic transformations by intestinal microbiota and human enzymes. Further, since these compounds target a wide array of biological systems, in-vivo testing is rather difficult since effects on alternative pathways need to be carefully eliminated. The purpose of this review is to discuss some of the challenges and benefits of pursuing this family of compounds for drug discovery. PMID:21731575
Maiese, Kenneth; Chong, Zhao Zhong; Shang, Yan Chen; Hou, Jinling
Globally, developed nations spend a significant amount of their resources on health care initiatives that poorly translate into increased population life expectancy. As an example, the United States devotes 16% of its gross domestic product to health care, the highest level in the world, but falls behind other nations that enjoy greater individual life expectancy. These observations point to the need for pioneering avenues of drug discovery to increase life span with controlled costs. In particular, innovative drug development for metabolic disorders such as diabetes mellitus becomes increasingly critical given that the number of diabetic people will increase exponentially over the next 20 years. This article discusses the elucidation and targeting of novel cellular pathways that are intimately tied to oxidative stress in diabetes mellitus for new treatment strategies. Pathways that involve wingless, β-nicotinamide adenine dinucleotide (NAD(+)) precursors, and cytokines govern complex biological pathways that determine both cell survival and longevity during diabetes mellitus and its complications. Furthermore, the role of these entities as biomarkers for disease can further enhance their utility irrespective of their treatment potential. Greater understanding of the intricacies of these unique cellular mechanisms will shape future drug discovery for diabetes mellitus to provide focused clinical care with limited or absent long-term complications.
Cheng, Tiejun; Pan, Yongmei; Hao, Ming; Wang, Yanli; Bryant, Stephen H
A bibliometric analysis of PubChem applications is presented by reviewing 1132 research articles. The massive volume of chemical structure and bioactivity data in PubChem and its online services have been used globally in various fields including chemical biology, medicinal chemistry and informatics research. PubChem supports drug discovery in many aspects such as lead identification and optimization, compound-target profiling, polypharmacology studies and unknown chemical identity elucidation. PubChem has also become a valuable resource for developing secondary databases, informatics tools and web services. The growing PubChem resource with its public availability offers support and great opportunities for the interrogation of pharmacological mechanisms and the genetic basis of diseases, which are vital for drug innovation and repurposing.
Hurko, Orest; Ryan, John L.
Summary: Of all the therapeutic areas, diseases of the CNS provide the biggest challenges to translational research in this era of increased productivity and novel targets. Risk reduction by translational research incorporates the “learn” phase of the “learn and confirm” paradigm proposed over a decade ago. Like traditional drug discovery in vitro and in laboratory animals, it precedes the traditional phase 1–3 studies of drug development. The focus is on ameliorating the current failure rate in phase 2 and the delays resulting from suboptimal choices in four key areas: initial test subjects, dosing, sensitive and early detection of therapeutic effect, and recognition of differences between animal models and human disease. Implementation of new technologies is the key to success in this emerging endeavor. PMID:16489374
Cheng, Tiejun; Pan, Yongmei; Hao, Ming; Wang, Yanli; Bryant, Stephen H.
A bibliometric analysis of PubChem applications is presented by reviewing 1132 research articles. The massive volume of chemical structure and bioactivity data in PubChem and its online services has been used globally in various fields including chemical biology, medicinal chemistry and informatics research. PubChem supports drug discovery in many aspects such as lead identification and optimization, compound–target profiling, polypharmacology studies and unknown chemical identity elucidation. PubChem has also become a valuable resource for developing secondary databases, informatics tools and web services. The growing PubChem resource with its public availability offers support and great opportunities for the interrogation of pharmacological mechanisms and the genetic basis of diseases, which are vital for drug innovation and repurposing. PMID:25168772
Piel, Markus; Vernaleken, Ingo; Rösch, Frank
Molecular imaging methods such as positron emission tomography (PET) are increasingly involved in the development of new drugs. Using radioactive tracers as imaging probes, PET allows the determination of the pharmacokinetic and pharmacodynamic properties of a drug candidate, via recording target engagement, the pattern of distribution, and metabolism. Because of the noninvasive nature and quantitative end point obtainable by molecular imaging, it seems inherently suited for the examination of a pharmaceutical's behavior in the brain. Molecular imaging, most especially PET, can therefore be a valuable tool in CNS drug research. In this Perspective, we present the basic principles of PET, the importance of appropriate tracer selection, the impact of improved radiopharmaceutical chemistry in radiotracer development, and the different roles that PET can fulfill in CNS drug research.
Roguska, Michael; Kaymakcalan, Zehra; Salfeld, Jochen
The number of therapeutic antibodies approved by regulatory agencies as novel drugs and the number of antibodies in development has increased significantly. The modular nature of antibody structure has enabled researchers to more predictably design therapeutic antibodies by choosing appropriate functional features most appropriate for a given antibody target and clinical indication. Advances in recombinant antibody technologies have allowed the routine generation of antibodies that can satisfy stringent drug design criteria, such as low immunogenicity, high affinity, target specificity, and commercially viable manufacturing methods. Engineering design opportunities exist for both the variable and the constant regions that encompass, in addition to antigen specificity and affinity, effector functions that mediate immune complex clearance or pharmacokinetics. These are discussed in the context of relevant in vivo and in vitro technologies, such as human IgG transgenic mice, phage display, and biologics manufacturing. Finally, therapeutic antibodies are compared with traditional drugs with respect to target class, selectivity, route of administration, intellectual property issues, and lead discovery and optimization.
Banerji, Udai; Workman, Paul
The Pharmacological Audit Trail (PhAT) comprises a set of critical questions that need to be asked during discovery and development of an anticancer drug. Key aspects include: (1) defining a patient population; (2) establishing pharmacokinetic characteristics; (3) providing evidence of target engagement, pathway modulation, and biological effect with proof of concept pharmacodynamic biomarkers; (4) determining intermediate biomarkers of response; (5) assessing tumor response; and (6) determining how to overcome resistance by combination or sequential therapy and new target/drug discovery. The questions asked in the PhAT should be viewed as a continuum and not used in isolation. Different drug development programmes derive different types of benefit from these questions. The PhAT is critical in making go-no-go decisions in the development of currently studied drugs and will continue to be relevant to discovery and development of future generations of anticancer agents.
Kizaka-Kondoh, Shinae; Kuchimaru, Takahiro; Kadonosono, Tetsuya
The microenvironment of solid tumors is characterized by low pO(2) that is well below physiological levels. Intratumoral hypoxia is a major factor contributing to cancer progression and is exacerbated as a result of oxygen consumption by rapidly proliferating tumor cells near blood vessels, poor lymphatic drainage resulting in high interstitial pressure, and irregular blood supply through immature tumor vasculature. Hypoxia-inducible factor-1 (HIF-1) is the main transcription factor that regulates cellular responses to hypoxia. Cellular changes induced by HIF-1 are extremely important targets for cancer therapy. Therefore, targeting strategies to counteract HIF-1-active cells are essential for cancer therapy. In this study, we introduce a novel strategy for targeting HIF-1-active cells.
Allosteric drug development holds promise for delivering medicines that are more selective and less toxic than those that target orthosteric sites. To date, the discovery of allosteric binding sites and lead compounds has been mostly serendipitous, achieved through high-throughput screening. Over the past decade, structural data has become more readily available for larger protein systems and more membrane protein classes (e.g., GPCRs and ion channels), which are common allosteric drug targets. In parallel, improved simulation methods now provide better atomistic understanding of the protein dynamics and cooperative motions that are critical to allosteric mechanisms. As a result of these advances, the field of predictive allosteric drug development is now on the cusp of a new era of rational structure-based computational methods. Here, we review algorithms that predict allosteric sites based on sequence data and molecular dynamics simulations, describe tools that assess the druggability of these pockets, and discuss how Markov state models and topology analyses provide insight into the relationship between protein dynamics and allosteric drug binding. In each section, we first provide an overview of the various method classes before describing relevant algorithms and software packages. PMID:27074285
Fray, M Jonathan; Macdonald, Simon J F; Baldwin, Ian R; Barton, Nick; Brown, Jack; Campbell, Ian B; Churcher, Ian; Coe, Diane M; Cooper, Anthony W J; Craven, Andrew P; Fisher, Gail; Inglis, Graham G A; Kelly, Henry A; Liddle, John; Maxwell, Aoife C; Patel, Vipulkumar K; Swanson, Stephen; Wellaway, Natalie
In this article, we describe a practical drug discovery project for third-year undergraduates. No previous knowledge of medicinal chemistry is assumed. Initial lecture workshops cover the basic principles; then students, in teams, seek to improve the profile of a weakly potent, insoluble phosphatidylinositide 3-kinase delta (PI3Kδ) inhibitor (1) through compound array design, molecular modelling, screening data analysis and the synthesis of target compounds in the laboratory. The project benefits from significant industrial support, including lectures, student mentoring and consumables. The aim is to make the learning experience as close as possible to real-life industrial situations. In total, 48 target compounds were prepared, the best of which (5b, 5j, 6b and 6ap) improved the potency and aqueous solubility of the lead compound (1) by 100-1000 fold and ≥tenfold, respectively.
G protein-coupled receptors (GPCRs) transmit extracellular signals into the intracellular space, and play key roles in the physiological regulation of virtually every cell and tissue. Characteristic for the GPCR superfamily of cell surface receptors are their seven transmembrane-spanning alpha-helices, an extracellular N terminus and intracellular C-terminal tail. Besides transmission of extracellular signals, their activity is modulated by cellular signals in an auto- or transregulatory fashion. The molecular complexity of GPCRs and their regulated signaling networks triggered the interest in academic research groups to explore them further, and their drugability and role in pathophysiology triggers pharmaceutical research towards small molecular weight ligands and therapeutic antibodies. About 30% of marketed drugs target GPCRs, which underlines the importance of this target class. This review describes current and emerging cellular assays for the ligand discovery of GPCRs.
Verma, Saroj; Prabhakar, Yenamandra S
The target based drug design approaches are a series of computational procedures, including visualization tools, to support the decision systems of drug design/discovery process. In the essence of biological targets shaping the potential lead/drug molecules, this review presents a comprehensive position of different components of target based drug design which include target identification, protein modeling, molecular dynamics simulations, binding/catalytic sites identification, docking, virtual screening, fragment based strategies, substructure treatment of targets in tackling drug resistance, in silico ADMET, structural vaccinology, etc along with the key issues involved therein and some well investigated case studies. The concepts and working of these procedures are critically discussed to arouse interest and to advance the drug research.
Peetla, Chiranjeevi; Stine, Andrew; Labhasetwar, Vinod
The transport of drugs or drug delivery systems across the cell membrane is a complex biological process, often difficult to understand because of its dynamic nature. In this regard, model lipid membranes, which mimic many aspects of cell-membrane lipids, have been very useful in helping investigators to discern the roles of lipids in cellular interactions. One can use drug-lipid interactions to predict pharmacokinetic properties of drugs, such as their transport, biodistribution, accumulation, and hence efficacy. These interactions can also be used to study the mechanisms of transport, based on the structure and hydrophilicity/hydrophobicity of drug molecules. In recent years, model lipid membranes have also been explored to understand their mechanisms of interactions with peptides, polymers, and nanocarriers. These interaction studies can be used to design and develop efficient drug delivery systems. Changes in the lipid composition of cells and tissue in certain disease conditions may alter biophysical interactions, which could be explored to develop target-specific drugs and drug delivery systems. In this review, we discuss different model membranes, drug-lipid interactions and their significance, studies of model membrane interactions with nanocarriers, and how biophysical interaction studies with lipid model membranes could play an important role in drug discovery and drug delivery. PMID:19432455
Chen, G; Jayawickreme, C; Way, J; Armour, S; Queen, K; Watson, C; Ignar, D; Chen, W J; Kenakin, T
This paper discusses the use of constitutively active G-protein-coupled receptor systems for drug discovery. Specifically, the ternary complex model is used to define the two major theoretical advantages of constitutive receptor screening-namely, the ability to detect antagonists as well as agonists directly and the fact that constitutive systems are more sensitive to agonists. In experimental studies, transient transfection of Chinese hamster ovary cyclic AMP response element (CRE) luciferase reporter cells with cDNA for human parathyroid hormone receptor, glucagon receptor, and glucagon-like peptide (GLP-1) receptor showed cDNA concentration-dependent constitutive activity with parathyroid hormone (PTH-1) and glucagon. In contrast, no constitutive activity was observed for GLP-1 receptor, yet responses to GLP-1 indicated that receptor expression had taken place. In another functional system, Xenopus laevi melanophores transfected with cDNA for human calcitonin receptor showed constitutive activity. Nine ligands for the calcitonin receptor either increased or decreased constitutive activity in this assay. The sensitivity of the system to human calcitonin increased with increasing constitutive activity. These data indicate that, for those receptors which naturally produce constitutive activity, screening in this mode could be advantageous over other methods.
Kufahl, Peter R.; Watterson, Lucas R.
Introduction Globally, alcohol abuse and dependence are significant contributors to chronic disease and injury and are responsible for nearly 4% of all deaths annually. Acamprosate (Campral), one of only three pharmacological treatments approved for the treatment of alcohol dependence, has shown mixed efficacy in clinical trials in maintaining abstinence of detoxified alcoholics since studies began in the 1980’s. Yielding inconsistent results, these studies have prompted skepticism. Areas Covered Herein, the authors review the preclinical studies which have assessed the efficacy of acamprosate in various animal models of alcohol dependence and discuss the disparate findings from the major clinical trials. Moreover, the authors discuss the major limitations of these preclinical and clinical studies and offer explanations for the often contradictory findings. The article also looks at the importance of the calcium moiety that accompanies the salt form of acamprosate and its relevance to its activity. Expert opinion The recent discovery that large doses of calcium largely duplicate the effects of acamprosate in animal models has introduced a serious challenge to the widely-held functional association between this drug and the glutamate neurotransmission system. Future research on acamprosate or newer pharmacotherapeutics should consider assessing plasma and/or brain levels of calcium as a correlate or mediating factor in anti-relapse efficacy. Furthermore, preclinical research on acamprosate has thus far lacked animal models of chemical dependence on alcohol, and the testing of rodents with histories of alcohol intoxication and withdrawal is suggested. PMID:25258174
Muñoz, Emir; Nováček, Vít; Vandenbussche, Pierre-Yves
We propose a new computational method for discovery of possible adverse drug reactions. The method consists of two key steps. First we use openly available resources to semi-automatically compile a consolidated data set describing drugs and their features (e.g., chemical structure, related targets, indications or known adverse reaction). The data set is represented as a graph, which allows for definition of graph-based similarity metrics. The metrics can then be used for propagating known adverse reactions between similar drugs, which leads to weighted (i.e., ranked) predictions of previously unknown links between drugs and their possible side effects. We implemented the proposed method in the form of a software prototype and evaluated our approach by discarding known drug-side effect links from our data and checking whether our prototype is able to re-discover them. As this is an evaluation methodology used by several recent state of the art approaches, we could compare our results with them. Our approach scored best in all widely used metrics like precision, recall or the ratio of relevant predictions present among the top ranked results. The improvement was as much as 125.79% over the next best approach. For instance, the F1 score was 0.5606 (66.35% better than the next best method). Most importantly, in 95.32% of cases, the top five results contain at least one, but typically three correctly predicted side effect (36.05% better than the second best approach). PMID:28269889
Kinoshita, Takayoshi; Doi, Kentaro; Sugiyama, Hajime; Kinoshita, Shuhei; Wada, Mutsuyo; Naruto, Shuji; Tomonaga, Atsushi
Many existing agents for diabetes therapy are unable to restore or maintain normal glucose homeostasis or prevent the eventual emergence of hyperglycemia-related complication. Therefore, agents based on novel mechanisms are sought to complement and extend the current therapeutic approaches. Based on the initial paper research, we focused on active STAT3 as an attractive pharmacological target for type 2 diabetes. The subsequent text mining with a unique query to identify suppressors but not activators of STAT3 revealed the ERK2/STAT3 pathway as a novel diabetes target. The description of ERK2 inhibitors as diabetes target had not been found in our text mining research at present. The mechanism-based peptide inhibitor for ERK2 was identified using the knowledge of the KIM sequence, which has an important role in the recognition of cognate kinases, phosphatases, scaffold proteins, and substrates. The peptide inhibitor was confirmed to exert effects in vitro and in vivo. The peptide inhibitor conferred a significant decrease in HOMA-IR levels on Day 28 compared with that in the vehicle group. Besides lowering the fasting blood glucose level, the peptide inhibitor also attenuated the blood glucose increment in the fed state, as compared with the vehicle group.
Drug discovery process many times encounters complex problems, which may be difficult to solve by human intelligence. Artificial Neural Networks (ANNs) are one of the Artificial Intelligence (AI) technologies used for solving such complex problems. ANNs are widely used for primary virtual screening of compounds, quantitative structure activity relationship studies, receptor modeling, formulation development, pharmacokinetics and in all other processes involving complex mathematical modeling. Despite having such advanced technologies and enough understanding of biological systems, drug discovery is still a lengthy, expensive, difficult and inefficient process with low rate of new successful therapeutic discovery. In this paper, author has discussed the drug discovery science and ANN from very basic angle, which may be helpful to understand the application of ANN for drug discovery to improve efficiency.
Schenk, Robyn L; Strasser, Andreas; Dewson, Grant
In 1988, the BCL-2 protein was found to promote cancer by limiting cell death rather than enhancing proliferation. This discovery set the wheels in motion for an almost 30 year journey involving many international research teams that has recently culminated in the approval for a drug, ABT-199/venetoclax/Venclexta that targets this protein in the treatment of cancer. This review will describe the long and winding path from the discovery of this protein and understanding the fundamental process of apoptosis that BCL-2 and its numerous homologues control, through to its exploitation as a drug target that is set to have significant benefit for cancer patients.
Murakami, Yoichi; Tripathi, Lokesh P; Prathipati, Philip; Mizuguchi, Kenji
Protein-protein interactions (PPIs) are vital to maintaining cellular homeostasis. Several PPI dysregulations have been implicated in the etiology of various diseases and hence PPIs have emerged as promising targets for drug discovery. Surface residues and hotspot residues at the interface of PPIs form the core regions, which play a key role in modulating cellular processes such as signal transduction and are used as starting points for drug design. In this review, we briefly discuss how PPI networks (PPINs) inferred from experimentally characterized PPI data have been utilized for knowledge discovery and how in silico approaches to PPI characterization can contribute to PPIN-based biological research. Next, we describe the principles of in silico PPI prediction and survey the existing PPI and PPI site prediction servers that are useful for drug discovery. Finally, we discuss the potential of in silico PPI prediction in drug discovery.
Gao, Guangxun; Chen, Liang; Huang, Chuanshu
Discovery of novel cancer chemotherapeutics focuses on screening and identifying compounds that can target 'cancer-specific' biological processes while causing minimal toxicity to non-tumor cells. Alternatively, model organisms with highly conserved cancer-related cellular processes relative to human cells may offer new opportunities for anticancer drug discovery when combined with chemical screening. Some organisms used for chemotherapeutic discovery include yeast, Drosophila, and zebrafish which are similar in important ways relevant to cancer study but offer distinct advantages as well. Here, we describe these model attributes and the rationale for using them in cancer drug screening research.
Gao, Guangxun; Chen, Liang; Huang, Chuanshu
Discovery of novel cancer chemotherapeutics focuses on screening and identifying compounds that can target ‘cancer-specific’ biological processes while causing minimal toxicity to non-tumor cells. Alternatively, model organisms with highly conserved cancer-related cellular processes relative to human cells may offer new opportunities for anticancer drug discovery when combined with chemical screening. Some organisms used for chemotherapeutic discovery include yeast, Drosophila, and zebrafish which are similar in important ways relevant to cancer study but offer distinct advantages as well. Here, we describe these model attributes and the rationale for using them in cancer drug screening research. PMID:24993385
Hao, Ge-Fei; Yang, Guang-Fu; Zhan, Chang-Guo
Drug resistance has become one of the biggest challenges in drug discovery and/or development and has attracted great research interests worldwide. During the past decade, computational strategies have been developed to predict target mutation-induced drug resistance. Meanwhile, various molecular design strategies, including targeting protein backbone, targeting highly conserved residues and dual/multiple targeting, have been used to design novel inhibitors for combating the drug resistance. In this article we review recent advances in development of computational methods for target mutation-induced drug resistance prediction and strategies for rational design of novel inhibitors that could be effective against the possible drug-resistant mutants of the target.
Natural products provide a successful supply of new chemical entities (NCEs) for drug discovery to treat human diseases. Approximately half of the NCEs are based on natural products and their derivatives. Notably, marine natural products, a largely untapped resource, have contributed to drug discovery and development with eight drugs or cosmeceuticals approved by the U.S. Food and Drug Administration and European Medicines Agency, and ten candidates undergoing clinical trials. Collaborative efforts from drug developers, biologists, organic, medicinal, and natural product chemists have elevated drug discoveries to new levels. These efforts are expected to continue to improve the efficiency of natural product-based drugs. Marinopyrroles are examined here as a case study for potential anticancer and antibiotic agents.
Haefliger, Benjamin; Prochazka, Laura; Angelici, Bartolomeo; Benenson, Yaakov
Development of drug discovery assays that combine high content with throughput is challenging. Information-processing gene networks can address this challenge by integrating multiple potential targets of drug candidates' activities into a small number of informative readouts, reporting simultaneously on specific and non-specific effects. Here we show a family of networks implementing this concept in a cell-based drug discovery assay for miRNA drug targets. The networks comprise multiple modules reporting on specific effects towards an intended miRNA target, together with non-specific effects on gene expression, off-target miRNAs and RNA interference pathway. We validate the assays using known perturbations of on- and off-target miRNAs, and evaluate an ∼700 compound library in an automated screen with a follow-up on specific and non-specific hits. We further customize and validate assays for additional drug targets and non-specific inputs. Our study offers a novel framework for precision drug discovery assays applicable to diverse target families. PMID:26880188
Buller, Fabian; Mannocci, Luca; Scheuermann, Jörg; Neri, Dario
DNA-encoded chemical libraries represent a novel avenue for the facile discovery of small molecule ligands against target proteins of biological or pharmaceutical importance. Library members consist of small molecules covalently attached to unique DNA fragments that serve as amplifiable identification barcodes. This encoding allows the in vitro selection of ligands at subpicomolar concentrations from large library populations by affinity capture on a target protein of interest, in analogy to established technologies for the selection of binding polypeptides (e.g., antibodies). Different library formats have been explored by various groups, allowing the construction of chemical libraries comprising up to millions of DNA-encoded compounds. Libraries before and after selection have been characterized by PCR amplification of the DNA codes and subsequent relative quantification of library members using high-throughput sequencing. The most enriched compounds have then been further analyzed in biological assays, in the presence or in the absence of linked DNA. This article reviews experimental strategies used for the construction of DNA-encoded chemical libraries, revealing how selection, decoding, and hit validation technologies have been used for drug discovery programs.
Jubb, Harry; Higueruelo, Alicia P; Winter, Anja; Blundell, Tom L
Although targeting protein-protein interfaces of regulatory multiprotein complexes has become a significant focus in drug discovery, it continues to pose major challenges. Most interfaces would be classed as 'undruggable' by conventional analyses, as they tend to be large, flat and featureless. Over the past decade, encouragement has come from the discovery of hotspots that contribute much of the free energy of interaction, and this has led to the development of tethering methods that target small molecules to these sites, often inducing adaptive changes. Equally important has been the recognition that many protein-protein interactions involve a continuous epitope of one partner and a well-defined groove or series of specific small pockets. These observations have stimulated the development of stapled α-helical peptides and other proteomimetic approaches. They have also led to the realisation that fragments might gain low-affinity 'footholds' on some protein-protein interfaces, and that these fragments might be elaborated to useful modulators of the interactions.
Verdine, Gregory L; Hilinski, Gerard J
Proteins that engage in intracellular interactions with other proteins are widely considered among the most biologically appealing yet chemically intractable targets for drug discovery. The critical interaction surfaces of these proteins typically lack the deep hydrophobic involutions that enable potent, selective targeting by small organic molecules, and their localization within the cell puts them beyond the reach of protein therapeutics. Considerable interest has therefore arisen in next-generation targeting molecules that combine the broad target recognition capabilities of protein therapeutics with the robust cell-penetrating ability of small molecules. One type that has shown promise in early-stage studies is hydrocarbon-stapled α-helical peptides, a novel class of synthetic miniproteins locked into their bioactive α-helical fold through the site-specific introduction of a chemical brace, an all-hydrocarbon staple. Stapling can greatly improve the pharmacologic performance of peptides, increasing their target affinity, proteolytic resistance, and serum half-life while conferring on them high levels of cell penetration through endocytic vesicle trafficking. Here, we discuss considerations crucial to the successful design and evaluation of potent stapled peptide interactions, our intention being to facilitate the broad application of this technology to intractable targets of both basic biologic interest and potential therapeutic value.
Salavert, Francisco; Hidago, Marta R.; Amadoz, Alicia; Çubuk, Cankut; Medina, Ignacio; Crespo, Daniel; Carbonell-Caballero, Jose; Dopazo, Joaquín
The discovery of actionable targets is crucial for targeted therapies and is also a constituent part of the drug discovery process. The success of an intervention over a target depends critically on its contribution, within the complex network of gene interactions, to the cellular processes responsible for disease progression or therapeutic response. Here we present PathAct, a web server that predicts the effect that interventions over genes (inhibitions or activations that simulate knock-outs, drug treatments or over-expressions) can have over signal transmission within signaling pathways and, ultimately, over the cell functionalities triggered by them. PathAct implements an advanced graphical interface that provides a unique interactive working environment in which the suitability of potentially actionable genes, that could eventually become drug targets for personalized or individualized therapies, can be easily tested. The PathAct tool can be found at: http://pathact.babelomics.org. PMID:27137885
Huang, Wenkang; Nussinov, Ruth; Zhang, Jian
Allostery is an intrinsic phenomenon of biological macromolecules involving regulation and/or signal transduction induced by a ligand binding to an allosteric site distinct from a molecule's active site. Allosteric drugs are currently receiving increased attention in drug discovery because drugs that target allosteric sites can provide important advantages over the corresponding orthosteric drugs including specific subtype selectivity within receptor families. Consequently, targeting allosteric sites, instead of orthosteric sites, can reduce drug-related side effects and toxicity. On the down side, allosteric drug discovery can be more challenging than traditional orthosteric drug discovery due to difficulties associated with determining the locations of allosteric sites and designing drugs based on these sites and the need for the allosteric effects to propagate through the structure, reach the ligand binding site and elicit a conformational change. In this study, we present computational tools ranging from the identification of potential allosteric sites to the design of "allosteric-like" modulator libraries. These tools may be particularly useful for allosteric drug discovery.
Redinbo, M R; Bencharit, S; Potter, P M
Human carboxylesterase 1 (hCE1) is a serine esterase involved in both drug metabolism and activation, as well as other biological processes. hCE1 catalyses the hydrolysis of heroin and cocaine, and the transesterification of cocaine in the presence of ethanol to the toxic metabolite cocaethylene. We have determined the crystal structures of hCE1 in complex with either the cocaine analogue homatropine or the heroin analogue naloxone. These are the first structures of a human carboxylesterase, and they provide details about narcotic metabolism in humans. hCE1's active site contains rigid and flexible pockets, explaining the enzyme's ability to act both specifically and promiscuously. hCE1 has also been reported to contain cholesteryl ester hydrolase, fatty acyl-CoA hydrolase and acyl-CoA:cholesterol acyltransferase activities, and thus appears to be involved in cholesterol metabolism. Since the enzyme may be useful as a treatment for cocaine overdose, and may afford protection against chemical weapons like Sarin, Soman and VX gas, hCE1 could serve as both a drug and a drug target. Selective hCE1 inhibitors targeted to several sites on the enzyme may also pave the way for novel clinical tools to manage cholesterol homoeostasis in humans.
Bhardwaj, Anshu; Scaria, Vinod; Raghava, Gajendra Pal Singh; Lynn, Andrew Michael; Chandra, Nagasuma; Banerjee, Sulagna; Raghunandanan, Muthukurussi V; Pandey, Vikas; Taneja, Bhupesh; Yadav, Jyoti; Dash, Debasis; Bhattacharya, Jaijit; Misra, Amit; Kumar, Anil; Ramachandran, Srinivasan; Thomas, Zakir; Brahmachari, Samir K
It is being realized that the traditional closed-door and market driven approaches for drug discovery may not be the best suited model for the diseases of the developing world such as tuberculosis and malaria, because most patients suffering from these diseases have poor paying capacity. To ensure that new drugs are created for patients suffering from these diseases, it is necessary to formulate an alternate paradigm of drug discovery process. The current model constrained by limitations for collaboration and for sharing of resources with confidentiality hampers the opportunities for bringing expertise from diverse fields. These limitations hinder the possibilities of lowering the cost of drug discovery. The Open Source Drug Discovery project initiated by Council of Scientific and Industrial Research, India has adopted an open source model to power wide participation across geographical borders. Open Source Drug Discovery emphasizes integrative science through collaboration, open-sharing, taking up multi-faceted approaches and accruing benefits from advances on different fronts of new drug discovery. Because the open source model is based on community participation, it has the potential to self-sustain continuous development by generating a storehouse of alternatives towards continued pursuit for new drug discovery. Since the inventions are community generated, the new chemical entities developed by Open Source Drug Discovery will be taken up for clinical trial in a non-exclusive manner by participation of multiple companies with majority funding from Open Source Drug Discovery. This will ensure availability of drugs through a lower cost community driven drug discovery process for diseases afflicting people with poor paying capacity. Hopefully what LINUX the World Wide Web have done for the information technology, Open Source Drug Discovery will do for drug discovery.
Soundararajan, Meera; Eswaran, Jeyanthy
The Ras GTPases are the founding members of large Ras superfamily, which constitutes more than 150 of these important class of enzymes. These GTPases function as GDP-GTP-regulated binary switches that control many fundamental cellular processes. There are a number of GTPases that have been identified recently, which do not confine to this prototype termed as "atypical GTPases" but have proved to play a remarkable role in vital cellular functions. In this review, we provide an overview of the crucial physiological functions mediated by RGK and Centaurin class of multi domain atypical GTPases. Moreover, the recently available atypical GTPase structures of the two families, regulation, physiological functions and their critical roles in various diseases will be discussed. In summary, this review will highlight the emerging atypical GTPase family which allows us to understand novel regulatory mechanisms and thus providing new avenues for drug discovery programs.
leishmanlal excreted factor (EF) antibody in rabbit sera was developed. The assay, using Leishmania trop ica and Leishmania donovani promastigote EF...tropica LRC L137 L52 Leishmaniia donovani LRC L52 These strains were obtained from the WHO Leishmania Peference Centre collection maintained in the...FO 0 AD M FINAL REPORT0 (N TARGET ORIENTED DRUGS AGAINST LEISHMANIA I URI ZEHAVI, Ph.D. and JOSEPH EL-ON, Ph.D. Supported by U.S. ARMY MEDICAL
Van Dam, Debby; De Deyn, Peter Paul
With increasing feasibility of predicting conversion of mild cognitive impairment to dementia based on biomarker profiling, the urgent need for efficacious disease-modifying compounds has become even more critical. Despite intensive research, underlying pathophysiological mechanisms remain insufficiently documented for purposeful target discovery. Translational research based on valid animal models may aid in alleviating some of the unmet needs in the current Alzheimer's disease pharmaceutical market, which includes disease-modification, increased efficacy and safety, reduction of the number of treatment unresponsive patients and patient compliance. The development and phenotyping of animal models is indeed essential in Alzheimer's disease-related research as valid models enable the appraisal of early pathological processes – which are often not accessible in patients, and subsequent target discovery and evaluation. This review paper summarizes and critically evaluates currently available animal models, and discusses their value to the Alzheimer drug discovery pipeline. Models dealt with include spontaneous models in various species, including senescence-accelerated mice, chemical and lesion-induced rodent models, and genetically modified models developed in Drosophila melanogaster, Caenorhabditis elegans, Danio rerio and rodents. Although highly valid animal models exist, none of the currently available models recapitulates all aspects of human Alzheimer's disease, and one should always be aware of the potential dangers of uncritical extrapolating from model organisms to a human condition that takes decades to develop and mainly involves higher cognitive functions. LINKED ARTICLES This article is part of a themed issue on Translational Neuropharmacology. To view the other articles in this issue visit http://dx.doi.org/10.1111/bph.2011.164.issue-4 PMID:21371009
The 2015 Nobel Prize in Physiology or Medicine has been awarded to William C. Campbell and Satoshi Omura, and Youyou Tu for the discovery of avermectins and artemisinin, respectively, therapies that revolutionized the treatment of devastating parasite diseases. With the recent technological advances, a New Golden Age of natural products drug discovery is dawning. PMID:26638061
Rodón, Jordi; Karachaliou, Niki; Sánchez, Jesús; Santarpia, Mariacarmela; Viteri, Santiago; Pilotto, Sara; Teixidó, Cristina; Riso, Aldo; Rosell, Rafael
Targeted therapy drugs are developed against specific molecular alterations on cancer cells. Because they are “targeted” to the tumor, these therapies are more effective and better tolerated than conventional therapies such as chemotherapy. In the last decade, great advances have been made in understanding of melanoma biology and identification of molecular mechanisms involved in malignant transformation of cells. The identification of oncogenic mutated kinases involved in this process provides an opportunity for development of new target therapies. The dependence of melanoma on BRAF-mutant kinase has provided an opportunity for development of mutation-specific inhibitors with high activity and excellent tolerance that are now being used in clinical practice. This marked a new era in the treatment of metastatic melanoma and much research is now ongoing to identify other “druggable” kinases and transduction signaling networking. It is expected that in the near future the spectrum of target drugs for melanoma treatment will increase. Herein, we review the most relevant potential novel drugs for melanoma treatment based on preclinical data and the results of early clinical trials. PMID:26605312
Yao, Lixia; Evans, James A; Rzhetsky, Andrey
Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development, explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies.
Yao, Lixia; Evans, James A; Rzhetsky, Andrey
Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development,explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery.These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use.Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies.
Drug discovery today is impossible without sophisticated modeling and computation. In this review we touch on previous advances in computational biology and by tracing the steps involved in pharmaceutical development, we explore a range of novel, high value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry ties for scientific and human benefit. Attention to these opportunities could promise punctuated advance, and will complement the well-established computational work on which drug discovery currently relies. PMID:19674801
Tao, Jianshi; Wendler, Philip; Connelly, Gene; Lim, Audrey; Zhang, Jiansu; King, Megan; Li, Tongchuan; Silverman, Jared A.; Schimmel, Paul R.; Tally, Francis P.
Genome projects are generating large numbers of potential new targets for drug discovery. One challenge is target validation, proving the usefulness of a specific target in an animal model. In this paper, we demonstrate a new approach to validation and assay development. We selected in vitro specific peptide binders to a potential pathogen target. By inducing the expression of a selected peptide in pathogen cells causing a lethal infection in mice, the animals were rescued. Thus, by combining in vitro selection methods for peptide binders with inducible expression in animals, the target's validity was rigorously tested and demonstrated. This approach to validation can be generalized and has the potential to become a valuable tool in the drug discovery process.
Rotella, David P
Small molecules remain the backbone for modern drug discovery. They are conceived and synthesized by medicinal chemists, many of whom were originally trained as organic chemists. Support from government and industry to provide training and personnel for continued development of this critical skill set has been declining for many years. This Viewpoint highlights the value of organic chemistry and organic medicinal chemists in the complex journey of drug discovery as a reminder that basic science support must be restored.
Jacobs, Robert T.; Nare, Bakela; Phillips, Margaret A.
African sleeping sickness is endemic in sub-Saharan Africa where the WHO estimates that 60 million people are at risk for the disease. Human African trypanosomiasis (HAT) is 100% fatal if untreated and the current drug therapies have significant limitations due to toxicity and difficult treatment regimes. No new chemical agents have been approved since eflornithine in 1990. The pentamidine analog DB289, which was in late stage clinical trials for the treatment of early stage HAT recently failed due to toxicity issues. A new protocol for the treatment of late-stage T. brucei gambiense that uses combination nifurtomox/eflornithine (NECT) was recently shown to have better safety and efficacy than eflornithine alone, while being easier to administer. This breakthrough represents the only new therapy for HAT since the approval of eflornithine. A number of research programs are on going to exploit the unusual biochemical pathways in the parasite to identify new targets for target based drug discovery programs. HTS efforts are also underway to discover new chemical entities through whole organism screening approaches. A number of inhibitors with anti-trypanosomal activity have been identified by both approaches, but none of the programs are yet at the stage of identifying a preclinical candidate. This dire situation underscores the need for continued effort to identify new chemical agents for the treatment of HAT. PMID:21401507
Blanchard, Scott C.; Feldman, Michael Brian; Wang, Leyi; Doudna Cate, James H.; Pulk, Arto; Altman, Roger B.; Wasserman, Michael R
The present invention relates to methods to identify molecules that binds in the neomycin binding pocket of a bacterial ribosome using structures of an intact bacterial ribosome that reveal how the ribosome binds tRNA in two functionally distinct states, determined by x-ray crystallography. One state positions tRNA in the peptidyl-tRNA binding site. The second, a fully rotated state, is stabilized by ribosome recycling factor (RRF) and binds tRNA in a highly bent conformation in a hybrid peptidyl/exit (P/E) site. Additionally, the invention relates to various assays, including single-molecule assay for ribosome recycling, and methods to identify compounds that interfere with ribosomal function by detecting newly identified intermediate FRET states using known and novel FRET pairs on the ribosome. The invention also provides vectors and compositions with an N-terminally tagged S13 protein.
Winchester, Catherine L; Pratt, Judith A; Morris, Brian J
Despite intensive research over many years, the treatment of schizophrenia remains a major health issue. Current and emerging treatments for schizophrenia are based upon the classical dopamine and glutamate hypotheses of disease. Existing first and second generation antipsychotic drugs based upon the dopamine hypothesis are limited by their inability to treat all symptom domains and their undesirable side effect profiles. Third generation drugs based upon the glutamate hypothesis of disease are currently under evaluation but are more likely to be used as add on treatments. Hence there is a large unmet clinical need. A major challenge in neuropsychiatric disease research is the relatively limited knowledge of disease mechanisms. However, as our understanding of the genetic causes of the disease evolves, novel strategies for the development of improved therapeutic agents will become apparent. In this review we consider the current status of knowledge of the genetic basis of schizophrenia, including methods for identifying genetic variants associated with the disorder and how they impact on gene function. Although the genetic architecture of schizophrenia is complex, some targets amenable to pharmacological intervention can be discerned. We conclude that many challenges lie ahead but the stratification of patients according to biobehavioural constructs that cross existing disease classifications but with common genetic and neurobiological bases, offer opportunities for new approaches to effective drug discovery.
Kuang, Qifan; Xu, Xin; Li, Rong; Dong, Yongcheng; Li, Yan; Huang, Ziyan; Li, Yizhou; Li, Menglong
The prediction of drug-target interactions is a key step in the drug discovery process, which serves to identify new drugs or novel targets for existing drugs. However, experimental methods for predicting drug-target interactions are expensive and time-consuming. Therefore, the in silico prediction of drug-target interactions has recently attracted increasing attention. In this study, we propose an eigenvalue transformation technique and apply this technique to two representative algorithms, the Regularized Least Squares classifier (RLS) and the semi-supervised link prediction classifier (SLP), that have been used to predict drug-target interaction. The results of computational experiments with these techniques show that algorithms including eigenvalue transformation achieved better performance on drug-target interaction prediction than did the original algorithms. These findings show that eigenvalue transformation is an efficient technique for improving the performance of methods for predicting drug-target interactions. We further show that, in theory, eigenvalue transformation can be viewed as a feature transformation on the kernel matrix. Accordingly, although we only apply this technique to two algorithms in the current study, eigenvalue transformation also has the potential to be applied to other algorithms based on kernels.
Li, Z; Wang, R-S; Zhang, X-S; Chen, L
High-throughput techniques produce massive data on a genome-wide scale which facilitate pharmaceutical research. Drug target discovery is a crucial step in the drug discovery process and also plays a vital role in therapeutics. In this study, the problem of detecting drug targets was addressed, which finds a set of enzymes whose inhibition stops the production of a given set of target compounds and meanwhile minimally eliminates non-target compounds in the context of metabolic networks. The model aims to make the side effects of drugs as small as possible and thus has practical significance of potential pharmaceutical applications. Specifically, by exploiting special features of metabolic systems, a novel approach was proposed to exactly formulate this drug target detection problem as an integer linear programming model, which ensures that optimal solutions can be found efficiently without any heuristic manipulations. To verify the effectiveness of our approach, computational experiments on both Escherichia coli and Homo sapiens metabolic pathways were conducted. The results show that our approach can identify the optimal drug targets in an exact and efficient manner. In particular, it can be applied to large-scale networks including the whole metabolic networks from most organisms.
von Korff, Modest; Rufener, Christian; Stritt, Manuel; Freyss, Joel; Bär, Roman; Sander, Thomas
Grid computing offers an opportunity to gain massive computing power at low costs. We give a short introduction into the drug discovery process and exemplify the use of grid computing for image processing, docking and 3D pharmacophore descriptor calculations. The principle of a grid and its architecture are briefly explained. More emphasis is laid on the issues related to a company-wide grid installation and embedding the grid into the research process. The future of grid computing in drug discovery is discussed in the expert opinion section. Most needed, besides reliable algorithms to predict compound properties, is embedding the grid seamlessly into the discovery process. User friendly access to powerful algorithms without any restrictions, that is, by a limited number of licenses, has to be the goal of grid computing in drug discovery.
Ekins, Sean; Waller, Chris L; Bradley, Mary P; Clark, Alex M; Williams, Antony J
Drug discovery is shifting focus from industry to outside partners and, in the process, creating new bottlenecks. Technologies like high throughput screening (HTS) have moved to a larger number of academic and institutional laboratories in the USA, with little coordination or consideration of the outputs and creating a translational gap. Although there have been collaborative public-private partnerships in Europe to share pharmaceutical data, the USA has seemingly lagged behind and this may hold it back. Sharing precompetitive data and models may accelerate discovery across the board, while finding the best collaborators, mining social media and mobile approaches to open drug discovery should be evaluated in our efforts to remove drug discovery bottlenecks. We describe four strategies to rectify the current unsustainable situation.
Hart, Thomas; Xie, Lei
Introduction The conventional one-drug-one-target-one-disease drug discovery process has been less successful in tracking multi-genic, multi-faceted complex diseases. Systems pharmacology has emerged as a new discipline to tackle the current challenges in drug discovery. The goal of systems pharmacology is to transform huge, heterogeneous, and dynamic biological and clinical data into interpretable and actionable mechanistic models for decision making in drug discovery and patient treatment. Thus, big data technology and data science will play an essential role in systems pharmacology. Areas covered This paper critically reviews the impact of three fundamental concepts of data science on systems pharmacology: similarity inference, overfitting avoidance, and disentangling causality from correlation. The authors then discuss recent advances and future directions in applying the three concepts of data science to drug discovery, with a focus on proteome-wide context-specific quantitative drug target deconvolution and personalized adverse drug reaction prediction. Expert opinion Data science will facilitate reducing the complexity of systems pharmacology modeling, detecting hidden correlations between complex data sets, and distinguishing causation from correlation. The power of data science can only be fully realized when integrated with mechanism-based multi-scale modeling that explicitly takes into account the hierarchical organization of biological systems from nucleic acid to proteins, to molecular interaction networks, to cells, to tissues, to patients, and to populations. PMID:26689499
Salfeld, Jochen G
Success in drug discovery depends largely on the implementation of appropriate strategies that build on new technologies and the appropriate mix of drug-discovery platforms and research management procedures. Close collaboration between pharmaceutical companies, biotechnology companies and academic institutions during the many intricate phases of drug discovery is necessary to address the need to co-ordinate and streamline target discovery and validation activities, which typically take much longer than anticipated. Antibodies have become an important segment of newly developed therapeutics for a wide range of indications and offer the appropriate risk/benefit profile to balance drug-discovery and development portfolios for optimum success. However, as with other discovery activities, long-term commitment and experience are required to exploit these new techniques fully. Companies with experience in managing the appropriate mix of small-molecule and antibody discovery efforts while implementing novel techniques will remain at the forefront of drug development.
Dwyer, Donard S.; Aamodt, Eric; Cohen, Bruce; Buttner, Edgar A.
Many important drugs approved to treat common human diseases were discovered by serendipity, without a firm understanding of their modes of action. As a result, the side effects and interactions of these medications are often unpredictable, and there is limited guidance for improving the design of next-generation drugs. Here, we review the innovative use of simple model organisms, especially Caenorhabditis elegans, to gain fresh insights into the complex biological effects of approved CNS medications. Whereas drug discovery involves the identification of new drug targets and lead compounds/biologics, and drug development spans preclinical testing to FDA approval, drug elucidation refers to the process of understanding the mechanisms of action of marketed drugs by studying their novel effects in model organisms. Drug elucidation studies have revealed new pathways affected by antipsychotic drugs, e.g., the insulin signaling pathway, a trace amine receptor and a nicotinic acetylcholine receptor. Similarly, novel targets of antidepressant drugs and lithium have been identified in C. elegans, including lipid-binding/transport proteins and the SGK-1 signaling pathway, respectively. Elucidation of the mode of action of anesthetic agents has shown that anesthesia can involve mitochondrial targets, leak currents, and gap junctions. The general approach reviewed in this article has advanced our knowledge about important drugs for CNS disorders and can guide future drug discovery efforts. PMID:25120487
Doshi, Rupak; Chen, Beverly R.; Vibat, Cecile Rose T.; Huang, Norman; Lee, Chang-Wook; Chang, Geoffrey
Nanobodies (Nbs) or single-domain antibodies are among the smallest and most stable binder scaffolds known. In vitro display is a powerful antibody discovery technique used worldwide. We describe the first adaptation of in vitro mRNA/cDNA display for the rapid, automatable discovery of Nbs against desired targets, and use it to discover the first ever reported nanobody against the human full-length glucose transporter, GLUT-1. We envision our streamlined method as a bench-top platform technology, in combination with various molecular evolution techniques, for expedited Nb discovery. PMID:25342225
Leung, Elaine L; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua; Liu, Liang
Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple '-omics' databases. The newly developed algorithm- or network-based computational models can tightly integrate '-omics' databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various '-omics' platforms and computational tools would accelerate development of network-based drug discovery and network medicine.
Leung, Elaine L.; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua
Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple ‘-omics’ databases. The newly developed algorithm- or network-based computational models can tightly integrate ‘-omics’ databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various ‘-omics’ platforms and computational tools would accelerate development of network-based drug discovery and network medicine. PMID:22877768
Heath, James R.; Ribas, Antoni; Mischel, Paul S.
The genetic, functional, or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development.1-3 In cancers, heterogeneity may be essential for tumor stability,4 but its precise role in tumor biology is poorly resolved. This challenges the design of accurate disease models for use in drug development, and can confound the interpretation of biomarker levels, and of patient responses to specific therapies. The complex nature of heterogeneous tissues has motivated the development of tools for single cell genomic, transcriptomic, and multiplex proteomic analysis. We review these tools, assess their advantages and limitations, and explore their potential applications in drug discovery and development. PMID:26669673
Chourasia, Rashmi; Jain, Sanjay K
Local skin targeting is of interest for the pharmaceutical and the cosmetic industry. A topically applied substance has basically three possibilities to penetrate into the skin: transcellular, intercellular, and follicular. The transfollicular path has been largely ignored because hair follicles constitute only 0.1% of the total skin. The hair follicle is a skin appendage with a complex structure containing many cell types that produce highly specialised proteins. The hair follicle is in a continuous cycle: anagen is the hair growth phase, catagen the involution phase and telogen is the resting phase. Nonetheless, the hair follicle has great potential for skin treatment, owing to its deep extension into the dermis and thus provides much deeper penetration and absorption of compounds beneath the skin than seen with the transdermal route. In the case of skin diseases and of cosmetic products, delivery to sweat glands or to the pilosebaceous unit is essential for the effectiveness of the drug. Increased accumulation in the pilosebaceous unit could treat alopecia, acne and skin cancer more efficiently and improve the effect of cosmetic substances and nutrients. Therefore, we review herein various drug delivery systems, including liposomes, niosomes, microspheres, nanoparticles, nanoemulsions, lipid nanocarriers, gene therapy and discuss the results of recent researches. We also review the drugs which have been investigated for pilosebaceous delivery.
Manallack, David T.; Prankerd, Richard J.; Yuriev, Elizabeth; Oprea, Tudor I.; Chalmers, David K.
While drug discovery scientists take heed of various guidelines concerning drug-like character, the influence of acid/base properties often remains under-scrutinised. Ionisation constants (pKa values) are fundamental to the variability of the biopharmaceutical characteristics of drugs and to underlying parameters such as logD and solubility. pKa values affect physicochemical properties such as aqueous solubility, which in turn influences drug formulation approaches. More importantly, absorption, distribution, metabolism, excretion and toxicity (ADMET) are profoundly affected by the charge state of compounds under varying pH conditions. Consideration of pKa values in conjunction with other molecular properties is of great significance and has the potential to be used to further improve the efficiency of drug discovery. Given the recent low annual output of new drugs from pharmaceutical companies, this review will provide a timely reminder of an important molecular property that influences clinical success. PMID:23099561
Alexandrov, Vadim; Brunner, Dani; Hanania, Taleen; Leahy, Emer
Drug testing with traditional behavioral assays constitutes a major bottleneck in the development of novel therapies. PsychoGenics developed three comprehensive highthroughtput systems, SmartCube®, NeuroCube® and PhenoCube® systems, to increase the efficiency of the drug screening and phenotyping in rodents. These three systems capture different domains of behavior, namely, cognitive, motor, circadian, social, anxiety-like, gait and others, using custom-built computer vision software and machine learning algorithms for analysis. This review exemplifies the use of the three systems and explains how they can advance drug screening with their applications to phenotyping of disease models, drug screening, selection of lead candidates, behavior-driven lead optimization, and drug repurposing. PMID:25592319
research working in concert with one another. The goal of this work is to use a molecular genetic approach both in the identification of new drug targets...analysis of critical genes in the Plasmodium falciparum for their role in drug resistance and as potential new drug targets using both the homologous P. falciparum system and the heterologous yeast system.
research working in concert with one another. The goal of this work is to use a molecular genetic approach both in the identification of new drug targets and...Plasmodium falciparum for their role in drug resistance and as potential new drug targets, including the analysis of gene expression in response to
Jensen, Janne; Hyllner, Johan; Björquist, Petter
Development of new drugs is costly and takes huge resources into consideration. The big pharmaceutical companies are currently facing increasing developmental costs and a lower success-rate of bringing new compounds to the market. Therefore, it is now of outmost importance that the drug-hunting companies minimize late attritions due to sub-optimal pharmacokinetic properties or unexpected toxicity when entering the clinical programs. To achieve this, a strong need to test new candidate drugs in assays of high human relevance in vitro as early as possible has been identified. The traditionally used cell systems are however remarkably limited in this sense, and new improved technologies are of greatest importance. The human embryonic stem cells (hESC) is one of the most powerful cell types known. They have not only the possibility to divide indefinitely; these cells can also differentiate into all mature cell types of the human body. This makes them potentially very valuable for pharmaceutical development, spanning from use as tools in early target studies, DMPK or safety assessment, as screening models to find new chemical entities modulating adult stem cell fate, or as the direct use in cell therapies. This review illustrates the use of hESC in the drug discovery process, today, as well as in a future perspective. This will specifically be exemplified with the most important cell type for pharmaceutical development-the hepatocyte. We discuss how hESC-derived hepatocyte-like cells could improve this process, and how these cells should be cultured if optimized functionality and usefulness should be achieved. J. Cell. Physiol. 219: 513-519, 2009. (c) 2009 Wiley-Liss, Inc.
Fischer, Peter M
The topics discussed at the conference covered many aspects of cancer research, from the genetic search for new targets, target validation and drug discovery, all the way to preclinical and clinical development of oncology drugs. Here the presentations on new metabolic, angiogenic, cell cycle and other molecular targets, as well as recent developments with experimental drugs with action on some of these targets, are summarised. Particular emphasis is placed on the emerging realisation that changes in the metabolic phenotype lie at the heart of cellular transformation. New insights into the biological links between cancer cell metabolism and the balance between survival and death signalling are likely to lead to the identification of a new category of anticancer targets.
Ochs, Christopher; Zheng, Ling; Gu, Huanying; Perl, Yehoshua; Geller, James; Kapusnik-Uner, Joan; Zakharchenko, Aleksandr
The National Drug File - Reference Terminology (NDF-RT) is a large and complex drug terminology. NDF-RT provides important information about clinical drugs, e.g., their chemical ingredients, mechanisms of action, dosage form and physiological effects. Within NDF-RT such information is represented using tens of thousands of roles. It is difficult to comprehend large, complex terminologies like NDF-RT. In previous studies, we introduced abstraction networks to summarize the content and structure of terminologies. In this paper, we introduce the Ingredient Abstraction Network to summarize NDF-RT's Chemical Ingredients and their associated drugs. Additionally, we introduce the Aggregate Ingredient Abstraction Network, for controlling the granularity of summarization provided by the Ingredient Abstraction Network. The Ingredient Abstraction Network is used to support the discovery of new candidate drug-drug interactions (DDIs) not appearing in First Databank, Inc.'s DDI knowledgebase.
FitzGerald, Garret A
The rate of new drug approvals in the US has remained essentially constant since 1950, while the costs of drug development have soared. Many commentators question the sustainability of the current model of drug development, in which large pharmaceutical companies incur markedly escalating costs to deliver the same number of products to market. This Issue Brief summarizes the problem, describes ongoing governmental efforts to influence the process, and suggests changes in regulatory science and translational medicine that may promote more successful development of safe and effective therapeutics
Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng
Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.
Wu, Wan-Ying; Hou, Jin-Jun; Long, Hua-Li; Yang, Wen-Zhi; Liang, Jian; Guo, De-An
Over the past 30 years, China has significantly improved the drug development environment by establishing a series of policies for the regulation of new drug approval. The regulatory system for new drug evaluation and registration in China was gradually developed in accordance with international standards. The approval and registration of TCM in China became as strict as those of chemical drugs and biological products. In this review, TCM-based new drug discovery and development are introduced according to the TCM classification of nine categories.
potential drug target enzymes. The yeast expression system should allow rapid screening of new drugs , greatly increasing the rate at which new...medication yet the world faces a crisis--drug resistance is emerging and spreading faster than drugs are being developed and the flow in the pipeline of new ... drugs has all but stopped. This represents a particular threat to the U.S. Military. A new strategy for drug development is urgently needed. Current
Yan, Ming; Baran, Phil S.
A synthetic strategy has been developed that provides easy access to structurally diverse analogues of naturally occurring antibiotics, providing a fresh means of attack in the war against drug-resistant bacteria. See Article p.338
Jin, Ping; Chen, Xiaofei
In recent years, there has been an expansion of the understanding of how epigenetic dysregulation plays a role in tumorigenesis, progression, metastasis and treatment resistance. Evidence has focused on two common and well-studied "epigenetic codes", i.e., DNA methylation and histone posttranslational modification, which regulate the transcriptional status in various types of cancer and the corresponding target agents. Aside from "writers" and "erasers", which refer to enzymes that catalyze and remove posttranslational modifications, respectively, "readers" bind to target proteins and recruit "writers" and "erasers" for regulating gene expression. A number of selective and potent anticancer compounds have been reported, some of which are in preclinical or clinical trials that have shown promising results, primarily against malignant neoplasms such as hematologic malignancies, with the subsequent emerging development of both monotherapy and co-administration with traditional cytotoxic medicines against solid tumors. Second-generation epigenetic agents such as EZH2 and BET inhibitors have greatly progressed. Epigenetic dysregulation has also provided feasibility for the diagnosis and treatment of cancer. In this review, we summarize the progress in epigenetics and drug discovery for cancer and certain clinical trials that may provide a perspective for future development.
Tralau-Stewart, Cathy J; Wyatt, Colin A; Kleyn, Dominique E; Ayad, Alex
The re-focusing of pharmaceutical industry research away from early discovery activities is stimulating the development of novel models of drug discovery, notably involving academia as a 'front end'. In this article the authors explore the drivers of change, the role of new entrants (universities with specialised core facilities) and novel partnership models. If they are to be sustainable and deliver, these new models must be flexible and properly funded by industry or public funding, rewarding all partners for contributions. The introduction of an industry-like process and experienced management teams signals a revolution in discovery that benefits society by improving the value gained from publicly funded research.
Garbaccio, Robert M; Parmee, Emma R
Chemical probes represent an important component of both academic and pharmaceutical drug discovery research. As a complement to prior reviews that have defined this scientific field, we aim to provide an industry perspective on the value of having high-quality chemical probes throughout the course of preclinical research. By studying examples from the internal Merck pipeline, we recognize that these probes require significant collaborative investment to realize their potential impact in clarifying the tractability and translation of a given therapeutic target. This perspective concludes with recommendations for chemical probe discovery aimed toward maximizing their potential to identify targets that result in the successful delivery of novel therapeutics.
Lee, Jonathan A; Berg, Ellen L
Innovation and new molecular entity production by the pharmaceutical industry has been below expectations. Surprisingly, more first-in-class small-molecule drugs approved by the U.S. Food and Drug Administration (FDA) between 1999 and 2008 were identified by functional phenotypic lead generation strategies reminiscent of pre-genomics pharmacology than contemporary molecular targeted strategies that encompass the vast majority of lead generation efforts. This observation, in conjunction with the difficulty in validating molecular targets for drug discovery, has diminished the impact of the "genomics revolution" and has led to a growing grassroots movement and now broader trend in pharma to reconsider the use of modern physiology-based or phenotypic drug discovery (PDD) strategies. This "From the Guest Editors" column provides an introduction and overview of the two-part special issues of Journal of Biomolecular Screening on PDD. Terminology and the business case for use of PDD are defined. Key issues such as assay performance, chemical optimization, target identification, and challenges to the organization and implementation of PDD are discussed. Possible solutions for these challenges and a new neoclassic vision for PDD that combines phenotypic and functional approaches with technology innovations resulting from the genomics-driven era of target-based drug discovery (TDD) are also described. Finally, an overview of the manuscripts in this special edition is provided.
Janero, David R
Research universities continue to produce new scientists capable of generating knowledge with the potential to inform disease etiology and treatment. Mounting interest of doctoral-level experimental science students in therapeutics-related research careers is discordant with the widespread lack of direct drug-discovery and development experience, let alone commercialization success, among university faculty and administrators. Likewise, the archetypical publication- and grant-fueled, principal investigator (PI)-focused academic system ("PI-stan") risks commoditization of science students pursuing their doctorates as a labor source, rendering them ill-prepared for career options related to therapeutics innovation by marginalizing their development of "beyond-the-bench" professional skills foundational to modern drug-discovery campaigns and career fluency. To militate against professionalization deficits in doctoral drug-discovery researchers, the author--a scientist-administrator-consultant with decades of discovery research and development (R&D), business, and educator experience in commercial and university settings--posits a critical need for pluridimensionality in graduate education and mentorship that extends well beyond thesis-related scientific domains/laboratory techniques to instill transferable operational-intelligence, project/people-management, and communication competencies. Specific initiatives are advocated to help enhance the doctoral science student's market competitiveness, adaptability, and navigation of the significant research, commercial, and occupational challenges associated with contemporary preclinical drug-discovery R&D.
Feixas, Ferran; Lindert, Steffen; Sinko, William; McCammon, J. Andrew
The proper understanding of biomolecular recognition mechanisms that take place in a drug target is of paramount importance to improve the efficiency of drug discovery and development. The intrinsic dynamic character of proteins has a strong influence on biomolecular recognition mechanisms and models such as conformational selection have been widely used to account for this dynamic association process. However, conformational changes occurring in the receptor prior and upon association with other molecules are diverse and not obvious to predict when only a few structures of the receptor are available. In view of the prominent role of protein flexibility in ligand binding and its implications for drug discovery, it is of great interest to identify receptor conformations that play a major role in biomolecular recognition before starting rational drug design efforts. In this review, we discuss a number of recent advances in computer-aided drug discovery techniques that have been proposed to incorporate receptor flexibility into structure-based drug design. The allowance for receptor flexibility provided by computational techniques such as molecular dynamics simulations or enhanced sampling techniques helps to improve the accuracy of methods used to estimate binding affinities and, thus, such methods can contribute to the discovery of novel drug leads. PMID:24332165
Qi, Da; King, Ross D; Hopkins, Andrew L; Bickerton, G Richard J; Soldatova, Larisa N
The paper presents an ontology for the description of Drug Discovery Investigation (DDI).This has been developed through the use of a Robot Scientist "Eve", and in consultation with industry. DDI aims to define the principle entities and the relations in the research and development phase of the drug discovery pipeline. DDI is highly transferable and extendable due to its adherence to accepted standards, and compliance with existing ontology resources. This enables DDI to be integrated with such related ontologies as the Vaccine Ontology, the Advancing Clinico-Genomic Trials on Cancer Master Ontology, etc. DDI is available at http://purl.org/ddi/wikipedia or http://purl.org/ddi/home.
Heath, James R; Ribas, Antoni; Mischel, Paul S
The genetic, functional or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development. Such heterogeneity hinders the design of accurate disease models and can confound the interpretation of biomarker levels and of patient responses to specific therapies. The complex nature of virtually all tissues has motivated the development of tools for single-cell genomic, transcriptomic and multiplex proteomic analyses. Here, we review these tools and assess their advantages and limitations. Emerging applications of single cell analysis tools in drug discovery and development, particularly in the field of oncology, are discussed.
Huang, Fuqiang; Zhang, Boya; Zhou, Shengtao; Zhao, Xia; Bian, Ce; Wei, Yuquan
The growing demand for new therapeutic strategies in the medical and pharmaceutic fields has resulted in a pressing need for novel druggable targets. Paradoxically, however, the targets of certain drugs that are already widely used in clinical practice have largely not been annotated. Because the pharmacologic effects of a drug can only be appreciated when its interactions with cellular components are clearly delineated, an integrated deconvolution of drug-target interactions for each drug is necessary. The emerging field of chemical proteomics represents a powerful mass spectrometry (MS)-based affinity chromatography approach for identifying proteome-wide small molecule-protein interactions and mapping these interactions to signaling and metabolic pathways. This technique could comprehensively characterize drug targets, profile the toxicity of known drugs, and identify possible off-target activities. With the use of this technique, candidate drug molecules could be optimized, and predictable side effects might consequently be avoided. Herein, we provide a holistic overview of the major chemical proteomic approaches and highlight recent advances in this area as well as its potential applications in drug discovery. PMID:22640626
Chen, Xing; Yan, Chenggang Clarence; Zhang, Xiaotian; Zhang, Xu; Dai, Feng; Yin, Jian; Zhang, Yongdong
Identification of drug-target interactions is an important process in drug discovery. Although high-throughput screening and other biological assays are becoming available, experimental methods for drug-target interaction identification remain to be extremely costly, time-consuming and challenging even nowadays. Therefore, various computational models have been developed to predict potential drug-target associations on a large scale. In this review, databases and web servers involved in drug-target identification and drug discovery are summarized. In addition, we mainly introduced some state-of-the-art computational models for drug-target interactions prediction, including network-based method, machine learning-based method and so on. Specially, for the machine learning-based method, much attention was paid to supervised and semi-supervised models, which have essential difference in the adoption of negative samples. Although significant improvements for drug-target interaction prediction have been obtained by many effective computational models, both network-based and machine learning-based methods have their disadvantages, respectively. Furthermore, we discuss the future directions of the network-based drug discovery and network approach for personalized drug discovery based on personalized medicine, genome sequencing, tumor clone-based network and cancer hallmark-based network. Finally, we discussed the new evaluation validation framework and the formulation of drug-target interactions prediction problem by more realistic regression formulation based on quantitative bioactivity data.
Holmes, Ann R; Cardno, Tony S; Strouse, J Jacob; Ivnitski-Steele, Irena; Keniya, Mikhail V; Lackovic, Kurt; Monk, Brian C; Sklar, Larry A; Cannon, Richard D
Resistance to antifungal drugs is an increasingly significant clinical problem. The most common antifungal resistance encountered is efflux pump-mediated resistance of Candida species to azole drugs. One approach to overcome this resistance is to inhibit the pumps and chemosensitize resistant strains to azole drugs. Drug discovery targeting fungal efflux pumps could thus result in the development of azole-enhancing combination therapy. Heterologous expression of fungal efflux pumps in Saccharomyces cerevisiae provides a versatile system for screening for pump inhibitors. Fungal efflux pumps transport a range of xenobiotics including fluorescent compounds. This enables the use of fluorescence-based detection, as well as growth inhibition assays, in screens to discover compounds targeting efflux-mediated antifungal drug resistance. A variety of medium- and high-throughput screens have been used to identify a number of chemical entities that inhibit fungal efflux pumps.
Cyclic peptide libraries have demonstrated significant potential when employed against challenging targets such as protein-protein interactions. While a variety of methods for library generation exist, genetically encoded libraries hold several advantages over their chemically synthesized counterparts; they are more readily accessible and allow straightforward hit deconvolution. One method for the intracellular generation of such libraries is split-intein circular ligation of peptides and proteins (SICLOPPS). Here we detail and discuss the deployment of SICLOPPS libraries for the identification of cyclic peptide inhibitors of a variety of targets.
Pettit, Robin K
Soil has the largest population of microbes of any habitat, but only about 0.3% of soil microbes are cultivable with current techniques. Cultured soil microbes have been an incredibly productive source of drugs, for example the cancer chemotherapeutics doxorubicin hydrochloride, bleomycin, daunorubicin and mitomycin. Unfortunately, the current yield of new drugs from soil microbes is low due to repeated cultivation of the same small fraction of cultivable microbes. Uncultured soil species represent a tremendous untapped resource of new antineoplastic agents. Methods have recently been developed to access the diversity of secondary metabolites from uncultured soil microbes. Briefly, total DNA is extracted from soil samples, purified, partially digested, and fragments inserted into vectors for expression in readily fermented microbes such as Escherichia coli. Clones expressing enzymatic and antibiotic activities that are encoded by novel sequences have been reported.
Minie, Mark; Chopra, Gaurav; Sethi, Geetika; Horst, Jeremy; White, George; Roy, Ambrish; Hatti, Kaushik; Samudrala, Ram
The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound–proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12–25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 ‘high value’ predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering. PMID:24980786
Ma, Cong; Yang, Xiao; Lewis, Peter J
Transcription, the first step of gene expression, is carried out by the enzyme RNA polymerase (RNAP) and is regulated through interaction with a series of protein transcription factors. RNAP and its associated transcription factors are highly conserved across the bacterial domain and represent excellent targets for broad-spectrum antibacterial agent discovery. Despite the numerous antibiotics on the market, there are only two series currently approved that target transcription. The determination of the three-dimensional structures of RNAP and transcription complexes at high resolution over the last 15 years has led to renewed interest in targeting this essential process for antibiotic development by utilizing rational structure-based approaches. In this review, we describe the inhibition of the bacterial transcription process with respect to structural studies of RNAP, highlight recent progress toward the discovery of novel transcription inhibitors, and suggest additional potential antibacterial targets for rational drug design.
Ma, Cong; Yang, Xiao
SUMMARY Transcription, the first step of gene expression, is carried out by the enzyme RNA polymerase (RNAP) and is regulated through interaction with a series of protein transcription factors. RNAP and its associated transcription factors are highly conserved across the bacterial domain and represent excellent targets for broad-spectrum antibacterial agent discovery. Despite the numerous antibiotics on the market, there are only two series currently approved that target transcription. The determination of the three-dimensional structures of RNAP and transcription complexes at high resolution over the last 15 years has led to renewed interest in targeting this essential process for antibiotic development by utilizing rational structure-based approaches. In this review, we describe the inhibition of the bacterial transcription process with respect to structural studies of RNAP, highlight recent progress toward the discovery of novel transcription inhibitors, and suggest additional potential antibacterial targets for rational drug design. PMID:26764017
Csermely, Peter; Korcsmáros, Tamás; Kiss, Huba J M; London, Gábor; Nussinov, Ruth
Despite considerable progress in genome- and proteome-based high-throughput screening methods and in rational drug design, the increase in approved drugs in the past decade did not match the increase of drug development costs. Network description and analysis not only give a systems-level understanding of drug action and disease complexity, but can also help to improve the efficiency of drug design. We give a comprehensive assessment of the analytical tools of network topology and dynamics. The state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets is summarized. We propose that network targeting follows two basic strategies. The "central hit strategy" selectively targets central nodes/edges of the flexible networks of infectious agents or cancer cells to kill them. The "network influence strategy" works against other diseases, where an efficient reconfiguration of rigid networks needs to be achieved by targeting the neighbors of central nodes/edges. It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates. We review the recent boom in network methods helping hit identification, lead selection optimizing drug efficacy, as well as minimizing side-effects and drug toxicity. Successful network-based drug development strategies are shown through the examples of infections, cancer, metabolic diseases, neurodegenerative diseases and aging. Summarizing >1200 references we suggest an optimized protocol of network-aided drug development, and provide a list of systems-level hallmarks of drug quality. Finally, we highlight network-related drug development trends helping to achieve these hallmarks by a cohesive, global approach.
Potterat, Olivier; Hamburger, Matthias
An overview is given on current efforts in drug development based on plant-derived natural products. Emphasis is on projects which have advanced to clinical development. Therapeutic areas covered include cancer, viral infections including HIV, malaria, inflammatory diseases, nociception and vaccine adjuvants, metabolic disorders, and neurodegenerative diseases. Aspects which are specific to plant-based drug discovery and development are also addressed, such as supply issues in the commercial development, and the Convention on Biological Diversity.
results provide us with a great perspective for designing novel GCS inhibitors. GCS is considered to be a critical enzyme implicated in cancer drug... Cytochrome P450 Inhibitors- A Study of Their Potency and Selectivity”, J. Sridhar, J. Liu, C.L.K. Stevens, and M. Foroozesh, Society of Toxicology...AD_________________ Award Number: W81XWH-11-1-0105 TITLE: A Drug Discovery Partnership for Personalized Breast Cancer Therapy
Zhan, Peng; Pannecouque, Christophe; De Clercq, Erik; Liu, Xinyong
The early effectiveness of combinatorial antiretroviral therapy (cART) in the treatment of HIV infection has been compromised to some extent by rapid development of multidrug-resistant HIV strains, poor bioavailability, and cumulative toxicities, and so there is a need for alternative strategies of antiretroviral drug discovery and additional therapeutic agents with novel action modes or targets. From this perspective, we first review current strategies of antiretroviral drug discovery and optimization, with the aid of selected examples from the recent literature. We highlight the development of phosphate ester-based prodrugs as a means to improve the aqueous solubility of HIV inhibitors, and the introduction of the substrate envelope hypothesis as a new approach for overcoming HIV drug resistance. Finally, we discuss future directions for research, including opportunities for exploitation of novel antiretroviral targets, and the strategy of activation of latent HIV reservoirs as a means to eradicate the virus.
Pasquato, Antonella; Burri, Dominique J; Kunz, Stefan
Arenaviruses are a large group of emerging viruses including several causative agents of severe hemorrhagic fevers with high mortality in man. Considering the number of people affected and the currently limited therapeutic options, novel efficacious therapeutics against arenaviruses are urgently needed. Over the past decade, significant advances in knowledge about the basic virology of arenaviruses have been accompanied by the development of novel therapeutics targeting different steps of the arenaviral life cycle. High-throughput, small-molecule screens identified potent and broadly active inhibitors of arenavirus entry that were instrumental for the dissection of unique features of arenavirus fusion. Novel inhibitors of arenavirus replication have been successfully tested in animal models and hold promise for application in humans. Late in the arenavirus life cycle, the proteolytic processing of the arenavirus envelope glycoprotein precursor and cellular factors critically involved virion assembly and budding provide further promising 'druggable' targets for novel therapeutics to combat human arenavirus infection.
Chatelain, Eric; Ioset, Jean-Robert
New models of drug discovery have been developed to overcome the lack of modern and effective drugs for neglected diseases such as human African trypanosomiasis (HAT; sleeping sickness), leishmaniasis, and Chagas disease, which have no financial viability for the pharmaceutical industry. With the purpose of combining the skills and research capacity in academia, pharmaceutical industry, and contract researchers, public-private partnerships or product development partnerships aim to create focused research consortia that address all aspects of drug discovery and development. These consortia not only emulate the projects within pharmaceutical and biotechnology industries, eg, identification and screening of libraries, medicinal chemistry, pharmacology and pharmacodynamics, formulation development, and manufacturing, but also use and strengthen existing capacity in disease-endemic countries, particularly for the conduct of clinical trials. The Drugs for Neglected Diseases initiative (DNDi) has adopted a model closely related to that of a virtual biotechnology company for the identification and optimization of drug leads. The application of this model to the development of drug candidates for the kinetoplastid infections of HAT, Chagas disease, and leishmaniasis has already led to the identification of new candidates issued from DNDi's own discovery pipeline. This demonstrates that the model DNDi has been implementing is working but its DNDi, neglected diseases sustainability remains to be proven.
Yuan, William; Jiang, Dadi; Nambiar, Dhanya K; Liew, Lydia P; Hay, Michael Patrick; Bloomstein, Joshua; Lu, Peter; Turner, Brandon; Le, Quynh-The; Tibshirani, Robert; Khatri, Purvesh; Moloney, Mark Gerard; Koong, Albert C
We describe a new library generation method, Machine-based Identification of Molecules Inside Characterized Space (MIMICS) that generates sets of molecules inspired by a text-based input. MIMICS-generated libraries were found to preserve distributions of properties while simultaneously increasing structural diversity. Newly identified MIMICS-generated compounds were found to be bioactive as inhibitors of specific components of the unfolded protein response (UPR) and the VEGFR2 pathway in cell-based assays, thus confirming that applicability of this methodology towards drug design applications. Wider application of MIMICS could facilitate the efficient utilization of chemical space.
Magedov, I. V.; Kornienko, A.
Multicomponent reactions are emerging as a powerful tool in alkaloid-based drug discovery. This Highlight describes several recent (all published in 2011) examples of the employment of multicomponent reactions for the synthesis of biologically active alkaloids and their medicinally relevant analogues. PMID:27917001
Wells, Timothy N C; Willis, Paul; Burrows, Jeremy N; Hooft van Huijsduijnen, Rob
There is a growing consensus that drug discovery thrives in an open environment. Here, we describe how the malaria community has embraced four levels of open data - open science, open innovation, open access and open source - to catalyse the development of new medicines, and consider principles that could enable open data approaches to be applied to other disease areas.
Grandjean, Nicolas; Charpiot, Brigitte; Pena, Carlos Andres; Peitsch, Manuel C
Patents are a major source of information in drug discovery and, when properly processed and analyzed, can yield a wealth of information on competitors activities, R&D trends, emerging fields, collaborations, among others. This review discusses the current state-of-the-art in textual data analysis and exploration methods as applied to patent analysis.:
Fang, J; Cai, C; Wang, Q; Lin, P; Zhao, Z; Cheng, F
Massive cancer genomics data have facilitated the rapid revolution of a novel oncology drug discovery paradigm through targeting clinically relevant driver genes or mutations for the development of precision oncology. Natural products with polypharmacological profiles have been demonstrated as promising agents for the development of novel cancer therapies. In this study, we developed an integrated systems pharmacology framework that facilitated identifying potential natural products that target mutated genes across 15 cancer types or subtypes in the realm of precision medicine. High performance was achieved for our systems pharmacology framework. In case studies, we computationally identified novel anticancer indications for several US Food and Drug Administration-approved or clinically investigational natural products (e.g., resveratrol, quercetin, genistein, and fisetin) through targeting significantly mutated genes in multiple cancer types. In summary, this study provides a powerful tool for the development of molecularly targeted cancer therapies through targeting the clinically actionable alterations by exploiting the systems pharmacology of natural products.
Fang, J; Cai, C; Wang, Q; Lin, P
Massive cancer genomics data have facilitated the rapid revolution of a novel oncology drug discovery paradigm through targeting clinically relevant driver genes or mutations for the development of precision oncology. Natural products with polypharmacological profiles have been demonstrated as promising agents for the development of novel cancer therapies. In this study, we developed an integrated systems pharmacology framework that facilitated identifying potential natural products that target mutated genes across 15 cancer types or subtypes in the realm of precision medicine. High performance was achieved for our systems pharmacology framework. In case studies, we computationally identified novel anticancer indications for several US Food and Drug Administration‐approved or clinically investigational natural products (e.g., resveratrol, quercetin, genistein, and fisetin) through targeting significantly mutated genes in multiple cancer types. In summary, this study provides a powerful tool for the development of molecularly targeted cancer therapies through targeting the clinically actionable alterations by exploiting the systems pharmacology of natural products. PMID:28294568
Frijters, Raoul; van Vugt, Marianne; Smeets, Ruben; van Schaik, René; de Vlieg, Jacob; Alkema, Wynand
The scientific literature represents a rich source for retrieval of knowledge on associations between biomedical concepts such as genes, diseases and cellular processes. A commonly used method to establish relationships between biomedical concepts from literature is co-occurrence. Apart from its use in knowledge retrieval, the co-occurrence method is also well-suited to discover new, hidden relationships between biomedical concepts following a simple ABC-principle, in which A and C have no direct relationship, but are connected via shared B-intermediates. In this paper we describe CoPub Discovery, a tool that mines the literature for new relationships between biomedical concepts. Statistical analysis using ROC curves showed that CoPub Discovery performed well over a wide range of settings and keyword thesauri. We subsequently used CoPub Discovery to search for new relationships between genes, drugs, pathways and diseases. Several of the newly found relationships were validated using independent literature sources. In addition, new predicted relationships between compounds and cell proliferation were validated and confirmed experimentally in an in vitro cell proliferation assay. The results show that CoPub Discovery is able to identify novel associations between genes, drugs, pathways and diseases that have a high probability of being biologically valid. This makes CoPub Discovery a useful tool to unravel the mechanisms behind disease, to find novel drug targets, or to find novel applications for existing drugs.
Frijters, Raoul; van Vugt, Marianne; Smeets, Ruben; van Schaik, René; de Vlieg, Jacob; Alkema, Wynand
The scientific literature represents a rich source for retrieval of knowledge on associations between biomedical concepts such as genes, diseases and cellular processes. A commonly used method to establish relationships between biomedical concepts from literature is co-occurrence. Apart from its use in knowledge retrieval, the co-occurrence method is also well-suited to discover new, hidden relationships between biomedical concepts following a simple ABC-principle, in which A and C have no direct relationship, but are connected via shared B-intermediates. In this paper we describe CoPub Discovery, a tool that mines the literature for new relationships between biomedical concepts. Statistical analysis using ROC curves showed that CoPub Discovery performed well over a wide range of settings and keyword thesauri. We subsequently used CoPub Discovery to search for new relationships between genes, drugs, pathways and diseases. Several of the newly found relationships were validated using independent literature sources. In addition, new predicted relationships between compounds and cell proliferation were validated and confirmed experimentally in an in vitro cell proliferation assay. The results show that CoPub Discovery is able to identify novel associations between genes, drugs, pathways and diseases that have a high probability of being biologically valid. This makes CoPub Discovery a useful tool to unravel the mechanisms behind disease, to find novel drug targets, or to find novel applications for existing drugs. PMID:20885778
Chautard, E; Thierry-Mieg, N; Ricard-Blum, S
Most genes, proteins and other components carry out their functions within a complex network of interactions and a single molecule can affect a wide range of other cell components. A global, integrative, approach has been developed for several years, including protein-protein interaction networks (interactomes). In this review, we describe the high-throughput methods used to identify new interactions and to build large interaction datasets. The minimum information required for reporting a molecular interaction experiment (MIMIx) has been defined as a standard for storing data in publicly available interaction databases. Several examples of interaction networks from molecular machines (proteasome) or organelles (phagosome, mitochondrion) to whole organisms (viruses, bacteria, yeast, fly, and worm) are given and attempts to cover the entire human interaction network are discussed. The methods used to perform the topological analysis of interaction networks and to extract biological information from them are presented. These investigations have provided clues on protein functions, signalling and metabolic pathways, and physiological processes, unraveled the molecular basis of some diseases (cancer, infectious diseases), and will be very useful to identify new therapeutic targets and for drug discovery. A major challenge is now to integrate data from different sources (interactome, transcriptome, phenome, localization) to switch from static to dynamic interaction networks. The merging of a viral interactome and the human interactome has been used to simulate viral infection, paving the way for future studies aiming at providing molecular basis of human diseases.
Vilar, Santiago; Quezada, Elías; Uriarte, Eugenio; Costanzi, Stefano; Borges, Fernanda; Viña, Dolores; Hripcsak, George
The development of computational methods to discover novel drug-target interactions on a large scale is of great interest. We propose a new method for virtual screening based on protein interaction profile similarity to discover new targets for molecules, including existing drugs. We calculated Target Interaction Profile Fingerprints (TIPFs) based on ChEMBL database to evaluate drug similarity and generated new putative compound-target candidates from the non-intersecting targets in each pair of compounds. A set of drugs was further studied in monoamine oxidase B (MAO-B) and cyclooxygenase-1 (COX-1) enzyme through molecular docking and experimental assays. The drug ethoxzolamide and the natural compound piperlongumine, present in Piper longum L, showed hMAO-B activity with IC50 values of 25 and 65 μM respectively. Five candidates, including lapatinib, SB-202190, RO-316233, GW786460X and indirubin-3′-monoxime were tested against human COX-1. Compounds SB-202190 and RO-316233 showed a IC50 in hCOX-1 of 24 and 25 μM respectively (similar range as potent inhibitors such as diclofenac and indomethacin in the same experimental conditions). Lapatinib and indirubin-3′-monoxime showed moderate hCOX-1 activity (19.5% and 28% of enzyme inhibition at 25 μM respectively). Our modeling constitutes a multi-target predictor for large scale virtual screening with potential in lead discovery, repositioning and drug safety. PMID:27845365
Lounnas, Valère; Ritschel, Tina; Kelder, Jan; McGuire, Ross; Bywater, Robert P.; Foloppe, Nicolas
The past decade has witnessed a paradigm shift in preclinical drug discovery with structure-based drug design (SBDD) making a comeback while high-throughput screening (HTS) methods have continued to generate disappointing results. There is a deficit of information between identified hits and the many criteria that must be fulfilled in parallel to convert them into preclinical candidates that have a real chance to become a drug. This gap can be bridged by investigating the interactions between the ligands and their receptors. Accurate calculations of the free energy of binding are still elusive; however progresses were made with respect to how one may deal with the versatile role of water. A corpus of knowledge combining X-ray structures, bioinformatics and molecular modeling techniques now allows drug designers to routinely produce receptor homology models of increasing quality. These models serve as a basis to establish and validate efficient rationales used to tailor and/or screen virtual libraries with enhanced chances of obtaining hits. Many case reports of successful SBDD show how synergy can be gained from the combined use of several techniques. The role of SBDD with respect to two different classes of widely investigated pharmaceutical targets: (a) protein kinases (PK) and (b) G-protein coupled receptors (GPCR) is discussed. Throughout these examples prototypical situations covering the current possibilities and limitations of SBDD are presented. PMID:24688704
a productive partnership with the Cancer Drug Validation Team at the Tulane Cancer Center. This inter-university collaboration involves training ...Identification of compounds with the potential for estrogen receptor activity. 15. SUBJECT TERMS Breast cancer, Partnership, Training 16. SECURITY...University involves training of Xavier researchers and students in drug target validation, biological assays of drug efficacy, evaluation of resistance
Csermely, Peter; Korcsmáros, Tamás; Kiss, Huba J.M.; London, Gábor; Nussinov, Ruth
Despite considerable progress in genome- and proteome-based high-throughput screening methods and in rational drug design, the increase in approved drugs in the past decade did not match the increase of drug development costs. Network description and analysis not only gives a systems-level understanding of drug action and disease complexity, but can also help to improve the efficiency of drug design. We give a comprehensive assessment of the analytical tools of network topology and dynamics. The state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets is summarized. We propose that network targeting follows two basic strategies. The “central hit strategy” selectively targets central node/edges of the flexible networks of infectious agents or cancer cells to kill them. The “network influence strategy” works against other diseases, where an efficient reconfiguration of rigid networks needs to be achieved. It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates. We review the recent boom in network methods helping hit identification, lead selection optimizing drug efficacy, as well as minimizing side-effects and drug toxicity. Successful network-based drug development strategies are shown through the examples of infections, cancer, metabolic diseases, neurodegenerative diseases and aging. Summarizing >1200 references we suggest an optimized protocol of network-aided drug development, and provide a list of systems-level hallmarks of drug quality. Finally, we highlight network-related drug development trends helping to achieve these hallmarks by a cohesive, global approach. PMID:23384594
Bueters, Tjerk; Gibson, Christopher; Visser, Sandra A G
In this perspective article, we explain how quantitative and translational pharmacology, when well-implemented, is believed to lead to improved clinical candidates and drug targets that are differentiated from current treatment options. Quantitative and translational pharmacology aims to build and continuously improve the quantitative relationship between drug exposure, target engagement, efficacy, safety and its interspecies relationship at every phase of drug discovery. Drug hunters should consider and apply these concepts to develop compounds with a higher probability of interrogating the clinical biological hypothesis. We offer different approaches to set an initial effective concentration or pharmacokinetic-pharmacodynamic target in man and to predict human pharmacokinetics that determine together the predicted human dose and dose schedule. All concepts are illustrated with ample literature examples.
Alonso-Padilla, Julio; Rodríguez, Ana
The discovery of new therapeutic options against Trypanosoma cruzi, the causative agent of Chagas disease, stands as a fundamental need. Currently, there are only two drugs available to treat this neglected disease, which represents a major public health problem in Latin America. Both available therapies, benznidazole and nifurtimox, have significant toxic side effects and their efficacy against the life-threatening symptomatic chronic stage of the disease is variable. Thus, there is an urgent need for new, improved anti-T. cruzi drugs. With the objective to reliably accelerate the drug discovery process against Chagas disease, several advances have been made in the last few years. Availability of engineered reporter gene expressing parasites triggered the development of phenotypic in vitro assays suitable for high throughput screening (HTS) as well as the establishment of new in vivo protocols that allow faster experimental outcomes. Recently, automated high content microscopy approaches have also been used to identify new parasitic inhibitors. These in vitro and in vivo early drug discovery approaches, which hopefully will contribute to bring better anti-T. cruzi drug entities in the near future, are reviewed here.
Ross, Brian; Tran, Thao; Bhattacharya, Pratip; Watterson, D Martin; Sailasuta, Napapon
We describe the details of the magnetic resonance spectroscopy and chemical shift imaging techniques for the human brain which have been developed over the last two decades. With these non-invasive tools, it is now readily possible to repeatedly assay up to 20 common brain metabolites. From the perspective of drug discovery, each of these metabolites could fulfill a number of useful functions: disease biomarker, surrogate marker of drug delivery, surrogate marker of drug efficacy and so on. To facilitate the possible utility of clinical magnetic resonance spectroscopy in future drug discovery, the major portion of the review is devoted to a detailed description of the well-validated neurochemical profiles of many common human brain disorders, for which MRS data now exists. Beyond proton, MRS, the commonest tool provided by the manufacturers of clinical MRI equipment, lays the world of heteronuclear NMR more familiar to chemists. Here too, with relatively little effort it has been possible to define neurochemical profiles of human brain disorders using (13)C MRS in particular. The future for drug discovery scientists is discussed. Finally, recognizing that a known feature of MR is the lack of sensitivity, we describe new efforts to harness hyperpolarization, with its 50,000 signal amplification, to conventional MRS.
Low productivity, rising R&D costs, dissipating proprietary products and dwindling pipelines are driving the pharmaceutical industry to unprecedented challenges and scrutiny. In this article I reflect on the current status of the pharmaceutical industry and reasons for continued low productivity. An emerging 'symbiotic model of innovation', that addresses underlying issues in drug failure and attempts to narrow gaps in current drug discovery processes, is discussed to boost productivity. The model emphasizes partnerships in innovation to deliver quality products in a cost-effective system. I also discuss diverse options to build a balanced research portfolio with higher potential for persistent delivery of drug molecules.
Thiazolidinedione (TZD) is a powerful insulin sensitizer in the treatment of type 2 diabetes. It acts as a ligand to the nuclear receptor PPARγ (peroxisome proliferator-activated receptor-gamma) and induces transcription of PPARγ responsive genes. TZD controls lipid synthesis and storage in adipose tissue, liver and many other tissues through PPARγ. Derivatives of TZD, such as rosiglitazone (Avandia) and pioglitazone (Actos), are more powerful than metformin or berberine in insulin sensitization. Although they have common side effects such as weight gain and edema, these did not influence the side effects in general. However, recent findings of risk for congestive heart failure and bladder cancer have indeed significantly impaired their future in many countries. European countries have prohibited those drugs and in 2011, US will terminate application of rosiglitazone in clinics and hospitals. The multiple country actions may mark the end of TZD era. As a result, there is a strong demand for identification of TZD substitute in the treatment of type 2 diabetes. In this regard, literature about PPARγ ligands and potential TZD substitute are reviewed in this article. Histone deacetylase (HDAC) inhibitor is emphasized as a new class of insulin sensitizer here. Regulators of SIRT1, CREB, NO, p38, ERK and Cdk5 are discussed in the activation of PPARγ.
Takaki, Kevin; Cosma, Christine L; Troll, Mark A; Ramakrishnan, Lalita
Treatment of tuberculosis, like other infectious diseases, is increasingly hindered by the emergence of drug resistance. Drug discovery efforts would be facilitated by facile screening tools that incorporate the complexities of human disease. Mycobacterium marinum-infected zebrafish larvae recapitulate key aspects of tuberculosis pathogenesis and drug treatment. Here, we develop a model for rapid in vivo drug screening using fluorescence-based methods for serial quantitative assessment of drug efficacy and toxicity. We provide proof-of-concept that both traditional bacterial-targeting antitubercular drugs and newly identified host-targeting drugs would be discovered through the use of this model. We demonstrate the model's utility for the identification of synergistic combinations of antibacterial drugs and demonstrate synergy between bacterial- and host-targeting compounds. Thus, the platform can be used to identify new antibacterial agents and entirely new classes of drugs that thwart infection by targeting host pathways. The methods developed here should be widely applicable to small-molecule screens for other infectious and noninfectious diseases.
Santos, Zenildo; Avci, Pinar; Hamblin, Michael R
Introduction Hair loss or alopecia affects the majority of the population at some time in their life, and increasingly, sufferers are demanding treatment. Three main types of alopecia (androgenic [AGA], areata [AA] and chemotherapy-induced [CIA]) are very different, and have their own laboratory models and separate drug-discovery efforts. Areas covered In this article, the authors review the biology of hair, hair follicle (HF) cycling, stem cells and signaling pathways. AGA, due to dihydrotesterone, is treated by 5-α reductase inhibitors, androgen receptor blockers and ATP-sensitive potassium channel-openers. AA, which involves attack by CD8+NK group 2D-positive (NKG2D+) T cells, is treated with immunosuppressives, biologics and JAK inhibitors. Meanwhile, CIA is treated by apoptosis inhibitors, cytokines and topical immunotherapy. Expert opinion The desire to treat alopecia with an easy topical preparation is expected to grow with time, particularly with an increasing aging population. The discovery of epidermal stem cells in the HF has given new life to the search for a cure for baldness. Drug discovery efforts are being increasingly centered on these stem cells, boosting the hair cycle and reversing miniaturization of HF. Better understanding of the molecular mechanisms underlying the immune attack in AA will yield new drugs. New discoveries in HF neogenesis and low-level light therapy will undoubtedly have a role to play. PMID:25662177
Vázquez-Naya, José M; Martínez-Romero, Marcos; Porto-Pazos, Ana B; Novoa, Francisco; Valladares-Ayerbes, Manuel; Pereira, Javier; Munteanu, Cristian R; Dorado, Julián
The complex diseases in the field of Neurology, Cardiology and Oncology have the most important impact on our society. The theoretical methods are fast and they involve some efficient tools aimed at discovering new active drugs specially designed for these diseases. The ontology of all the items that are linked with the molecule metabolism and the treatment of these diseases gives us the possibility to correlate information from different levels and to discover new relationships between complex diseases such as common drug targets and disease patterns. This review presents the ontologies used to process drug discovery and design in the most common complex diseases.
Wang, Yuhao; Zeng, Jianyang
Motivation: In silico prediction of drug-target interactions plays an important role toward identifying and developing new uses of existing or abandoned drugs. Network-based approaches have recently become a popular tool for discovering new drug-target interactions (DTIs). Unfortunately, most of these network-based approaches can only predict binary interactions between drugs and targets, and information about different types of interactions has not been well exploited for DTI prediction in previous studies. On the other hand, incorporating additional information about drug-target relationships or drug modes of action can improve prediction of DTIs. Furthermore, the predicted types of DTIs can broaden our understanding about the molecular basis of drug action. Results: We propose a first machine learning approach to integrate multiple types of DTIs and predict unknown drug-target relationships or drug modes of action. We cast the new DTI prediction problem into a two-layer graphical model, called restricted Boltzmann machine, and apply a practical learning algorithm to train our model and make predictions. Tests on two public databases show that our restricted Boltzmann machine model can effectively capture the latent features of a DTI network and achieve excellent performance on predicting different types of DTIs, with the area under precision-recall curve up to 89.6. In addition, we demonstrate that integrating multiple types of DTIs can significantly outperform other predictions either by simply mixing multiple types of interactions without distinction or using only a single interaction type. Further tests show that our approach can infer a high fraction of novel DTIs that has been validated by known experiments in the literature or other databases. These results indicate that our approach can have highly practical relevance to DTI prediction and drug repositioning, and hence advance the drug discovery process. Availability: Software and datasets are available
Huang, Guohua; Yan, Fengxia; Tan, Duoduo
Drug discovery and development is not only a time-consuming and labor-intensive process but also full of risk. Identifying targets of small molecules helps evaluate safety of drugs and find new therapeutic applications. The biotechnology measures a wide variety of properties related to drug and targets from different perspectives, thus generating a large body of data. This undoubtedly provides a solid foundation to explore relationships between drugs and targets. A large number of computational techniques have recently been developed for drug target prediction. In this paper, we summarize these computational methods and classify them into structure-based, molecular activity-based, side-effect-based and multi-omics-based predictions according to the used data for inference. The multi-omics-based methods are further grouped into two types: classifier-based and network-based predictions. Furthermore，the advantages and limitations of each type of methods are discussed. Finally, we point out the future directions of computational predictions for drug targets.
Ludington, Jennifer L
One of the most powerful tools for designing drug molecules is an understanding of the target protein's binding site. Identifying key amino acids and understanding the electronic, steric, and solvation properties of the site enables the design of potent ligands. Of equal importance for the success of a drug discovery program is the evaluation of binding site druggability. Determining, a priori, if a particular binding site has the appropriate character to bind drug-like ligands saves research time and money.While there are a variety of experimental and computational techniques to identify and characterize binding sites, the focus of this chapter is on Binding Site Analysis (BSA) using virtual fragment simulations. The methodology of the technique is described, along with examples of successful application to drug discovery programs. BSA both indicates if a protein is a viable target for drug discovery and provides a roadmap for designing ligands. Using a computational fragment-based method is a effective means of understanding of a binding site.
Qin, Chu; Tao, Lin; Liu, Xin; Shi, Zhe; Zhang, Cun Long; Tan, Chun Yan; Chen, Yu Zong; Jiang, Yu Yang
Due to extensive bioprospecting efforts of the past and technology factors, there have been questions about drug discovery prospect from untapped species. We analyzed recent trends of approved drugs derived from previously untapped species, which show no sign of untapped drug-productive species being near extinction and suggest high probability of deriving new drugs from new species in existing drug-productive species families and clusters. Case histories of recently approved drugs reveal useful strategies for deriving new drugs from the scaffolds and pharmacophores of the natural product leads of these untapped species. New technologies such as cryptic gene-cluster exploration may generate novel natural products with highly anticipated potential impact on drug discovery. PMID:22808057
Shi, Jian-Yu; Yiu, Siu-Ming; Li, Yiming; Leung, Henry C M; Chin, Francis Y L
Predicting drug-target interaction using computational approaches is an important step in drug discovery and repositioning. To predict whether there will be an interaction between a drug and a target, most existing methods identify similar drugs and targets in the database. The prediction is then made based on the known interactions of these drugs and targets. This idea is promising. However, there are two shortcomings that have not yet been addressed appropriately. Firstly, most of the methods only use 2D chemical structures and protein sequences to measure the similarity of drugs and targets respectively. However, this information may not fully capture the characteristics determining whether a drug will interact with a target. Secondly, there are very few known interactions, i.e. many interactions are "missing" in the database. Existing approaches are biased towards known interactions and have no good solutions to handle possibly missing interactions which affect the accuracy of the prediction. In this paper, we enhance the similarity measures to include non-structural (and non-sequence-based) information and introduce the concept of a "super-target" to handle the problem of possibly missing interactions. Based on evaluations on real data, we show that our similarity measure is better than the existing measures and our approach is able to achieve higher accuracy than the two best existing algorithms, WNN-GIP and KBMF2K. Our approach is available at http://web.hku.hk/∼liym1018/projects/drug/drug.html or http://www.bmlnwpu.org/us/tools/PredictingDTI_S2/METHODS.html.
Neves, Bruno J; Andrade, Carolina H; Cravo, Pedro V L
Schistosomiasis is a neglected parasitic tropical disease that claims around 200,000 human lives every year. Praziquantel (PZQ), the only drug recommended by the World Health Organization for the treatment and control of human schistosomiasis, is now facing the threat of drug resistance, indicating the urgent need for new effective compounds to treat this disease. Therefore, globally, there is renewed interest in natural products (NPs) as a starting point for drug discovery and development for schistosomiasis. Recent advances in genomics, proteomics, bioinformatics, and cheminformatics have brought about unprecedented opportunities for the rapid and more cost-effective discovery of new bioactive compounds against neglected tropical diseases. This review highlights the main contributions that NP drug discovery and development have made in the treatment of schistosomiasis and it discusses how integration with virtual screening (VS) strategies may contribute to accelerating the development of new schistosomidal leads, especially through the identification of unexplored, biologically active chemical scaffolds and structural optimization of NPs with previously established activity.
Larsen, Martha J.; Larsen, Scott D.; Fribley, Andrew; Grembecka, Jolanta; Homan, Kristoff; Mapp, Anna; Haak, Andrew; Nikolovska-Coleska, Zaneta; Stuckey, Jeanne A.; Sun, Duxin
High throughput screening (HTS) is an integral part of a highly collaborative approach to drug discovery at the University of Michigan. The HTS lab is one of four core centers that provide services to identify, produce, screen and follow-up on biomedical targets for faculty. Key features of this system are: protein cloning and purification, protein crystallography, small molecule and siRNA HTS, medicinal chemistry and pharmacokinetics. Therapeutic areas that have been targeted include anti-bacterial, metabolic, neurodegenerative, cardiovascular, anti-cancer and anti-viral. The centers work in a coordinated, interactive environment to affordably provide academic investigators with the technology, informatics and expertise necessary for successful drug discovery. This review provides an overview of these centers at the University of Michigan, along with case examples of successful collaborations with faculty. PMID:24409957
Zhang, Tao; Zhao, Mingzhu; Pang, Yushu; Zhang, Wen; Angela Liu, Limin; Wei, Dong-Qing
The cytochrome P450 superfamily is responsible primarily for human drug metabolism, which is of critical importance for the drug discovery and development. Rapid advancement of bioinformatics, functional genomics and metabolomics has been made over the last decade. These disciplines are essential in target identification, lead discovery and optimization. In this review, we summarize the recent progress on cytochrome P450 and its role on drug metabolism in the context of bioinformatics, functional genomics and metabolomics. Data are integrated into various databases and web-based platforms on cytochrome P450. These research tools and resources are playing an increasingly important role in drug discovery, and are helping in achieving the ultimate goal of personalized medicine, that is, to prescribe personalized drugs according to each person's genetic makeup, metabolic level, and drug disposition.
NITULESCU, GEORGE MIHAI; MARGINA, DENISA; JUZENAS, PETRAS; PENG, QIAN; OLARU, OCTAVIAN TUDOREL; SALOUSTROS, EMMANOUIL; FENGA, CONCETTINA; SPANDIDOS, DEMETRIOS A.; LIBRA, MASSIMO; TSATSAKIS, ARISTIDIS M.
Targeted cancer therapies are used to inhibit the growth, progression, and metastasis of the tumor by interfering with specific molecular targets and are currently the focus of anticancer drug development. Protein kinase B, also known as Akt, plays a central role in many types of cancer and has been validated as a therapeutic target nearly two decades ago. This review summarizes the intracellular functions of Akt as a pivotal point of converging signaling pathways involved in cell growth, proliferation, apoptotis and neo-angiogenesis, and focuses on the drug design strategies to develop potent anticancer agents targeting Akt. The discovery process of Akt inhibitors has evolved from adenosine triphosphate (ATP)-competitive agents to alternative approaches employing allosteric sites in order to overcome the high degree of structural similarity between Akt isoforms in the catalytic domain, and considerable structural analogy to the AGC kinase family. This process has led to the discovery of inhibitors with greater specificity, reduced side-effects and lower toxicity. A second generation of Akt has inhibitors emerged by incorporating a chemically reactive Michael acceptor template to target the nucleophile cysteines in the catalytic activation loop. The review outlines the development of several promising drug candidates emphasizing the importance of each chemical scaffold. We explore the pipeline of Akt inhibitors and their preclinical and clinical examination status, presenting the potential clinical application of these agents as a monotherapy or in combination with ionizing radiation, other targeted therapies, or chemotherapy. PMID:26698230
Yokley, Brian H; Hartman, Matthew; Slusher, Barbara S
There was a greater than 50% decline in central nervous system (CNS) drug discovery and development programs by major pharmaceutical companies from 2009 to 2014. This decline was paralleled by a rise in the number of university led drug discovery centers, many in the CNS area, and a growth in the number of public-private drug discovery partnerships. Diverse operating models have emerged as the academic drug discovery centers adapt to this changing ecosystem.
Jana, S; Mandlekar, S; Marathe, P
The prodrug design is a versatile, powerful method that can be applied to a wide range of parent drug molecules, administration routes, and formulations. Clinically, the majority of prodrugs are used with the aim of enhancing drug permeation by increasing lipophilicity, or by improving aqueous solubility. Prodrug design may improve the bioavailability of parent molecule, and thus can be integrated into the iterative process of lead optimization, rather than employing it as a post-hoc approach. The purpose of this review is to provide an update of advances and progress in the knowledge of current strategic approaches of prodrug design, along with their real-world utility in drug discovery and development. The review covers the type of prodrugs and functional groups that are amenable to prodrug design. Various prodrug approaches for improving oral drug delivery are discussed, with numerous examples of marketed prodrugs, including improved aqueous solubility, improved lipophilicity, transporter-mediated absorption, and prodrug design to achieve site-specific delivery. Tools employed for prodrug screening, and specific challenges in prodrug research and development are also elaborated. This article is intended to encourage discovery scientists to be creative and consider a rationally designed prodrug approach during the lead optimization phase of drug discovery programs, when the structure activity relationship (SAR) for the drug target is incompatible with pharmacokinetic or biopharmaceutical objectives.
It is generally recognized that drug discovery and development are very time and resources consuming processes. There is an ever growing effort to apply computational power to the combined chemical and biological space in order to streamline drug discovery, design, development and optimization. In biomedical arena, computer-aided or in silico design is being utilized to expedite and facilitate hit identification, hit-to-lead selection, optimize the absorption, distribution, metabolism, excretion and toxicity profile and avoid safety issues. Commonly used computational approaches include ligand-based drug design (pharmacophore, a 3-D spatial arrangement of chemical features essential for biological activity), structure-based drug design (drug-target docking), and quantitative structure-activity and quantitative structure-property relationships. Regulatory agencies as well as pharmaceutical industry are actively involved in development of computational tools that will improve effectiveness and efficiency of drug discovery and development process, decrease use of animals, and increase predictability. It is expected that the power of CADDD will grow as the technology continues to evolve. PMID:17229415
Saeidnia, Soodabeh; Gohari, Ahmad R; Manayi, Azadeh
Pharmacognosy is a science, which study natural products as a source of new drug leads and effective drug development. Rational and economic search for novel lead structures could maximize the speed of drug discovery by using powerful high technology methods. Reverse pharmacognosy, a complementary to pharmacognosy, couples the high throughput screening (HTS), virtual screening and databases along with the knowledge of traditional medicines. These strategies lead to identification of numerous in vitro active and selective hits enhancing the speed of drug discovery from natural sources. Besides, reverse pharmacology is a target base drug discovery approach; in the first step, a hypothesis is made that the alteration of specific protein activity will produce beneficial curative effects. Both, reverse pharmacognosy and reverse pharmacology take advantages of high technology methods to accomplish their particular purposes. Moreover, reverse pharmacognosy effectively utilize traditional medicines and natural products as promising sources to provide new drug leads as well as promote the rational use of them by using valuable information like protein structure databases and chemical libraries which prepare pharmacological profile of traditional medicine, plant extract or natural compounds.
Tan, Yuxiang; Hu, Yong; Liu, Xiaoxiao; Yin, Zhinan; Chen, Xue-Wen; Liu, Mei
Adverse drug reactions (ADRs) are a major public health concern, causing over 100,000 fatalities in the United States every year with an annual cost of $136 billion. Early detection and accurate prediction of ADRs is thus vital for drug development and patient safety. Multiple scientific disciplines, namely pharmacology, pharmacovigilance, and pharmacoinformatics, have been addressing the ADR problem from different perspectives. With the same goal of improving drug safety, this article summarizes and links the research efforts in the multiple disciplines into a single framework from comprehensive understanding of the interactions between drugs and biological system and the identification of genetic and phenotypic predispositions of patients susceptible to higher ADR risks and finally to the current state of implementation of medication-related decision support systems. We start by describing available computational resources for building drug-target interaction networks with biological annotations, which provides a fundamental knowledge for ADR prediction. Databases are classified by functions to help users in selection. Post-marketing surveillance is then introduced where data-driven approach can not only enhance the prediction accuracy of ADRs but also enables the discovery of genetic and phenotypic risk factors of ADRs. Understanding genetic risk factors for ADR requires well organized patient genetics information and analysis by pharmacogenomic approaches. Finally, current state of clinical decision support systems is presented and described how clinicians can be assisted with the integrated knowledgebase to minimize the risk of ADR. This review ends with a discussion of existing challenges in each of disciplines with potential solutions and future directions.
Davies, Mark; Nowotka, Michał; Papadatos, George; Dedman, Nathan; Gaulton, Anna; Atkinson, Francis; Bellis, Louisa; Overington, John P.
ChEMBL is now a well-established resource in the fields of drug discovery and medicinal chemistry research. The ChEMBL database curates and stores standardized bioactivity, molecule, target and drug data extracted from multiple sources, including the primary medicinal chemistry literature. Programmatic access to ChEMBL data has been improved by a recent update to the ChEMBL web services (version 2.0.x, https://www.ebi.ac.uk/chembl/api/data/docs), which exposes significantly more data from the underlying database and introduces new functionality. To complement the data-focused services, a utility service (version 1.0.x, https://www.ebi.ac.uk/chembl/api/utils/docs), which provides RESTful access to commonly used cheminformatics methods, has also been concurrently developed. The ChEMBL web services can be used together or independently to build applications and data processing workflows relevant to drug discovery and chemical biology. PMID:25883136
Matter, Alex; Keller, Thomas H
Non-profit organizations (NPO) play an increasingly important role in drug discovery and development for diseases that are neglected by the pharmaceutical industry because of low or absent commercial incentives. Governments and major private foundations such as the Wellcome Trust and the Bill & Melinda Gates Foundation increasingly step in to provide strategic direction, communication platforms and major resources, motivated by the fact that major healthcare problems remain unsolved. Drug discovery in the field of neglected diseases is fraught with complexities since, in many cases, important tools are lacking including readily available diagnostics, molecular epidemiology, appropriate model systems, representative strain collections, biomarkers, up-to-date trial methodologies and regulatory strategies. On top of this, the high hurdles addressing novel drug targets must be cleared.
Perryman, Alexander L.; Horta Andrade, Carolina
The Zika virus outbreak in the Americas has caused global concern. To help accelerate this fight against Zika, we launched the OpenZika project. OpenZika is an IBM World Community Grid Project that uses distributed computing on millions of computers and Android devices to run docking experiments, in order to dock tens of millions of drug-like compounds against crystal structures and homology models of Zika proteins (and other related flavivirus targets). This will enable the identification of new candidates that can then be tested in vitro, to advance the discovery and development of new antiviral drugs against the Zika virus. The docking data is being made openly accessible so that all members of the global research community can use it to further advance drug discovery studies against Zika and other related flaviviruses. PMID:27764115
Qian Cutrone, Jingfang Jenny; Huang, Xiaohua Stella; Kozlowski, Edward S; Bao, Ye; Wang, Yingzi; Poronsky, Christopher S; Drexler, Dieter M; Tymiak, Adrienne A
Synthetic macrocyclic peptides with natural and unnatural amino acids have gained considerable attention from a number of pharmaceutical/biopharmaceutical companies in recent years as a promising approach to drug discovery, particularly for targets involving protein-protein or protein-peptide interactions. Analytical scientists charged with characterizing these leads face multiple challenges including dealing with a class of complex molecules with the potential for multiple isomers and variable charge states and no established standards for acceptable analytical characterization of materials used in drug discovery. In addition, due to the lack of intermediate purification during solid phase peptide synthesis, the final products usually contain a complex profile of impurities. In this paper, practical analytical strategies and methodologies were developed to address these challenges, including a tiered approach to assessing the purity of macrocyclic peptides at different stages of drug discovery. Our results also showed that successful progression and characterization of a new drug discovery modality benefited from active analytical engagement, focusing on fit-for-purpose analyses and leveraging a broad palette of analytical technologies and resources.
Ravna, Aina W.; Sager, Georg; Dahl, Svein G.; Sylte, Ingebrigt
Current therapeutic drugs act on four main types of molecular targets: enzymes, receptors, ion channels and transporters, among which a major part (60-70%) are membrane proteins. This review discusses the molecular structures and potential impact of membrane transporter proteins on new drug discovery. The three-dimensional (3D) molecular structure of a protein contains information about the active site and possible ligand binding, and about evolutionary relationships within the protein family. Transporters have a recognition site for a particular substrate, which may be used as a target for drugs inhibiting the transporter or acting as a false substrate. Three groups of transporters have particular interest as drug targets: the major facilitator superfamily, which includes almost 4000 different proteins transporting sugars, polyols, drugs, neurotransmitters, metabolites, amino acids, peptides, organic and inorganic anions and many other substrates; the ATP-binding cassette superfamily, which plays an important role in multidrug resistance in cancer chemotherapy; and the neurotransmitter:sodium symporter family, which includes the molecular targets for some of the most widely used psychotropic drugs. Recent technical advances have increased the number of known 3D structures of membrane transporters, and demonstrated that they form a divergent group of proteins with large conformational flexibility which facilitates transport of the substrate.
Donev, Alexander N; Tobias, Randall D
Dose-response studies are an essential part of the drug discovery process. They are typically carried out on a large number of chemical compounds using serial dilution experimental designs. This paper proposes a method of selecting the key parameters of these designs (maximum dose, dilution factor, number of concentrations and number of replicated observations for each concentration) depending on the stage of the drug discovery process where the study takes place. This is achieved by employing and extending results from optimal design theory. Population D- and D(S)-optimality are defined and used to evaluate the precision of estimating the potency of the tested compounds. The proposed methodology is easy to use and creates opportunities to reduce the cost of the experiments without compromising the quality of the data obtained in them.
Wright, Peter M; Seiple, Ian B; Myers, Andrew G
The discovery and implementation of antibiotics in the early twentieth century transformed human health and wellbeing. Chemical synthesis enabled the development of the first antibacterial substances, organoarsenicals and sulfa drugs, but these were soon outshone by a host of more powerful and vastly more complex antibiotics from nature: penicillin, streptomycin, tetracycline, and erythromycin, among others. These primary defences are now significantly less effective as an unavoidable consequence of rapid evolution of resistance within pathogenic bacteria, made worse by widespread misuse of antibiotics. For decades medicinal chemists replenished the arsenal of antibiotics by semisynthetic and to a lesser degree fully synthetic routes, but economic factors have led to a subsidence of this effort, which places society on the precipice of a disaster. We believe that the strategic application of modern chemical synthesis to antibacterial drug discovery must play a critical role if a crisis of global proportions is to be averted.
Williams, Antony J; Ekins, Sean; Clark, Alex M; Jack, J James; Apodaca, Richard L
Mobile hardware and software technology continues to evolve very rapidly and presents drug discovery scientists with new platforms for accessing data and performing data analysis. Smartphones and tablet computers can now be used to perform many of the operations previously addressed by laptops or desktop computers. Although the smaller screen sizes and requirements for touch-screen manipulation can present user-interface design challenges, especially with chemistry-related applications, these limitations are driving innovative solutions. In this early review of the topic, we collectively present our diverse experiences as software developer, chemistry database expert and naïve user, in terms of what mobile platforms could provide to the drug discovery chemist in the way of applications in the future as this disruptive technology takes off.
Loging, William; Harland, Lee; Williams-Jones, Bryn
The vast range of in silico resources that are available in life sciences research hold much promise towards aiding the drug discovery process. To fully realize this opportunity, computational scientists must consider the practical issues of data integration and identify how best to apply these resources scientifically. In this article we describe in silico approaches that are driven towards the identification of testable laboratory hypotheses; we also address common challenges in the field. We focus on flexible, high-throughput techniques, which may be initiated independently of 'wet-lab' experimentation, and which may be applied to multiple disease areas. The utility of these approaches in drug discovery highlights the contribution that in silico techniques can make and emphasizes the need for collaboration between the areas of disease research and computational science.
Wright, Peter M.; Seiple, Ian B.; Myers, Andrew G.
The discovery and implementation of antibiotics in the early twentieth century transformed human health and wellbeing. Chemical synthesis enabled the development of the first antibacterial substances, organoarsenicals and sulfa drugs, but these were soon outshone by a host of more powerful and vastly more complex antibiotics from nature: penicillin, streptomycin, tetracycline, and erythromycin, among others. These primary defences are now significantly less effective as an unavoidable consequence of rapid evolution of resistance within pathogenic bacteria, made worse by widespread misuse of antibiotics. For decades medicinal chemists replenished the arsenal of antibiotics by semisynthetic and to a lesser degree fully synthetic routes, but economic factors have led to a subsidence of this effort, which places society on the precipice of a disaster. We believe that the strategic application of modern chemical synthesis to antibacterial drug discovery must play a critical role if a crisis of global proportions is to be averted. PMID:24990531
Dias, Daniel A.; Urban, Sylvia; Roessner, Ute
Historically, natural products have been used since ancient times and in folklore for the treatment of many diseases and illnesses. Classical natural product chemistry methodologies enabled a vast array of bioactive secondary metabolites from terrestrial and marine sources to be discovered. Many of these natural products have gone on to become current drug candidates. This brief review aims to highlight historically significant bioactive marine and terrestrial natural products, their use in folklore and dereplication techniques to rapidly facilitate their discovery. Furthermore a discussion of how natural product chemistry has resulted in the identification of many drug candidates; the application of advanced hyphenated spectroscopic techniques to aid in their discovery, the future of natural product chemistry and finally adopting metabolomic profiling and dereplication approaches for the comprehensive study of natural product extracts will be discussed. PMID:24957513
López-Vallejo, Fabian; Caulfield, Thomas; Martínez-Mayorga, Karina; Giulianotti, Marc A; Nefzi, Adel; Houghten, Richard A; Medina-Franco, Jose L
Virtual screening is increasingly being used in drug discovery programs with a growing number of successful applications. Experimental methodologies developed to speed up the drug discovery processes include high-throughput screening and combinatorial chemistry. The complementarities between computational and experimental screenings have been recognized and reviewed in the literature. Computational methods have also been used in the combinatorial chemistry field, in particular in library design. However, the integration of computational and combinatorial chemistry screenings has been attempted only recently. Combinatorial libraries (experimental or virtual) represent a notable source of chemically related compounds. Advances in combinatorial chemistry and deconvolution strategies, have enabled the rapid exploration of novel and dense regions in the chemical space. The present review is focused on the integration of virtual and experimental screening of combinatorial libraries. Applications of virtual screening to discover novel anticancer agents and our ongoing efforts towards the integration of virtual screening and combinatorial chemistry are also discussed.
The isolation and extraction of novel bioactive secondary metabolites from marine microorganisms have a biomedical potential for future drug discovery as the oceans cover 70% of the planet's surface and life on earth originates from sea. Wide range of novel bioactive secondary metabolites exhibiting pharmacodynamic properties has been isolated from marine microorganisms and many to be discovered. The compounds isolated from marine organisms (macro and micro) are important in their natural form and also as templates for synthetic modifications for the treatments for variety of deadly to minor diseases. Many technical issues are yet to overcome before wide-scale bioprospecting of marine microorganisms becomes a reality. This chapter focuses on some novel secondary metabolites having antitumor, antivirus, enzyme inhibitor, and other bioactive properties identified and isolated from marine microorganisms including bacteria, actinomycetes, fungi, and cyanobacteria, which could serve as potentials for drug discovery after their clinical trials.
Islam, Md Mahmudul; Hameed, H M Adnan; Mugweru, Julius; Chhotaray, Chiranjibi; Wang, Changwei; Tan, Yaoju; Liu, Jianxiong; Li, Xinjie; Tan, Shouyong; Ojima, Iwao; Yew, Wing Wai; Nuermberger, Eric; Lamichhane, Gyanu; Zhang, Tianyu
Drug-resistant tuberculosis (TB) poses a significant challenge to the successful treatment and control of TB worldwide. Resistance to anti-TB drugs has existed since the beginning of the chemotherapy era. New insights into the resistant mechanisms of anti-TB drugs have been provided. Better understanding of drug resistance mechanisms helps in the development of new tools for the rapid diagnosis of drug-resistant TB. There is also a pressing need in the development of new drugs with novel targets to improve the current treatment of TB and to prevent the emergence of drug resistance in Mycobacterium tuberculosis. This review summarizes the anti-TB drug resistance mechanisms, furnishes some possible novel drug targets in the development of new agents for TB therapy and discusses the usefulness using known targets to develop new anti-TB drugs. Whole genome sequencing is currently an advanced technology to uncover drug resistance mechanisms in M. tuberculosis. However, further research is required to unravel the significance of some newly discovered gene mutations in their contribution to drug resistance.
Li, Xiangyi; Qin, Guangrong; Yang, Qingmin
Drug combination is a powerful and promising approach for complex disease therapy such as cancer and cardiovascular disease. However, the number of synergistic drug combinations approved by the Food and Drug Administration is very small. To bridge the gap between urgent need and low yield, researchers have constructed various models to identify synergistic drug combinations. Among these models, biomolecular network-based model is outstanding because of its ability to reflect and illustrate the relationships among drugs, disease-related genes, therapeutic targets, and disease-specific signaling pathways as a system. In this review, we analyzed and classified models for synergistic drug combination prediction in recent decade according to their respective algorithms. Besides, we collected useful resources including databases and analysis tools for synergistic drug combination prediction. It should provide a quick resource for computational biologists who work with network medicine or synergistic drug combination designing. PMID:27891522
Frei, Priska; Navarra, Giulio; Sager, Christoph P; Silbermann, Marleen; Varga, Norbert; Wamhoff, Eike-Christian
A summit amongst the summits: The 11(th) Swiss Course on Medicinal Chemistry was held in October 2014, again in the scenic setting of the Alps in Leysin, Switzerland. One hundred participants, mostly from industry, experienced a week of expert talks about numerous aspects of drug discovery and medicinal chemistry. In this conference report, we briefly summarize the essential topics of this event, while the most inspiring lectures are described in greater detail.
Davies-Coleman, Michael T; Veale, Clinton G L
Recent developments in marine drug discovery from three South African marine invertebrates, the tube worm Cephalodiscus gilchristi, the ascidian Lissoclinum sp. and the sponge Topsentia pachastrelloides, are presented. Recent reports of the bioactivity and synthesis of the anti-cancer secondary metabolites cephalostatin and mandelalides (from C. gilchristi and Lissoclinum sp., respectively) and various analogues are presented. The threat of drug-resistant pathogens, e.g., methicillin-resistant Staphylococcus aureus (MRSA), is assuming greater global significance, and medicinal chemistry strategies to exploit the potent MRSA PK inhibition, first revealed by two marine secondary metabolites, cis-3,4-dihydrohamacanthin B and bromodeoxytopsentin from T. pachastrelloides, are compared.
Beutler, John A.
Natural products have contributed to the development of many drugs for diverse indications. While most U.S. pharmaceutical companies have reduced or eliminated their in-house natural product groups, new paradigms and new enterprises have evolved to carry on a role for natural products in the pharmaceutical industry. Many of the reasons for the decline in popularity of natural products are being addressed by the development of new techniques for screening and production. This overview aims to inform pharmacologists of current strategies and techniques that make natural products a viable strategic choice for inclusion in drug discovery programs. PMID:20161632
Davies-Coleman, Michael T.; Veale, Clinton G. L.
Recent developments in marine drug discovery from three South African marine invertebrates, the tube worm Cephalodiscus gilchristi, the ascidian Lissoclinum sp. and the sponge Topsentia pachastrelloides, are presented. Recent reports of the bioactivity and synthesis of the anti-cancer secondary metabolites cephalostatin and mandelalides (from C. gilchristi and Lissoclinum sp., respectively) and various analogues are presented. The threat of drug-resistant pathogens, e.g., methicillin-resistant Staphylococcus aureus (MRSA), is assuming greater global significance, and medicinal chemistry strategies to exploit the potent MRSA PK inhibition, first revealed by two marine secondary metabolites, cis-3,4-dihydrohamacanthin B and bromodeoxytopsentin from T. pachastrelloides, are compared. PMID:26473891
Mah, Robert; Thomas, Jason R; Shafer, Cynthia M
In recent years, the number of drug candidates with a covalent mechanism of action progressing through clinical trials or being approved by the FDA has increased significantly. And as interest in covalent inhibitors has increased, the technical challenges for characterizing and optimizing these inhibitors have become evident. A number of new tools have been developed to aid this process, but these have not gained wide-spread use. This review will highlight a number of methods and tools useful for prosecuting covalent inhibitor drug discovery programs.
Chodera, John D.; Mobley, David L.; Shirts, Michael R.; Dixon, Richard W.; Branson, Kim; Pande, Vijay S.
Improved rational drug design methods are needed to lower the cost and increase the success rate of drug discovery and development. Alchemical binding free energy calculations, one potential tool for rational design, have progressed rapidly over the last decade, but still fall short of providing robust tools for pharmaceutical engineering. Recent studies, especially on model receptor systems, have clarified many of the challenges that must be overcome for robust predictions of binding affnity to be useful in rational design. In this review, inspired by a recent joint academic/industry meeting organized by the authors, we discuss these challenges and suggest a number of promising approaches for overcoming them. PMID:21349700
Mobley, David L.; Klimovich, Pavel V.
Computational techniques see widespread use in pharmaceutical drug discovery, but typically prove unreliable in predicting trends in protein-ligand binding. Alchemical free energy calculations seek to change that by providing rigorous binding free energies from molecular simulations. Given adequate sampling and an accurate enough force field, these techniques yield accurate free energy estimates. Recent innovations in alchemical techniques have sparked a resurgence of interest in these calculations. Still, many obstacles stand in the way of their routine application in a drug discovery context, including the one we focus on here, sampling. Sampling of binding modes poses a particular challenge as binding modes are often separated by large energy barriers, leading to slow transitions. Binding modes are difficult to predict, and in some cases multiple binding modes may contribute to binding. In view of these hurdles, we present a framework for dealing carefully with uncertainty in binding mode or conformation in the context of free energy calculations. With careful sampling, free energy techniques show considerable promise for aiding drug discovery.
Holdgate, Geoffrey; Geschwindner, Stefan; Breeze, Alex; Davies, Gareth; Colclough, Nicola; Temesi, David; Ward, Lara
Biophysical methods have become established in many areas of drug discovery. Application of these methods was once restricted to a relatively small number of scientists using specialized, low throughput technologies and methods. Now, automated high-throughput instruments are to be found in a growing number of laboratories. Many biophysical methods are capable of measuring the equilibrium binding constants between pairs of molecules crucial for molecular recognition processes, encompassing protein-protein, protein-small molecule, and protein-nucleic acid interactions, and several can be used to measure the kinetic or thermodynamic components controlling these biological processes. For a full characterization of a binding process, determinations of stoichiometry, binding mode, and any conformational changes associated with such interactions are also required. The suite of biophysical methods that are now available represents a powerful toolbox of techniques which can effectively deliver this full characterization.The aim of this chapter is to provide the reader with an overview of the drug discovery process and how biophysical methods, such as surface plasmon resonance (SPR), isothermal titration calorimetry (ITC), nuclear magnetic resonance, mass spectrometry (MS), and thermal unfolding methods can answer specific questions in order to influence project progression and outcomes. The selection of these examples is based upon the experiences of the authors at AstraZeneca, and relevant approaches are highlighted where they have utility in a particular drug discovery scenario.
Liu, Yong; Wu, Min; Miao, Chunyan; Zhao, Peilin; Li, Xiao-Li
In pharmaceutical sciences, a crucial step of the drug discovery process is the identification of drug-target interactions. However, only a small portion of the drug-target interactions have been experimentally validated, as the experimental validation is laborious and costly. To improve the drug discovery efficiency, there is a great need for the development of accurate computational approaches that can predict potential drug-target interactions to direct the experimental verification. In this paper, we propose a novel drug-target interaction prediction algorithm, namely neighborhood regularized logistic matrix factorization (NRLMF). Specifically, the proposed NRLMF method focuses on modeling the probability that a drug would interact with a target by logistic matrix factorization, where the properties of drugs and targets are represented by drug-specific and target-specific latent vectors, respectively. Moreover, NRLMF assigns higher importance levels to positive observations (i.e., the observed interacting drug-target pairs) than negative observations (i.e., the unknown pairs). Because the positive observations are already experimentally verified, they are usually more trustworthy. Furthermore, the local structure of the drug-target interaction data has also been exploited via neighborhood regularization to achieve better prediction accuracy. We conducted extensive experiments over four benchmark datasets, and NRLMF demonstrated its effectiveness compared with five state-of-the-art approaches.
Shu, Chih-Wen; Liu, Pei-Feng; Huang, Chun-Ming
Autophagy is an evolutionally conserved process in cells for cleaning abnormal proteins and organelles in a lysosome dependent manner. Growing studies have shown that defects or induced autophagy contributes to many diseases including aging, neurodegeneration, pathogen infection, and cancer. However, the precise involvement of autophagy in health and disease remains controversial because the theories are built on limited assays and chemical modulators, indicating that the role of autophagy in diseases may require further verification. Many food and drug administration (FDA) approved drugs modulate autophagy signaling, suggesting that modulation of autophagy with pharmacological agonists or antagonists provides a potential therapy for autophagy-related diseases. This suggestion raises an attractive issue on drug discovery for exploring chemical modulators of autophagy. High throughput screening (HTS) is becoming a powerful tool for drug discovery that may accelerate screening specific autophagy modulators to clarify the role of autophagy in diseases. Herein, this review lays out current autophagy assays to specifically measure autophagy components such as LC3 (mammalian homologue of yeast Atg8) and Atg4. These assays are feasible or successful for HTS with certain chemical libraries, which might be informative for this intensively growing field as research tools and hopefully developing new drugs for autophagy-related diseases.
Hristovski, Dimitar; Kastrin, Andrej; Dinevski, Dejan; Burgun, Anita; Žiberna, Lovro; Rindflesch, Thomas C
We report on our research in using literature-based discovery (LBD) to provide pharmacological and/or pharmacogenomic explanations for reported adverse drug effects. The goal of LBD is to generate novel and potentially useful hypotheses by analyzing the scientific literature and optionally some additional resources. Our assumption is that drugs have effects on some genes or proteins and that these genes or proteins are associated with the observed adverse effects. Therefore, by using LBD we try to find genes or proteins that link the drugs with the reported adverse effects. These genes or proteins can be used to provide insight into the processes causing the adverse effects. Initial results show that our method has the potential to assist in explaining reported adverse drug effects.
Lionta, Evanthia; Spyrou, George; Vassilatis, Demetrios K.; Cournia, Zoe
Structure-based drug discovery (SBDD) is becoming an essential tool in assisting fast and cost-efficient lead discovery and optimization. The application of rational, structure-based drug design is proven to be more efficient than the traditional way of drug discovery since it aims to understand the molecular basis of a disease and utilizes the knowledge of the three-dimensional structure of the biological target in the process. In this review, we focus on the principles and applications of Virtual Screening (VS) within the context of SBDD and examine different procedures ranging from the initial stages of the process that include receptor and library pre-processing, to docking, scoring and post-processing of topscoring hits. Recent improvements in structure-based virtual screening (SBVS) efficiency through ensemble docking, induced fit and consensus docking are also discussed. The review highlights advances in the field within the framework of several success studies that have led to nM inhibition directly from VS and provides recent trends in library design as well as discusses limitations of the method. Applications of SBVS in the design of substrates for engineered proteins that enable the discovery of new metabolic and signal transduction pathways and the design of inhibitors of multifunctional proteins are also reviewed. Finally, we contribute two promising VS protocols recently developed by us that aim to increase inhibitor selectivity. In the first protocol, we describe the discovery of micromolar inhibitors through SBVS designed to inhibit the mutant H1047R PI3Kα kinase. Second, we discuss a strategy for the identification of selective binders for the RXRα nuclear receptor. In this protocol, a set of target structures is constructed for ensemble docking based on binding site shape characterization and clustering, aiming to enhance the hit rate of selective inhibitors for the desired protein target through the SBVS process. PMID:25262799
Swaminathan, Soumya; Sundaramurthi, Jagadish Chandrabose; Palaniappan, Alangudi Natarajan; Narayanan, Sujatha
Emergence of drug-resistant tuberculosis (DR-TB) is a big challenge in TB control. The delay in diagnosis of DR-TB leads to its increased transmission, and therefore prevalence. Recent developments in genomics have enabled whole genome sequencing (WGS) of Mycobacterium tuberculosis (M. tuberculosis) from 3-day-old liquid culture and directly from uncultured sputa, while new bioinformatics tools facilitate to determine DR mutations rapidly from the resulting sequences. The present drug discovery and development pipeline is filled with candidate drugs which have shown efficacy against DR-TB. Furthermore, some of the FDA-approved drugs are being evaluated for repurposing, and this approach appears promising as several drugs are reported to enhance efficacy of the standard TB drugs, reduce drug tolerance, or modulate the host immune response to control the growth of intracellular M. tuberculosis. Recent developments in genomics and bioinformatics along with new drug discovery collectively have the potential to result in synergistic impact leading to the development of a rapid protocol to determine the drug resistance profile of the infecting strain so as to provide personalized medicine. Hence, in this review, we discuss recent developments in WGS, bioinformatics and drug discovery to perceive how they would transform the management of tuberculosis in a timely manner.
Bhabak, Krishna P; Arenz, Christoph
While the evidence for an involvement of sphingolipids (SLs) in a variety of diseases is rapidly increasing, the development of sphingolipid-related drugs is still in its infancy. In fact, the recently FDA-approved fingolimod or FTY-720 (see chapter by J. Pfeilschifter for more information) is the first drug on the market to interfere with sphingolipid signaling. The reasons for this lagging are manifold and within this chapter we try to name some of them. Ceramide is in the center of sphingolipid metabolism. We describe the most important and most recent inhibitors for enzymes controlling cellular ceramide levels.
Khalid, Nauman; Kobayashi, Isao; Nakajima, Mitsutoshi
Microelectromechanical systems (MEMS) and micro total analysis systems (μTAS) revolutionized the biochemical and electronic industries, and this miniaturization process became a key driver for many markets. Now, it is a driving force for innovations in life sciences, diagnostics, analytical sciences, and chemistry, which are called 'lab-on-a-chip, (LOC)' devices. The use of these devices allows the development of fast, portable, and easy-to-use systems with a high level of functional integration for applications such as point-of-care diagnostics, forensics, the analysis of biomolecules, environmental or food analysis, and drug development. In this review, we report on the latest developments in fabrication methods and production methodologies to tailor LOC devices. A brief overview of scale-up strategies is also presented together with their potential applications in drug delivery and discovery. The impact of LOC devices on drug development and discovery has been extensively reviewed in the past. The current research focuses on fast and accurate detection of genomics, cell mutations and analysis, drug delivery, and discovery. The current research also differentiates the LOC devices into new terminology of microengineering, like organ-on-a-chip, stem cells-on-a-chip, human-on-a-chip, and body-on-a-chip. Key challenges will be the transfer of fabricated LOC devices from lab-scale to industrial large-scale production. Moreover, extensive toxicological studies are needed to justify the use of microfabricated drug delivery vehicles in biological systems. It will also be challenging to transfer the in vitro findings to suitable and promising in vivo models. For further resources related to this article, please visit the WIREs website.
Sun, Jing; Nan, Guangxian
Protein kinases are critical modulators of a variety of intracellular and extracellular signal transduction pathways, and abnormal phosphorylation events can contribute to disease progression in a variety of diseases. As a result, protein kinases have emerged as important new drug targets for small molecule therapeutics. The mitogen-activated protein kinase (MAPK) signaling pathway transmits signals from the cell membrane to the nucleus in response to a variety of different stimuli. Because this pathway controls a broad spectrum of cellular processes, including growth, inflammation, and stress responses, it is accepted as a therapeutic target for cancer and peripheral inflammatory disorders. There is also increasing evidence that MAPK is an important regulator of ischemic and hemorrhagic cerebral vascular disease, raising the possibility that it might be a drug discovery target for stroke. In this review, we discuss the MAPK signaling pathway in association with its activation in stroke-induced brain injury.
countries. Up to now, chemotherapy is still the main treatment modality in prostate cancers10-11, however the efficacy of the therapy is limited...by severe toxic side effects induced by anticancer drugs on healthy tissues. Targeted chemotherapy which can be achieved by attaching a ligand for...peptide library targeted to α6 integrin receptors will be constructed by ODOC method with the aim of discovery of new ligand for targeted chemotherapy
Keiser, Michael J.; Setola, Vincent; Irwin, John J.; Laggner, Christian; Abbas, Atheir; Hufeisen, Sandra J.; Jensen, Niels H.; Kuijer, Michael B.; Matos, Roberto C.; Tran, Thuy B.; Whaley, Ryan; Glennon, Richard A.; Hert, Jérôme; Thomas, Kelan L.H.; Edwards, Douglas D.; Shoichet, Brian K.; Roth, Bryan L.
Whereas drugs are intended to be selective, at least some bind to several physiologic targets, explaining both side effects and efficacy. As many drug-target combinations exist, it would be useful to explore possible interactions computationally. Here, we compared 3,665 FDA-approved and investigational drugs against hundreds of targets, defining each target by its ligands. Chemical similarities between drugs and ligand sets predicted thousands of unanticipated associations. Thirty were tested experimentally, including the antagonism of the β1 receptor by the transporter inhibitor Prozac, the inhibition of the 5-HT transporter by the ion channel drug Vadilex, and antagonism of the histamine H4 receptor by the enzyme inhibitor Rescriptor. Overall, 23 new drug-target associations were confirmed, five of which were potent (< 100 nM). The physiological relevance of one such, the drug DMT on serotonergic receptors, was confirmed in a knock-out mouse. The chemical similarity approach is systematic and comprehensive, and may suggest side-effects and new indications for many drugs. PMID:19881490
Waszkielewicz, A.M; Gunia, A; Szkaradek, N; Słoczyńska, K; Krupińska, S; Marona, H
Ion channel targeted drugs have always been related with either the central nervous system (CNS), the peripheral nervous system, or the cardiovascular system. Within the CNS, basic indications of drugs are: sleep disorders, anxiety, epilepsy, pain, etc. However, traditional channel blockers have multiple adverse events, mainly due to low specificity of mechanism of action. Lately, novel ion channel subtypes have been discovered, which gives premises to drug discovery process led towards specific channel subtypes. An example is Na+ channels, whose subtypes 1.3 and 1.7-1.9 are responsible for pain, and 1.1 and 1.2 – for epilepsy. Moreover, new drug candidates have been recognized. This review is focusing on ion channels subtypes, which play a significant role in current drug discovery and development process. The knowledge on channel subtypes has developed rapidly, giving new nomenclatures of ion channels. For example, Ca2+ channels are not any more divided to T, L, N, P/Q, and R, but they are described as Cav1.1-Cav3.3, with even newer nomenclature α1A-α1I and α1S. Moreover, new channels such as P2X1-P2X7, as well as TRPA1-TRPV1 have been discovered, giving premises for new types of analgesic drugs. PMID:23409712
Yan, Zhiqiang; Wang, Jin
Highly efficient and specific biomolecular recognition requires both affinity and specificity. Previous quantitative descriptions of biomolecular recognition were mostly driven by improving the affinity prediction, but lack of quantification of specificity. We developed a novel method SPA (SPecificity and Affinity) based on our funneled energy landscape theory. The strategy is to simultaneously optimize the quantified specificity of the ``native'' protein-ligand complex discriminating against ``non-native'' binding modes and the affinity prediction. The benchmark testing of SPA shows the best performance against 16 other popular scoring functions in industry and academia on both prediction of binding affinity and ``native'' binding pose. For the target COX-2 of nonsteroidal anti-inflammatory drugs, SPA successfully discriminates the drugs from the diversity set, and the selective drugs from non-selective drugs. The remarkable performance demonstrates that SPA has significant potential applications in identifying lead compounds for drug discovery.
Castle, Neil; Printzenhoff, David; Zellmer, Shannon; Antonio, Brett; Wickenden, Alan; Silvia, Christopher
Voltage dependent sodium channels are widely recognized as valuable targets for the development of therapeutic interventions for neuroexcitatory disorders such as epilepsy and pain as well as cardiac arrhythmias. An ongoing challenge for sodium channel drug discovery is the ability to readily evaluate state dependent interactions, which are known to underlie inhibition by many clinically used local anesthetic, antiepileptic and antiarrhythmic sodium channel blockers. While patch-clamp electrophysiology is still considered the most effective way of measuring ion channel function and pharmacology, it does not have the throughput to be useful in early stages of drug discovery in which there is often a need to evaluate many thousands to hundreds of thousands of compounds. Fortunately over the past five years, there has been significant progress in developing much higher throughput electrophysiology platforms like the PatchXpress and IonWorks, which are now widely used in drug discovery. This review highlights the strengths and weaknesses of these two high throughput devices for use in sodium channel inhibitor drug discovery programs. Overall, the PatchXpress and IonWorks electrophysiology platforms have individual strengths that make them complementary to each other. Both platforms are capable of measuring state dependent modulation of sodium channels. IonWorks has the throughput to allow for effective screening of libraries of tens of thousands of compounds whereas the PatchXpress has more flexibility to provide quantitative voltage clamp, which is useful in structure activity evaluations for the hit-to-lead and lead optimization stages of sodium channel drug discovery.
Chen, Lei; Zeng, Wei-Ming
Determination of drug's target protein is very important for studying drug-target interaction network, while drug-target interaction network is a key area in the drug discovery pipeline. Thus correct prediction of drug's target protein is very helpful to promote the development of drug discovery. In this study, we developed a two-step similarity-based method to predict drug's target group. In each step, a similarity score (obtained by graph representation in the first step, and chemical functional group representation in the second step) was employed to make prediction. Since some drugs can target proteins distributing in more than one group of proteins, the method provided a series of candidate target groups for each drug. As a result, the first-order prediction accuracy on training set and test set were 79.01% and 76.43%, respectively, which were much higher than the success rate of a random guess. The results show that using graph representation to encode drug is a good choice in this area. We expect that this contribution will provide some help to understand drug-target interaction network.
Taylor, Alexandria P; Robinson, Ralph P; Fobian, Yvette M; Blakemore, David C; Jones, Lyn H; Fadeyi, Olugbeminiyi
New advances in synthetic methodologies that allow rapid access to a wide variety of functionalized heterocyclic compounds are of critical importance to the medicinal chemist as it provides the ability to expand the available drug-like chemical space and drive more efficient delivery of drug discovery programs. Furthermore, the development of robust synthetic routes that can readily generate bulk quantities of a desired compound help to accelerate the drug development process. While established synthetic methodologies are commonly utilized during the course of a drug discovery program, the development of innovative heterocyclic syntheses that allow for different bond forming strategies are having a significant impact in the pharmaceutical industry. This review will focus on recent applications of new methodologies in C-H activation, photoredox chemistry, borrowing hydrogen catalysis, multicomponent reactions, regio- and stereoselective syntheses, as well as other new, innovative general syntheses for the formation and functionalization of heterocycles that have helped drive project delivery. Additionally, the importance and value of collaborations between industry and academia in shaping the development of innovative synthetic approaches to functionalized heterocycles that are of greatest interest to the pharmaceutical industry will be highlighted.
Wilson, Christina; Terry, Alvin V.
Schizophrenia is a devastating mental illness that is associated with a lifetime of disability. For patients to successfully function in society, the amelioration of disease symptoms is imperative. The recently published results of two large antipsychotic clinical trials (e.g., CATIE, CUtLASS) clearly exemplified the limitations of currently available treatment options for schizophrenia, and further highlighted the critical need for novel drug discovery and development in this field. One of the biggest challenges in schizophrenia-related drug discovery is to find an appropriate animal model of the illness so that novel hypotheses can be tested at the basic science level. A number of pharmacological, genetic, and neurodevelopmental models have been introduced; however, none of these models has been rigorously evaluated for translational relevance or to satisfy requirements of “face,” “construct” and “predictive” validity. Given the apparent polygenic nature of schizophrenia and the limited translational significance of pharmacological models, neurodevelopmental models may offer the best chance of success. The purpose of this review is to provide a general overview of the various neurodevelopmental models of schizophrenia that have been introduced to date, and to summarize their behavioral and neurochemical phenotypes that may be useful from a drug discovery and development standpoint. While it may be that, in the final analysis, no single animal model will satisfy all the requirements necessary for drug discovery purposes, several of the models may be useful for modeling various phenomenological and pathophysiological components of schizophrenia that could be targeted independently with separate molecules or multi-target drugs. PMID:20643635
Bellis, Louisa J; Akhtar, Ruth; Al-Lazikani, Bissan; Atkinson, Francis; Bento, A Patricia; Chambers, Jon; Davies, Mark; Gaulton, Anna; Hersey, Anne; Ikeda, Kazuyoshi; Krüger, Felix A; Light, Yvonne; McGlinchey, Shaun; Santos, Rita; Stauch, Benjamin; Overington, John P
The challenge of translating the huge amount of genomic and biochemical data into new drugs is a costly and challenging task. Historically, there has been comparatively little focus on linking the biochemical and chemical worlds. To address this need, we have developed ChEMBL, an online resource of small-molecule SAR (structure-activity relationship) data, which can be used to support chemical biology, lead discovery and target selection in drug discovery. The database contains the abstracted structures, properties and biological activities for over 700000 distinct compounds and in excess of more than 3 million bioactivity records abstracted from over 40000 publications. Additional public domain resources can be readily integrated into the same data model (e.g. PubChem BioAssay data). The compounds in ChEMBL are largely extracted from the primary medicinal chemistry literature, and are therefore usually 'drug-like' or 'lead-like' small molecules with full experimental context. The data cover a significant fraction of the discovery of modern drugs, and are useful in a wide range of drug design and discovery tasks. In addition to the compound data, ChEMBL also contains information for over 8000 protein, cell line and whole-organism 'targets', with over 4000 of those being proteins linked to their underlying genes. The database is searchable both chemically, using an interactive compound sketch tool, protein sequences, family hierarchies, SMILES strings, compound research codes and key words, and biologically, using a variety of gene identifiers, protein sequence similarity and protein families. The information retrieved can then be readily filtered and downloaded into various formats. ChEMBL can be accessed online at https://www.ebi.ac.uk/chembldb.
Raffa, Robert B.; Raffa, Kenneth F.
Introduction There is a pervasive and growing concern about the small number of new pharmaceutical agents. There are many proposed explanations for this trend that do not involve the drug-discovery process per se, but the discovery process itself has also come under scrutiny. If the current paradigms are indeed not working, where are novel ideas to come from? Perhaps it is time to look to novel sources. Areas covered The receptor-signaling and 2nd-messenger transduction processes present in insects are quite similar to those in mammals (involving G proteins, ion channels, etc.). However, a review of these systems reveals an unprecedented degree of high potency and receptor selectivity to an extent greater than that modeled in most current drug-discovery approaches. Expert opinion A better understanding of insect receptor pharmacology could stimulate novel theoretical and practical ideas in mammalian pharmacology (drug discovery) and, conversely, the application of pharmacology and medicinal chemistry principles could stimulate novel advances in entomology (safer and more targeted control of pest species). PMID:21984882
Many pharmaceutical companies worldwide specialize in oncology drug development and marketing. Among them, we have continued to take up the challenge of understanding the metabolism of pyrimidines as essential components of deoxyribonucleic acid for many years, and have provided unique products such as UFT(®) and TS-1 for cancer patients. Using our cumulative experience and knowledge, we are currently developing novel agents such as TAS-114, a dual inhibitor of deoxyuridine triphosphatase and dihydropyrimidine dehydrogenase, and TAS-102, a unique pyrimidine derivative inducing deoxyribonucleic acid dysfunction in cancer cells. Regarding molecular-targeted drugs, we have made huge efforts to establish ideal drug discovery platforms for the last several years. For kinase inhibitors, we established three core platforms such as a kinase-directed chemical library, a kinase assay panel and a target selection informatics system. The core platforms were further combined with peripheral technologies to measure essential parameters such as physicochemical properties, pharmacokinetics, efficacy and toxicities. Unique drug candidates have been identified at an early stage by assessing all important parameters. Several promising programs are proceeding simultaneously in the clinical or preclinical development stage such as TAS-115, a dual inhibitor of c-Met and vascular endothelial growth factor receptor, TAS-2104, a selective Aurora A inhibitor, TAS-117, an allosteric Akt inhibitor, TAS-2985, an irreversible fibroblast growth factor receptor inhibitor and TAS-2913, a T790M mutant selective epidermal growth factor receptor inhibitor. Other than kinase inhibitors, another drug discovery engine was established based on the fragment-based drug discovery technology. TAS-116, a new class of Hsp-90α/β inhibitor, is one of the products. Taiho's final goal is to provide innovative anticancer drugs together with companion diagnostics that are truly beneficial for patients.
Altstiel, L D
The major barrier to Alzheimer disease (AD) drug discovery and development in the biotechnology industry is scale. Most biotechnology companies do not have the personnel or expertise to carry a drug from the bench to the market. Much effort in the industry has been directed toward the elucidation of molecular mechanisms of AD and the identification of new targets. Advances in biotechnology have generated new insights into disease mechanisms, increased the number of lead compounds, and accelerated biologic screening. The majority of costs associated with drug development are in clinical testing and development activities, many of which are driven by regulatory issues. For most biotechnology companies, the costs of such trials and the infrastructure necessary to support them are prohibitive. Another significant barrier is the definition of therapeutic benefit for AD drugs; Food and Drug Administration (FDA) precedent has established that a drug must show superiority to placebo on a performance-based test of cognition and a measure of global clinical function. This restrictive definition is biased toward drugs that enhance performance on memory-based tests. Newer AD drugs are targeted toward slowing disease progression; however, there is currently no accepted definition of what constitutes efficacy in disease progression. Despite these obstacles, the biotechnology industry has much to offer AD drug discovery and development. Biotechnology firms have already developed essential technology for AD drug development and will continue to do so. Biotechnology companies can move more quickly; of course, the trick is to move quickly in the right direction. Speed may offset some of the problems associated with lack of scale. Additionally, biotechnology companies can afford to address markets that may be too restricted for larger pharmaceutical companies. This advantage will have increasing importance, as therapies are developed to address subtypes of AD.
Rostami, Elham; Kashanian, Soheila; Azandaryani, Abbas H; Faramarzi, Hossain; Dolatabadi, Jafar Ezzati Nazhad; Omidfar, Kobra
The present review aims to show the features of solid lipid nanoparticles (SLNs) which are at the forefront of the rapidly developing field of nanotechnology with several potential applications in drug delivery and research. Because of some unique features of SLNs such as their unique size dependent properties it offers possibility to develop new therapeutics. A common denominator of all these SLN-based platforms is to deliver drugs into specific tissues or cells in a pathological setting with minimal adverse effects on bystander cells. SLNs are capable to incorporate drugs into nanocarriers which lead to a new prototype in drug delivery which maybe used for drug targeting. Hence solid lipid nanoparticles hold great promise for reaching the goal of controlled and site specific drug delivery and hence attracted wide attention of researchers. This review presents a broad treatment of targeted solid lipid nanoparticles discussing their types such as antibody SLN, magnetic SLN, pH sensitive SLN and cationic SLN.
Background The early drug discovery phase in pharmaceutical research and development marks the beginning of a long, complex and costly process of bringing a new molecular entity to market. As such, it plays a critical role in helping to maintain a robust downstream clinical development pipeline. Despite its importance, however, to our knowledge there are no published in silico models to simulate the progression of discrete virtual projects through a discovery milestone system. Results Multiple variables were tested and their impact on productivity metrics examined. Simulations predict that there is an optimum number of scientists for a given drug discovery portfolio, beyond which output in the form of preclinical candidates per year will remain flat. The model further predicts that the frequency of compounds to successfully pass the candidate selection milestone as a function of time will be irregular, with projects entering preclinical development in clusters marked by periods of low apparent productivity. Conclusions The model may be useful as a tool to facilitate analysis of historical growth and achievement over time, help gauge current working group progress against future performance expectations, and provide the basis for dialogue regarding working group best practices and resource deployment strategies. PMID:23186040
Elmer, Greg I; Kafkafi, Neri
The discovery of truly efficacious treatments that lead to full recovery is a daunting task in psychiatric illness. A systems-based orientation to in vivo pharmacology has been suggested as a way to transform psychiatric drug discovery and development. A critical catalyst in the success of recent systems biology efforts has been the incorporation of data mining strategies. Our approach to the drug discovery problem has been to utilize the whole animal to provide a systems response that is subsequently mined for predictive attributes with known psychopharmacological value. Our in vivo data mining approach, termed Pattern Array, establishes a framework for screening novel chemical entities based upon a response that represents the net pharmacological effect on the system of interest, namely the central nervous system (CNS). Large scale screening of small molecules by non-conventional approaches such as this at a systems level may improve the identification of novel chemical entities with psychiatric utility. This type of approach will compliment the more labor-intensive models based upon construct validity. It will take the collective effort of many disciplines and numerous strategies in close association with clinical colleagues to address quality of life issues and breakthrough treatment barriers in psychiatric illness.
Wang, Lingle; Deng, Yuqing; Wu, Yujie; Kim, Byungchan; LeBard, David N; Wandschneider, Dan; Beachy, Mike; Friesner, Richard A; Abel, Robert
The accurate prediction of protein-ligand binding free energies remains a significant challenge of central importance in computational biophysics and structure-based drug design. Multiple recent advances including the development of greatly improved protein and ligand molecular mechanics force fields, more efficient enhanced sampling methods, and low-cost powerful GPU computing clusters have enabled accurate and reliable predictions of relative protein-ligand binding free energies through the free energy perturbation (FEP) methods. However, the existing FEP methods can only be used to calculate the relative binding free energies for R-group modifications or single-atom modifications and cannot be used to efficiently evaluate scaffold hopping modifications to a lead molecule. Scaffold hopping or core hopping, a very common design strategy in drug discovery projects, is critical not only in the early stages of a discovery campaign where novel active matter must be identified but also in lead optimization where the resolution of a variety of ADME/Tox problems may require identification of a novel core structure. In this paper, we introduce a method that enables theoretically rigorous, yet computationally tractable, relative protein-ligand binding free energy calculations to be pursued for scaffold hopping modifications. We apply the method to six pharmaceutically interesting cases where diverse types of scaffold hopping modifications were required to identify the drug molecules ultimately sent into the clinic. For these six diverse cases, the predicted binding affinities were in close agreement with experiment, demonstrating the wide applicability and the significant impact Core Hopping FEP may provide in drug discovery projects.
Embryonic stem cells provide a potential resource for research and drug screening. To make such a resource feasible, it is necessary to generate cells of sufficient quality and quantity. The challenge is to expand cell numbers while maintaining the fidelity of phenotype and to control and direct differentiation to produce the cell type of interest in a format that is suitable for drug screening. At present, large-scale culturing of human ES cell lines is problematic and provides substantial challenges. This article provides an overview of current bioprocessing techniques that could be used to generate cells for drug discovery applications. This will generate further technical expertise that can be applied in the production of cells for potential therapeutic applications.
Wang, Zhiyun; Du, Jian; Che, Pao-Lin; Meledeo, M Adam; Yarema, Kevin J
Metabolic glycoengineering, a technique pioneered almost two decades ago wherein monosaccharide analogs are utilized to install non-natural sugars into the glycocalyx of mammalian cells, has undergone a recent flurry of advances spurred by efforts to make the methodology more efficient. This article describes the versatility of metabolic glycoengineering, which is a prime example of 'chemical glycobiology,' and gives an overview of its capability to endow complex carbohydrates in living cells and animals with interesting (and useful!) functionalities. Then an overview is provided describing how acylated monosaccharides, a class of molecules originally intended to be efficiently-used, membrane-permeable metabolic intermediates, have led to the discovery that a subset of these compounds (e.g. tributanoylated hexosamines) display unanticipated 'scaffold-dependent' activities; this finding establishes these molecules as a versatile platform for drug discovery.
Pandey, Udai Bhan
The common fruit fly, Drosophila melanogaster, is a well studied and highly tractable genetic model organism for understanding molecular mechanisms of human diseases. Many basic biological, physiological, and neurological properties are conserved between mammals and D. melanogaster, and nearly 75% of human disease-causing genes are believed to have a functional homolog in the fly. In the discovery process for therapeutics, traditional approaches employ high-throughput screening for small molecules that is based primarily on in vitro cell culture, enzymatic assays, or receptor binding assays. The majority of positive hits identified through these types of in vitro screens, unfortunately, are found to be ineffective and/or toxic in subsequent validation experiments in whole-animal models. New tools and platforms are needed in the discovery arena to overcome these limitations. The incorporation of D. melanogaster into the therapeutic discovery process holds tremendous promise for an enhanced rate of discovery of higher quality leads. D. melanogaster models of human diseases provide several unique features such as powerful genetics, highly conserved disease pathways, and very low comparative costs. The fly can effectively be used for low- to high-throughput drug screens as well as in target discovery. Here, we review the basic biology of the fly and discuss models of human diseases and opportunities for therapeutic discovery for central nervous system disorders, inflammatory disorders, cardiovascular disease, cancer, and diabetes. We also provide information and resources for those interested in pursuing fly models of human disease, as well as those interested in using D. melanogaster in the drug discovery process. PMID:21415126
Chen, Lu; Morrow, John K; Tran, Hoang T; Phatak, Sharangdhar S; Du-Cuny, Lei; Zhang, Shuxing
As an important aspect of computer-aided drug design, structure-based drug design brought a new horizon to pharmaceutical development. This in silico method permeates all aspects of drug discovery today, including lead identification, lead optimization, ADMET prediction and drug repurposing. Structure-based drug design has resulted in fruitful successes drug discovery targeting proteinligand and protein-protein interactions. Meanwhile, challenges, noted by low accuracy and combinatoric issues, may also cause failures. In this review, state-of-the-art techniques for protein modeling (e.g. structure prediction, modeling protein flexibility, etc.), hit identification/ optimization (e.g. molecular docking, focused library design, fragment-based design, molecular dynamic, etc.), and polypharmacology design will be discussed. We will explore how structure-based techniques can facilitate the drug discovery process and interplay with other experimental approaches.
Chen, Lu; Morrow, John K.; Tran, Hoang T.; Phatak, Sharangdhar S.; Du-Cuny, Lei; Zhang, Shuxing
As an important aspect of computer-aided drug design, structure-based drug design brought a new horizon to pharmaceutical development. This in silico method permeates all aspects of drug discovery today, including lead identification, lead optimization, ADMET prediction and drug repurposing. Structure-based drug design has resulted in fruitful successes drug discovery targeting protein-ligand and protein-protein interactions. Meanwhile, challenges, noted by low accuracy and combinatoric issues, may also cause failures. In this review, state-of-the-art techniques for protein modeling (e.g. structure prediction, modeling protein flexibility, etc.), hit identification/optimization (e.g. molecular docking, focused library design, fragment-based design, molecular dynamic, etc.), and polypharmacology design will be discussed. We will explore how structure-based techniques can facilitate the drug discovery process and interplay with other experimental approaches. PMID:22316152
Background Efficient identification of drug targets is one of major challenges for drug discovery and drug development. Traditional approaches to drug target identification include literature search-based target prioritization and in vitro binding assays which are both time-consuming and labor intensive. Computational integration of different knowledge sources is a more effective alternative. Wealth of omics data generated from genomic, proteomic and metabolomic techniques changes the way researchers view drug targets and provides unprecedent opportunities for drug target identification. Results In this paper, we develop a method based on flux balance analysis (FBA) of metabolic networks to identify potential drug targets. This method consists of two linear programming (LP) models, which first finds the steady optimal fluxes of reactions and the mass flows of metabolites in the pathologic state and then determines the fluxes and mass flows in the medication state with the minimal side effect caused by the medication. Drug targets are identified by comparing the fluxes of reactions in both states and examining the change of reaction fluxes. We give an illustrative example to show that the drug target identification problem can be solved effectively by our method, then apply it to a hyperuricemia-related purine metabolic pathway. Known drug targets for hyperuricemia are correctly identified by our two-stage FBA method, and the side effects of these targets are also taken into account. A number of other promising drug targets are found to be both effective and safe. Conclusions Our method is an efficient procedure for drug target identification through flux balance analysis of large-scale metabolic networks. It can generate testable predictions, provide insights into drug action mechanisms and guide experimental design of drug discovery. PMID:21689470
Cheng, Feng; Theodorescu, Dan; Schulman, Ira G.; Lee, Jae K.
Liver toxicity (hepatotoxicity) is a critical issue in drug discovery and development. Standard preclinical evaluation of drug hepatotoxicity is generally performed using in vivo animal systems. However, only a small number of preselected compounds can be examined in vivo due to high experimental costs. A more efficient yet accurate screening technique which can identify potentially hepatotoxic compounds in the early stages of drug development would thus be valuable. Here, we develop and apply a novel genomic prediction technique for screening hepatotoxic compounds based on in vitro human liver cell tests. Using a training set of in vivo rodent experiments for drug hepatotoxicity evaluation, we discovered common biomarkers of drug-induced liver toxicity among six heterogeneous compounds. This gene set was further triaged to a subset of 32 genes that can be used as a multi-gene expression signature to predict hepatotoxicity. This multi-gene predictor was independently validated and showed consistently high prediction performance on five test sets of in vitro human liver cell and in vivo animal toxicity experiments. The predictor also demonstrated utility in evaluating different degrees of toxicity in response to drug concentrations which may be useful not only for discerning a compound’s general hepatotoxicity but also for determining its toxic concentration. PMID:21884709
Xu, Hua; Jones, Lyn H
First introduced by K Barry Sharpless in 2001, the term 'click chemistry' soon became a widely used description of chemical reactions that proceed rapidly, cleanly and in a manner that is often compatible with aqueous solutions. Click chemistry is frequently employed throughout the process of drug discovery, and greatly helps advance research programs in the pharmaceutical industry. It facilitates library synthesis to support medicinal chemistry optimization, helps identify the targets and off-targets of drug candidates, and can facilitate the determination of drug efficacy in clinical trials. In the last decade, a large number of patent applications covering the various types and utilities of click chemistry have been filed. In this review, we provide the first analysis of click chemistry applications.
Lushington, Gerald H.; Dong, Yinghua; Theertham, Bhargav
The magnitude of the challenges in preclinical drug discovery is evident in the large amount of capital invested in such efforts in pursuit of a small static number of eventually successful marketable therapeutics. An explosion in the availability of potentially drug-like compounds and chemical biology data on these molecules can provide us with the means to improve the eventual success rates for compounds being considered at the preclinical level, but only if the community is able to access available information in an efficient and meaningful way. Thus, chemical database resources are critical to any serious drug discovery effort. This paper explores the basic principles underlying the development and implementation of chemical databases, and examines key issues of how molecular information may be encoded within these databases so as to enhance the likelihood that users will be able to extract meaningful information from data queries. In addition to a broad survey of conventional data representation and query strategies, key enabling technologies such as new context-sensitive chemical similarity measures and chemical cartridges are examined, with recommendations on how such resources may be integrated into a practical database environment. PMID:23782037
Khachaturian, Zaven S
The rapid pace of neurobiology research has increased the prospects of developing drugs to prevent neurodegenerative disorders. Although the goal of delaying the onset of brain disorders may be within the grasp of modern medicine, there are several critical barriers to progress. Among these is the lack of appropriate models and modeling systems for specific neurodegenerative diseases. Traditionally, in drug discovery, testing, and development, a combination of models is used. These include in vitro, in vivo, transgenic, and other animal models. However, each of these models has limitations. In this article, the author advocates the use of "in silico" modeling systems, which could complement currently available models and enable investigators to simulate alternative strategies to modulate neural function in a dynamic interactive mode. Advances in computer technology, including increasing speed and memory, and ready access to parallel processing systems have made it easier for investigators to develop databases for computer abstractions of neural function and dysfunction and to begin to develop prototypes for use in complex systems modeling environments. Multimodeling systems have been widely used in other areas of science to study emergent behavior of complex systems, such as the impact of atmospheric changes on weather, flight patterns of birds in a flock, and the behavior of traders in a commodities market. Adoption of such approaches should increase understanding of the complexities of signal transduction pathways in neural networks and accelerate the drug discovery process.
Elson, Elliot L.; Genin, Guy M.
The functions, form and mechanical properties of cells are inextricably linked to their extracellular environment. Cells from solid tissues change fundamentally when, isolated from this environment, they are cultured on rigid two-dimensional substrata. These changes limit the significance of mechanical measurements on cells in two-dimensional culture and motivate the development of constructs with cells embedded in three-dimensional matrices that mimic the natural tissue. While measurements of cell mechanics are difficult in natural tissues, they have proven effective in engineered tissue constructs, especially constructs that emphasize specific cell types and their functions, e.g. engineered heart tissues. Tissue constructs developed as models of disease also have been useful as platforms for drug discovery. Underlying the use of tissue constructs as platforms for basic research and drug discovery is integration of multiscale biomaterials measurement and computational modelling to dissect the distinguishable mechanical responses separately of cells and extracellular matrix from measurements on tissue constructs and to quantify the effects of drug treatment on these responses. These methods and their application are the main subjects of this review. PMID:26855763
Tipping, W. J.; Lee, M.; Serrels, A.; Brunton, V. G.
Optical microscopy techniques have emerged as a cornerstone of biomedical research, capable of probing the cellular functions of a vast range of substrates, whilst being minimally invasive to the cells or tissues of interest. Incorporating biological imaging into the early stages of the drug discovery process can provide invaluable information about drug activity within complex disease models. Spontaneous Raman spectroscopy has been widely used as a platform for the study of cells and their components based on chemical composition; but slow acquisition rates, poor resolution and a lack of sensitivity have hampered further development. A new generation of stimulated Raman techniques is emerging which allows the imaging of cells, tissues and organisms at faster acquisition speeds, and with greater resolution and sensitivity than previously possible. This review focuses on the development of stimulated Raman scattering (SRS), and covers the use of bioorthogonal tags to enhance sample detection, and recent applications of both spontaneous Raman and SRS as novel imaging platforms to facilitate the drug discovery process. PMID:26839248
Honório, Kathia M; Moda, Tiago L; Andricopulo, Adriano D
The discovery and development of a new drug are time-consuming, difficult and expensive. This complex process has evolved from classical methods into an integration of modern technologies and innovative strategies addressed to the design of new chemical entities to treat a variety of diseases. The development of new drug candidates is often limited by initial compounds lacking reasonable chemical and biological properties for further lead optimization. Huge libraries of compounds are frequently selected for biological screening using a variety of techniques and standard models to assess potency, affinity and selectivity. In this context, it is very important to study the pharmacokinetic profile of the compounds under investigation. Recent advances have been made in the collection of data and the development of models to assess and predict pharmacokinetic properties (ADME--absorption, distribution, metabolism and excretion) of bioactive compounds in the early stages of drug discovery projects. This paper provides a brief perspective on the evolution of in silico ADME tools, addressing challenges, limitations, and opportunities in medicinal chemistry.
Eckmann, D. M.; Composto, R. J.; Tsourkas, A.; Muzykantov, V. R.
Polymer-based nanogel formulations offer features attractive for drug delivery, including ease of synthesis, controllable swelling and viscoelasticity as well as drug loading and release characteristics, passive and active targeting, and the ability to formulate nanogel carriers that can respond to biological stimuli. These unique features and low toxicity make the nanogels a favorable option for vascular drug targeting. In this review, we address key chemical and biological aspects of nanogel drug carrier design. In particular, we highlight published studies of nanogel design, descriptions of nanogel functional characteristics and their behavior in biological models. These studies form a compendium of information that supports the scientific and clinical rationale for development of this carrier for targeted therapeutic interventions. PMID:25485112
Liu, Jie; Lee, Wen-hui; Zhang, Yun
The discovery of new drugs requires the development of improved animal models for drug testing. The Chinese tree shrew is considered to be a realistic candidate model. To assess the potential of the Chinese tree shrew for pharmacological testing, we performed drug target prediction and analysis on genomic and transcriptomic scales. Using our pipeline, 3,482 proteins were predicted to be drug targets. Of these predicted targets, 446 and 1,049 proteins with the highest rank and total scores, respectively, included homologs of targets for cancer chemotherapy, depression, age-related decline and cardiovascular disease. Based on comparative analyses, more than half of drug target proteins identified from the tree shrew genome were shown to be higher similarity to human targets than in the mouse. Target validation also demonstrated that the constitutive expression of the proteinase-activated receptors of tree shrew platelets is similar to that of human platelets but differs from that of mouse platelets. We developed an effective pipeline and search strategy for drug target prediction and the evaluation of model-based target identification for drug testing. This work provides useful information for future studies of the Chinese tree shrew as a source of novel targets for drug discovery research. PMID:25105297
Mazanetz, Michael P; Marmon, Robert J; Reisser, Catherine B T; Morao, Inaki
Technological advances in high-throughput screening methods, combinatorial chemistry and the design of virtual libraries have evolved in the pursuit of challenging drug targets. Over the last two decades a vast amount of data has been generated within these fields and as a consequence data mining methods have been developed to extract key pieces of information from these large data pools. Much of this data is now available in the public domain. This has been helpful in the arena of drug discovery for both academic groups and for small to medium sized enterprises which previously would not have had access to such data resources. Commercial data mining software is sometimes prohibitively expensive and the alternate open source data mining software is gaining momentum in both academia and in industrial applications as the costs of research and development continue to rise. KNIME, the Konstanz Information Miner, has emerged as a leader in open source data mining tools. KNIME provides an integrated solution for the data mining requirements across the drug discovery pipeline through a visual assembly of data workflows drawing from an extensive repository of tools. This review will examine KNIME as an open source data mining tool and its applications in drug discovery.
Ratnam, Joseline; Zdrazil, Barbara; Digles, Daniela; Cuadrado-Rodriguez, Emiliano; Neefs, Jean-Marc; Tipney, Hannah; Siebes, Ronald; Waagmeester, Andra; Bradley, Glyn; Chau, Chau Han; Richter, Lars; Brea, Jose; Evelo, Chris T; Jacoby, Edgar; Senger, Stefan; Loza, Maria Isabel; Ecker, Gerhard F; Chichester, Christine
Integration of open access, curated, high-quality information from multiple disciplines in the Life and Biomedical Sciences provides a holistic understanding of the domain. Additionally, the effective linking of diverse data sources can unearth hidden relationships and guide potential research strategies. However, given the lack of consistency between descriptors and identifiers used in different resources and the absence of a simple mechanism to link them, gathering and combining relevant, comprehensive information from diverse databases remains a challenge. The Open Pharmacological Concepts Triple Store (Open PHACTS) is an Innovative Medicines Initiative project that uses semantic web technology approaches to enable scientists to easily access and process data from multiple sources to solve real-world drug discovery problems. The project draws together sources of publicly-available pharmacological, physicochemical and biomolecular data, represents it in a stable infrastructure and provides well-defined information exploration and retrieval methods. Here, we highlight the utility of this platform in conjunction with workflow tools to solve pharmacological research questions that require interoperability between target, compound, and pathway data. Use cases presented herein cover 1) the comprehensive identification of chemical matter for a dopamine receptor drug discovery program 2) the identification of compounds active against all targets in the Epidermal growth factor receptor (ErbB) signaling pathway that have a relevance to disease and 3) the evaluation of established targets in the Vitamin D metabolism pathway to aid novel Vitamin D analogue design. The example workflows presented illustrate how the Open PHACTS Discovery Platform can be used to exploit existing knowledge and generate new hypotheses in the process of drug discovery.
Halling-Brown, Mark D.; Bulusu, Krishna C.; Patel, Mishal; Tym, Joe E.; Al-Lazikani, Bissan
canSAR is a fully integrated cancer research and drug discovery resource developed to utilize the growing publicly available biological annotation, chemical screening, RNA interference screening, expression, amplification and 3D structural data. Scientists can, in a single place, rapidly identify biological annotation of a target, its structural characterization, expression levels and protein interaction data, as well as suitable cell lines for experiments, potential tool compounds and similarity to known drug targets. canSAR has, from the outset, been completely use-case driven which has dramatically influenced the design of the back-end and the functionality provided through the interfaces. The Web interface at http://cansar.icr.ac.uk provides flexible, multipoint entry into canSAR. This allows easy access to the multidisciplinary data within, including target and compound synopses, bioactivity views and expert tools for chemogenomic, expression and protein interaction network data. PMID:22013161
Chang, Jerry; Tomlinson, Ian; Warnement, Michael; Iwamoto, Hideki
The serotonin (5-hydroxytryptamine, 5-HT) transporter (SERT) protein plays a central role in terminating 5-HT neurotransmission and is the most important therapeutic target for the treatment of major depression and anxiety disorders. We report an innovative, versatile, and target-selective quantum dot (QD) labeling approach for SERT in single Xenopus oocytes that can be adopted as a drug-screening platform. Our labeling approach employs a custom-made, QD-tagged indoleamine derivative ligand, IDT318, that is structurally similar to 5-HT and accesses the primary binding site with enhanced human SERT selectivity. Incubating QD-labeled oocytes with paroxetine (Paxil), a high-affinity SERT-specific inhibitor, showed a concentration- and time-dependent decrease in QD fluorescence, demonstrating the utility of our approach for the identification of SERT modulators. Furthermore, with the development of ligands aimed at other pharmacologically relevant targets, our approach may potentially form the basis for a multitarget drug discovery platform.
Müller, Joachim; Hemphill, Andrew
Antiparasitic chemotherapy is an important issue for drug development. Traditionally, novel compounds with antiprotozoan activities have been identified by screening of compound libraries in high-throughput systems. More recently developed approaches employ target-based drug design supported by genomics and proteomics of protozoan parasites. In this chapter, the drug targets in protozoan parasites are reviewed. The gene-expression machinery has been among the first targets for antiparasitic drugs and is still under investigation as a target for novel compounds. Other targets include cytoskeletal proteins, proteins involved in intracellular signaling, membranes, and enzymes participating in intermediary metabolism. In apicomplexan parasites, the apicoplast is a suitable target for established and novel drugs. Some drugs act on multiple subcellular targets. Drugs with nitro groups generate free radicals under anaerobic growth conditions, and drugs with peroxide groups generate radicals under aerobic growth conditions, both affecting multiple cellular pathways. Mefloquine and thiazolides are presented as examples for antiprotozoan compounds with multiple (side) effects. The classic approach of drug discovery employing high-throughput physiological screenings followed by identification of drug targets has yielded the mainstream of current antiprotozoal drugs. Target-based drug design supported by genomics and proteomics of protozoan parasites has not produced any antiparasitic drug so far. The reason for this is discussed and a synthesis of both methods is proposed.
Flannery, Erika L.; Chatterjee, Arnab K.; Winzeler, Elizabeth A.
Malaria elimination has recently been reinstated as a global health priority but current therapies seem to be insufficient for the task. Elimination efforts require new drug classes that alleviate symptoms, prevent transmission and provide a radical cure. To develop these next generation medicines, public-private partnerships are funding innovative approaches to identify compounds that target multiple parasite species at multiple stages of the parasite lifecycle. Here, we review the cell-, chemistry- and target-based approaches used to discover new drug candidates that are currently in clinical trials or undergoing preclinical testing. PMID:24217412
Sakurada, Kazuhiro; McDonald, Fiona M; Shimada, Fumiki
As William Shakespeare beautifully described, increasing age often causes loss of tissue and organ function. The increase in average life expectancy in many countries is generating an aging society and an increase in age-related health problems. Regenerative medicine is expected to be a powerful actor in this drama, and stem cell technology may hold the key to the development of innovative treatments for acute and chronic degenerative conditions. This Review surveys the present situation and some future prospects for regenerative medicine and stem cell based drug discovery.
Kinch, Michael S; Flath, Richard
The way in which new medicines are discovered has irreversibly changed and the future sustainability of the enterprise is characterized by an unprecedented period of uncertainty. Herein, we convey that these changes provide unprecedented opportunities for many different players within the private and public sectors to work together and develop new models that ensure the sustainability of activities that have had an extraordinary impact; in terms of promoting public health and driving economic value. Specific examples of experiments are provided to demonstrate some of the new thinking that will be needed to ensure continuation of new drug discovery.
Schreyer, Adrian M; Blundell, Tom L
CREDO is a unique relational database storing all pairwise atomic interactions of inter- as well as intra-molecular contacts between small molecules and macromolecules found in experimentally determined structures from the Protein Data Bank. These interactions are integrated with further chemical and biological data. The database implements useful data structures and algorithms such as cheminformatics routines to create a comprehensive analysis platform for drug discovery. The database can be accessed through a web-based interface, downloads of data sets and web services at http://www-cryst.bioc.cam.ac.uk/credo. Database URL: http://www-cryst.bioc.cam.ac.uk/credo.
DeLano, Warren L
Widespread adoption of open-source software for network infrastructure, web servers, code development, and operating systems leads one to ask how far it can go. Will "open source" spread broadly, or will it be restricted to niches frequented by hopeful hobbyists and midnight hackers? Here we identify reasons for the success of open-source software and predict how consumers in drug discovery will benefit from new open-source products that address their needs with increased flexibility and in ways complementary to proprietary options.
Alexandre, François-René; Domon, Lisianne; Frère, Stéphane; Testard, Alexandra; Thiéry, Valérie; Besson, Thierry
The interest of microwaves in drug discovery and multi-step synthesis is exposed with the aim of describing our strategy. These studies are connected with our work on the synthesis of original heterocyclic compounds with potential pharmaceutical value. Reactions in the presence of solvent and solvent-free synthesis can be realised under a variety of conditions; for some of these selected results are given, and where available, results from comparison with the same solvent-free conditions but with classical heating are given.
Fujioka, Masahiko; Omori, Naoki
Therapeutic effects through G protein-coupled receptors (GPCRs) are promoted by a full agonist, partial agonist, neutral antagonist or inverse agonist. Dramatic change of function such as from a neutral antagonist to a full agonist with minimal variation of ligand structure is a phenomenon that medicinal chemists often encounter. This is also influenced by a change of assay format. The subtle nature of structure-function relationships is difficult to grasp unless carefully considered from both chemistry and assay perspectives. In this article we discuss the subtle aspects of GPCR drug discovery from the medicinal chemistry perspective.
Kappe, C Oliver; Dallinger, Doris
In the past few years, using microwave energy to heat and drive chemical reactions has become increasingly popular in the medicinal chemistry community. First described 20 years ago, this non-classical heating method has matured from a laboratory curiosity to an established technique that is heavily used in academia and industry. One of the many advantages of using rapid 'microwave flash heating' for chemical synthesis is the dramatic reduction in reaction times--from days and hours to minutes and seconds. As will be discussed here, there are good reasons why many pharmaceutical companies are incorporating microwave chemistry into their drug discovery efforts.
Denny, P W; Steel, P G
High-throughput screening (HTS) efforts for neglected tropical disease (NTD) drug discovery have recently received increased attention because several initiatives have begun to attempt to reduce the deficit in new and clinically acceptable therapies for this spectrum of infectious diseases. HTS primarily uses two basic approaches, cell-based and in vitro target-directed screening. Both of these approaches have problems; for example, cell-based screening does not reveal the target or targets that are hit, whereas in vitro methodologies lack a cellular context. Furthermore, both can be technically challenging, expensive, and difficult to miniaturize for ultra-HTS [(u)HTS]. The application of yeast-based systems may overcome some of these problems and offer a cost-effective platform for target-directed screening within a eukaryotic cell context. Here, we review the advantages and limitations of the technologies that may be used in yeast cell-based, target-directed screening protocols, and we discuss how these are beginning to be used in NTD drug discovery.
Bailey, Derek J; McDevitt, Molly T; Westphall, Michael S; Pagliarini, David J; Coon, Joshua J
A mass spectrometry (MS) method is described here that can reproducibly identify hundreds of peptides across multiple experiments. The method uses intelligent data acquisition to precisely target peptides while simultaneously identifying thousands of other, nontargeted peptides in a single nano-LC-MS/MS experiment. We introduce an online peptide elution order alignment algorithm that targets peptides based on their relative elution order, eliminating the need for retention-time-based scheduling. We have applied this method to target 500 mouse peptides across six technical replicate nano-LC-MS/MS experiments and were able to identify 440 of these in all six, compared with only 256 peptides using data-dependent acquisition (DDA). A total of 3757 other peptides were also identified within the same experiment, illustrating that this hybrid method does not eliminate the novel discovery advantages of DDA. The method was also tested on a set of mice in biological quadruplicate and increased the number of identified target peptides in all four mice by over 80% (826 vs 459) compared with the standard DDA method. We envision real-time data analysis as a powerful tool to improve the quality and reproducibility of proteomic data sets.
Doyle, Orla M; Mehta, Mitul A; Brammer, Michael J
Neuroimaging has been identified as a potentially powerful probe for the in vivo study of drug effects on the brain with utility across several phases of drug development spanning preclinical and clinical investigations. Specifically, neuroimaging can provide insight into drug penetration and distribution, target engagement, pharmacodynamics, mechanistic action and potential indicators of clinical efficacy. In this review, we focus on machine learning approaches for neuroimaging which enable us to make predictions at the individual level based on the distributed effects across the whole brain. Crucially, these approaches can be trained on data from one study and applied to an independent study and, unlike group-level statistics, can be readily use to assess the generalisability to unseen data. In this review, we present examples and suggestions for how machine learning could help answer fundamental questions spanning the drug discovery pipeline: (1) Who should I recruit for this study? (2) What should I measure and when should I measure it? (3) How does the pharmacological agent behave using an experimental medicine model?, and (4) How does a compound differ from and/or resemble existing compounds? Specifically, we present studies from the literature and we suggest areas for the focus of future development. Further refinement and tailoring of machine learning techniques may help realise their tremendous potential for drug discovery and drug validation.
Salon, John A.; Lodowski, David T.
Crucial as molecular sensors for many vital physiological processes, seven-transmembrane domain G protein-coupled receptors (GPCRs) comprise the largest family of proteins targeted by drug discovery. Together with structures of the prototypical GPCR rhodopsin, solved structures of other liganded GPCRs promise to provide insights into the structural basis of the superfamily's biochemical functions and assist in the development of new therapeutic modalities and drugs. One of the greatest technical and theoretical challenges to elucidating and exploiting structure-function relationships in these systems is the emerging concept of GPCR conformational flexibility and its cause-effect relationship for receptor-receptor and receptor-effector interactions. Such conformational changes can be subtle and triggered by relatively small binding energy effects, leading to full or partial efficacy in the activation or inactivation of the receptor system at large. Pharmacological dogma generally dictates that these changes manifest themselves through kinetic modulation of the receptor's G protein partners. Atomic resolution information derived from increasingly available receptor structures provides an entrée to the understanding of these events and practically applying it to drug design. Supported by structure-activity relationship information arising from empirical screening, a unified structural model of GPCR activation/inactivation promises to both accelerate drug discovery in this field and improve our fundamental understanding of structure-based drug design in general. This review discusses fundamental problems that persist in drug design and GPCR structural determination. PMID:21969326
Experiments and numerical simulations using a flow phantom for magnetic drug targeting have been undertaken. The flow phantom is a half y-branched tube configuration where the main tube represents an artery from which a tumour-supplying artery, which is simulated by the side branch of the flow phantom, branches off. In the experiments a quantification of the amount of magnetic particles targeted towards the branch by a magnetic field applied via a permanent magnet is achieved by impedance measurement using sensor coils. Measuring the targeting efficiency, i.e. the relative amount of particles targeted to the side branch, for different field configurations one obtains targeting maps which combine the targeting efficiency with the magnetic force densities in characteristic points in the flow phantom. It could be shown that targeting efficiency depends strongly on the magnetic field configuration. A corresponding numerical model has been set up, which allows the simulation of targeting efficiency for variable field configuration. With this simulation good agreement of targeting efficiency with experimental data has been found. Thus, the basis has been laid for future calculations of optimal field configurations in clinical applications of magnetic drug targeting. Moreover, the numerical model allows the variation of additional parameters of the drug targeting process and thus an estimation of the influence, e.g. of the fluid properties on the targeting efficiency. Corresponding calculations have shown that the non-Newtonian behaviour of the fluid will significantly influence the targeting process, an aspect which has to be taken into account, especially recalling the fact that the viscosity of magnetic suspensions depends strongly on the magnetic field strength and the mechanical load.